Property:CSDMS meeting abstract
From CSDMS
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A barrier aware Riemann solver is developed for the shallow water equations in the presence of the sub-grid-scale barriers using an explicit finite volume scheme. Our algorithm guarantees that the barrier-containing cell can be split into two effective cells that are maintained outside of the reset of the grid structure. To avoid time-steps constrained by the size of small cut cells, we redistribute the fluxes computed on those cells engaging a modified h-box method. The solver ensures that water does not cross the barrier when it is not supposed to, maintain large time-steps relative to the cells being cut through and retain the desirable properties. Also, the wet-dry interface, the boundary between cells that are wet (or flooded) and dry are well handled so that quantities going to zero and conservation are carefully integrated into the method. The work is built off of the GeoClaw package so inherits various extensions to tsunami and storm surge simulations. +
A critical part of predicting and representing coastal responses during large storms is to represent the areas of compound flooding where both oceanic factors (tides and surge), and hydrologic factors (i.e., rainfall-runoff processes), as well as their interactions impact water levels and flow velocities. During extreme events, these compound flood waters can remobilize thick layers of sediment, exposing material that had been buried for many years. One such event was Hurricane Harvey which made a landfall along the Texas Gulf Coast (US) on August 26, 2017. Within Galveston Bay, compound flooding occurred and persisted for weeks as the result of the interaction between the storm surges created as storm approached the coast, and a subsequent long-lasting flood pulse induced by the torrential rainfall associated with the hurricane. The flooding mobilized thick layers of sediment, including contaminated sediment from the Buffalo Bayou shipping channel. Sediment core data taken after the storm showed that these contaminants were transported several 10s of km. To predict the response of this type of event requires numerical models that can account for the rainfall-runoff processes, sediment erosion and transport, and oceanographic processes including storm surges, tides and wind-driven currents.
These types of coupled models are currently being developed and tested as part of the NOAA funded Coastal Ocean Modeling Testbed (COMT). The eventual goal of our project is to develop the capability to represent compound flooding and the associated particulate and contaminant fluxes across the river – to ocean continuum. Specifically, we plan to link a hydrological model (WRF-Hydro) to a Galveston Bay hydrodynamic model (ROMS) and apply it to large compound flooding events such as Hurricane Harvey. A higher resolution model capable of representing the Buffalo Bayou shipping channel will then be nested within the Galveston Bay model and used to reproduce sediment erosion and contaminant exposure patterns that were observed in the wake of Hurricane Harvey. In this poster we present preliminary model development that links the high – resolution (~20m) hydrodynamic model of Buffalo Bayou with the lower – resolution (~100 m) hydrodynamic model of Galveston Bay. The 20-m model grid resolves the relatively deep shipping channels and is being used in initial model runs to represent typical conditions in the upper Galveston Bay and Buffalo Bayou shipping channel.
A dynamic framework coupling social and ecological sub-systems while aligning management, policy, governance, science, legal and decision-making elements under an overarching goal will be presented and described. A nested set of conceptual models is used to represent and analyze the general internal organization and functioning of a federal agency. External connectivities are also addressed while the conceptual model is able to generate testable hypotheses. The selection of managing for resilience as the main goal of the framework as well as their underpinning elements will be illustrated and explained. The overall functioning of the proposed resilience framework seeks to mimic and anticipate environmental change and is aligned with commonly used elements of resilience-thinking. Dynamic management frameworks addressing socio-ecological dynamics can facilitate the efficient and effective utilization of resources, reduce uncertainty for decision and policy makers, and lead to more defensible decisions on resources. +
A goal of the geomorphology community is to translate our understanding of past and present processes to predict landscape change in the future. Here we present our knowledge about relict permafrost landscapes across central Appalachia, and we propose a framework through which the geologic record and landscape models may be used to predict change in modern permafrost settings. The onset of Quaternary glacial cycles profoundly influenced the pace and pattern of erosion in mid-latitude settings through the development and subsequent degradation of perennially-frozen soils. Lidar-based mapping documents extensive periglacial alteration of the central Appalachian landscape, including solifluction lobes and other mass-wasting features. These features appear aspect-modulated, implying microclimate control. Geomorphic mapping, shallow geophysical imaging and cosmogenic nuclide dating reveal that periglacial erosion sets regolith patterns, subsurface architecture and erosion rates for multiple glacial cycles. Moreover, a combination of slow erosion rates and structural traps means headwater valleys and basins preserve direct records of upland erosional response to climate change, and planned work to core modern peat bogs may provide paleoclimate and paleoecological markers like pollen and leaf waxes in addition to quartz-rich debris for cosmogenic dating. Geologic data can be supplemented by permafrost hydrology models for an improved understanding of both the microclimate and long-term climate controls on periglacial hillslope processes. Informative models pair realistic active layer flow paths, accounting for both infiltration and permafrost thaw, with effective stress calculations to develop more accurate failure depth estimates. Such process-based models will be key to predicting future periglacial landscape change as warming exceeds historical trends. +
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A major challenge of geophysics today is addressing the problems of general interest through intense collaboration that bridges disciplinary boundaries. Such collaborations are greatly complicated by the fact that Earth Sciences have steadily diverged and evolved to the point of the Tower of Babel. Scientific jargon makes it difficult to meaningfully explore ideas across disciplines, while lack of cyberinfrastructure for sharing causes poor reproducibility and code reuse.<br>
My vision for an EarthCube frontend is that of a maximally simple API that could be run from any platform or in a browser. At it's core, it would support the following functionality:
# make it really simple for someone to submit their own data, models and software with provenance and descriptive metadata;
# support data discovery in 4D space, at a range of scales, through semantically-enabled metadata (and the data might - and will - be stored in one of the existing databases);
# have potential for elaborate visualization capabilities;
# build up upon a social network of some sort (so that there's a face behind each data component); and, finally,
# make it easy to create, modify and run workflows remotely through intelligent combination of software and data components.
The last point seems critical for long term useability of EarthCube, and requires upfront thinking and code coupling capabilities.<br>
Specifically, the plug-and-play component programming approach used by CSDMS could be adapted by the larger solid Earth geophysics community with great long-term benefits, hopefully resulting in better scientific reproducibility, code reuse and, eventually, streamlined collaboration. +
A major issue, hampering our understanding about the human impacts on sediment fluxes is our limited knowledge about the magnitude and controlling factors of catchment sediment yields (SY, t km-2 y-1) under ‘baseline’ conditions, i.e. the SY that could be expected from a catchment if it was unaffected by human impacts.
To address this problem, a dataset was set up with measured SY-data from 146 catchments in Europe that are little or not affected by humans in terms of land use and have no significant reservoirs, lakes, impoundments or glaciers in their upstream area. The considered catchments span a wide range in catchment areas (0.3 – 4,000km²) and observed SY-values (0.5 – 3,100 t km-2 y-1). Analyses of these data indicates that climate exerts little control on the observed range of SY-values. However, strong correlations were found between SY and average catchment slope, lithology and tectonic activity (as derived from a globally available earthquake hazard map). Based on these findings, a regression model was developed that allows predicting baseline SY. Model calibration and validation results indicate that this model is able to provide robust approximations of the baseline SY, with >95% of predictions deviating less than one order of magnitude from the measured SY-values.
This model can therefore significantly improve our understanding about the controlling factors of SY and their sensitivity to human impacts. However, it is also the first model that explicitly considers the effect of tectonic activity on catchment SY. Despite the relatively limited tectonic activity in many of these catchments, differences in earthquake sensitivity alone was found to explain already more than 40% of the observed variation in SY. Our results therefore illustrate that tectonic activity has a strong, but hitherto largely neglected, influence on SY. +
A mathematical model of carbonate platform sedimentation is presented in which the depth-dependent carbonate growth rate determines the depositional rate of a platform top responding to relative sea-level rise. This model predicts that carbonate platform evolution is primarily controlled by the initial water depth and the sediment production rate at the initial depth, rather than by the maximum potential production rate and imposed rate of relative sea-level rise. A long-standing paradox in the understanding of drowned carbonate platforms in the geological record is based on comparing relatively slow long-term rates of relative sea-level rise with maximum growth potentials of healthy platforms. The model presented here demonstrates that a carbonate platform could be paradoxically drowned by a constant relative sea-level rise when the rate is still less than the maximum carbonate production potential. This does not require other external controls of environmental change, such as nutrient supply or siliciclastic sedimentation. If the rate of relative sea-level rise is higher than the production rate at the initial water depth, the top of the carbonate platform gradually drops below the active photic zone and drowns even if the rate of relative sea-level rise is lower than the maximum carbonate accumulation growth potential. This result effectively resolves the paradox of a drowned carbonate platform. Test runs conducted at bracketed rates of relative sea-level rise have determined how fast the system catches up and maintains the “keep-up” phase, which is a measure of the time necessary for the basin to respond fully to the external forcing. The duration of the “catch-up” phase of platform response (termed carbonate response time) scales with the initial seawater depth and the platform-top aggradation rate. The catch-up duration can be significantly elongated with an increase in the rate of relative sea-level rise. The transition from the catch-up to the keep-up phases can also be delayed by a time interval associated with ecological reestablishment after platform flooding. The carbonate model here employs a logistic equation to model the colonization of carbonate-producing marine organisms and captures the initial time interval for full ecological reestablishment. The increase in delay time due to the carbonate response time and self-organized processes associated with biological colonization, implies a greater likelihood of autogenic origin for high-frequency cyclic strata than has been previously estimated.
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A new approach for mapping landslide hazard is developed by combining probabilities of landslide probability derived from a data-driven statistical approach and process-based model of shallow landsliding. Our statistical approach integrates the influence of seven site attributes on observed landslides using a frequency ratio method. Influential attributes and resulting susceptibility maps depend on the observations of landslides considered: all types of landslides, debris avalanches only, or source areas of debris avalanches. For each landslide type the frequency ration (FR) classification is converted into a Stability Index (SI), mapped across our study domain in the North Cascades National Park, WA. Using distributed landslide observations a continuous function is developed to relate local SI values to landslide probability. This probability is combined with spatially distributed probability of landsliding obtained from Landlab using a two-dimensional binning method that employs empirical and modeled based probabilities as indices and calculates empirical probability of landsliding at the intersections of bin ranges of the empirical and process-based probability domains. Based on this we developed a probabilistic correction factor to modeled local landslide probability. Improvements in distinguishing potantially unstable domain with the proposed model is quantified statistically. +
A
A new class of models based on population ecology, nutrient-geochemistry, and sedimentology is able to simulate carbonate accretion in reef and shelf environments. Unlike previous models for carbonates, they produce very detailed simulations of facies variabilities in space and time. With adjustments to the model runs the range of variabilities can be explored and described statistically. We look at comparisons of the statistics from the models and in outcrops/drillcores of carbonate rocks and ecological transects of present-day seabed areas. +
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A new submerged aquatic vegetation (SAV) model is developed and incorporated into the fully coupled hydrodynamic-water quality framework of SCHISM-ICM in order to account for the impacts of SAV to the aquatic system. This multidisciplinary study incorporates biogeochemistry, hydrodynamics, numerical computing and field survey data. The interactions between SAV, hydrodynamics and biogeochemistry contain several complex nonlinear feedback loops, which had not previously been explored. My research uses a fully coupled hydrodynamic-biogeochemistry-SAV model to quantitatively explore the relative contributions of each process associated with SAV (from purely physical processes such as dragging, to purely biological processes such as growth) to its total impact on the system. Through applications, we find that SAV generally encourages phytoplankton accumulation by increasing the residence time, while suppressing local primary production of the phytoplankton through competition for light and nutrients. The dynamic feedback of SAV to hydrodynamics is significant, accounting for up to 80% of the changes of the water quality variables. Our results highlight the importance of incorporating the nonlinear feedback loops in a model in order to correctly account for complex hydrodynamic and biogeochemical processes. This new SAV model has immediate applications in the monitoring and guidance of SAV removal (e.g. San Francisco Bay and Delta) or recovery (e.g. Chesapeake Bay) in different systems over the world. +
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A number of two- and three-dimensional models are currently available to calculate sediment transport and channel change in rivers. These three-dimensional models rely on time-averaging and parameterization of the turbulence. Available depth-averaged, two-dimensional models also rely on simple boundary stress closures. In relatively simple channels these models have predictive capability, but they often perform poorly when there is large-scale flow separation or when secondary circulation is strong. Sharp meanders, channel constrictions, many engineering structures, vegetation, and certain types of bedforms all cause flow separation, secondary circulation, and free shear layers. Turbulence-resolving flow and sediment transport models may do better at predicting channel change in complex channels, but at a substantially larger computational cost. With parallelization, turbulence-resolving models can now be developed and applied to refractory fluvial morphodynamic problems.
Detached-Eddy Simulation (DES) is a hybrid large eddy simulation (LES) and Reynolds-averaged Navier Stokes (RANS) method. RANS is applied to the near-bed grid cells, where grid resolution is not sufficient to fully resolve wall turbulence. LES is applied further from the bed and banks. A one equation turbulence closure model with a wall-distance dependence, such as that of Spalart and Allmaras (SA), is ideally suited for the DES approach. The rough wall extension of the SA model is utilized herein. Our river DES numerical modeling system was developed in OpenFOAM. The model resolves large-scale turbulence using DES and simultaneously integrates the suspended sediment advection-diffusion equation, wherein advection is provided by the DES velocity field minus particle settling, and diffusion is provided by the sub-grid or RANS eddy viscosity. As such, turbulent suspension throughout most of the flow depth results from resolved turbulent motions. A two-dimensional, depth-averaged flow model, also written in OpenFOAM, determines the local water surface elevation. A separate program was written to automatically construct the block-hexagonal, computational grid between the calculated water surface and a triangulated surface of a digital elevation model of the given river reach. Domain decomposition of the grid is employed to break up the integration between multiple processors, and Open MPI provides communication between the processors. The model has shown very good scalability up to at least 128 processors.
Results of the modeling system will be shown of flow and suspended sediment model in lateral separation eddies in the Colorado River in Grand Canyon. The eddy recirculation zones exist downstream of channel constrictions from tributary debris fans. The modeling system is currently being developed and validated to be used in designing discharges from Glen Canyon Dam for the preservation of sandbar beaches, which are critical habitat for endangered fish.
Keywords: fluvial geomorphology, sediment transport, lateral separation zones.
Movie at:
https://csdms.colorado.edu/mediawiki/images/GrandCanyonDES.avi
A series of controlled laboratory experiments were conducted at the St. Anthony Falls laboratory of the University of Minnesota to study the effect of changing precipitation patterns on landscape evolution over long-time scales. High resolution digital elevation (DEM) both in space and time along with instantaneous sediment transport rates were measured over a range of rainfall and uplift rates. These experiments were designed to develop a complete drainage network by growth and propagation of erosional instabilities in response to tectonic uplift. We focus our study to the investigation of how changes in the frequency and magnitude of large-scale rainfall patterns (e.g. monsoonal variability) might influence the development of mountainous landscapes. Preliminary analysis suggests that the statistics of topographic signatures, for example, evolution of drainage network, slopes, curvatures, etc., show dependence on both rainfall patterns and uplift rate. The implications of these results for predictive modeling of landscapes and the resulting sediment transport are discussed. +
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A series of controlled laboratory experiments were conducted to study the effect of changing precipitation patterns on landscape evolution at the short and long-time scales. High resolution digital elevation (DEM) both in space and time were measured for a range of rainfall patterns and uplift rates. Results from our study show distinct signatures of extreme climatic fluctuations on the statistical and geometrical structure of landscape features. These signatures are evident in widening and deepening of channels and valleys, change in drainage patterns within a basin and change in the probabilistic structure of erosional events, such as, landslides and debris flows. Our results suggest a change in scale-dependent behavior of erosion rates at the transient state resulting in a regime shift in the transport processes in channels from supply-limited to sediment-flux dependent. This regime shift causes variation in sediment supply, and thus in water to sediment flux ratio (Qs/Qw), in channels of different sub-drainage basins which is further manifested in the longitudinal river profiles as the abrupt changes in their gradients (knickpoints), advecting upstream on the river network as the time proceeds. +
A
A two-dimensional numerical model was developed for simulating free surface flow. The model is based on the solutions of two-dimensional depth averaged Navier-Stokes equations. A finite volume method is applied such that mass conservation is satisfied both locally and globally. The model adopted the two-step, high resolution MUSCL-Hancock scheme. This Godunov type scheme is used together with the approximate Riemann solver. The boundary cells are treated as cut-cells in order to accommodate arbitrarily geometries of natural rivers. There are sixteen types of cut-cells depending on the slope of the boundary intersection with the cell. A cell merging technique is incorporated in the model that combines small cells with neighboring cells to create a larger cell, helps keeping the CFL condition. The cut-cells approach permits a fully boundary-fitted mesh without implementing a complex mesh generation procedure for irregular geometries. The model is verified by several laboratory experiments including unsteady flow passing through cylindrical piers and dam break flow in a rectangular channel. The model is also applied to simulate a 100-year flood event occurred at the Huron Island reach of the Mississippi River, where flow paths in the island formed a complex channel network as flood propagates. +
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Acoustic sediment monitoring technology provides a practical means to obtain high resolution estimates of suspended sand flux. However, bed bedload flux can be a significant component of total load and remains difficult to measure directly. In most cases, bedload is treated as a power-law function of water discharge, a constant fraction of suspended sand flux, or ignored. However, bedload flux may vary independently from water discharge or suspended sediment flux in supply-limited rivers due to systematic grain size and reach-geometric effects. We propose a model for bedload flux that enables improved prediction using variables that are routinely measured at acoustic sediment monitoring stations.<br><br>Though this model is rooted in causal physical theory, it contains several scaling parameters that must be constrained empirically. To this end, we propose a Bayesian statistical procedure that facilitates propagation of uncertainty from multiple sources of information. Application of this procedure is demonstrated at one monitoring station on the Colorado River in Grand Canyon National Park. Repeat bathymetric surveys of dune migration in the reach adjacent to the monitoring station are used to estimate bedload flux, providing an observational basis for statistical analysis. Parameter estimation and prediction are also informed by data from other rivers, which is incorporated in a hierarchical framework.<br><br>We find that conventional methods of estimating bedload flux fail to capture fluctuations driven by the interaction between flow strength and sediment supply, and can introduce large persistent biases to estimates of total load. Our model is applicable in a wide range of scenarios, and substantially reduces the uncertainty associated with estimating bedload flux in sand bed rivers. +
Addressing society's water and energy challenges requires sustainable use of the Earth's critical zones and subsurface environment, as well as technological innovations in treatment and other engineered systems. Reactive transport models (RTMs) provide a powerful tool to inform engineering design and provide solutions for these critical challenges. In this keynote, I will showcase the flexibility and value of RTMs using real-world applications that focus on (1) assessing groundwater quality management with respect to nitrate under agricultural managed aquifer recharge, and (2) systematically investigating the physical, chemical and biological conditions that enhance CO2 drawdown rates in agricultural settings using enhanced weathering. The keynote will conclude with a discussion of the possibilities to advance the use of reactive transport models and future research opportunities therein. +
After Glacial Lake Agassiz drained ~8.5 ka, the Red River (North Dakota, USA) formed, flowing northward into Lake Winnipeg and incising into paleolacustrine sediment as it meandered. The Red River provides a natural experiment to interrogate the role of slope change on river meandering and morphologic evolution as it is characterized by shallow bed slopes (~0.0001), which have been controlled by crustal deformation due to glacial isostatic adjustment (GIA) in response to ice sheet unloading since the river’s inception. GIA has changed Red River channel elevation by 10s of meters, reducing slopes by up to 60% in the downstream reaches. We isolate the role of slope in order to explore its importance to lateral migration rate relative to other factors such as bank strength, sediment supply, and fluid flow.
We quantified the impact of GIA-induced slope changes on the Red River’s morphology by performing an analysis of river meanders and cutoffs (Kodama et al., 2023). We constructed a dataset that quantified the number of meanders, cutoffs, and modeled change in slopes caused by GIA along the Red River. Notably, the abundance of cutoffs normalized for channel width (a proxy for time-averaged meander rate) statistically significantly correlates with changes in slope, with far fewer cutoffs in the downstream reaches of the river, where the largest slope reduction occurred. We expanded this analysis to two tributaries of the Red River, and found that this relationship holds in all three river systems regardless of sign (negative or positive) of the GIA-induced slope change. We infer that slope drives changes in lateral migration rate for these detachment-limited systems by modulating the magnitude of shear stress on riverbanks.
We next developed a modeling framework by modifying a simple kinematic model of meander migration (Howard & Knutson, 1984) to explore the impact of GIA-induced slope change on the temporal trends of meander migration rate along the Red River. Previous work showed that the meander rate of two Red River meander scrolls exponentially decayed over the Holocene (Brooks 2003), which we are able to simulate with our GIA forced meandering model. Our study isolates the role of slope on river lateral migration and highlights how rivers near former ice sheets can respond to changes in slope that occur over thousands of years.
After Superstorm Sandy impacted the New Jersey coastline in 2012, the state’s primary coastal resiliency plan was to fortify the entire shoreline by constructing large-scale berm-dune systems along the beach. These large artificial dunes, funded entirely by Congress, were constructed with the goal of mitigating future storm damage to houses and infrastructure. Two long-term management questions are 1) is it feasible for a beachfront community to maintain these projects over the long term?; and 2) if not, what fraction of the cost would need to be subsidized? To tackle these questions, we use a “geo-economic” model that captures the natural processes of beach and dune erosion and migration via storm overwash coupled with engineering interventions of beach nourishment and dune construction. The economic portion of the model accounts for the relationship between property values and berm-dune geometry. Previous work suggests that due to their protective and recreational value, higher dunes and wider beaches increase that property values. However, it is unclear whether this relationship holds true for dune protection some years after a storm has occurred as lags in major storm events may lead to perceptions of lower risks. Thus, beachfront communities may place greater value upon viewership and private property, rather than on protection by artificial dunes. By deriving mathematical expressions for optimal berm and dune size as a function of geologic and economic parameters, our model suggests that changes in risk perception can lower property values and therefore reduce the ability of a community to keep up with the costs of maintaining these structures. We are currently testing this hypothesis by analyzing past and present LiDAR imagery (i.e. 2010, 2014, and 2018) and real-estate data from Long Beach Island, NJ. +
Agricultural expansion has led to high rates of deforestation and land-use change in tropical ecosystems, relegating many of the remaining native forests to networks of fragmented patches. As a result, large forest-dwelling ungulates may alter movement and habitat-use patterns to accommodate for the changed spatial orientation of essential resources. In turn, some native patches may be subjected to increased ungulate impacts (e.g. trampling, bioturbation, and seed dispersal/ predation), while others may be devoid of these influences. We created an individual-based model utilizing empirical ungulate movement data from white-lipped peccaries (WLP) in the Brazilian Cerrado to evaluate variations in habitat use with degree of fragmentation (e.g. connectivity and number of patches) and percent of native forest cover (FC). In the model, a peccary herd moves across a landscape with a percent FC between 10% and 100% and one to four native forest patches. We then quantified the distribution of habitat-use intensity and percent of unused native habitat after five years. To empirically quantify impacts of white-lipped peccary habitat use, we measured seedling density in 72 1x1 plots in the Cerrado, 44 with and 28 without WLP.
Results indicate that in a fully-connected landscape (one-patch simulations), as percent FC decreases, the frequency distribution of habitat use goes from narrow and left-skewed (low use in the majority of the habitat) to widely and evenly distributed (no use to high use in distinct parts of the habitat), reflecting a more heterogeneous use of the habitat with less FC. In a fragmented landscape (two-four patch simulations) below 30% FC, habitat use is driven by the degree of connectivity between forest patches. However, above 60% FC, the percent of unused forest is negligible (similar to one-patch simulations), indicating that patch spatial configuration is no longer the driving factor of habitat use past a 60% FC threshold. Between 40% and 60% FC, habitat use is a function of both connectivity and percent FC. Preliminary empirical results suggest riparian forests have the greatest difference in mean seedling density between areas with or without WLP, while palm swamps have the least. Collectively, these results suggest conservation measures in agricultural landscapes should emphasize percent FC, connectivity, or both, depending on the amount of forest remaining and that riparian zones may be most adversely affected by the loss of large ungulates.
Alluvial megafans are sensitive recorders of landscape evolution: the influence of both autogenic processes and allogenic forcing and of the coupled dynamics of the fan with its mountainous catchment can often be deciphered from the megafan sediment record and the system’s morphometric characteristics. The Lannemezan megafan in the northern Pyrenean foreland was abandoned by its mountainous feeder stream during the Quaternary and subsequently incised. During the incision, a flight of alluvial terraces was left along the stream network. We use numerical models (CIDRE model, Carretier et al. 2015) to explore the relative roles of autogenic processes and external forcing in the building, abandonment and incision of a foreland megafan. We then compare the results with the inferred evolution of the Lannemezan megafan. We conclude that autogenic processes are sufficient to explain the building of a megafan and the long-term entrenchment of its feeding river at the time and space scales that match the Lannemezan setting. In the case of the Lannemezan megafan, climate, through temporal variations in precipitation rate, may have played a second-order role in the pattern of incision at a shorter time-scale. In contrast, base-level changes, tectonic activity in the mountain range or tilting of the foreland through flexural isostatic rebound do not appear to have played a role in the abandonment of the Lannemezan megafan. +
Alluvial rivers record the external drivers of change, such as climate, tectonics and anthropogenic disturbances, and they code their dynamics in their bankfull channel geometry and planform geometries and longitudinal profiles. The key to understanding the past and predicting the future alluvial rivers is learning to interpret the language of the grains of sediment and to decode the responses they record. Sand-bed river long-profile evolution model (SRLP) is a complete mechanistic model, describing both transient and steady-state long-profile evolution of a transport-limited sand-bed river by linking sediment transport and river morphodynamics, including planform (width) adjustment as a function of excess shear stress (following Parker, 1978, and Dunne et al., 2018), thereby linearizing the sediment-transport response to changing river discharge. Through quantifying the changes in the river's bed elevation, cross section, and channel slope, this one-dimensional, physics-based model captures the internal dynamics of this inherently complicated system and ultimately provides the critical information about how the river is responding to both natural and anthropogenic disturbances. We now further aim to understand and model how sediment is transported and where it is deposited within sand-bed alluvial river networks, how different portions of the alluvial river network respond and how the behavior of those network components are impacted over both human and geological time scales. In order to do this, we use an updated network model approach (by Wickert A., GRLP v2.0.0-alpha). This latest release works as a core network engine, allows integration of different process modules and ultimately provides a new network-model platform where we can include SRLP model. Through the addition of SRLP module, we present examples of long-profiles of sand-bed alluvial river networks under a variety of base level and water- and sediment-supply boundary conditions and investigate the mainstem river and both upstream and downstream tributary responses over time. Finally, we compare the response of the model of linked sand-bed tributaries to the one of gravel-bed rivers to further discuss the effects of variations in grain- and reach-scale dynamics on the longitudinal evolution of these two classes.
Along Andean-type convergent margins, the preserved stratigraphic successions in retroarc foreland basins record complex interactions between oceanic plate subduction, overriding lithosphere deformation, and surface processes. Modeling their interactions and their impacts on basin stratigraphy helps to distinguish the geological footprint of the operating processes. We use a source-to-sink landscape evolution model, Badlands, to investigate the basin stratigraphic formation in response to changes in subduction morphology, hinterland orogenic uplift, overriding lithosphere strength, and surface erosional efficiency. Our modeling results reveal distinguishable responses of basin sedimentation to the imposed tectonic and surface forcings. Firstly, with sufficient sediment supply (i.e., the basin is filled with sediments), subduction at higher slab dip leads to development of shallower and narrower basins, with increasing volume of fluvial and shallow-water deposits accumulation. For mechanically thicker overriding plates, a deeper foreland basin tends to develop, though the basin width does not show consistent changes with increasing lithosphere strength. When sediment supply is further enhanced by either increasing orogenic uplift rate or surface erodibility, the basin sedimentation extends horizontally while the basin depth changes in an opposite way. Secondly, our basin subsidence analysis reveals strong impact of flexural rebound at the foredeep on modifying the basin morphology and strata dipping. We further found positive correlations between the flexural rebound and the progradation of fluvial deposits at the foredeep. Lastly, by normalizing the basin width to orogenic belt width and basin depth to maximum foreland flexure, we categorize the basins to be accommodation-dominant and supply-dominant, which helps to evaluate the impact of varying each contributing process on the basin development. Overall, our source-to-sink models reveal the complex interactions between surface and tectonic forcings, and highlight the huge potential of extracting their signals from the geological record.
Along a quarter of the Beaufort Sea coast, back-barrier estuaries modulate the transport and transformation of nitrogen and carbon, impacting food webs and carbon budgets. These estuaries are adjacent to permafrost, a large carbon reservoir that contains ~1700 Gt of organic carbon that is thawing from rapid Arctic warming. Thawed dissolved organic matter and nutrients may be transported to the coastal ocean by groundwater and rivers, adding nutrients to the coast that may impact production and biogeochemical cycles. It is unclear what effect permafrost thaw will have on Arctic estuarine biogeochemistry, partly because present-day spatial and temporal variability of residence time and export in Arctic back-barrier estuaries is unknown and complicates efforts to predict future change. To investigate the residence time of water, as well as estuary-shelf fluxes, this study uses a numerical modeling approach. Specifically, a hydrodynamic model, the Regional Ocean Modeling System (ROMS), is being implemented for Arey, Kaktovik, and Jago Lagoons along the Beaufort Sea coast of northern Alaska. The model accounts for processes including local winds, rivers, and larger scale circulation. Analysis will focus on variations in circulation dynamics within the ice break-up and open water season of 2019. +
Along wave-influenced deltas, wave-driven longshore currents usually interact with the fluvial jet at the river mouth, creating a sharp gradient alongshore in sediment transport/deposition and hence a corresponding change in coastline morphology. When multiple channels intersect a delta coastline, morphological changes can take on a complex outlook driven by the multiplicity of the river channels and their ‘hydraulic groyne effect’, whereby the overall effect of the river jets is to limit the loss of sediment within the coastal littoral system and ensure shoreline stability. This study explores the dynamic relationships between waves and fluvial discharge along a coastline intersected by river mouths by employing a numerical model of an idealized delta coastline containing two river mouths. The modelling is undertaken using Delft3D, in order to simulate both sediment transport and wave propagation along with the accompanying changes in coastline morphology. Analysis focuses on the relative change in coastline morphology, updrift, and downdrift of the river channels, in relation to varying scenarios of the incident wave climate, fluvial input, and river channel geometry. Specifically, water discharge entering the basin is set temporally constant during a model run but is varied in the range of 500 - 2000 m3/s between runs. Further, 3 scenarios of fluvial sediment discharge corresponding to low, medium, and high sediment discharges, are incorporated into each fluvial discharge scenario. Finally, waves approach the coastline from an incident angle of <45o, generating longshore sediment transport proportional to its significant height and approach angle, which are varied between model runs in the ranges of 1.0 - 1.5 m and 15 - 42 degrees, respectively. The study is set to provide new insights into the morphodynamics of wave-influenced deltas resulting from the interaction of waves with fluvial discharges at interannual timescales. +
Although mangroves provide several beneficial ecosystem services, such as blue carbon storage, coastal protection, and nursery habitats, they rapidly decline due to human development and climate change. In particular, in areas in the Caribbean, such as Puerto Rico, climate change
will likely lead to an increase in evaporation over precipitation. Such an increase in drought-like conditions will drive porewater salinity to increase exceeding the threshold beyond which mangroves can survive. To improve our understanding of this interplay, we developed a numerical model using the Landlab Python library that describes the spatial distribution of vegetation and die-back in low-lying and undeveloped mangrove islands where freshwater inputs come solely from precipitation. We apply the model to a series of islands with elongated and asymmetric die-backs in La Parguera, a bay environment in southern Puerto Rico. Our model can explain the die-back shape and location for all islands as a function of the average net evaporation rate (i.e. evaporation – precipitation), the island's edge water salinity, and the mangrove soil dispersion coefficient, or the porewater exchange through tidal flushing. We gathered evaporation data from the Woods Hole Oceanographic Institute's OAFLUX project and precipitation data from the Tropical Rain Monitoring Mission, and quantified the soil dispersion as a function of the area of red mangroves, which was calculated via satellite imagery analysis. Additionally, we infered the outer edge salinity from the maximum canopy heights, gathered from Goddard's LiDAR, Hyperspectral, and Thermal Imager. In our model results, some islands presented a subtle bayward shift of the die-back. This can be explained by a higher island's edge water salinity on the landwards side, where bay depths are shallow and mixing with the rest of the bay is low. This spatial difference in salinity was consistent with the differences in canopy heights derived from LiDAR, and fell within the range of values reported in the literature. This portable modeling framework can be applied to other low lying mangrove carbonate islands with complex geometries.
Although numerous approaches for deriving water depth from bands of remotely-sensed imagery in the visible spectrum exist, digital terrain models for remote tropical carbonate landscapes remain few in number. The paucity is due, in part, to the lack of in situ measurements of pertinent information needed to tune water depth derivation algorithms. In many cases, the collection of the needed ground-truth data is often prohibitively expensive or logistically infeasible. We present an approach for deriving water depth from multi-spectral satellite imagery without the need for direct measurement of water depth, bottom reflectance, or water column properties within the site of interest. The reliability of the approach is demonstrated for five satellite images, each at a different study site, with overall RMSE values ranging from 0.84 m to 1.56 m when using chlorophyll concentrations equal to 0.05 $\text{mg m}^{-3}$ and a generic seafloor spectrum generated from a spectral library of common benthic constituents. Sensitivity analyses show that the model is robust to selection of bottom reflectance inputs and errors in the atmospheric correction and sensitive to parameterization of chlorophyll concentration. +
An Extreme Value Analysis (EVA) model is realized for seafloor elevation changes in an area of shallow continental shelf in the North Sea. Extreme events have practical application in this area of abundant Unexploded Ordinance at the seabed and also wind energy projects. The events being examined are from the motion of seabed sediment in megaripples, sand waves, sand bars and sand sheets, but driven by normal and extreme swell- and wind-waves, tides and human activities. Changes of seabed elevation up to 8m in one year are observed, but rare.
The observational dataset for the study is a large, publicly available compilation of 3-decades of annual, hydrographic-standard bathymetric soundings in the German Bight, provided in gridded form at a spatial resolution of 50m. Counts of annual seabed elevation changes by elapsed time were compiled and related to the seabed features, such as tidal channels (which have previously been well studied).
The change statistics were compared to forms of the Generalized Extreme Value and Generalized Pareto distributions, per pixel and also by small morphodynamically uniform subareas. The Generalized Pareto distribution with coefficient c ≈ -6.0 to -6.5 appears to be the appropriate model, but adjusted according to water depths and locations on features.
The result suggests a method to statistically model seabed behavior including extreme events. +
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An Isopycnic Coordinate Ocean Model is used to represent the propagation of internal tides in the Bay of Biscay and their desintegration into solitons. To model important vertical variability of the thermocline, such as solitons, a non-hydrostatic model is necessary. In this study, we test the possibility of integrated non-hydrostatics terms under weakly nonlinear and nonhydrostatic approximation. Non-hydrostatic terms derived with this assumption, are directly added to the hydrostatic equations. We then address numerical problems : mesh size limitation responsible for numerical dispersion, numerical instabilities. After having investigated these problems analytically and tested the limitation, a stable method is proposed. Results for a 2D idealised configuration of the Bay of Biscay is described : the model is forced by the semi-diurnal tidal wave M2, two layers of different density are considered. The internal waves is desintegrated into solitons after few tidal periods. +
An accurate, three-dimensional Navier–Stokes based immersed boundary code called TURBINS has been developed, validated and tested, for the purpose of simulating density-driven gravity and turbidity currents propagating over complex topographies. The code is second order accurate in space and third order in time, uses MPI, and employs a domain decomposition approach for parallelism. It makes use of multigrid preconditioners and Krylov iterative solvers for the systems of linear equations obtained by the finite difference discretization of the governing equations. Various boundary conditions on the complex geometry are imposed via the direct forcing variant of the immersed boundary approach, utilizing a stable interpolation method. Bi- and trilinear interpolations are employed in such a way that the original discretization accuracy is retained with no additional restriction on the time step. Weak and strong scaling tests were performed for a uniform flow over array of spheres. We obtain very good scaling results as expected for multigrid solvers. We perform convergence tests via uniform flow over cylinder. Both skin friction and pressure coefficients show very good agreement with results reported by other authors.
Subsequently, a computational investigation was conducted of mono-, bi- and polydisperse lock-exchange turbidity currents interacting with complex bottom topography. Our simulation results are compared against laboratory experiments of other authors. Several features of the flow such as deposit profiles, front location, suspended mass and runout length are discussed. For a monodisperse lock-exchange current propagating over a flat surface, we investigate the influence of the boundary conditions at the streamwise and top boundaries, and we generally find good agreement with corresponding laboratory experiments. However, we note some differences with a second set of experimental data for polydisperse turbidity currents over flat surfaces. A comparison with experimental data for bidisperse currents with varying mass fractions of coarse and fine particles yields good agreement for all cases except those where the current consists almost exclusively of fine particles. For polydisperse currents over a two-dimensional bottom topography, significant discrepancies are observed. Potential reasons are discussed, including erosion and bedload transport.
Finally, we investigate the influence of a three-dimensional Gaussian bump on the deposit pattern of a bidisperse current. The suspension includes two particle sizes with a settling velocity ratio of 10. As the current travels over the bottom topography, we record instantaneous deposit profiles and wall shear stress contours. As the current impinges on the obstacle, it becomes strongly three-dimensional (see Fig. 1). Comparison of the final deposit profiles near the Gaussian bump against the case of a flat surface shows a smaller influence of the topography on the fine particles than on the coarse ones. Due to lateral deflection, deposition generally decreases near the bump, while increasing away from it. Some distance downstream of the obstacle, the deposit profiles lose their memory of the bump and become nearly uniform again. Instantaneous wall shear stress profiles are employed in order to estimate the critical conditions at which bedload transport and/or particle resuspension can occur in various regions.
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An enduring obstacle to reliable modeling of the short and long term evolution of the stream channel-hillslope ensemble has been the difficulty of estimating stresses generated by stream hydrodynamics. To capture the influence of complex 3D flows on bedrock channel evolution, we derive the contribution of hydrodynamic stresses to the stress state of surrounding bedrock through a Smoothed Particle Hydrodynamics (SPH) approximation of the Navier-Stokes (N-S) equations. The GPU-accelerated SPH solution locally integrates the N-S equations by discretizing the flow into millions of particles which communicate local motions to neighbor particles using a smoothing kernel. Coupling the flow solutions to the stress-strain formulation of the Failure Earth Response Model (FERM) provides three-dimensional erosion as a function of the strength-stress ratio of each point in the computational domain. This novel approach allows the resulting geomorphic response to be quantified for bedrock channels with bends, knickpoints, plunge pools, and other geometric and hydrodynamic complexities. Strength parameters used in FERM (tensile strength, cohesion, and friction angle) are readily constrained with field observations. Fluvial stresses calculated with SPH are added to the other components of the total stress state, such as slope-generated and tectonically-generated stresses. From the coupling of SPH and FERM we gain 3D physics-based erosion and a dynamic link between complex flows and hillslope dynamics in a finite element framework. Initial results indicate that the inertial forces generated by a simple 45° bend in a bedrock channel exceed the shear forces by a factor of two or more. Capturing these inertial forces and their 3D erosive potential provides a more complete understanding of the stream channel-hillslope ensemble. +
An enduring obstacle to reliable modeling of the short and long-term evolution of the stream channel-hillslope ensemble has been the difficulty of estimating stresses generated by stream hydrodynamics. To capture the influence of complex three-dimensional (3D) flows on bedrock channel evolution, we derive the contribution of hydrodynamic stresses to the stress state of the underlying bedrock through a Smoothed Particle Hydrodynamics (SPH) approximation of the Navier-Stokes equations as calculated by the DualSPHysics code (Crespo et al., 2015). Coupling the SPH flow solutions to the stress-strain formulation of the Failure Earth REsponse Model (FERM) (Koons et al., 2013) provides three-dimensional erosion as a function of the strength-stress ratio of each point in the computational domain. From the coupling of SPH and FERM we gain a 3D physics-based erosion scheme and a two-way link between complex flows and hillslope dynamics in a finite element framework. +
Analysis of topography can reveal signals resulting from both past and currently active tectonic regimes. In central Aotearoa New Zealand today, the Marlborough faults transfer plate boundary motion from the Hikurangi subduction zone to the highly oblique Alpine fault. The rocks of the Marlborough region have hosted active structures since the mid-Cretaceous when they sat at the edge of the Gondwana margin. Here we use tectonic geomorphology in conjunction with geological observations to unravel the long-term tectonic history of this plate boundary transition zone with emphasis on variations along and across strike, with depth and in time. To understand the active deformation occurring under the present tectonic regime, as manifested by recent complex faulting during the 2016 Mw 7.8 Kaikōura earthquake, we focus on understanding the 3D structure of the region as well as the development of, and control by, inherited structures. Cretaceous restoration of eastern Marlborough suggests that the major faults formed during extension of Te Riu-a-Māui Zealandia preceding breakaway from Gondwana. Overall, given the uncertainties of the reconstruction, the Cretaceous structural similarity of paleo-Marlborough with wider South Zealandia seems a remarkably clear and consistent match. How much of the distinctive landscape of Marlborough is due to the constraints of the current plate boundary versus the influence of tectonic inheritance? +
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Analyzing patterns of shoreline change between repeated LIDAR surveys reveals disparate styles of behavior on different temporal and spatial scales (Lazarus and Murray, GRL 2007; Lazarus, Ashton, Murray, Tebbens, and Burroughs, in review). We use wavelet analysis to investigate the mean variance (or spectral power) of cross-shore shoreline change, as well as the alongshore locations exhibiting high variance, across a range of scales. The time spans between surveys range from one to 12 years. On scales of a kilometer and less, the variance of shoreline change does not increase with the length of time between surveys. On these spatial scales, significant changes in shoreline location tend to occur in localized zones, and these zones shift from one time period to another rather than accumulating. Incidentally, the variance across these scales also exhibits a power-law behavior, even though different processes are known to dominate shoreline change on different scales within the range from 10-103 m. However, on scales larger than a kilometer, a peak in the variance appears, and both the magnitude of the variance and the alongshore scale of maximum variance increases over time; on these scales of a few to ten kilometers, shoreline changes do accumulate.
We interpret these observations as follows: On scales of a kilometer and less, each wave event creates an alongshore-heterogeneous pattern of shoreline change, with the alongshore locations of accentuated shoreline change depending on the characteristics of the waves (height, period, deep-water approach angle) and how those waves interact with heterogeneities on the seafloor—bathymetric features on the inner continental shelf are associated with shoreline change on the kilometer scale (List REFSXXX), and those in the surf zone and swash zones produce changes with alongshore scales on the order of one hundred meters and ten meters, respectively . Repeating such shoreline changes over many wave events superimposes essentially independent patterns of change, with effectively no memory of previous changes. The cumulative changes on scales of a few to ten kilometers, in contrast, suggest a diffusion of plan-view coastline shape; the relationship between the length scales of the variance peak over different time scales are consistent with diffusion, given estimates of effective diffusivity for this coastline (REF ANDREW, JORDAN). Apparently, on large alongshore length scales, the residual alongshore sediment flux that emerges from the many disparate wave events and associated complicated smaller scale patterns of sediment transport can be treated as related to shoreline orientation (the gradient in shoreline location)—the way that a long-term, large-scale, gradient-related flux of soil creep on hillslopes emerges from the complicated smaller-scale patterns of tree throw, gopher burrows, etc..
Answers to scientific questions often involve coupled systems that lie within separate fields of study. An example of this is flexural isostasy and surface mass transport. Erosion, deposition, and moving ice masses change loads on the Earth surface, which induce a flexural isostatic response. These isostatic deflections in turn change topography, which is a large control on surface processes. We couple a landscape evolution model (CHILD) and a flexural isostasy model (Flexure) within the CSDMS framework to understand interactions between these processes. We highlight a few scenarios in which this feedback is crucial for understanding what happens on the surface of the Earth: foredeeps around mountain belts, rivers at the margins of large ice sheets, and the "old age" of decaying mountain ranges. We also show how the response changes from simple analytical solutions for flexural isostasy to numerical solutions that allow us to explore spatial variability in lithospheric strength. This work places the spotlight on the kinds of advances that can be made when members of the broader Earth surface process community design their models to be coupleable, share them, and connect them under the unified framework developed by CSDMS. We encourage Earth surface scientists to unleash their creativity in constructing, sharing, and coupling their models to better learn how these building blocks make up the wonderfully complicated Earth surface system. +
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Anthropogenic activities associated with climate change and urbanization in coastal deltas (i.e.
groundwater extraction, coastal engineering and urban loading) have resulted in freshwater
degradation through the upwelling of saline paleowater. Factors controlling the preservation of
paleowater, and the initiation of exfiltration and subsequent upwelling of saline water are not yet
well understood. This research uses coupled morphodynamic-hydrogeologic modeling to
evaluate the groundwater response to geomorphic change. Delft3D is used to model the
formation of coastal deltas throughout the Holocene and create generic three-dimensional
distributions of sediment deposits characteristic of fluvial, wave, and tidal dominated deltas. The
generated sediment deposits are used to create three-dimensional effective grain-size maps by
convoluting the spatial distribution of each grain-size. This accounts for the combined effect of
multiple grain-sizes while preserving basin-scale heterogeneity commonly seen in highly
heterogeneous depositional environments. The effective grain size maps are used as the
geologic input for density-dependent groundwater flow and solute transport modeling. Results
are expected to show that the degree of aquifer heterogeneity correlates to the balance of fluvial
and marine morphological forces shaping sediment deposition. Spatial variability in basin-scale
aquifer heterogeneity is anticipated to control the exfiltration and upwelling patterns of saline
paleowater in deltaic environments. The modeling approach taken in this research is novel and
allows for the investigation of evolving groundwater systems with changes in landscape. Results
of this study will allow for the assessment of delta vulnerability to freshwater degradation from
upwelling saline paleowater, based on morphological classification. In the future, this research
may be used to help determine which deltas are most at risk for salinization and where science
and engineering efforts can be most beneficial to society.
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Any code that attempts to simulate large scale geophysical flows and their effect on topography needs a way to couple local flow properties to a rate of sediment erosion or deposition. However, the mechanisms responsible for a particle’s entrainment into a flow are poorly understood. Early erosional models setup a force balance between the fluctuating hydrodynamic forces acting on a particle and the adhesive forces holding a particle to the substrate. Later researchers eschewed this force balance in favor of an energy balance. They claim that a particle is constantly receiving energy from turbulent fluctuations in the flow near the surface, and that a particle will become entrained when it receives a critical amount of energy.
Despite all the work that has gone into deriving an erosion model based on theory, the most popular, and most accurate erosion model used in geophysical codes is the Garcia-Parker model, which is a simple fit to several sets of experimental data. But because their model is empirical, it’s impossible to know under what circumstances the model can and cannot be reasonably applied. A theoretical model would be much more desirable for precisely this reason.
Our goal is to better understand the mechanisms of particle entrainment through the use of direct numerical simulation. We are using a code developed at Lawrence Livermore National Laboratory, which solves the incompressible Navier-Stokes equations and uses a Lagrange multiplier method to enforce the correct boundary condition on the surface of the particles within the computational domain. With this method, we are able to accurately simulate the motion of thousands, or even tens of thousands of particles in an external flow in two or three dimensions. With this code, we can study in detail the coupling between local flow structures and the forces on a particle, which will hopefully lead to a better, theoretically based model for erosion. +
Arctic coasts have been impacted by rapid environmental change over the last 30 years. Warming air and water temperatures and the increased duration of the open water season, correlate with increases in the rate of already rapid erosion of ice-rich bluffs along the Beaufort Sea coast. To investigate longer-term changes in near-shore wave dynamics and storm surge set up as a result of sea-ice retreat, we coupled two simple modules.
Following Dean and Dalrymple (1991), we model wind-driven setup as a function of wind speed and direction, azimuth relative to the shore-normal, fetch and bathymetry. The wave module calculates the wave field for fetch-limited waves in shallow water based on the Shore Protection Manual (1984). For a given wind speed, dynamic water depth and fetch, we predict the significant wave height and wave period. Both modules require fetch as a controlling parameter. Sea-ice influenced coasts, are unique in that fetch is spatially variable due to the geometry of the shoreline and temporally variable as the location of the sea ice edge moves through the sea ice free season. We determine the distance to the sea ice edge using daily Nimbus 7-SMMR/SSM/I and DMSP SSMI Passive Microwave Sea Ice Concentration data. The sea ice edge is defined at a threshold sea ice concentration of 15%. We find a good match between the model predictions and our observed records of meteorological conditions and nearshore water level and waves along the Beaufort Coast in the summers of 2009 and 2010.
Over the period 1979-2012, fetch has increased significantly. In our study area near Drew Point, Alaska, the open water season itself lengthened from ~45 days to ~90 days. In the 1980’s and early 1990’s wave dynamics were fetch-limited during a significant period of the open water season. More recently, the distance from the coast to the sea ice edge shifts extremely rapidly (often 100’s of km over 1-2 weeks); fetch therefore only minimally influences wave dynamics as offshore distance exceeds the 140 km threshold over most of the open water season. Wave heights and surge set-up events on average have not changed in magnitude significantly, but storm surge set up events have increased in frequency.
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Arctic hydrological processes impose an important feedback on permafrost thermal conditions. Changes in permafrost hydrology could accelerate its thawing, resulting in a positive effect on permafrost carbon decomposition rates. Therefore, it is important to understand how geomorphic and other landscape processes control permafrost distribution and its properties such as soil saturation, ice content, active layer thickness (ALT) and temperature. The Advanced Terrestrial Simulator (ATS) is a collection of hydro-thermal processes designed to work within a flexibly configured modeling framework. ATS includes the soil physics needed to capture permafrost dynamics, including ice, gas, and liquid water content, multi-layered soil physics, and flow of unfrozen water in the presence of phase change. In this study, we directly address one of the tasks of the NGEE-Arctic project by modeling the effect of climate and environmental drivers on ALT and permafrost thickness and its distribution along the subarctic hillslope. Model runs demonstrate the likely role of vegetation-snow-permafrost-hydrology interactions by exploring snow depth and organic layer influence on horizontal and vertical patterns of permafrost. Understanding changes in hydrologic flow paths and soil moisture is important to predict evolution of ecosystem and biogeochemical processes that control climate feedbacks. In addition, hillslope flowpaths, vegetation, soil organic matter distribution, variation in soil depth and mineralogy are important components of the subgrid spatial extent of permafrost. This study explores the ways to improve the quality of the permafrost predictions at the subgrid scale and contribute to the better modeling of the permafrost related processes at the pan-Arctic scale. +
Arctic rivers play a crucial role in transporting sediment and nutrients from permafrost landscapes to the Arctic Ocean, influencing both landscape evolution and biogeochemical cycles. These river systems are undergoing significant transformations due to decreasing snow, intensified summer precipitation, altering vegetation, and permafrost thaw. Over a seasonal cycle the thermal state of Arctic rivers changes as their beds and banks thaw. Long-term observations indicate a rise in Arctic river discharge. However, our understanding of the complex mechanisms governing sediment transport in these rivers remains limited.
To address this gap, we focus on the Canning River, a gravel-bed river situated in continuous permafrost in Alaska. Previous studies on small nearby rivers during the 1970s suggested that sediment transport is hindered during the ice break-up flood because the channel bed remains frozen while cold river water starts running, slowing the sediment bed from thawing. This would imply a decoupling of sediment transport from water discharge, at least seasonally, in Arctic rivers. To investigate this hypothesis, we conducted fieldwork during the summers of 2022 and the spring of 2023, representing periods of high river discharge with differing thermal states. Our data collection included measurements of discharge, temperature, suspended sediment fluxes, grain size distributions, seismic signals, ground temperature, and river ice thickness, which we compared to a historical 5-year river discharge record.
We model how the river freezes to its bed over extended stretches during winter, and how it forms aufeis up to 2 meters thick despite limited water flow. Observed water temperature around the ice break-up period hovers around 0°C, potentially requiring several days to thaw the matrix sands and prohibiting pebble movement, according to our thermal model. Conversely, by mid-summer, water temperature rises to approximately 12°C. Although mid-summer river discharge peaks are lower, suspended sediment increases substantially during intense rainfall events, indicating a strong coupling with river discharge. These initial findings suggest that annual sediment transport might amplify with warming conditions, as the river water may no longer freeze to the channel bed and as summer flows intensify.
As a foundation of many ecological systems, vegetation is often a central component of ecological models used for forecasting and management. Many models are narrowly constrained by the system, species, and/or processes of interest and lack the ability to simulate specific management actions. This specificity limits their applicability to new, nonstationary, or actively-managed systems. The objective of this work is to create a Landlab component that combines an individual-based model design with grid-based model components to describe vegetation dynamics within and between grid cells. GenVeg is process-based, incorporating polymorphic plant-scale processes such as photosynthesis, dispersal, and seasonal allocation of biomass resources. Plant taxonomic principles are used to adapt the model methods based on the species (or representative species) of interest. Feedbacks between plants, plant communities, and the local physical environment utilize existing Landlab components and grid geometry to represent vegetation dynamics across the landscape. GenVeg is designed to be applied at a scale on the order of 10s to 1000s of meters over years to decades, which are scales relevant to ecosystem management and engineering planning. While the component is still under development, we will demonstrate its use within a dune environment utilizing coastal water levels and soil moisture to drive vegetation distribution across an idealized foredune system. +
As a rift evolves from its initiation until continental breakup it goes through a number of different phases that can be associated with distinct rifted-margin domains and major sedimentary basins. Seismic and geophysical data around the globe can give us glimpses into the progression through these domains, however, it is not well understood how the fault network evolves to produce them. Additionally, sedimentation and erosion are known factors that influence the longevity of an evolving fault and may affect the overall rift evolution. Previous work has qualitatively investigated the effect surface processes have on an evolving rift, however, there has not been a quantitative approach to analyze changes to the fault network through time.
To investigate the quantitative effect of surface processes on an evolving rift fault network, we utilized the two-way coupling between the geodynamics code ASPECT and the landscape evolution code FastScape to run 12 high-resolution 2D rift models. Using FastScape, we vary the erosional efficiency of the stream power law by changing the bedrock erodibility (Kf) from no surface processes to low (Kf= 10-6 m0.2/yr), medium (10-5 m0.2/yr), and high (10-4 m0.2/yr) efficiency. We then apply this to three different model setups that represent a wide, asymmetric, and symmetric rift. We analyze the models using the fault analysis toolbox (fatbox), which can track and correlate individual faults and their properties through time. Specifically, we utilize this toolbox to track the evolution of the number of faults and the cumulative fault system length and displacement through time and investigate how they change depending on the efficiency of surface processes and the rift type.
Through this analysis, we find that regardless of the rift type or the efficiency of surface processes the rift fault network evolves through up to five distinct phases: 1) distributed deformation and coalescence, 2) fault system growth, 3) fault system decline and basin-ward localization, 4) rift migration, and 5) continental breakup. While we find that surface processes do not exert a strong control on the phase progression or final rifted margin architecture, they do affect the temporal evolution of the fault network by increasing fault longevity. As faults live longer with greater surface processes, the fault network phases are prolonged and continental breakup is delayed. Additionally, greater surface process efficiency leads to fewer faults forming which causes a less complex fault network.
As climate change and environmental variability increase pressure on vulnerable communities, migration is one possible adaptation strategy. However, the decision to migrate is complex, and environmental factors are rarely the sole drivers of that decision. Rather, the decision to migrate is often influenced by a combination of economic, social, political, and environmental pressures. This is especially true in coastal communities in Bangladesh, where temporary migration has long been a method of livelihood diversification, and researchers are trying to understand how environmental factors influence existing migration flows. This work addresses a gap in current research by beginning to investigate how different “push” and “pull” drivers of migration might have distinctive variables that contribute to the ultimate decision to move or stay. In this study, random forest classification models are applied to a dataset consisting of household surveys from more than 1,200 households in southwestern Bangladesh to directly assess key variables that influence five types of migration in coastal communities: temporary migration within a village due to environmental stress, migration for education, migration for healthcare, migration for trade or commerce, and migration to visit relatives. This work demonstrates that these types of migration do have different drivers, which yields insights into the complex motivations that impact the decision to migrate. However, livelihood variables and individual aspirations were key for all investigated forms of migration. In the process, this work demonstrates that random forest models could be a powerful method for improving predictive accuracy of migration models to better inform migration policy and planning. +
As coastal regions become more developed, many communities are considering costly engineering solutions to address coastal change, including "soft" approaches, such as beach replenishments or dune constructions, and hard structures, such as seawalls, revetments, bulkheads, or groins. Given current rates of sea level rise and the associated shoreline losses that coastal communities face, however, it is unclear whether the benefits generated by these protection measures justify the costs. We are building a set of integrated geologic and economic models to better understand the coupled evolution of developed shorelines under alternative protection policies. The first model incorporates dune construction and sediment overwash relocation into a morphodynamic model for dune evolution. We use this model to assess the costs of constructing an optimal cross-sectional area for a long-term dune system, and we explore the “geo-economic” effects on ocean views that may be diminished by constructing a dune system of particular size seaward of protected properties. A second model simulates beach width dynamics for two adjacent communities, each with their own groin structure. We use the model to analyze both coordinated and uncoordinated strategies between the two communities, reflecting individual community decisions to protect or retreat. A third model incorporates beach nourishment practices into a morphodynamic model for barrier evolution that accounts for shoreface dynamics. Results show that the efficiency of beach nourishment can be affected by the dynamic state of the shoreface during each nourishment episode. In general, these models reinforce the need to refine numerical coastal management tools to incorporate bi-directional interactions between natural processes and human responses to shoreline change. +
As one of the three major Asian marginal seas in the western Pacific, the SCS occupies less than 1% total ocean area while accommodating 15% atoll (25434.6 km2) in the globe (GSA, 2009), which mainly distribute in the Xisha, Zhongsha and Nansha Islands. Atolls in the SCS are generally ellipse-shaped with a longer axis extending in the NE-SW direction and a wider southwest reef platform compared to the northeast. One possible explanation ascribed such features to the monsoon circulation (northeast and southwest monsoons blow alternatively in winter and summer) over the SCS (Zeng, 1984). Waves and currents influence the atoll development by (1) sediment suspension and transportation that can influence the transparency of the water, thus the symbiotic algae and the coral growth, (2) supply of dissolved oxygen and nutrient and (3) removal of metabolic wastes under normal weathers, while storm waves can cause large-scaled breakage, transportation and reconfiguration of reefs (e.g. Chappell, 1980; Storlazzi et al., 2005). Yet, little data was available regarding the hydrodynamic conditions of the forereef of the SCS atolls. Here, we conducted in situ tripod mooring observations (ADCP, ADV & CTD) for at least one tide cycle in 15-18 m water depth at the southeast forereef of three typical atolls – Xiaonanxun (NX), Anda (AD) and Kugui (KG) Reef – in the SCS, respectively, and collected coral sediment samples at different zonation of atolls in September 2017. During the observation periods, tide elevations varied by ca.1 m in all the three sites, with the highest 1.16 m in AD and lowest 0.96 m in KG. Mean flow velocity turns out to be as weak as about 0.1 m/s, with the weakest ~0.05 m/s in KG. Wave influence appears to be strongest in NX, with the significant wave height of ~1 m, in contrast to the 0.6 m and 0.4 m in AD and KG, respectively. The hydrodynamic observations under normal weathers should be able to transport the fine reef debris alone, with limited sediment transport rates of 0.61, 0.01 and 0.64 m3/m per tidal period in the observations in NX, AD and KG, respectively. Coarse coral rubbles and gravels might be only transported during extreme weathers. More observations and modeling work are needed, e.g. simulations of waves’ influence on atoll sedimentary systems’ development with XBeach.
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As part of the Mediterranean Landscape Dynamics (MedLand) project to create a modeling laboratory for human-landscape interaction, we have developed a suite of landscape evolution tools in the GRASS GIS environment. The core of this tool set is a Python script to estimate sediment transport for hillslopes, gullies/rills, and small channels, and simulate resulting terrain change for high-resolution 3D digital landscapes. Because it takes advantage of raster-optimized routines in GRASS, it is very fast on normal desktop systems, making it ideal for simulating long-term landscape change resulting from human activity, climate change, or other drivers. We provide examples of how this landscape evolution model is being used in the MedLand project. +
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Assessing the tsunami hazard in regions with infrequent or no instrumental or historical records of tsunamis is a challenge for emergency managers. In the absence of these records, coastal geologists rely on evidence of past tsunami inundation from buried sedimentary deposits to identify the presence of a tsunami hazard and to determine the recurrence of past events. One persistent challenge in assessing tsunami hazard from sandy coastal deposits is inferring the relative magnitude of past tsunamis from characteristics of the deposits. Recent reanalysis of field data from the 2011 Tohoku-oki earthquake and tsunami show that the volume of onshore sandy tsunami deposits is highly correlated with offshore tsunami magnitude, seafloor deformation, and fault slip. To further explore these relationships, we employ a Delft3D-FLOW hydrodynamic and sediment transport model to simulate onshore tsunami deposit volume from offshore slip of the 2011 Tohoku-oki earthquake and tsunami. We use the Satake et al. (2013) tsunami source model to derive the hydrodynamic boundary conditions for the sediment transport simulations. The Delft3D-FLOW model uses van Rijn (2007) sediment transport formulations and coefficients and a two-dimensional, vertically layered grid to model sediment transport with the effect of suspended-sediment induced density stratification on the vertical turbulent mixing. We model how variation in offshore slip affects tsunami deposit volume for a wide range of sediment sources, offshore and onshore slopes, and boundary roughness conditions. Model results show a strong correlation between onshore tsunami deposit volume and adjacent offshore co-seismic slip if ample sediment is available in the model to be eroded and transported. These results are consistent with data from the 2011 Tohoku tsunami at sites with sufficiently wide beaches and without shoreline armoring. We continue to test the model to evaluate sensitivity to parameters that may not be well known for paleo-tsunamis such as width of fault rupture, paleo-topography, and changes in sea level. Ultimately, this approach may be able to reconstruct past tsunami magnitudes and improve assessment of tsunami hazard.
* Satake, K., Fujii, Y., Harada, T., & Namegaya, Y. (2013). Time and space distribution of coseismic slip of the 2011 Tohoku earthquake as inferred from tsunami waveform data. Bulletin of the seismological society of America, 103(2B), 1473-1492.
At a global scale, deltas significantly concentrate people by providing diverse ecosystem services and benefits for their populations. At the same time, deltas are also recognized as one of the most vulnerable coastal environments, due to a range of adverse drivers operating at multiple scales. These include global climate change and sea-level rise, catchment changes, deltaic-scale subsidence and land cover changes, such as rice to aquaculture. These drivers threaten deltas and their ecosystem services, which often provide livelihoods for the poorest communities in these regions. Responding to these issues presents a development challenge: how to develop deltaic areas in ways that are sustainable, and benefit all residents? In response to this broad question we have developed an integrated framework to analyze ecosystem services in deltas and their linkages to human well-being. The main study area is part of the world’s most populated delta, the Ganges-Brahmaputra-Meghna Delta within Bangladesh. The framework adopts a systemic perspective to represent the principal biophysical and socio-ecological components and their interaction. A range of methods are integrated within a quantitative framework, including biophysical and socio-economic modelling, as well as analysis of governance through scenario development. The approach is iterative, with learning both within the project team and with national policy-making stakeholders. The analysis allows the exploration of biophysical and social outcomes for the delta under different scenarios and policy choices. Some example results will be presented as well as some thoughts on the next steps. +
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At the Visual World Investigation Lab of the Nature Research Center, we are developing a module where museum visitors investigate geomorphic and land-use scenarios through a landscape evolution model. Visitors use touchscreen computers to select simplified inputs for the CHILD model. Model visualizations will be produced for each trial in which they run the scenario. For example, visitors can explore the impact of the percentage of impervious surfaces in a section of urbanized Raleigh that will be adjusted by scaling infiltration parameters, and how the headwaters of the Little Tennessee River would differ if the southern Appalachians were still undergoing tectonic uplift. These scenarios provide relatable experiences to visitors, an opportunity to educate them upon the science behind the scenarios, and the purpose and limitations of models. We will first develop the framework of the module to be able to accept scenarios and its inputs, including digital elevation models, such that others can contribute scenarios. This module is early in its conception, thus we will present our initial framework with the intent to elicit feedback from the community. +
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At the catchment scale, alluvial rivers co-adjust their planform, cross-sectional, and longitudinal geometries in response to changing water and sediment inputs, base level and the transport of this sediment through the fluvial system. In this study, we derive a simple, physics-based model to understand and predict sand-bed river long-profile form and evolution. This model links sediment transport and river morphodynamics, following an analogous approach to that taken by Wickert and Schildgen (2019) for gravel-bed rivers. It allows for planform (width) adjustments as a function of excess shear stress by following Parker (1978); this linearizes the sediment-transport response to changing river discharge, and ultimately suggests a diffusive form for sand-bed river long-profile evolution. Here, we also present model results of gravel- and sand-bed river long profiles under a variety of water- and sediment-supply and base-level conditions to discuss how these may help us to better interpret the geological and geomorphological context of alluvial rivers, and better predict their changes over time. This expression for the long-profile evolution of transport-limited sand-bed rivers provides forward momentum to merge theory and models for gravel-bed and sand-bed river systems, to look at the alluvial river system response as a whole (from bedrock-alluvial transition to the point at which backwater effects become significant) over both human and geological time scales, and to decipher the long-term rate and magnitude of this response to facilitate a better understanding of the evolution of fluvial landscapes. +
At the margins of many glaciers, we observe visually-striking layers of concentrated sediment incorporated into ice near the base of the glacier. Despite the prevalence of these ice-sediment facies, sediment transported in basal ice is rarely quantified in the overall sediment transport budget for glacial systems. Previous facies descriptions have been linked to formation mechanisms that depend on specific configurations of the topography or hydrology beneath a glacier, which remains inconsistent with observations of similar facies across disparate regions, climate zones, and geologic settings. Here, we use detailed descriptions of ice-sediment facies from Mendenhall glacier, Alaska, to inform a numerical model of sediment entrainment in basal ice. We find that the overall volume of entrained sediment is strongly related to the glacier’s thermal regime near the ice-sediment interface. Further, we present a likely mechanism for the formation of dispersed ice facies that explains the natural variability in sediment characteristics observed at Mendenhall glacier and other alpine systems. These results show that ice-sediment facies are a plausible archive for understanding the subglacial environment, even in the absence of additional constraints on temperature or hydrologic connectivity at the bed. +
Barrier island response to sea level rise depends on their ability to transgress and move sediment to the back barrier, either through flood-tidal delta deposition, or via storm overwash. Our understanding of these processes over decadal to centennial time scales, however, is limited and poorly constrained.
We have developed a new barrier inlet environment (BRIE) model to better understand the interplay between tidal dynamics, overwash fluxes, and sea-level rise on barrier evolution. The BRIE model combines existing overwash and shoreface formulations with alongshore sediment transport, inlet stability, inlet migration and flood-tidal delta deposition. Within BRIE, inlets can open, close, migrate, merge with other inlets, and build flood-tidal delta deposits. The model accounts for feedbacks between overwash and inlets through their mutual dependence on barrier geometry.<br><br>Model results suggest that when flood-tidal delta deposition is sufficiently large, barriers require less storm overwash to transgress and aggrade during sea level rise. In particular in micro-tidal environments with asymmetric wave climates and high alongshore sediment transport, tidal inlets are effective in depositing flood-tidal deltas and constitute the majority of the transgressive sediment flux. Additionally, we show that artificial inlet stabilization (via jetty construction or maintenance dredging) can make barrier islands more vulnerable to sea level rise. +
Barrier islands and other coastal landforms are highly dynamic systems, changing in response a spectrum of disturbances from multi-decadal ‘press’ disturbances like sea-level rise (SLR) to often more intense episodic perturbations like storms. As a result, multiple stable ecomorphological states exist on barrier islands. In this study, we use a probabilistic Bayesian network approach to investigate the likelihood of shifts among alternative equilibrium states on Fire Island, New York under three scenarios of shoreline change driven by sea-level rise (SLR). Specifically, we highlight areas that are most likely (i) to become inundated, (ii) to shift from one non-inundated state (or landcover type) to another (e.g., a forest becomes beach), or (iii) to remain in the current landcover state. We explore the effects of these changes on the availability of coastal ecosystem types, piping plover habitat, and anthropogenic development. +
Bedload flux is notoriously challenging to measure and model with its dynamics, therefore, remains largely unknown in most fluvial systems worldwide. We present a global scale bedload flux model as part of the WBMsed modeling framework. The results show that the model can very well predict the distribution of water discharge and suspended sediment and well predict bedload. Bedload predictions’ sensitivity to river slope, particle size, discharge, river width, and suspended sediment were analyzed, showing that the model is most responsive to spatial dynamics in river discharge and slope. The relationship between bedload and total sediment flux is analyzed globally and in representative longitudinal river profiles (Amazon, Mississippi, and Lena Rivers). The results show that while, as expected, the proportion of bedload is decreasing from headwater to the coasts, there is considerable variability between basins and along river corridors. The topographic and hydrological longitudinal profiles of rivers are shown to be the key driver of bedload longitudinal trends with fluctuations in slope controlling its more local dynamics. Differences in bedload dynamics between major river basins are attributed to the level of anthropogenic modifications, flow regimes, and topographic characteristics. +
Bedrock lithology has been shown to strongly influence how rivers and landscapes respond to tectonic perturbations, yet the specific variables and mechanisms that set how lithology controls river erosion are poorly understood. Recent field and modeling work suggests that one important lithologic control on channel response may be the delivery of large, generally immobile boulders from hillslopes to channels. This raises the possibility that differences in boulder delivery rates between lithologies may cause substantial differences in how landscapes respond to tectonics. An intriguing recent study suggested that in the Mendocino Triple Junction (MTJ) region of northern California, bedrock lithology might control the frequency and size of boulders delivered to channels, and therefore govern channel steepness and river evolution (Bennett et al., 2016). We further test this hypothesis here.
The Central Belt of the Franciscan Complex, a mix of sheared graywacke and mudstone, contains large blocks of more resistant serpentinite, greenstone, and amphibolite that are delivered to channels by earthflows. The adjacent Coastal Belt generally lacks such boulders, and sediment delivery to channels is dominated by shallow landsliding. This geologic setting provides a unique opportunity to test whether boulder abundance exerts a first-order control on landscape form. We use a landscape-scale analysis of channel steepness and active width indices, local topographic relief, lithology, and mapped boulder occurrence to understand the differences between the catchments eroding the Central Belt and those eroding the Coastal Belt. We find that channels are steeper in the Central Belt than in the Coastal Belt, both across the whole MTJ region and when averaged over 10-50 km2 subcatchments. Channels are also generally narrower in the Central Belt. This result could reflect lithologic controls or spatial heterogeneity in erosion rates. To control for the latter, we construct clusters of neighboring subcatchments that are free of knickpoints to explore possible controls of lithologic makeup (percent of a subcatchment underlain by Central Belt rocks) on channel steepness independent of erosion rate variations. We find inconsistent relationships between lithologic makeup and channel steepness within a given cluster of catchments with similar baselevel history. Finally, we compared channel segments adjacent to hillslope failures with segments far from failures. Central Belt channels show greater absolute increases in steepness adjacent to hillslope failures, but relative increases in steepness are consistent between the Central Belt and Coastal Belt.
Our preliminary results suggest that Central Belt channels are steeper and narrower than Coastal Belt channels, but that the lithological influence on steepness is difficult to disentangle from the effects of spatially variable erosion rates. We are continuing to map in-channel boulder size distributions to assess the relative importance of intra- vs. inter-lithologic variability in setting boulder concentrations and landscape form.
Besides long-term monitoring in changes of thermal state of permafrost and active layer thickness, the knowledge of permafrost distribution at very fine scales (tens of meters) in discontinuous permafrost is still largely unknown in Qinghai-Tibet Plateau (QTP). A permafrost island was found by using geophysical investigations in the Heihe River Basin in northeastern QTP. Permafrost island was present at PT10 site beneath alpine steppe and coarse soil with a quality of gravel in surface soil (Fig. 1, Fig. 2). In contrast, permafrost is absent at SFGT site with density land cover area and relatively less gravel. The results showed that the ground surface temperature (5 cm) at PT10 site is lower in winter and higher in summer than the SFG site. The presence of permafrost is caused by soil conditions, especially by high thermal conductivity, based on field investigations. To address the controlling factors of permafrost presentences a 1D heat transfer model is used to compare the ground temperature difference between these two sites by only changing the soil conditions. +
Block-mantled hillslopes responding to river incision deliver large blocks of rock to channels. These blocks inhibit fluvial erosion by shielding the bed and reducing available bed shear stress. Block delivery by hillslopes in response to channel incision therefore feeds back on the boundary conditions felt by the hillslopes: larger numbers of blocks, or larger blocks, reduce the rate at which the hillslope boundary condition is lowering. This coupled set of feedbacks can lead to oscillatory behavior in both channels and hillslopes with periods of rapid channel incision interspersed with intervals of little to no incision. For a hillslope with a line supply of blocks (such as might originate from a resistant caprock overlying a less resistant layer), we expect that these feedbacks are strong only when the source of blocks is relatively close to the channel. Once the block source has retreated sufficiently far from the channel, blocks will weather away before reaching the channel and the oscillatory channel-hillslope feedbacks described above will cease. Our questions are 1) For how long after initial river incision through a caprock do oscillatory channel-hillslope feedbacks persist? and 2) How far must the block source retreat from the channel before such feedbacks become negligible?<br><br>We use the new BlockLab 2-D landscape evolution model to assess the spatial and temporal extent of oscillatory channel-hillslope feedbacks. We model a channel incising a lithological sequence consisting of a weak layer underlying a resistant caprock. Blocks from the caprock are delivered to the channel and inhibit river incision. We find that at early time, temporal variation in the erosion rate boundary condition felt by the hillslope is significant. As the resistant layer retreats further from the channel, variations in both the channel erosion rate and the resistant layer retreat rate decline. The rate of these reductions in variability with time is set by competition between 1) the ability of the hillslope to deliver multiple large blocks to the channel (a function of initial block size, block weathering rate, and the distance the blocks had to travel before arriving at the channel), and 2) the ability of the channel to overcome the erosion-inhibiting effects of blocks (set by fluvial discharge and the block erodibility coefficient). We find that after enough model time has passed, the resistant layer has retreated far enough from the channel that block effects on the channel are negligible and oscillatory channel-hillslope feedbacks no longer exist. This distance is primarily a function of initial block size and block weathering rate. Our results indicate that channel and hillslope evolution rates in block-mantled landscapes may be highly unsteady, depending on the strength of coupling between the channels and hillslopes.
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Breaking waves, especially plunging breakers, generate intense turbulence and is crucial in dissipating incident wave energy, suspending and transporting sediment in the surf zone. Therefore quantifying breaking-induced turbulence kinetic energy (TKE) is essential in understanding surf zone processes. Surf zone hydrodynamic data collected at the Large-scale Sediment Transport Facility (LSTF) at the U.S. Army Engineer Research and Development center were used here. One LSTF case, with irregular waves (3 s peak period), is examined here. This case resulted in dominantly plunging type of breaker. Waves and currents were measured simultaneously at 10 cross-shore locations and throughout the water column, with a sampling rate of 20 Hz. In order to separate orbital wave motion from turbulent motion, an adaptive moving average filter is developed, involving a 5-point moving average, with additional 3-point moving average at sections with more fluctuations. This adaptive moving average filter is able to maintain more wave energy as compared with the results from 7-point moving average, while resolve more turbulence energy as compared with the result from 5-point moving average.
The TKE was calculated based on the resolved turbulence. Large TKE was generated at the water surface associated with wave breaking and dissipated rapidly downward. The TKE decreased nearly one order of magnitude downward within 15 cm. The TKE reached a minimum value at approximately 50%-80% of the water depth, and increased towards the bottom due to the generation of bed-induced turbulence. The TKE flux during wave crest and tough indicate that, at the bottom and middle layers of the water column, the TKE is transported dominantly onshore, while for the top layer, it is transported mostly offshore. +
By using a fixed-mesh approach, morphodynamic models have some difficulty to predict realistic equilibrium hydraulic geometries with vertical banks. In order to properly account for bank erosion without resorting to a complicated moving mesh algorithm, an immersed boundary approach that handles lateral bank retreat through fix computational cells is needed.<br>
One of the main goals of the FESD Delta Dynamics Collaboration is developing a tested, high-resolution quantitative numerical model to predict the coupled morphologic and ecologic evolution of deltas from engineering to geologic time scales. This model should be able to describe the creation and destruction of deltas made of numerous channels, mouth bars, and other channel-edge features, therefore requiring an approach that is able to deal with the disruption, destruction, and creation of sub-aerial land. In principle, these sub-aerial land surfaces can be randomly distributed over the computational domain. <br>
We propose a new approach in Delft3D based on the volume of fluid algorithm, widely used in the literature for tracking moving interfaces between different fluids. We employ this method for implicitly tracking moving bank interfaces. This approach easily handles complicated geometries and can easily tackle the problem of merging or splitting of dry regions characterized by vertical vegetated banks. +
By using spatially-varying estimates of seabed bottom drag (z0) the performance of ocean current and tide numerical models may be improved. To an extent, the seabed database dbSEABED is able to supply these values from data on the seabed materials and features. But then adjustments for varying dynamic (wave, flow) conditions are also required. So the data and model must work closely together. We developed methods for calculating inputs of z0 for circulation models in this way. Preliminary outputs from this new globally capable facility are demonstrated for the NW European Shelf region (NWES). +
Cellular automata models have gained widespread popularity in fluvial geomorphology as a tool for testing hypotheses about the mechanisms that may be essential for the formation of landscape patterning. For instance, studies of braided rivers using cellular automata modeling suggested that erodible banks are an essential characteristic for formation of the braid-plain morphology. In wetlands with emergent vegetation and complicated flow patterns, distilling the relevant, nonlinear interactions to a relatively simple set of rules that can be used in cellular automata modeling poses challenges, but the advantage of doing so lies in the ability to perform sensitivity analyses or examine system evolution over millennia. Here I show how a hierarchical modeling strategy was used to develop a cellular automata simulation of the evolution of a regular, parallel-drainage patterned landscape in the Everglades. The Ridge and Slough Cellular Automata Landscape model (RASCAL) suggested that this landscape structure is stable only over a small range of water-surface slopes (the driving variable for flow)—a result that both explains the limited distribution of low-gradient parallel-drainage systems worldwide and would likely have not been detected had a non-hierarchical CAM been used. Additional sensitivity analyses with RASCAL show how interactions between flow, vegetation, and sediment transport can lead to a wide variety of other regular and amorphous landscape patterns, depending on the relative strength of physical and biological feedbacks. Comparisons between RASCAL and well-known CAM models of braided stream dynamics raise interesting questions about the level of complexity that need to be incorporated into models of transitional (low- to high-energy) environments such as wet meadows and small/intermittent streams. +
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Changes in landscape structure are known to affect species macroevolution largely by altering habitat connectivity. Species can disperse across a greater area when habitats expand. Habitat fragmentation reduces gene flow and increases rates of speciation. Conversely, a shrinking habitat increases the likelihood of species extinction.
We integrated macroevolution processes (dispersal, speciation, and extinction) into the landscape evolution modeling toolkit called Landlab. Here, we present a new Landlab component, BiotaEvolver that tracks and evolves the species introduced to a model grid. In one model, surface process components evolve the landscape and BiotaEvolver evolves the species in response to topographic change or other characteristics of the model set by the user. BiotaEvolver provides a base species and users can subclass this object to define properties and behaviors of species types.
We demonstrate BiotaEvolver using scenarios of drainage rearrangement and stream species. Stream captures and high macroevolution process rates occurred within a limited combination of parameters and conditions in hundreds of model runs. The number of species increased most rapidly after a response period following a perturbation. Species numbers declined then became stable after this period. +
Changes in upstream land-use have significantly transformed downstream coastal ecosystems around the globe. Restoration of coastal ecosystems often focuses on local-scale processes, thereby overlooking landscape-scale interactions that can ultimately determine restoration outcomes. Here we use an idealized bio-morphodynamic model, based on estuaries in New Zealand, to investigate the effects of both increased sediment inputs caused by upstream deforestation following European settlement and mangrove removal on estuarine morphology. Our results show that coastal mangrove removal initiatives, guided by knowledge on local-scale bio-morphodynamic feedbacks, cannot mitigate estuarine mud-infilling and restore antecedent sandy ecosystems. Unexpectedly, removal of mangroves enhances estuary-scale sediment trapping due to altered sedimentation patterns. Only reductions in upstream sediment supply can limit estuarine muddification. Our study demonstrates that bio-morphodynamic feedbacks can have contrasting effects at local and estuary scales. Consequently, human interventions like vegetation removal can lead to counterintuitive responses in estuarine landscape behavior that impede restoration efforts, highlighting that more holistic management approaches are needed. +
Changing sea level and ice volume since the Last Glacial Maximum (LGM, 26-19 ka) has been an intensively studied topic for decades, and yet we have still not been able to adequately close the water volume budget at the LGM. At the LGM, global sea level was depressed by approximately 125-135 m relative to the present level. Past researchers have attempted to account for the storage of this water as an estimated 52*106 km3 of land-based ice. However, relative sea level, ice sheet morphology, and isostacy studies at local and regional scales have been unable to reasonably place high enough ice volumes to meet this global total, accounting for only approximately 120 m of sea-level change. This discrepancy has resulted in the so-called ‘missing ice’ problem.
We propose that some portion of this ‘missing’ water was stored not as ice, but in lakes and groundwater. Thus far, no studies have attempted to determine the volume of water stored in lakes and groundwater at the LGM. Groundwater storage could potentially account for a large volume of water, reducing the missing water volume by a significant margin. Differing topography and recharge rates may have resulted in greater terrestrial water storage, which can help us to close the water budget. Indeed, many large proglacial and pluvial lakes are known to have existed and may indicate higher groundwater levels. Furthermore, assessing groundwater levels at 500 year intervals from the LGM to the present day can provide insights into changes in water storage and inputs to the ocean over time.
It is challenging to assess groundwater levels with precision since various factors, including evapotranspiration, topography, and sea level all play a role in controlling groundwater level at a particular location. However, a recent model (Reinfelder et al., 2013) was able to estimate modern groundwater levels on a global scale. By using this model in combination with modelled topography and climate data for the LGM and each 500 year time step, we are able to compare the volume of water stored in the ground from the LGM to the present day to test whether groundwater would be a viable reservoir for LGM water storage. The model provides depths to water table, thus allowing computation of changing storage volumes.
The model covers the entire globe at a resolution of 30 arc-seconds. The large datasets and iterative nature of the model require MSI’s computational power to perform the calculations. So far, preliminary results have shown that over a metre of additional sea-level equivalent water was stored in the ground at the LGM.
Chemical erosion of regolith is of wide interest due to its role in Earth’s topographic evolution, the supply of nutrients to soils and streams, and the global carbon cycle. Theory and experiments suggest that chemical erosion rates (W) should be strongly controlled by physical erosion rates (E), which affect W by removing weathered regolith and regulating mineral supply rates to the regolith from its underlying parent material. A global compilation of field measurements reveals a wide range of relationships between W and E, with some sites exhibiting positive relationships between W and E, some exhibiting negative relationships, and others exhibiting a flat relationship within uncertainty. Here we apply a numerical model to explore the variety of W-E relationships that can be generated by transient perturbations in E in well-mixed regolith.
Our modeling results show that transient relationships between W and E during erosional perturbations can strongly deviate from steady-state relationships. These deviations ultimately result from the time lag in changes in W following imposed changes in E. As a consequence of the lag, a hysteresis develops in plots of W versus E during transients in E. This yields a positive relationship between W and E at some times during a transient perturbation, a flat relationship at other times, and a negative relationship at other times. The shape and duration of these transient hystereses can be modulated by climate and lithology, as the lag time increases linearly with a characteristic regolith production time and decreases with a characteristic mineral dissolution time, both of which are affected by climatic and lithologic factors. Our results show that even in the absence of variations in climate and lithology, however, a range of W-E relationships can be generated by a single perturbation in E. To the extent that these model results capture the behavior of chemical and physical erosion in natural landscapes, these results may aid interpretation of field measurements of W and E.
Climate change and reduced water availability in arid regions has important implications for how channels will change as they adjust to a new steady-state characterized by different riparian populations. While much study has been devoted to the effects riparian vegetation has on fluvial processes (Tal & Paola, 2010; Osterkamp & Hupp, 2010; Corenblit et al., 2009), the complexity of natural channels obscures exactly how these feedbacks modify long-term channel evolution, making prediction of the larger impacts of vegetation change on channel morphology difficult. In order to isolate the impact vegetation has on morphology, single channels that are variably vegetated along their length are desirable for study because flow conditions and long-term sediment flux change minimally between major tributaries (Bertoldi et al., 2011). Comparisons made in such dryland channels in Henry Mountains, Utah, USA, where groundwater springs juxtapose vegetated and un-vegetated reaches allow us to examine two hypotheses: first, that disruptions to normal fluvial processes caused by in-channel vegetation produce distinct morphological responses to floods at the scale of single flood events, and, second, that these responses accumulate on the timescale of multiple floods to produce channel morphologies in vegetated reaches that are fundamentally different from those in unvegetated reaches. Analysis of repeat airborne LiDAR data for these areas provides an opportunity to quantify morphological parameters and elevation differences, and to attempt to correlate these metrics with quantitative metrics of vegetation. Field observations from October, 2017 in this region agree with the results of LiDAR analyses and indicate that the presence of dense vegetation seems to produce more uniform cross-sectional shape with narrow, deeply incised channels supported by intense rooting on banks, and a longitudinal profile that is characterized by frequent vegetation-supported, non-bedrock knickpoints. Future work will involve modelling flood flows to determine the degree and areal extent of channel reworking during a flooding event and the influence of vegetation on shear stress for comparison with LiDAR differencing results.
Climate change has altered the frequency and intensity of hydrologic events like precipitation and flood, yielding vulnerability of communities dwelling in coastal and inland flood plains. Flood prediction and mitigation systems are necessary for improving public safety and community resilience all over the world at Country, continental and global scales. Numerical simulation of flood event has become a very useful and commonly used tool for studying and predicting flood events and susceptibility. One of the major challenges in hydraulic modeling is accurate description of river and floodplain geometries. The increased availability of high-resolution DEMs (e.g. LiDAR data) alleviates this challenge for floodplains but (with the exception of blue/green LiDAR surveys) not for river channels. Here we investigate the effect of river bathymetry data on numerical simulations of flood events. Two numerical models (GSSHA and Mike 21) were used for comparison in the results. Three channel geometry inputs were simulated for three river reaches of different sizes: DEM-captured elevation (water surface), hydraulic geometries (empirical estimation), and observed river bathymetry. +
Climate change has led to unprecedented precipitation events in the hyper-arid Atacama Desert of Northern Chile. On the coast of the El Salado watershed, legacy mine tailings infilled the watershed-ocean connection, while the river channel has been altered both by tailings and urbanization. Loss of life and destruction of infrastructure in a large flood event in 2015 resulted from the coupling of anthropogenic geomorphic changes with unusual climate events. We carry out unsteady two-dimensional simulations fully coupled with the sediment concentration to identify the influence of tailing deposits. The analysis incorporates high-resolution topography data from both pre- and post-flood, where the pre-flood scenario represents the presence of tailings, and the post-flood scenario reflects partial erosion of these deposits. Results highlight the important role of topographic alterations in enhancing the hazard to people and critical infrastructure.
Additionally, an upscaling methodology based on porosity is presented for an urban flood simulation in Santiago de Chile, adjacent to the Andean foothills. In this model, topographic information is included at the subgrid-level to optimize CPU time at the cost of some loss in the accuracy of the results. We analyze how accuracy is affected by gradually increasing grid resolution, specifically when estimating flood extent and associated hazards. Results suggest that the cell size can be increased up to the street width, capturing the main flow paths and hazards while significantly reducing the CPU time employed by classical models.
The integration of an upscaling scheme to model concentrated flows coupled with surface dynamics is particularly valuable for comprehensively assessing flood hazards, meeting real-time decision-making needs. +
Climatically controlled surface processes redistribute mass and modulate solid-Earth stress fields, potentially driving changes in tectonics. Examples of climatically-influenced tectonics exist in glaciated orogens, however this phenomenon has not been well documented in fluvial systems. Here we describe a previously undiscussed feedback between hillslope and fluvial processes that buffers climate-tectonic interactions, helping to explain the dearth of observations of climatically influenced tectonics in fluvial systems. Using remote sensing and field investigation, we quantify production, deposition, and transport of landslide sediments resulting from the 2009 Typhoon Morakot in Southern Taiwan, which delivered record-breaking rainfall triggering more than 22,000 landslides across 7800km^2. An annual landslide catalog facilitates use of area-volume scaling to estimate amount of landslide material distributed across a strong northward gradient in tectonic uplift in Southern Taiwan. Landslide volume and frequency exhibit similarly positive trends with distance from the southern tip of the orogen. Exploiting a wealth of publicly available imagery and elevation data, we map sediment aggradation throughout fifteen drainage basins and observe 10’s of meters of aggradation with the distribution tightly coupled to areas of greatest exhumation. Sediment transport modeling across the orogen suggests that areas of highest exhumation will be inundated with sediment over three orders of magnitude longer than less exhumed basins. Estimating the frequency of events like Typhoon Morakot, we expect the most active basins in the study area to have their channels buried by landslide sediment for up to 50% of any given time period, while less active basins will be able to incise nearly 100% of the same time period. This feedback suggests that as landscapes become more exhumed, the erosional buffering effects of extreme storms and earthquakes that cause widespread landslides are amplified, driving a negative feedback between climate driven surface processes and tectonics in fluvial systems.
Close to half a billion people live in deltaic regions worldwide, including in a number of mega-cities. River deltaic landforms act as central locations for agricultural production, livestock farming, and hydrocarbon extraction. The understanding of riverine sediment fluxes and associated delta morphology changes, aids in planning engineering works such as identification of flood-prone areas, installation of coastal defense structures, dam construction, and restoration activities of extensively altered areas.
The overarching goal of the study is to elucidate the interconnectivity between fluvial fluxes and associated landform changes in large global deltas. The following research questions are investigated: (1) Are changes in fluvial sediment flux to the delta directly linked to changes in delta morphology? (2) What are the magnitudes and trends of riverine sediment fluxes that can be expected throughout the 21st century? A multifaceted research approach combining (a) satellite remote sensing analysis of delta morphology changes (progradation/degradation), and (b) numerical modeling of riverine water and sediment fluxes, is used on selected large river deltas globally.
Major outcomes of the study indicate that the synoptic capability of remote sensing provides a useful reconnaissance tool to infer on the rates at which the deltas change. An overview of global delta change is presented with a special focus on case studies with severe degradation and interesting flux estimates. The outcomes of the study yield a number of novel insights into fluvial fluxes of the 21st century and transform our analytical capabilities for studying delta morphology change and sediment flux dynamics in large rivers, globally. +
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Close to half a billion people live on deltas, many of which are threatened by flooding. Delta flooding also imperils valuable ecological wetlands. In order to protect deltas, it is critical to understand the mechanisms of flooding and evaluate the roles of different forcing factors.
Delft3D, a widely used 3D hydrodynamic and sediment transport model, has been applied to the Wax Lake Delta in Louisiana in order to explore the impacts of wind, waves, and vegetation during extreme conditions. Using wind and pressure field inputs of Hurricane Rita in 2005, the simulation indicates that the deltaic hydrodynamics and morphologic changes are determined by the interactions of all three factors. Wind shows a large impact on water level and velocity, especially in the shallow water zone, where water level increases by ~2 m and water velocity increases by ~1 m/s. Waves, on the other hand, demonstrate almost no effect on water level and velocity, but significantly increase sediment transport due to increasing bed shear stress. Sediment deposition occurs primarily at the coast, when water floods higher elevated land and velocities start to decrease, leading to a significant drop in bed shear stress. Vegetation, a critical factor that influences deltaic hydrodynamics, is represented in the model by adding 2D roughness to the bed. The vegetated wetland and its surrounding area show a notably different pattern in erosion and deposition compared to the unvegetated simulations. The vegetated islands receive significant deposition, while adjacent channels become much more eroded because water is routed through channels when the surrounding vegetated islands are more difficult to erode.
To take into account the impact plant roots have on the soil (increase in soil strength and therefore an effectively reduction in erosion), a new root routine has been added to Delft3D. This routine mimics this process by increasing the soil critical shear stress required to reduce erosion. The modeled results indicate that more deposition appears on the vegetated root area, while more significant erosion simultaneously occurs at those sides of these islands that are facing the ocean. This illustrates that, while vegetation can protect land from erosion, it can also intensify erosion in the surrounding area. Therefore, the use of natural vegetation as a protection against coastal erosion processes requires more research.
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Coastal aquifers, vital freshwater sources for over a billion people globally, often face saltwater intrusion, especially in island freshwater lenses. Despite extensive studies on sea-level rise, storm surges, and over-pumping, the impact of droughts on coastal aquifers, particularly barrier island aquifers reliant solely on aerial recharge, remains understudied. Understanding recharge and salinization processes is crucial for sustainable water resource management amid potential climate change impacts. This study introduces a novel approach to assess a freshwater lens's response to drought conditions, incorporating in-situ observations, geophysical measurements, and numerical modeling. Examining a Northeastern U.S. barrier island's shallow unconfined aquifer during the 2020 drought, the research reveals a reduction in the freshwater lens volume during reduced recharge, emphasizing the vulnerability to droughts and the potential for recovery. Comprehensive studies in this area are essential for informed water resource management. +
Coastal areas globally face increasing threats from intensified weather events and rising sea levels, leading to challenges such as fluctuations in groundwater levels and salinity intrusions. This presents a significant concern for the Department of Defense (DoD), which manages over 1700 coastal sites worldwide, with several facing heightened vulnerability to these environmental changes. We aim to evaluate the susceptibility of DoD coastal sites to sea-level rise and saltwater intrusion, utilizing the Defense Regional Sea Level (DRSL) database that includes projections for five global sea-level rise scenarios and extreme water events. To achieve this, we have adopted a two-pronged strategy. First, we conduct an in-depth vulnerability analysis considering the current situation, sea-level trends, and topographic elevation. The vulnerability analysis aids in selecting sites for detailed further investigation. Subsequently, we formulate Reduced Order Models (ROMs), including Dynamic Mode Decomposition (DMD) and the Unified Fourier Neural Operator (U-FNO) for sites with a range of vulnerabilities. DMD and U-FNO are selected for their efficiency, enabling faster execution and thousands of runs to assess site vulnerability under future climate scenarios through the century's end. Trained on site-specific mechanistic models, both DMD and U-FNO accurately simulate current groundwater and salinity conditions, providing reliable forecasts of future impacts on DoD sites, utilizing data from the DRSL database and climate model projections. This approach clarifies the immediate risks and facilitates the transfer of essential knowledge throughout DoD's extensive network, fostering a deep understanding of global coastal vulnerabilities. Ultimately, this informs the development of targeted, effective mitigation strategies, safeguarding critical defense infrastructure against the impacts of climate change. +
Coastal communities facing erosion require beach maintenance for property protection and recreation. While some communities may have the means to pay for sand nourishment, others may benefit from their neighbor’s alongshore-transported sediments. If communities expect to free-ride off beach nourishment carried out by a neighbor, incentives favoring inaction may lead to narrower beaches overall. Recent work coupling human and natural systems found that coordination between neighboring communities is preferable economically to each community acting independently. Contrasting past work, we model two communities acting without knowledge of a jointly determined economically optimal nourishment program. Instead, nourishment behavior is triggered by a traditionally imposed minimum beach threshold and bounded by a predefined seaward edge. The goal is not to limit sand loss; rather, nourishment decisions are based on separate or joint benefit-cost assessments for two communities. We compare two management approaches: (1) sequential/decentralized decisions, where the updrift community chooses first and the downdrift community reacts second; and (2) simultaneous/coordinated decisions where both communities make a joint choice. We test how variable up/downdrift property values affect outcomes under these two approaches. Results suggest that communities do not always favor coordinating simultaneously. When both up- and downdrift communities have high property values, sequential/decentralized decisions are favored, leading to updrift over-nourishment to maintain beach width. This enhances alongshore sediment availability, thus providing higher marginal benefits for downdrift communities whom under-nourish. When the property values of the updrift community are low and the property values of the downdrift community are high, however, the outcome results in abandonment of property by the updrift community instead of coordinating with the downdrift community. Overall, we find that the distribution of property values across neighboring communities can be a driver for both strategy selection and the decision-making process.
Coastal ecosystems, infrastructure, and human health are vulnerable to extreme precipitation, flooding, and water-quality impacts. Integrating a hydrologic model (WRF-Hydro) into the Coupled Ocean Atmosphere Wave Sediment Transport modeling system (COAWST), which includes ocean (ROMS), atmosphere (WRF), surface-wave (SWAN, WAVEWATCHIII), sediment (CSTMS), and sea-ice components, offers the potential to investigate compound flooding and the dispersal of contaminants, sediments, and other material at the land-ocean boundary. Here, the new model coupling is described, along with an application to Hurricane Florence.
Extreme precipitation during Hurricane Florence, which made landfall in North Carolina in September, 2018, led to breaches of hog-waste lagoons, coal-ash pits, and wastewater facilities. In the weeks following the storm, historic freshwater discharge carrying pollutants, sediment, organic matter, and other debris was released to the coastal ocean, contributing to beach closures, algal blooms, hypoxic conditions, and other ecosystem impacts. The Cape Fear river basin, North Carolina’s largest watershed, is used as a case study. Progress in model coupling applied to this region includes (1) a two-way coupled ROMS and WRF-Hydro simulation in which fluxes between the ocean and hydrology models are computed from the pressure gradient at the ocean-land boundary, and (2) a one-way coupled simulation in which a WRF-Hydro simulation provides river point-source forcing in ROMS. The work as part of the one-way coupled simulation demonstrates how the pathways of land-sourced tracers can be tracked in the coastal ocean; a suite of different flood and wind scenarios are studied and used to map the arrival and departure times of threshold-exceeding contaminants that contribute to swimming advisories and other impacts. Next steps are described for continuing the ocean-hydrology model coupling efforts to improve forecasts of compound flooding and water quality impacts.
Coastal erosion and wetland loss are affecting Louisiana to such an extent that the loss of land between 1932 and 2016 was close to 5,000 km2. To mitigate this decline, coastal protection and restoration projects are being planned and implemented by the State of Louisiana, United States. The Louisiana Coastal Master Plan (CMP) is an adaptive management approach that provides a suite of projects that are predicted to build or maintain land and protect coastal communities. Restoring the coast with this 50-year large-scale restoration and risk reduction plan has the potential to change the biomass and distribution of economically and ecologically important fisheries species in this region. However, not restoring the coast may have negative impacts on these species due to the loss of habitat. This research uses an ecosystem model to evaluate the effects of plan implementation versus a future without action (FWOA) on the biomass and distribution of fisheries species in the estuaries over 50 years of model simulations. By simulating effects using a spatially-explicit ecosystem model, not only can the changes in biomass in response to plan implementation be evaluated, but also the distribution of species in response to the planned restoration and risk reduction projects. Simulations are performed under two relative sea level rise (SLR) scenarios to understand the effects of climate change on project performance and subsequent fisheries species biomass and distribution. Simulation output of eight economically
important fisheries species shows that the plan mostly results in increases in species biomass, but that the outcomes are species-specific and basin-specific. The SLR scenario highly affects the amount of wetland habitat maintained after 50 years (with higher levels of wetland loss under increased SLR) and, subsequently, the biomass of species depending on that habitat. Species distribution results can be used to identify expected changes for specific species on a regional basis. By making this type of information available to resource managers, precautionary measures of ecosystem management and adaptation can be implemented.
Coastal flooding is an increasingly prominent hazard in the northeast United States, causing both property damage and disruption of daily life. Tide gauge records provide historical water level data and are used to estimate current return periods of storm tides (tide level plus storm surge) from both hurricanes and nor’easters. We calculate the interannual joint probability exceedance curves for select tide gauges in the Philadelphia, New Jersey, and New York City megaregion using the quasi‐nonstationary skew surge joint probability method (qn‐SSJPM) from Baranes et al. (2020). Analysis of the probability of storm tides for hurricane versus nor’easter seasons will be discussed, including geographic variations of the storm tide exceedance curves. Results from this study can be compared to storm climatology and used by social scientists and city planners to assess risk associated with the flood hazard in the area. By understanding the ways that probability of storm tide in summer and winter may change in the future, communities can better plan and prepare for future hazards. +
Coastal foredunes are dynamic ecogeomorphic landforms that provide increased resilience for both natural habitats and developed communities. Despite their dynamic nature, dunes can be stabilized with vegetation and are therefore an adaptable nature-based solution that can be utilized for flood risk management. However, coastal habitats are rapidly changing and require modeling support to understand the effectiveness of vegetated dunes under changing environmental conditions. Most existing dune morphology models incorporate vegetation implicitly, using percent cover or plant height to affect sediment accretion and erosion, rather than explicitly simulating ecological processes such as mortality and dispersal. A coupled modeling approach that integrates process-based dune and vegetation models is necessary to better understand plant-sediment-water interactions and manage coastal dune systems. Through this work, we demonstrate the coupling of AeoLiS, a process-based aeolian sediment transport model with GenVeg, a generalized vegetation model under development in Landlab and parameterized with growth, functional morphology, and sand accretion of native and non-native plant species from a common garden experiment in Nehalem Bay State Park, Oregon. This work highlights how vegetation morphology affects dune building and resilience to better inform dune management and restoration actions. +
Coastal landscapes are dynamic, subject to drowning by sea level rise, erosion driven by alongshore transport, and inundation by large storm events. Coastlines are also highly developed. Along the U.S. coasts, communities continuously develop and implement beach management strategies to protect coastal infrastructure and maintain recreational value. From sediment source to sink, littoral cells often span many coastal communities. Even as physical processes grade along these littoral cells, separate communities along this coast possibly enact different management strategies. By expanding upon an existing alongshore-coupled dynamic model of coastal profile and barrier evolution, we analyze the feedbacks between alongshore and cross-shore processes as well as human response to local shoreline change across multiple communities within the same littoral cell. Incorporating the possibility of intercommunity cooperation allows us to valuate variable coastal resilience strategies for communities within a littoral cell, particularly the benefit of coordinated versus uncoordinated activities. Both sediment transport processes and a cost-benefit analysis for each community determine optimal beach management strategies. Model results provide insights useful for understanding coastal processes and planning, allowing for more robust coastal management decisions, which depend upon future rates of sea-level rise. +
Coastal-plain depositional systems such as fluvial deltas are archives of past external (allogenic) forcing, such as sea-level variations, and their evolution can be described by two geomorphic boundaries: the alluvial-basement transition or upstream boundary, and the shoreline or downstream boundary. Patterns of landward/seaward migration of the shoreline (i.e., transgression/regression) and the alluvial basement transition (i.e., coastal onlap/offlap) in the rock record are often used for reconstruction of past sea-level changes. Theories for stratigraphic interpretation, however, need to be adapted to deal with internal (autogenic) processes that could play a significant role, but are to date largely unexplored. In particular, in-situ organic matter accumulation via plant growth has generally received little attention despite accounting for a significant volume fraction in most fluvio-deltaic plains and likely affect their response to sea level variations. To fill this knowledge gap, we develop a geometric model for the long-profile evolution of a fluvio-deltaic environment that accounts for sea-level cycles and organic sediment dynamics. The model assumes that sedimentological processes (i.e., inorganic and organic sedimentation) operate to preserve a linear geometry for both the delta plain or topset, and the subaqueous offshore region or forest. Changes in topset length can occur via shoreline transgression/regression, or coastal onlap/offlap, and the magnitude and timing of these changes can be directly related to the amplitude, phase and frequency of the sea-level variations. The model predicts that the maximum organic fraction occurs when the organic matter accumulation rate matches the accommodation rate, an observation consistent with field observations from coal geology. Further, we find that organic matter accumulation during the topset aggradation and organic matter erosion and decay during topset degradation generally results in substantial increase in the coastal onlap/offlap amplitude, which can result in an overestimation of the sea-level variations. These results are consistent with the discrepancy in sea-level amplitude reconstructions between sequence stratigraphic models and geochemical models over the Cretaceous.
Coasts are among the most intensely used environments on the planet, but they also present dynamic and unique hazards including flooding and erosion. Over the next century, these risk are likely to intensify across many coastal localities due to changes in environmental conditions, including sea level rise and changing wave climate patterns as induced by climate change. Managing these hazards and protecting vulnerable areas is challenging and requires an understanding of the behavior of coastal systems and longer-term prediction of their future evolution in the face of a changing climate.
Many existing one-dimensional coastal evolution models can effectively simulate the evolution of coastal environments. However, due to their 1D nature, they are unable to model the additional and combined effects of a variable water level and sea level rise. Hence, a new model, the Coastline Evolution Model 2D (CEM2D), has been built that is capable of simulating these processes.
CEM2D has been built from the 1D parent model – the Coastline Evolution Model (CEM) - that was originally developed by Ashton et al. (2001), Ashton and Murray (2006) and Valvo et al. (2006). CEM2D has been developed accordingly to the underlying assumption and mathematical framework of CEM, but applied over a two-dimensional grid. At the core of this framework is the calculation of longshore sediment transport rates using the CERC formula and Linear Wave Theory. Wave shadowing calculations are also used to ensure that sediment transport is negligible in shadowed areas. The distribution of material across the shoreface is controlled by a steepest descent formula that routes sediment from higher to lower elevations across the domain according to defined thresholds, whilst maintaining the average slope angle.
CEM2D provides a step forward in the field of coastal numerical modelling. It fills a gap between one-dimensional models of shoreline change that provide insights into the fundamental processes that control coastal morphodynamics and more complex and computationally expensive two- and three-dimensional models that are capable of simulating more complex processes and feedbacks. Key applications of CEM2D include improving our understanding of the meso-scale morphodynamic behaviour of coastal systems, their sensitivities to changing environmental conditions and the influence that climate change may have on their evolution over centennial to decadal timescales.
Conservation biologist, modeler, blogger, nature photographer, animal friend, swing dancer, Ecopathologist… All these describe Adrian Dahood, who tragically lost her life along with 33 others in a diving boat fire off the coast of California. She will be remembered fondly, and her legacy as a scientist and policy expert will remain alive within the scientific community. Please check out her photos, blogs, postcards and scientific papers, and I hope she can bring a smile to your face as well. +
Coupled process-based numerical models have the potential to greatly enhance our understanding of the drivers of coastal change by allowing for detailed simulations of the processes involved within each model core of the coupling. However, producing accurate hindcasts and forecasts with these coupled frameworks can be challenging due to a wide array of parameters that interact nonlinearly across and within the individual model cores and the potentially substantial computational cost that limits both the number and duration of simulations that can be reasonably performed. Additionally, many model parameters (e.g., wave asymmetry and skewness or sediment transport coefficients) that are critical for model calibration are unitless coefficients in the model formulations and thus cannot be readily measured in the field. Here, we use Windsurf, a coupled beach-dune modeling system that includes Aeolis, the Coastal Dune Model, and XBeach, paired with two surrogate neural network models, to produce a pair of hindcasts and forecasts to replicate observed modes of dune and beach morphological change on a developed barrier island on the US Atlantic coast (Bogue Banks, North Carolina). The first neural network aids in the calibration process by allowing for the prediction of Windsurf’s error surface over thousands of potential parameterizations to rapidly identify a potential best calibration before actually running the model. Windsurf is then run within a genetic algorithm to further hone the collection model parameter settings. Once Windsurf is finished running, we use the output to train a second neural network which contains a Long Short-Term Memory (LSTM) layer to produce five-year forecasts of dune crest height and dune toe elevation. We test our results by comparing them to observed data collected in the field between 2016-2020 using Real-Time Kinematic Global Positioning System (RTK-GPS) and find our forecasts (from the hindcasts) produce reasonably accurate predictions of dune morphology change at interannual scale.
Coupling models from different domains (e.g., ecology, hydrology, geology, etc.) is usually difficult because of the heterogeneity in operating system requirements, programming languages, variable names, units and tempo-spatial properties. Among multiple solutions to address the issue of integrating heterogeneous models, a loosely-coupled, serviced-oriented approach is gradually gaining momentum. By leveraging the World Wide Web, the service-oriented approach lowers the interoperability barrier of coupling models due to its innate capability of allowing the independence of programming languages and operating system requirements. While the service-oriented paradigm has been applied to integrate models wrapped with some standard interfaces, this paper considers the Basic Model Interface (BMI) as the model interface. Compared with most modeling interfaces, BMI is able to (1) enrich the semantic information of variable names by mapping the models’ internal variables with a set of standard names, and (2) be easily adopted in other modeling frameworks due to its framework-agnostic property. We developed a set of JSON-based endpoints to expose the BMI-enabled models as web services, through storing variable values in the network common data form file during the communication between web services to reduce network latency. Then, a smart modeling framework, the Experimental Modeling Environment for Linking and Interoperability (EMELI), was enhanced into a web application (i.e., EMELI-Web) to integrate the BMI-enabled web service models in a user-friendly web platform. The whole orchestration was then implemented in coupling TopoFlow components, a set of spatially distributed hydrologic models, as a case study. We demonstrate that BMI helps connect web service models by reducing the heterogeneity of variable names, and EMELI-Web makes it convenient to couple BMI-enabled web service models. +
Crop models are used to simulate crop development, yield and irrigation requirements, but their performance can be influenced by environmental and management conditions such as climate and irrigation strategies. Hence, performing a sensitivity analysis on these models is crucial to identifying influential parameters which informs model calibration. Here, we performed a global sensitivity analysis (Morris Screening method) on crop yield and irrigation on 34 crop parameters using the AquaCrop-OSPy model. This analysis is done for corn in Sheridan, KS under different water treatments (irrigated and rainfed) for varying meteorological scenarios represented by past years annual precipitation (normal-2021, wet-2019 and dry-2002). Thresholds of 0.3t/ha and 20mm are used for yield and irrigation respectively to identify influential parameters. Overall, parameter importance varies for yield and irrigation: parameters related to biomass and yield, root and canopy development, and irrigation strategy are the most influential for yield while those related to irrigation strategy, and root and canopy development are the most influential for irrigation. In general, yield was responsive to fewer parameters in rainfed conditions and simulations with drier meteorological conditions. The normal and wet scenarios have similar influential parameters with varying order of influence for yield under irrigated conditions. However, under rainfed conditions, the normal scenario only has two influential parameters (minimum effective rooting depth and the excess of potential fruits, a parameter related to biomass and yield), while 8 parameters related to biomass and yield production, water stress, and root development are influential during the wet scenario. Yield under irrigated conditions during the wetter years (receiving normal and high precipitation) tends to be impacted by water and temperature stress parameters. The influential parameters will further be analyzed using the Sobol method to calculate each parameter's influence on the output’s variance and interaction with other parameters, and ultimately used to guide model calibration.
Debris flows pose a hazard to infrastructure and human life. However, predicting debris flows remains a challenge due to uncertainty in initiation mechanisms, and the difficultly in appropriately parameterizing the resistance equations that describe flow velocities. Additionally, one of the limitations to progress in modeling debris-flow timing is the lack of empirical data from natural watersheds that can be used for parameter estimation and validation of predictions. Most quantitative measurements of debris flows are conducted in flumes, or unique watersheds where debris flows are known to occur annually, both of which suggest particularly remarkable conditions that may not reflect the majority of conditions where debris flows are manifested. This research addresses those challenges by using measured debris-flow timing in nine watersheds that were burned by a wildfire in 2009 to calibrate and test debris flow model parameterizations. Debris-flow timing was captured using pressure transducers attached to the channel bed. We used a kinematic wave rainfall-runoff model that we developed in python using the landlab environment to model flow timing. We separated the nine study watersheds into two categories: calibration and testing. For the calibration watersheds, model parameters were estimated based on prior research and then changed iteratively using a storm with known rainfall to minimize an objective function of the observed and modeled flow timing. Following hundreds of model realizations, we arrived at a set of best-fit parameters for saturated hydraulic conductivity (Ks) and the Manning’s roughness parameter (n). We found that a single value of Ks could be used in each of the model watersheds because, following wildfires, this parameter is typically reduced to very low values with a relatively small variance. In contrast n varied systematically as a function of upstream contributing drainage area, and thus values of n could be estimated for uncalibrated basins. When Ks and n were applied to test basins without any calibration we found that a reasonable result in estimated debris-flow timing was attained. These results suggest that given the appropriate scaling estimates it may be possible to estimate debris-flow timing within minutes and to capture multiple debris-flow surges separated by several hours.
Debris flows pose a significant threat to downstream communities in mountainous regions across the world, and there is a continued need for methods to delineate hazard zones associated with debris-flow inundation. Here we present ProDF, a reduced-complexity debris-flow inundation model for rapid hazard assessment. We calibrated and tested ProDF against observed debris-flow inundation at eight study sites across the western United States. While the debris flows at these sites varied in initiation mechanism, volume, and flow characteristics, results show that ProDF is capable of accurately reproducing observed inundation extent across different geographic settings. ProDF reproduced observed inundation while maintaining computational efficiency, suggesting the model may be especially applicable in rapid hazard assessment scenarios. +
Debris flows, sediment laden gravity driven fluvial processes, are a common issue in Southern California. They often occur during peak streamflow, making precipitation an important predictor for debris flow activity. However, the low temporal sampling of precipitation data used to calculate streamflow is often insufficient to forecast peak flows accurately. Here, we evaluate the effect of precipitation data resolution on discharge using 30-minute IMERG-early data averaged over different time intervals to model streamflow. We apply the results to a dimensionless discharge threshold model to predict debris flow locations. The streamflow values were calculated with the Distributed Hydrology Soil Vegetation Model and the debris flow model was programmed to be compatible with the Basic Model Interface (BMI). BMI was selected for this project because it standardizes model coupling, which enabled a hydrologic driven landslide model to run efficiently. The landslide model follows Tang et al. (2019) to produce dimensionless discharge and debris flow threshold values for stream segments. This can be used to predict where we would likely see a debris flow based on the given streamflow data. We ran these models with precipitation data of different temporal resolutions and evaluated their effect on dimensionless discharge. The model was able to capture a portion of debris flows using higher temporal resolution precipitation data. Of the 138 stream segments evaluated, 122 were predicted to have a dimensionless discharge value above the calculated thresholds when using 30-minute data, which largely matched observations from aerial imagery. In contrast, lower temporal resolution data did not capture these results. Initial debris flow predictions using high resolution precipitation data coincide in stream segments that experienced landslides. We conclude that high resolution precipitation data is critically important for predicting debris flow events. +
Decision making is a cultural process fundamental to slowing environmental destruction in all its guises. Although crucial to understanding environmental decision making, working toward a viable interdisciplinary model that could be used across problems and sites is not without obstacles. In order for coupled models to capture realistic lag times and interactions between social choices and the environment, algorithms of decision making must incorporate the influence of spatial-temporal local differences. This is especially true for coupled human-earth system models or agent-based models designed to inform policy. Here we provide a case study from the Paraná Delta of Argentina where a neighborhood assembly fights against pollution in the delta caused by an engineering failure. We combine components of a decision making framework with concepts from cultural and geographic theory, and then filter the combination through ethnographic description and interpretation to track how local culture influences decisions, and hence, lag times between actions and outcomes. Although fundamental to human decision making processes, sociocultural dynamics are often left out of formal behavioral modules coupled to environmental models. Through this experiment, we expand the capacity of such a framework for carrying cultural meaning and social interaction. +
Degradation of ice-rich permafrost is caused by rapid Arctic warming. Likely this degradation already has altered the water balance by increasing runoff and flooding. But here we ask, how do the hydrological changes in river systems, in turn, affect the permafrost conditions? How does river flooding affects permafrost thermal state in floodplains and deltas? What if the timing of river flooding changes with Arctic warming?
We develop a first-order heat budget approach to simulate evolving river flood water temperature over the seasonal inundation period. Solar radiation, air temperature and wind control the different components of heat exchange between the atmosphere and the river water surface. An additional term specifically calculates the exchange of heat between the river water and the channel bed and subsurface. Then, this river and flood water temperature is coupled to the Control Volume Permafrost Model (CVPM), which models detailed thermal state of shallow permafrost. We apply the combined model to the Kuparuk river floodplain and delta, a medium-sized river system on the North Slope of Alaska. Results indicate that permafrost underlaying the floodplain warms during inundation, and the active layer thickness (ALT) can increase for more several meters with sustained standing water. Permafrost underlying the floodplain farthest laterally from the main channel is only warmed by the short-lived spring snowmelt flood. We find that earlier arrival of the spring freshet and associated earlier inundation onset, as well as the increase of river discharge can significantly increase subsurface permafrost temperature, and lead to the deepening of the active layer. The sedimentary characteristics of the deposits in the floodplain are an important controls on the response of permafrost thermal state to inundation. River corridors, especially in the continuous zone of permafrost in the Arctic, are increasingly vulnerable to future changes in timing and magnitude of freshwater flooding as a result of earlier spring snowmelt and river breakup, and increasing river discharge.
Delivery of large blocks of rock from steepened hillslopes to incising river channels inhibits river incision and strongly influences the river longitudinal profile. We use a model of bedrock channel reach evolution to explore the implications of hillslope block delivery for erosion rate-slope scaling. We show that incorporating hillslope block delivery results in steeper channels at most erosion rates, but that blocks are ineffective at steepening channels with very high erosion rates because their residence time in the channel is too short. Our results indicate that the complex processes of block delivery, transport, degradation, and erosion inhibition may be parameterized in the simple shear stress/stream power framework with simple erosion-rate-dependent threshold rules. Finally, we investigate the effects of blocks on channel evolution for different scenarios of hydrologic variability, and compare and contrast our results with those of more common stochastic-threshold channel incision models. We show that hillslope-derived blocks have a different signature in erosion rate-slope space than the effects of constant erosion thresholds, and propose characteristic scaling that could be observed in the field to provide evidence for the influence of hillslope-channel coupling on landscape form. +
Delta environments, on which over half a billion people live worldwide, are sustained by sediment delivery. Factors such as subsidence and sea level rise cause deltas to sink relative to sea level if adequate sediment is not delivered to and retained on their surfaces, resulting in flooding, land degradation and loss, which endangers anthropogenic activities and populations. The future of fluvial sediment fluxes, a key mechanism for sediment delivery to deltas, is uncertain due to complex environmental changes which are predicted to occur during the coming decades. Fluvial sediment fluxes under environmental changes were investigated to assess the global sustainability of delta environments under potential future scenarios up to 2100. Climate change, reservoir construction, and population and GDP (as proxies for other anthropogenic influences) change datasets were used to drive the catchment numerical model WBMsed, which was used to investigate the effects of these environmental changes on fluvial sediment delivery. This method produced fluvial sediment fluxes under 12 scenarios of climate and socioeconomic change which are used to assess the future sustainability of 47 deltas, although the approach can be applied to deltas, rivers, and coastal systems worldwide. The results suggest that fluvial sediment delivery to most deltas will decrease throughout the 21st century, primarily due to anthropogenic activities. These deltas will likely become unsustainable environments, if they are not already, unless catchment management plans are drastically altered. +
Delta integrity is a function of adequate fluvial sediment supply since the form at the shoreline is the result interaction between fluvial and basinal processes. Globally, sediment supply to river deltas has been on the decline. Specifically, present sediment supply to the Niger Delta is less than what is required for a sustained growth. Anthropogenic intervention in the lower Niger Basin and within the delta is the main control of the decrease in sediment supply. Changes in shore form is a main consequence of shifting volume of sediment supply in the Niger Delta region. This study attempts a morphodynamic analysis of shoreline changes along the Niger Delta using recent high resolution remote sensing techniques within the Google Earth Engine Platform. Attempt will also be made to characterise the spatial or temporal variability in shoreline dynamics along the Niger Delta with a view to establish the drivers of change. The study will also attempt to model the future evolution of the Niger Delta given present forcing scenarios. The research is within the overall framework of ensuring a sustainable development within the Niger Delta coastal zone in order to preserve its huge economic and ecological potentials for future generation. +
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Delta morphology is traditionally explained by differences in fluvial energy and wave and tidal energy. However, deltas influenced by similar ratios of river to marine energy can display strikingly different morphologies. Other variables, such as grain size of the sediment load delivered to the delta, influence delta morphology, but these models are largely qualitative leaving many questions unanswered. To better understand how grain size modifies deltaic processes and morphologies we conducted 33 numerical modeling experiments using the morphodynamic physics-based model Delft3D and quantified the effects produced by different grain sizes. In these 33 runs we change the median (0.01 – 1 mm), standard deviation (0.1 – 3 φ), and skewness (-0.7 – 0.7) of the incoming grain-size distribution. The model setup includes a river carrying constant discharge entering a standing body of water devoid of tides, waves, and sea-level change. The results show that delta morphology undergoes a transition as median grain size and standard deviation increase while changing skewness has little effect. At low median grain size and standard deviation, deltas have elongate planform morphologies with sinuous shorelines characterized by shallow topset gradients ranging from 1 x 10<sup>-4</sup> to 3 x 10<sup>-4</sup>, and 1 - 8 stable active channels. At high median grain size and standard deviation, deltas transition to semi-circular planform morphologies with smooth shorelines characterized by steeper topset gradients ranging from 1 x 10<sup>-3</sup> to 2 x 10<sup>-3</sup>, and 14 - 16 mobile channels. The change in delta morphology can be morphodynamically linked to changes in grain size. As grain size increases delta morphology transitions from elongate to semi-circular because the average topset gradient increases. For a given set of flow conditions, larger grain sizes require a steeper topset gradient to mobilize and transport. The average topset gradient reaches a dynamic equilibrium through time. This requires that, per unit length of seaward progradation, deltas with steeper gradients have higher vertical sedimentation rates. Higher sedimentation rates, in turn, perch the channel above the surrounding floodplain (so-called ‘super-elevation’) resulting in unstable channels that frequently avulse and create periods of overbank flow. That overbank flow is more erosive because the steeper gradient causes higher shear stresses on the floodplain, which creates more channels. More channels reduce the average water and sediment discharge at a given channel mouth, which creates time scales for mouth bar formation in coarse-grained deltas that are longer than the avulsion time scale. This effectively suppresses the process of bifurcation around river mouth bars in coarse-grained deltas, which in turn creates semi-circular morphologies with smooth shorelines as channels avulse across the topset. On the other hand, finest-grained (i.e. mud) deltas have low topset gradients and fewer channels. The high water and sediment discharge per channel, coupled with the slow settling velocity of mud, advects the sediment far from channel mouths, which in turn creates mouth bar growth and avulsion time scales that are longer than the delta life. This creates an elongate delta as stable channels prograde basinward. Deltas with intermediate grain sizes have nearly equal avulsion and bifurcation time scales, creating roughly semi-circular shapes but with significant shoreline roughness where mouth bars form.
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Delta shoreline structure has long been hypothesized to encode information on the relative influence of fluvial, wave, and tidal processes on delta formation and evolution. However analyses and comparisons of deltaic shorelines have typically been qualitative or utilized relatively coarse quantitative metrics. We ask whether robust quantification of shoreline structure would enable mapping of deltas to a physically-based space in which the relative influence of the different processes could be compared, as has recently been done using a sediment flux budget approach. To explore this question, we analyze Landsat-derived shorelines from more than 50 deltas across the globe. Since the shorelines exhibit variability on scales ranging from tens of meters to tens of kilometers, we propose a multiscale characterization of shoreline structure by mapping the shorelines to a univariate series, through a macro-scale convexity-informed framework, and using localized multi-resolution analysis via wavelets to quantify shoreline variability across a range of spatial scales within and across deltas. Specifically, we focus on the relative energy contributed by meso-scale features (river mouths) and small-scale (less than 1 km scale features). We find that distinct classes of deltas naturally emerge in that metric space, which we attribute to the different processes driving the sources and sinks of sediment in these systems. The analysis suggests the potential towards a quantitative, process-based classification of delta morphology via multi-scale analysis of shoreline structure. +
Deltaic, estuarine, and barrier coasts are experiencing unprecedentedly fast rates of morphological changes, which constitute a threat to people, infrastructures, and economies. Predicting these changes in the future could help to develop cost-efficient mitigation and adaptation plans. Here I present recent progresses in simulating large scale and long term coastal evolution using a new morphodynamic-oriented model. Through opportune simplifications the model simulates tides, surges (hurricanes), wind waves, swells, sand/mud/organic sediment, stratigraphy, and vegetation in a numerically-efficient way. The model reproduces the self-organization of barrier islands and the formation of marshes in the backbarrier/estuarine region. The model emphasizes how mud supply is a major driver for the long-term retreat of marshes. The model also simulates how riverine inputs into backbarrier basins – for example through man-made river diversions – can reduce both marsh edge erosion and barrier island retreat. +
Deltas are home to approximately 7% of global population and play a crucial role in regional food security owing to the favorable conditions for agriculture. As a result, these areas are often heavily irrigated as humans strive to use the local water resource to maximise production. This study aims to incorporate irrigation practices into the LISFLOOD-FP hydrodynamic model to determine the impact of irrigation on the flood dynamics of the Mekong Delta, one of the most intensively irrigated deltas. Irrigation data is based on global databases of irrigation area, crop type and crop calendars, supplemented with local information allowing for this approach to be used across irrigated areas around the world. This study therefore builds upon the localized estimates of flood storage capacity of paddy fields through the region and generates a new estimate across a wider area that is subsequently used to assess the impact on the hydrodynamics and flood inundation pattern. It is envisaged this approach can be used for future analysis of the impact of the changing irrigation practices of the Mekong Delta. +
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Deltas are the important interface between continents and oceans, providing home to over half a billion people. The unique environment supports a wide variety of diverse ecosystems and is highly susceptible to a broad spectrum of interacting forces. Therefore it is critical to understand its current and future changes, especially against the background of climate change and human impact, something that could be explored by studying its historical evolution process. Delta evolution is mainly governed by: a) sediment load supply from its contributing river, and 2) ocean dynamics (e.g. waves, tides). Fluvial sediment supply to a delta fluctuates over time either e.g. due to shifts in climate or, on shorter time scales, due to human interference (e.g. deforestation which could increase sediment supply or the emplacement of dams and reservoirs that reduces the sediment supply). How does this affect the morphology of a delta? Waves interact on deltas by dispersing fluvial sediment, reshaping its shoreline, how will it be illustrated in delta’s shape and morphology?
To study this, we explored hypothetical delta evolution scenarios given the following boundary conditions: a medium size upstream drainage basin (~80,000km2) with, as base case, a typical Mediterranean climate. The analysis is done through coupling two numerical models, HydroTrend and CEM. HydroTrend, a climate-driven hydrological transport model, is applied to replicate freshwater and sediment flux to the delta, and subsequently a coastline evolution model (CEM) is applied to simulate the according changes in the delta’s coastline morphology. A component-modeling tool (CMT) developed by CSDMS, is used to couple the models for this study. Several scenarios are considered that take into account: 1) stepwise increasing fluvial sediment supply, to the delta and 2) the release time of these stepwise sediment increases by changing the storm intensity for periods of time.
Preliminary model experiments will be presented demonstrating: 1) the capability of the CMT to couple models that represent different process domains and were developed and designed independently (i.e. without the intentions of such coupling), 2) the impact of changes in fluvial sediment on deltas.
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Deltas are threatened not only by climate and environmental changes (sea level rise, soil salinization, water shortages and erosion), but also by socioeconomic factors (high population density, intensive land use). These processes threaten people’s livelihoods and wellbeing, and as a result, there is a growing concern that significant environmental change induced migration might occur from deltaic areas. Migration, however, is already happening for economic, education and other reasons (e.g. livelihood change, marriage, planned relocation, etc.). Migration has multiple, interlinked drivers and depending on the perspective, can be considered as a positive or negative phenomenon.
The DECCMA project (Deltas, Vulnerability & Climate Change: Migration & Adaptation) studies migration as part of a suite of adaptation options available to the coastal populations in the Ganges delta in Bangladesh, the Mahanadi delta in India and the Volta delta in Ghana. It aims to develop a holistic framework of analysis that assesses the impact of climate and environmental change, economics and governance on the migration patterns of these areas. The project will test plausible future scenarios and evaluate them by considering a range of perspectives.
The dynamic Bayesian Network integrated model of the DECCMA project formally brings together the project elements in fully coupled, quantitative assessment framework. The presentation introduces the overall integration concept and describes the household decision-making component in detail. This component is based on a detailed household survey from delta migrant sending and receiving areas. We describe the model structure, and contrast the model setup and sensitivities across the three study areas. In doing so we illustrate some key causal relationships between changes in the environment, livelihoods and migration decision. The outputs of the integrative modelling is used to objectively evaluate the simulated environmental, social and economic changes for decision makers including the benefits and disadvantages of migration as an adaptation option.
Deltas exhibit spatially and temporally variable subsidence due, in part, to faulting that lowers the land surface over time, thereby converting subaerial land to open water. In light of expected billion-dollar investments globally to redirect sediment via channel diversions and thus restore delta land, it is crucial to understand whether discrete faulting-induced subsidence events drive distributary channel networks to reorganize. Here, we take inspiration from examples from two deltas of faulting with documented surface expression and with distinct flux-to-shoreline symmetries: the symmetric-flux Selenga River delta (Russia) and the asymmetric-flux Mississippi River delta (Louisiana, USA). Using simulations with the DeltaRCM numerical model resembling these deltaic landscapes, we examine distributary network reorganization to faulting-induced subsidence over a range of surface area and slip displacement. Our findings indicate that in a symmetric-flux delta system, the duration of fault surface expression is strongly and non-linearly related to displacement, because slip above a threshold length-scale drives wholesale channel network reorganization, whereas smaller displacement does not. In contrast, displacement is only weakly related to network reorganization in the asymmetric-flux simulations. In this environment, faults located in areas of the delta not maintaining a surface-water connection to the main channel at the time of the subsidence event do not instigate network reorganization. Moreover, for the range of surface area and slip displacement we examined, areas of faulting also do not significantly influence the distributary network at later times. Nevertheless, all faulting events in simulated deltas, with both symmetric and asymmetric flux, create accommodation space and so inhibit the construction of subaerial land to some degree. +
Densely populated coastal deltas worldwide face cascading flood and salinization hazards associated with sea-level rise, storm surges, dwindling sediment supplies, and land subsidence. One of the greatest hurdles to hazard prediction stems from quantifying the land-subsidence component, which exhibits significant spatial and temporal variations across any given delta. Here, we present a delta-subsidence model capable of quantifying these variations. The model is built upon fundamental principles of effective stress, conservation of mass, and Darcy flow; as well as constitutive relations for porosity and edaphic factors (e.g. roots, burrows). For an input sediment column and deposition rate, we quantify the depth-profile of vertical land motion over time, allowing for direct comparison with field observations spanning various depths, timescales, and methods (e.g., GPS stations; Rod-surface-elevation tables; C14 and OSL ages). Preliminary results demonstrate the model can accurately resolve decadal-scale subsidence patterns on the Ganges-Brahmaputra delta, including subsidence hotspots associated with fine-grained lithologies, buried Pleistocene paleovalleys, and river embankments constructed in the 1950’s. This predictive subsidence model can improve assessments of coastal flood hazards on the Ganges-Brahmaputra and other deltas worldwide; and help inform ongoing billion-dollar restoration efforts facing crucial decisions as to where and when coastal barriers, sediment diversions, and settlement relocations will be implemented in the coming century. +
Deposition of sediment from upland sources has the potential to increase flood risk in downstream riverside communities by reducing the carrying capacity of rivers and causing overbank flow. However, the morphodynamic response of rivers to variable upstream sediment supply remains poorly understood, and operational flood models do not account for sediment in flood prediction.
We introduce a framework for integrating source-to-sink sediment dynamics using coupled hydrological, hydrodynamic and landscape evolution models to quantify and better predict flooding events. A Distributed Hydrology Soil Vegetation Model is used to simulate upland streamflow and land coverage over numerical grids of river networks. Modules from the Python toolkit, Landlab, generate and route sediment from mountain sources (i.e. landslides, exposed glacial till) in the same domain. Streamflow and sediment from these upland models are delivered to a Delft3D hydrodynamic, sediment transport and morphodynamic model to characterize the effects of sediment-routing on lowland, coastal floodplains and investigate the impact on flood risk. This modeling framework is tested for three Puget Sound, WA basins: the Nooksack River, Skagit River and Mt. Rainier drainage, where gage analysis performed on historic USGS indicates regional morphodynamic patterns, with potential implications on flood risk. To ensure accurate model-coupling, the model ensemble is tested in an idealized, Landlab-generated domain.
Funded by the National Science Foundation. +
Depressions are inwardly-draining regions of digital elevation models (DEMs). For modeling purposes, depressions are often removed to create a "hydrologically corrected" DEM. However, this compromises model realism and creates perfectly flat surfaces that must be handled in some other way. If depressions are not removed, the movement of water within them must be modeled. This is challenging because depressions are often deeply nested, one inside the other.
Here, we present a novel data structure – the depression hierarchy – which uses a forest of binary trees to capture and abstract the full topographic and the topologic complexity of depressions. The depression hierarchy can be used to quickly manipulate individual depressions or depression networks, as well as to accelerate dynamic models of hydrological flow, as shown in our Fill-Spill-Merge poster. While the algorithm is implemented in C++ for performance reasons, we have also developed a Python wrapper using the pybind11 library. This enables users to capitalize on the strengths of both languages. The Python wrapper also streamlines the process of integrating the depression hierarchy into the CSDMS model interfaces and Landlab.
Open source code is available on GitHub at https://github.com/r-barnes/Barnes2019-DepressionHierarchy and https://github.com/r-barnes/pydephier. +
Depressions—inwardly-draining regions—are common to many landscapes. When there is sufficient water availability, depressions take the form of lakes and wetlands; otherwise, they may be dry. Depressions can be hard to model, so hydrological flow models often eliminate them through filling or breaching, producing unrealistic results. However, models that retain depressions are often undesirably expensive to run. Our Depression Hierarchy poster shows how we began to address this by developing a data structure to capture the full topographic complexity of depressions in a region. Here, we present a Fill-Spill-Merge algorithm that utilizes depression hierarchies to rapidly process and distribute runoff. Runoff fills depressions, which then overflow and spill into their neighbors. If both a depression and its neighbor fill, they merge. In case studies, the algorithm runs 90–2,600× faster (with a 2,000–63,000× reduction in compute time) than commonly-used iterative methods and produces a more accurate output. Complete, well-commented, open-source code with 97% test coverage is available on Github and Zenodo. +
Depth averaged, adaptive, Cartesian grid models have been used effectively in the modeling of tsunamis, landslides, flooding, debris flows and other phenomena in which the computational domain can be reasonably approximated by a logically Cartesian mesh. One such code, GeoClaw (D. George, R. J. LeVeque, K. Mandli, M. Berger), is already part of the CSDMS model repository. A new code, ForestClaw, a parallel library based on adaptive quadtrees, has been extended with the GeoClaw library. This GeoClaw extension of ForestClaw gives GeoClaw users distributed parallelism and a C-interface for enhanced interoperability with other codes, while maintaining the core functionality of GeoClaw. We will describe the basic features of the ForestClaw code (www.forestclaw.org) and present results using the GeoClaw extension of ForestClaw to model the 1976 Teton Dam failure. If time permits, we will also describe on-going work to model dispersion and transport of volcanic ash using the Ash3d (H. Schweiger, R. Denlinger, L. Mastin, Cascade Volcanic Observatory, USGS) extension of ForestClaw. +
Despite the essential role sub-aerial reef islands on atolls play as home to terrestrial ecosystems and human infrastructure, the morphologic processes and environmental forcings responsible for their formation and maintenance remain poorly understood. Given that predicted sea-level rise by the end of this century is at least half a meter (Horton et al., 2014), it is important to understand how atolls and their reef islands will respond to accelerated sea-level rise for island nations where the highest elevation may be less than 5 meters (Webb and Kench, 2010). Atolls are oceanic reef systems consisting of a shallow reef platform encircling a lagoon containing multiple islets around the reef edge (Carter et al., 1994). Atolls come in a variety of shapes from circular to rectangular and size from 5 to 50 km width of the inner lagoon (Fig. 1a and 1b). I want to understand why atolls vary in their morphology and whether wave climate is the primary driver of atoll morphology. Previous work has highlighted the importance of wave energy on reef morphology and atoll morphology (Stoddart, 1965; Kench et al., 2006). Around a given atoll, the morphology of the reef islands may change significantly from small individual islets or larger continuous islets that are more suitable for human habitation (Fig. 1c and 1d). I will create a global dataset of atoll morphometrics to compare to external forcing, e.g. comparing reef width to the mean wave climate. Using Google Earth Engine, a cloud-based geospatial analysis platform to collate Landsat imagery, I can measure a range of morphometrics including atoll size and shape, reef flat width, reef island size and shape, and distribution of reef islands around an atoll. I will compare these morphometrics to global waves simulated by WaveWatch3. By compiling a global dataset of atoll morphometrics, I am able to better understand the impact of wave climate on atoll morphology and long-term evolution.
References:
Carter, R.W.G., Woodroffe, C.D.D., McLean, R.F., and Woodroffe, C.D.D., 1994, Coral Atolls, in Carter, R.W.G. and Woodroffe, C.D. eds., Coastal evolution: Late Quaternary shoreline morphodynamics, Cambridge University Press, Cambridge, p. 267–302.
Horton, B.P., Rahmstorf, S., Engelhart, S.E., and Kemp, A.C., 2014, Expert assessment of sea-level rise by AD 2100 and AD 2300: Quaternary Science Reviews, v. 84, p. 1–6, doi: 10.1016/j.quascirev.2013.11.002.
Kench, P.S., Brander, R.W., Parnell, K.E., and McLean, R.F., 2006, Wave energy gradients across a Maldivian atoll: Implications for island geomorphology: Geomorphology, v. 81.
Stoddart, D.R., 1965, The shape of atolls: Marine Geology, v. 3.
Webb, A.P., and Kench, P.S., 2010, The dynamic response of reef islands to sea-level rise: Evidence from multi-decadal analysis of island change in the Central Pacific: Global and Planetary Change, v. 72.
Distributed systems of reservoirs (DSR) provide an alternative to large dams and reservoirs for riverine flow regulation and flood management. A DSR consists of temporary, small-in-size reservoirs, or detention ponds, spatially distributed across a watershed. A DSR can be as effective as a single large reservoir in terms of water storage and flow regulation and has overall a limited environmental impact. The effectiveness of a DSR depends, among others, on the number of reservoirs and their locations, making this approach to flood management a geographic problem.
In this work I propose a framework for reservoir modeling and siting. The main research objective is to find the optimal spatial configuration for a DSR that overall maximizes water storage capacity and minimizes reservoir footprint extent and system cost. First, reservoir models are generated on numerous locations along a river network, especially on small streams and tributaries, based on local topography. Shape, geometry and capacity is defined for each candidate reservoir. Then heuristic search is used to find an optimal subset of reservoirs given some spatial and structural cost constraints.
Preliminary results for real watersheds in northeastern Iowa suggest that, costs being equal, DSRs with many reservoirs of small average size have a higher storage capacity than DSRs with fewer reservoirs with a larger average size. That represents the necessary first step for future research on the effect of different configurations of DSRs on flood wave magnitude and propagation, assessing the scale of their benefits and comparing benefits with costs and impacts. +
Due to its biodiversity, ecosystem services offered and deforestation experienced since the 16th century, there are several protected areas in Atlantic Forest, such as the Juréia-Itatins Mosaic of Protected Areas (MUCJI), state of São Paulo, Brazil. Illegal deforestation in the MUCJI and surroundings have been increasing, caused by urban and agricultural expansion, reducing Atlantic Forest naturalness. This work aimed to simulate scenarios of landscape naturalness of MUCJI and neighboring municipalities for 2050 year, considering the periods 1985-2002 and 2002-2019, which correspond, respectively, to the scenarios before and after the creation of the MUCJI and National System of Protected Areas (SNUC). The landscape naturalness was evaluated by generating Distance to Nature index (D2N) maps for years 1985, 2002 and 2019, which was used as input data in simulation. The forecasting of both scenarios was conducted using cellular automata, weights of evidence and Markov chain, in Dinamica EGO environmental modeling platform. Both forecasted projections suggested that there would be a slight decrease in landscape naturalness. However, the scenario without the MUCJI implementation would reach 165.15 ha of non-natural ecotope in the study area, while the scenario with MUCJI would reach 112.77 ha. The SNUC and the creation of the MUCJI would have been contributed to maintain the naturalness of the study area, reducing losses in landscape naturalness. However, municipal planning and the MUCJI management plans should consider urban and agricultural expansion and access roads as important drivers of loss of landscape naturalness, triggering deforestation and biodiversity damages.
Keywords: Atlantic Forest; Protected Areas; Modeling; Landscape Naturalness; Distance to Nature Index. +
During storms nutrients and contaminants are washed from landscapes into rivers in the form of fine particulate matter. Once in a river, fine particles are typically treated as if they pass through the environment as wash load without interacting with the stream bed. However, laboratory and field experiments have demonstrated that fine particles can be advected towards the bed where they participate in hyporheic exchange and eventual filtration within the river bed. Irreversibly filtered particles can only be remobilized through scour and bed erosion. Therefore, understanding fine particle transport, storage, and remobilization in rivers requires coupling fine particle dynamics and sediment morphodynamics.<br>Here we analyze the dynamics of solute tracers, fine suspended particles, and bed morphodynamics within a coastal stream during baseflow and an experimental flood. These field data represent a unique set of coupled surface and subsurface observations of solute and fine particle dynamics and simultaneous time-lapse photography of sandy bedform motion. From the time-lapse photography, we use novel image analysis techniques to extract time series of bedform wavelength and celerity. In tandem, we utilize existing databases of bedform topography from laboratory experiments to determine relations between the statistical distributions of bedform wavelength, height, and the maximum scour depths. The understanding gained from the high-resolution experimental dataset allows us to create time series of bedform height and scour depth to explore how changing bedform dynamics affects solute and fine particle residence times within the stream bed. +
During the 21st century, anthropogenically modulated changes in climate and land cover will drive variations in sediment dynamics throughout rivers, reservoirs, and coastlines. These changes threaten the integrity of dams, levees, and riparian ecosystems, necessitating strategies to help mitigate their associated hazards and to detect and prevent adverse consequences of engineering solutions. To optimize these strategies, geomorphologists require calibrated, watershed-scale numerical simulations of sediment transport that can predict how fluvial networks will respond to different forcings throughout their catchments.
We aim to develop watershed-scale landscape evolution models of several U.S. rivers to explore how climate and land-use change over the coming decades to centuries will influence sediment delivery to reservoirs, locks, harbors, and coasts. The models will be calibrated by historical sediment flux data, allowing them to predict how the fluvial systems will respond to plausible scenarios of future climatic and anthropogenic forcings. The Chattahoochee River in the southeastern U.S. is an ideal catchment to begin this work due to its recent urban development and sedimentation records near its outlet at Lake Seminole. We devise procedures for processing USGS NHDPlus HR datasets (Moore et al., 2019) at the HU4 and HU8 scale for compatibility with the fluvial process components of Landlab (Hobley et al., 2017; Barnhard et al., 2020). Using NLCD land cover products (Wickham et al., 2021), NRI erosion rate estimates (USDA, 2020), and historical streamflow and sediment load data (USGS, 2021), we will leverage Landlab to construct models of the Chattahoochee catchment and test their ability to replicate sedimentation records at Lake Seminole. Here, we present preliminary results obtained by applying these procedures to the Chestatee branch of the Chattahoochee River and its outlet at Lake Lanier in northern Georgia. Future versions of this workflow will use a range of projected 21st century precipitation and land cover changes to predict potential variations in future sediment generation, transport, and storage throughout the Chattahoochee watershed and other U.S. rivers.
Earthquakes can trigger the failure of thousands or even tens of thousands of landslides throughout tectonically active landscapes. Short (<10 years) term studies of these events reveal their important place in a hillslope and fluvial hazard cascade. However, it remains unclear if these widespread catastrophic landslide events leave a long lasting impact on landscape forms, and what that impact would look like. We present landscape evolution model experimental design and some preliminary results exploring the impact of earthquakes or other widespread simultaneous landsliding events on landscapes at timescales much longer than the event return intervals. We use the Hylands Landlab component to test landslide, hillslope, and river sediment interactions, and probe landscape metrics like hilltop concavity, drainage density, slope-area relationships, and possibly valley width to test and validate our models. +
Eastern oysters (Crassostrea virginica) are reef-building organisms that occupy tidal and subtidal zones along the eastern coasts of the Americas. They provide key ecosystem services by improving water quality, providing habitat, providing food, and adding to local economies. At the population level, eastern oysters also form reefs which protect coastal habitats from storms and tidal erosion by attenuating waves. The decline of eastern oyster populations coupled with increased coastal storm intensity and rising sea level is exposing coastal habitats to higher levels of risk. One potential avenue to increase coastal protection is to use artificial reef structures that can also boost eastern oyster populations. Yet, there is little research on how oyster population dynamics influence the structure of the reef–artificial or not, and in turn, how the reef structure influences wave attenuation. Our research aims to address this gap by developing a model to simulate oyster populations in St. Augustine, Florida using an agent-based model coded in the Mesa Python framework. This will be coupled with the Landlab TidalFlowCalculator component, to simulate how reef structures affect tidal velocity and water depth. This model represents the first phase of a larger research effort, which aims to investigate the effects of climate change on the evolution of reef structures and estimate their wave attenuation performance over time. +
Ecohydrological modeling capacity of Landlab is introduced and illustrated using examples that couple components for local soil moisture and plant dynamics with spatially explicit cellular automaton-based (CA) plant establishment, mortality, fire and grazing. Several key features of arid and semiarid ecosystems are discussed. Coexistence of tree-grass cover on north facing slopes (NFS) and shrub cover on south facing slopes (SFS) in central New Mexico is attributed to the competitive advantage of trees due to their longer seed dispersal range against shrubs in cooler and more moist NFS. Incorporating a rule on the inhibitory effects of shrubs on grasses enhance modeled shrub cover, while both trees and grasses are favored when runon is included in the local soil moisture model. Feedbacks among livestock grazing, grassland fire frequency and size, resource redistribution and woody plant encroachment are investigated using different ecohydrologic model configurations. These feedbacks are manifested in a three-phase woody plant expansion processes in the model, with rates of encroachment controlled by the state transition probabilities in relation to plant susceptibility to fires, grazing, and age-related mortality. A critical area of woody plant emerges in the model with which a negative feedback between fire size and woody plant expansion begins. Our results underscore the need for developing models that emphasize local and non-local plant interactions for modeling transient ecosystems. +
Environmental change interacts with human migration in complex ways and across multiple scales. This complexity makes agent-based modeling (ABM) a powerful tool to investigate environment-migration dynamics. Here, we present results from an original ABM of environmental migration in Bangladesh. The model simulates an origin community and how a stylized environmental shock to the community impacts labor opportunities and household decisions surrounding migration. Pattern-oriented modeling is a useful approach for evaluating ABM’s by assessing a model’s ability to reproduce multiple observed patterns of phenomena. We use a pattern-oriented approach to test our model’s ability to reproduce multi-level patterns of environmental migration from the literature. Previous work used machine learning methods to calibrate our ABM by identifying regions in parameter space that successfully reproduced the observed patterns. We demonstrated that a strictly income-based migration decision method was able to reproduce patterns of interest, but inconsistently. However, the pattern-oriented approach allows us to implement more complex, behaviorally driven decision-making methods of migration and evaluate their success. In this work, we will present preliminary results implementing and comparing different decision-making methods in our ABM based on existing theories including Theory of Planned Behavior, Protection Motivation Theory, and a mobility potential framework. Ultimately, we hypothesize that a hybrid framework of migration decision-making that includes community norms, social networks, and place attachment will most successfully be able to replicate known patterns of environmental migration. +
Environmental migration is an example of a complex coupled human and natural system with dynamics that operate across multiple spatial and temporal scales. Agent-based modeling (ABM) has demonstrated potential for studying such complex systems, especially where individual decision-making is an important component. In this work, we use an original ABM of environmental shock, livelihood opportunities, and migration decisions to study dynamics of environmental migration in rural Bangladesh. As ABMs are sensitive to the decision-making methods used, we present results utilizing multiple plausible decision-making methods for households deciding whether or not to send an internal migrant. We present results using both a simple economic method based on utility maximization as well as a more behaviorally complex method based on the Theory of Planned Behavior. We hypothesized that a more behaviorally complex decision method which incorporates social networks and community norms would more successfully reproduce the patterns of migration. However, using a pattern-oriented approach to reproduce two key patterns of migration from the empirical literature, we demonstrate that an economic model can reproduce our patterns of interest with high levels of success. For both decision methods, the level of community inequality in distribution of land ownership, which impacts the number of agricultural jobs available within the community, is critically important for patterns of migration outcomes. In this way, our model suggests that community-level inequality is has significant implications of migration dynamics in this study area. +
Ephemeral, steep-side channels (known as gullies and arroyos) are fundamental elements of soil erosion that threaten agricultural lands worldwide with the associated expectation that landscape degradation will accelerate due to anthropogenic climate change. Gullies are also central to landscape evolution as they are dynamic features that intensively altered between infilling and incision phases in the recent geological past. Yet, exogenic (e.g., due to climate or land-use change) and autogenic (e.g., due to natural oscillations between erosion/deposition phases) drivers of gully formation and of changes in their widespread occurrence are incompletely understood and quantified. This is, in part, because erosional dynamics of gully landforms are complex and hard to capture due to: (1) episodic and discontinuous sediment movement in response to discrete rain events, (2) unstable channel walls with frequent mass wasting, and (3) soil and vegetation properties that vary dynamically thus altering both the hydrology and slope stability.
In this work, we focus on developing a new catchment-scale gully erosion model that enables quantification of soil erosion rates and topographic evolution in response to changes in rainfall patterns and vegetation cover over historical and longer timescales. The model includes explicit representation of rainstorm runoff and erosion over sub-minute time scales. During simulation, soil particles are transported both in suspension and as bedload in accordance with their size. Episodic bank failures and headcuts evolve based on local stability criteria derived from soil properties and failure geometry. This poster presents the model configuration, its main components, and the general modeling approach that aims to bridging gaps between event-scale hydrology, sediment dynamics and longer-term landscape evolution models using new and existing components in the Landlab modeling library. We also present preliminary results of model validation against runoff and sediment data from a field site and a sensitivity analysis on how sediment flux and landform development respond to plausible changes in rainstorm properties, landcover, and vegetation dynamics.
Eroding coasts make up the majority of the coastlines on Earth, including the west coast of the United States, and host critical infrastructure like roads, railways, and residential structures. The precarious siting of infrastructure is particularly true for Del Mar, California, where a major railway between Los Angeles and San Diego sits within just a few meters of a cliff edge that is closely backed by dense housing subdivisions. Coastal cliff retreat presents a danger to these communities that is potentially amplified under rising sea level conditions, among other factors, yet constraints on retreat rates are most often limited to those derived from historical imagn ery and maps dating back 10-100 years. These modern retreat rates are then used, in conjunction with multi-model ensembles, for forecasting cliff retreat over the next 50-100 years in order to gauge future impacts to coastal communities. Managers and policymakers make decisions for mitigation efforts based on these results, however they may not capture the full picture of cliff retreat, and the factors that influence it, over time. While nearly all of the existing forecasting models explicitly account for projected sea level rise, the majority of them ignore other factors (e.g. subtidal and subaerial weathering) that may also play a large role.
A recently developed combination of in situ-produced cosmogenic 10Be surface exposure dating in conjunction with a new numerical model of shore platform profile development that takes into account sea level rise, intertidal weathering, and wave attack on cliff retreat provides quantification of cliff retreat histories over hundreds to thousands of years via cliff-normal 10Be sample transects. Here, we use a shore-perpendicular transect of cosmogenic 10Be concentrations from the surface of a sandy claystone shore platform exposed along a narrow and sandy beach backed by a near vertical ~20-meter-tall cliff in Del Mar, California to present a long-term cliff retreat rate of 5.5 - 8 cm a-1 over the last two millennia for this site. This is the first long term cliff retreat rate for any coast in North America determined by this new methodology. Existing decadal retreat rates at and proximal to this site range from 5-20 cm a-1, suggesting that cliff retreat here may be accelerating towards the present. Preliminary modeling results suggest that uplift-corrected sea level rise in Southern California, which remained constant during the late Holocene (0.8 mm a-1) but doubled in the last century, cannot alone explain this potential increase, as modeled platform geometries and associated development rates show a dependence on the imposed weathering rate as well as wave erosion efficacy. Recent investigation into the relative influence of weathering and wave attack on observed cliff retreat at this same location also shows a roughly equal contribution for both drivers. We further explore this and other potential drivers (e.g. land use change) for this potential increase, and speculate on the implications of these results for future cliff retreat forecasting efforts.
Exchange of material across the nearshore region, extending from the shoreline to a few kilometers offshore, determines the concentrations of pathogens and nutrients near the coast and the transport of larvae, whose cross-shore positions influence dispersal and recruitment. Here, we describe a framework for estimating the relative importance of cross-shore exchange mechanisms, including winds, Stokes drift, rip currents, internal waves, and diurnal heating and cooling (Moulton et al., 2023). For each mechanism, we define an exchange velocity as a function of environmental conditions. The exchange velocity applies for organisms that keep a particular depth due to swimming or buoyancy. A related exchange diffusivity quantifies horizontal spreading of particles without enough vertical swimming speed or buoyancy to counteract turbulent velocities. This framework provides a way to determine which processes are important for cross-shore exchange for a particular study site, time period, and particle behavior. I will also describe approaches we've used to communicate the framework to different audiences, including an interactive tools developed by undergraduates.
Moulton M, Suanda S, Garwood J, Kumar N, Fewings M, Pringle J. Exchange of Plankton, Pollutants, and Particles Across the Nearshore Region. Annual Review of Marine Science. 2023 January 16; 15(1):167-202. DOI:10.1146/annurev-marine-032122-115057 +
Extreme drought events are becoming more frequent and severe. For example, since the flash drought of 2012 that ravaged the central United States, 2019 was the only year that has not experienced a billion dollar drought disaster. Examining how vegetation-atmosphere interactions change during extreme drought events can improve our understanding of how resilient different plants are at dealing with water stress during drought. We couple a prognostic phenology routine to a 1-D version of the Duke Coupled surface-subsurface Hydrology Model with dynamic vegetation (DCHM-V) to simultaneously simulate changes in plant life stage with water, energy, and carbon fluxes. The predictive phenology model simulates daily changes in canopy greenness and density based on the current meteorological conditions within the DCHM-V. We run the DCHM-V at a 4 km spatial resolution and hourly time step for pixels encompassing three AmeriFlux sites in the Midwestern United States. Modeling phenological changes and resulting land-atmosphere interactions allows us to investigate physical processes governing vegetation water use strategies in response to flash drought. Results show that vegetation under average water-use scenarios experience smaller reductions in growth as compared to isohydric or anisohydric water-use strategies. Transpiration dominates evapotranspiration with ample precipitation but is nearly cut in half during extreme drought resulting in reduced plant water use efficiency. These findings demonstrate the importance of incorporating dynamic phenological when investigating how vegetation modulates water, energy, and carbon under different water stress conditions, and have implications for improving predictions of drought impacts on the land surface. +
Features of landscape morphology including slope, curvature, and drainage dissection are important controls on runoff generation in upland landscapes, while over long timescales runoff plays an essential role in shaping these same features through surface erosion. Many hydrologists have speculated about the importance of this coevolution and its potential for generating hydrological insights; however, observational and computational limits have long prevented direct study of coupled hydro-geomorphic systems over long timescales. What kinds of hydrological features do landscapes exhibit when their runoff is `in-tune' with the form of the landscape? Here we answer this question using a new coupled hydro-geomorphic model that is sophisticated enough to capture saturated and unsaturated zone storage and water balance partitioning between surface flow, subsurface flow, and evapotranspiration, but efficient enough to drive a landscape evolution model over millions of years. We nondimensionalize the model to arrive at a minimal set of dimensionless numbers that provide insight into how hydrologic and geomorphic parameters together affect the ultimate state. Model results show a diverse array of behaviors observed in real watersheds, including the presence of variable source areas and nonperennial streams. We also found some results that were unique and surprising, such as non-dendritic drainage networks. We hope that these results will inspire hydrologists to consider the role that landscape history plays in the hydrological processes observed today and inspire geomorphologists to consider the role of more nuanced hydrological processes in long-term landscape evolution. +
Field-based observations and numerical models of strike-slip faults indicate that the regional footprint and preservation of the landscape response depends on fault slip rates, climatic conditions, and surface erosional activity. Arid desert environments, on one end of the climate spectrum, are especially sensitive to climate changes and tend to provide an excellent record of fault-slip histories and landscape modification in response to faulting. For example, the Salar Grande strike-slip fault slips at slow to moderate rates (~1 mm/yr) across the Atacama Desert of Chile and is characterized by long periods of hyper aridity with the absence of fluvial activity, but still preserves dextral offset geomarkers evidencing past humid periods and faulting. Conversely, wet environments are intensively affected by constant fluvial erosion and mass wasting. For example, in Aotearoa New Zealand, complex systems of parallel right-lateral faults in the Tararua Mountains, North Island, interact with each other with neighboring rivers flowing across and along fault branches that slip at different rates (< 1 mm/yr to > 10 mm/yr) and juxtapose different scale high-relief topography (shutter ridges). Inspired by the complexities of these real-world contrasting strike-slip fault settings, we create analog numerical simulations in Landlab to observe the role of climate variability, sediment, and the interaction between multiple structures affecting the topography. Model results are compared with field observations, focusing on channels, ridges, and mountain range scale observations. +
Field-based studies, remote sensing analyses, and model development inform our understanding of patterns and processes in incipient delta formation and continued progradation. Rarely, however, have the three approaches been used together to understand the entire progradation history of a real-world system. This may be largely due to the paucity of appropriate sites: an accessible location where a delta has been growing for just a few decades. One site that meets these criteria is Mamawi Creek delta, located within the larger Peace Athabasca Delta ecosystem in northeastern Alberta, Canada. Mamawi Creek delta began forming in 1982, just two years before the beginning of Landsat TM observations over boreal Canada. Due to strong scientific interest and human presence in the region, data on sediment, flow, water levels, and elevations have been collected for decades. Here, we use these available field data to create a site-specific morphodynamic model of Mamawi Creek Delta in Delft3D. Leveraging discoveries from previous modeling studies that have examined how inputs, such as percent of cohesive sediment and median grain size, affect resulting delta forms, we approach the inverse question to see how observed delta characteristics in the Landsat record can constrain model setup and inputs. By comparing annual model outputs against remotely sensed observations of true delta form over the last 40 years, we learn the limitations of our field data and consequences of model simplifications. We then iteratively use these comparisons to inform model parameter adjustments and changes to boundary conditions that enhance agreement between these two methods, ultimately producing a simulated delta that acceptably mimics observed progradation. +
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Flash floods are among the most devastating natural hazards, which cause loss of life and severe economic damages. Modeling flash floods to provide warnings to the public to prevent/mitigate the impacts of this type of disaster is still challenging. A coupled model which consists of the currently used Hydrology Laboratory - Research Distributed Hydrologic Model (HL-RDHM) at NWS and a high resolution hydraulic model (BreZo) has been developed for flash flood modeling purposes. The model employs HL-RDHM as a rainfall-runoff generator in coarse resolution to produce surface runoff which will be zoned into point source hydrographs at the sub-catchment outlets. With point source input, BreZo simulates the spatial distributions of water depth and velocity of the flow in the river/channel and flood plain.
The model was utilized to investigate the historical flash flood event in the Upper Little Missouri River watershed, Arkansas. This event occurred on June 11th, 2010 and had killed 20 people and caused severe property damages. The catchment was divided into 55 sub-catchments based on Digital Elevation Model (DEM) at 10m resolution from USGS. From HL-RDHM surface runoff, 55 hydrographs can be derived, which then become 55 point sources as input in BreZo. The system was calibrated by tuning the roughness parameter in BreZo to best match the USGS discharge observation at the catchment outlet. The simulation results show the system performed very well not only for the total discharge at the catchment outlet (Nash-Sutcliffe efficiency = 0.91) but also the spatial distribution of the flash floods. +
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Flood hazards can increase or decrease as a result of changes in the frequency of high flows and changes in the geometry of river channels, through aggradation, incision, or widening. Across the US, Slater et al. (2015) found that a statistically significant majority of studied sites saw increases in the frequency of flooding over the past several decades. Notably, the magnitude of channel response and hydrologic non-stationarity varied between channels within a region. Here, we focus in on a single region, the Pacific Northwest, and ask 1) can the geomorphic characteristics of a basin explain historical changes in flood hazard? And, 2) how will flood risk change with climate change in relation to source-to-sink sediment dynamics? As a first step in understanding the sensitivity of different basins to future climate change, we look at historical records of both channel geometry change and discharge records at ~60 USGS gage sites across Washington state. We find substantial variation among the studied sites in the magnitude of channel change (quantified in terms of changes in the stage-discharge relationship) over the past 3 decades. Some channels have maintained a steady stage-discharge relationship over 30 years, while others change dramatically on an annual basis. Many, but not all, of these unstable channels drain basins with retreating alpine glaciers. Inspecting the discharge records, we find substantial variation as well, likely driven by the differences in hydrologic regime. In the future, we will use this understanding of historical channel sensitivity to inform our predictive models of both channel geometry change and non-stationarity in high flows. +
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Floodplain deposition maintains and builds up low-lying lands along rivers and in deltas. Floodplain aggradation processes and patterns determine how vulnerability of low-lying land changes over timescales of decades to hundreds of years. Over the longterm, floodplain deposition and channel migration determine the depositional architecture with impacts on groundwater and hydrocarbon reservoirs.
We build and enhanced a 3D floodplain architecture model, AquaTellUs. AquaTellUs uses a nested model approach; a 2D longitudinal profile, embedded as a dynamical flowpath in a 3D grid-based space. A main channel belt is modeled as a 2D longitudinal profile that responds dynamically to changes in discharge, sediment load and sea level. Sediment flux is described with a modified Exner equation by separate erosion and sedimentation components. Erosion flux along the main flowpath depends on river discharge and channel slope, and is independent of grain-size. Depositional flux along the channel path as well as in the lateral direction into the floodplain depends on the local stream velocity, and on grainsize-dependant settling rates. Multiple grainsize classes are independently tracked.
Floodplain deposition is an event-driven system, only peak discharge events cause overbanking, flooding and perhaps channel avulsion. The computational architecture of AquaTellUs preserves stratigraphy by event, allowing for preservation of information of depositional layers of variable thickness and composition.
We here present experiments that show the pronounced effect of different probability density functions for river discharge and sediment load, i.e. flooding recurrence times, on the stratigraphic architecture. +
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Floods can be devastating to society and the environment. Recent flood events around the globe, such as Harvey and Irma for instance, have been disastrous and broke records in damage and loss of life. Flood disasters often operate at spatial and temporal scales that far exceed local and regional, or even national, assessment and response capabilities. There is no doubt that remote sensing observations of floods, particularly from satellites, can be of great value. Earth observation (EO) data of floods can either be used directly through numerous services providing flood maps and other datasets, or indirectly through integration with hydrodynamic models simulating events continuously in time and space. In this project, we demonstrate the value of satellite flood maps for Harvey 2017 and Twitter feeds during the event for integration with a forecast inundation model (LISFLOOD-FP). Initial results are illustrated and we discuss current challenges and next steps. +
Flow network models are commonly used to study the formation and evolution of karst conduit systems and subglacial conduit systems. Such models involve: 1) numerical solution of flow within the network, and 2) calculation of the rate of change of conduit or fracture size within each segment of the network. Solution of flow and conduit growth is alternated to simulate long-term evolution of the system. Head loss equations, such as the Darcy-Weisbach or Hagen Poiseuille Equations, and a prescription of flow conservation at conduit junctions, are used to iteratively solve for flow within each segment of the network. In the case of karst development codes, discharges within the network are used along with kinetic rate equations to calculate transport and dissolution rates within every conduit segment. For subglacial systems, pressure head and frictional energy dissipation determined from the flow solution are utilized to calculate conduit growth by ice melting and closure due to ice creep. The Landlab modeling environment and associated gridding library greatly ease the development of a flow solver. Here we present the first stages of development of a conduit evolution code within Landlab, with applications both to subglacial and karst systems. Future work will focus on coupling landscape evolution models with network growth models to examine interactions between surface and subsurface processes. +
Flow routing calculations are routinely performed in geomorphic and hydrologic analyses. These require an appropriate flow-routing surface, which is generally a digital elevation model which has been pre-processed to remove all depressions from its surface. This allows the flow-routing surface to host a continuous, integrated drainage network. However, real landscapes contain natural depressions that can store water and break up the drainage network. These are an important part of the hydrologic system, and should be represented in flow-routing surfaces. The challenge is in removing from a DEM only those depressions which would be filled under reasonable hydrologic conditions at a given location, and not all depressions indiscriminately. To address this problem, we developed FlowFill, an algorithm that routes a prescribed amount of runoff across the surface in order to flood depressions, but only if enough water is available. This method conserves water volume and allows a user to select a runoff depth that is reasonable for the region of interest. Typically, smaller depressions or those in wet areas or with large catchments are flooded, while other depressions may not be completely filled, thus permitting internal drainage and disruptions to hydrologic connectivity. Results are shown at a sample location using a range of runoff depths, with the resulting flow-routing surfaces with filled and unfilled depressions and the drainage network structure associated with the result. +
Fluid-driven granular flows sculpt Earth's surface through processes such as soil creep, landslides and debris flows, and river bed-load and suspended sediment transport. In the case of river bed-load transport, grains may move by rolling, sliding, and jumping within a thin layer known as bed-load layer. In this layer, it is common for grains to segregate by size (a process that has been extensively studied) or shape, which has only recently been recognized as an important control. Here we perform numerical simulations to examine how shape-driven particle segregation is controlled by 1) purely granular interactions and 2) fluid-granular dynamics. To isolate granular dynamics, we construct a DEM model using LIGGGHTS to examine segregation of dry grains of different shapes in a rotating drum. To fold in the role of fluid drag, we use a CFD-DEM model (OpenFOAM + LIGGGHTS) to study particle segregation in open channel laminar flow. To efficiently simulate different shapes, we use bonded spherical particles to construct spheres, cubes, and cylinders. For the former, we use a horizontal cylinder filled with the same particles, and rotate it at low angular velocities. Meanwhile, for the latter, we set a periodic channel filled with spherical and non-spherical particles, of equal mean volume, sheared by a viscous Couette flow which imposes enough shear stress to move the particles by bed-load transport. For both, we investigate the statistical properties of the segregation by size and shape that non-spherical grains experience in the systems by tracking hundreds of individual trajectories throughout the entire bed, and the mechanisms involved that are mainly driven by particle collisions and fluid-grain interactions. These results illuminate the role of grain shape in controlling sediment transport, with implications for natural rivers, hillslopes, and aeolian systems. +
Fluvial bedload is a fundamental process by which coarse sediment is transferred through landscapes by fluvial action and is characterized by cyclic sequences of particle motion and rest. Bedload transport has many complex physical controls but may be well described stochastically by distributions of grain step length and rest time obtained through tracer studies. However, none of these tracer studies have investigated the influence of large wood on distributions of step length or rest time, limiting the applicability of stochastic sediment transport models in these settings. Large wood is a major component of many forested rivers and is increasing because of disturbances such as wildfire and insect infestations as well as the use of wood in rivers as part of ‘natural flood risk management’ practice in the UK. This study aims to investigate and model the influence of large wood on grain-scale bedload transport.
St Louis Creek, an alpine stream in the Fraser Experimental Forest, Colorado, is experiencing increased wood loading resulting from the infestation of the mountain pine beetle in the past decades. We inserted 957 Passive Integrative Transponders (PIT) tagged cobbles in 2016 upstream of a wood loaded reach and measured and tagged >20 pieces of large wood in the channel. We resurvey the cobbles and wood on an annual basis after snowmelt, building distributions of rock-step lengths and rest time distributions as well as observing any changes and transport of large wood. Additionally, we are developing novel active tracer tags, with integrated accelerometer technology, which will help to constrain these distributions and investigate the influence of woody debris.
We observed increased probabilities of grain deposition around large wood in the first 3 years of resurvey data, and preliminary statistical analysis suggests a significant influence of wood presence, and its relative stream position, on transport likelihood and distance, although additional annual data is required to verify its reproducibility. Over the next two snowmelt seasons, active tags will provide detail on the transport behaviour of cobbles at unprecedented levels, allowing us to refine stochastic bedload transport models in environments where biota is significantly interacting with earth surface processes.
Fluvial deltas have worldwide socio-economic importance as human development and infrastructure centers and provide several ecosystem services, including storm protection and nursery habitats. Their subsurface architecture also holds clues to past climate and sea-level change that can be reconstructed from stratigraphy. A significant challenge in inverting stratigraphy is separating the signals of external forcing, such as variations in sea level, and internal processes, such as the dynamics of the fluvial surface and channel network variations. In a previous work, we analyzed laboratory flume data from the Tulane Delta Basin using an experimental run with oscillating sea level conditions and constant sediment supply. We found that the dynamics of the fluvial surface play an important role in delaying the response of the upper portion of the subaerial topset. To further quantify this phenomenon, we couple this flume experiment with a numerical modeling framework that integrates the topset with a subaqueous offshore region or foreset. The numerical model can explain the topset slope, convexity dynamics, and sediment partitioning between the topset and the foreset under sea level variations. For example, it captures how during sea-level rise (SLR), low sedimentation near the topset's center reduces the subaerial slope and increases convexity, while during sea-level fall (SLF), high sedimentation increases the slope and concavity. Moreover, the model can explain the counterintuitive observation of higher sediment topset bypass to the foreset under SLR than SLF due to the reduction in subaerial slope, partially explained by a higher presence of active channels during SLR than SLF. These results underscore the importance of internal processes such as fluvial surface and channel dynamics, which can result in net erosion during SLR and net deposition during SLF, potentially complicating the reconstruction of paleo sea-level from deltaic deposits. +
Fluvial incision patterns help us understand the role of precipitation in river formation and evolution. The effects of drainage area, sediment supply and precipitation are closely linked and disentangling them is a challenging task.
In this study, we model different precipitation scenarios and use the stream power law to analyse river profiles. We focus on the analysis of the χ coordinate, a transformation of the stream-power law to capture changes in slope with distance downstream. The value of this coordinate is controlled by the concavity index, θ, which sets the steepness of the rivers downstream.
Similar χ profile shapes can be caused by different precipitation patterns, tectonic forcings or lithologies. However, choosing different θ coefficient values will lead to patterns similar to those arising from the natural forcings above, distorting the original physical signal.
In this study, we use the modelling framework Fastscape to generate landscapes that evolve to steady state under different precipitation scenarios. We test multiple precipitation models and calculate the χ profiles of the resulting simulated rivers using LSDTopoTools. We complete the analysis by comparing the model results to real topographic data from sites featuring a strong precipitation gradient, such as the Pyrenees, the Alburz mountains and the Andes.
This piece of research provides further insight on the importance of constraining the θ coefficient in χ profiles, in particular when disentangling the role of precipitation in river incision mechanisms. +
Fluvial incision since late Miocene time has shaped the modern transition between the Central Rocky Mountains and the adjacent High Plains of North America. Incision has formed a distinctive pattern of deep gouges at the mountain front centered around large drainages, most notably the Arkansas and South Platte Rivers. While there is a clear contrast in material strength and erodibility between the crystalline rocks that comprise the core of the mountains and the sedimentary packages that overlie the plains, researchers seldom account for this contrast when attempting to model the geomorphic evolution of the plains. In this study we set an explicit boundary across which erodibility changes from a value representative of granite, for the Central Rockies, to a value representative of coarse sandstone, for the High Plains. We then evolve the landscape with constant, uniform uplift and fluvial incision with sediment transport dependent upon a characteristic transport length. We find that with no external forcing beyond steady uplift and even on a landscape of modest gradient, it is possible to recreate deep incision at the mountain front simply by running water across substrates with highly contrasting erodibilities. This preliminary result has applications to future studies of the geomorphic evolution of the High Plains as it causes us to re-evaluate the sensitivity of this landscape to the material properties of the mountains and plains. In future work, this may guide us to look more closely at intrinsic properties of the landscape as an explanation for geomorphic expression before considering external forces. +
Fluvial sediment dynamics play an important role in the functioning and connectivity of the earth’s natural systems. It is not only one of the primary drivers of landscape development and channel morphodynamics, but also has important implications for water resources, ecology, geochemical cycling, and socio-economic aspects. Although anthropogenic influences are a major cause of changes in river sediment transport processes, it is widely accepted that these processes are also sensitive to climate change. Future climate changes particularly rises in temperature driven by increased greenhouse gas emissions, are projected to considerably impact 21st-century precipitation distribution which will alter fluvial processes, soil erosion and sediment loads worldwide. Predicting the responses of riverine fluxes to future climate is, therefore, vital for the management of fluvial systems. In this study, we conduct a global scale analysis of future suspended sediment and water discharge dynamics in response to the changing climate. We use a spatially and temporally explicit global scale hydrogeomorphic model, WBMsed. Changes in the earth’s climate system were obtained by forcing the model with downscaled precipitation and temperature projections generated by multiple General Circulation Models (GCMs), each driven by four Representative Concentration Pathways (RCPs). We investigate climate-induced spatial and temporal trends and variability in global suspended sediment loads and river discharge dynamics in the 21st century. +
Fluvial terraces are commonly interpreted as recorders of past environmental (e.g. tectonic or climatic) conditions. However, controls on terrace formation through river incision, and on the destruction of terraces through lateral erosion are poorly understood. Here, we present results from a physical experiment performed at the St. Anthony Falls Laboratory that provide insights into the formation and preservation potential of alluvial terraces, into dynamics of alluvial valley width, and the dependence of these parameters on external forcings: primarily on river response to base level fall. The model was performed in a wooden box with dimensions of ~4 meters by ~2.5 meters by ~0.5 meters, which was filled with silica sand with a unimodal grain size distribution (D50= 0.14 mm). Sediment and water were mixed and fed into the box via a gravel diffuser to inhibit scour. A single channel incised down to the base level, which was steadily lowered by a weir. Six experiments were performed, each with a constant water discharge of 0.1 L/s and a sediment flux of 0.022 L/s, and with a base-level fall rate of 0mm/hr, 25mm/hr, 50mm/hr, 200mm/hr, 300mm/hr, and 400mm/hr. We collected aerial photographs every 20 seconds and digital elevation models (DEMs) every 15 minutes throughout each experiment. Terraces formed in the experiments with base level fall due to incision and headwards knickpoint retreat. Major sidewall collapses and progressive valley widening were observed and controlled by the lateral migration of the channel. +
Fluvial valley width is determined by a combination of factors including regional lithology and drainage organization, as well as regional glacial and uplift history. In both topographic analysis and numerical modeling-based studies, valley width has been observed to follow a power law scaling relationship with drainage area. Local to regional scale studies have also demonstrated the influence of lithology, differential uplift, and drainage reorganization on this relationship. Yet, significant uncertainty remains regarding how these trends extend to the scale of large river networks and how they are influenced by transient forcing. The Upper Mississippi River Valley, initially incised during the early Pleistocene, presents a case study that encompasses a wide range of valley forms likely influenced by some combination of these factors, including by not limited to Spatially variable glacial history, bedrock lithology, and punctuated drainage reorganization events. This research aims to analyze the variable contribution of lithology, downstream changes in drainage area and history of reorganization, and regional variability in glacial isostatic adjustment in determining downstream trends in valley morphology. By isolating these effects, we aim to determine whether there is an extractable signal of the conditions during initial valley incision embedded in modern valley topography. Here we present a dataset of high-resolution valley aspect ratio and curvature, paired with longitudinal trends in drainage area and bedrock lithology. This is compared with empirical expectations for valley width scaling. Preliminary analysis found an overall downstream valley widening trend, however with multiple perturbations, including narrow gorges, and locally beveled valley walls caused by a combination of lithologic transitions and differing drainage integration histories. +
Following pioneering modeling work examining the evolution of wave-influenced deltas (Ashton et al., 2013; Nienhuis et al., 2013), we coupled the River and Floodplain Evolution Model (RAFEM) to the Coastline Evolution Model (CEM). Results of a recent suite of model experiments (conducted using the CSDMS software stack and Dakota) lead to new insights: 1) The preferred location of avulsions (a distance from the river mouth scaling with the backwater length), previously observed in laboratory models and in the field, can arise for geometric reasons that are independent of those recently suggested (Chatanantavet et al., 2012; Ganti et al., 2016). This alternative explanation applies when the river longitudinal profile tends to diffuse more rapidly than the floodplain longitudinal profile. 2) Although the timescale for avulsions is expected to increase with increasing wave influence (Swenson, 2005), we find that this depends on the angular wave distribution. When wave influence is strong and the angular mix of wave influences tends to smooth a nearly straight coastline (coastline diffusion), progradation is slowed and avulsions delayed. However if the angular wave distribution produces anti-diffusive coastline evolution, a strong wave influence still leads to cuspate delta shapes, but avulsions are barely delayed. 3) Although increasing sea-level-rise rate is expected to cause more rapid avulsions, and does in laboratory deltas, we unexpectedly find that this is not true for river-dominated deltas in our model (or for anti-diffusive wave climates). The explanation, involving the role of sea-level-rise related transgression (or decreased progradation), raises potentially important questions about geometrical differences between laboratory deltas and natural deltas. 4) The magnitude and timescale of autogenic variability in sediment delivery rates at the river mouth depends on wave climate, sea-level-rise rate (for some wave climates), and on the amount of super elevation of the river channel (relative to the surrounding floodplain) required to trigger avulsions.
* Ashton, A. D., Hutton, E. W., Kettner, A. J., Xing, F., Kallumadikal, J., Nienhuis, J., and Giosan, L. (2013), “Progress in coupling models of coastline and fluvial dynamics,” Computers & Geosciences, 53, 21–29.
* Chatanantavet, P., Lamb, M. P., and Nittrouer, J. A. (2012), “Backwater controls of avulsion location on deltas,” Geophysical Research Letters, 39.
* Ganti, V., Chadwick, A. J., Hassenruck-Gudipati, H. J., Fuller, B. M., and Lamb, M. P. (2016b), “Experimental river delta size set by multiple floods and backwater hydrodynamics,” Science advances, 2, e1501768.
* Nienhuis, J. H., Ashton, A. D., Roos, P. C., Hulscher, S. J., and Giosan, L. (2013), “Wave reworking of abandoned deltas,” Geophysical research letters, 40, 5899– 5903.
* Swenson, J. B. (2005), “Relative importance of fluvial input and wave energy in controlling the timescale for distributary-channel avulsion,” Geophysical Research Letters, 32.
For a subset of global deltas, morphological evolution is due to the competing actions of the river, which brings about the delivery of terrestrial sediment, and waves, which redistribute the input sediment across the coastline. Given that there are many such coastlines where waves exert considerable influence worldwide, an improved understanding of the effect of waves on the morphological evolution of coastal delta settings is imperative, especially in view of the perceived declining influence of the river input. Accordingly, this study presents a preliminary numerical model approach applied to investigate the planform evolution of deltaic coastlines due to the interplay between flow discharge and waves. Model simulations were undertaken with the coupled Delft3D and SWAN (Simulating Waves Nearshore) numerical models for fluvial and wave input, respectively. Additionally, the idealized numerical model represents a straight, sandy deltaic coastline interrupted by two fluvial discharge outlets, and, at the same time, affected by waves approaching from a dominant direction. We found that the modelled deltas evolved into diverse shoreline - and - river–mouth forms under varying combinations of wave and river inputs. The modelling approach also makes a preliminary distinction between the relative effects of waves’ significant height (Hs) and incidence angle (αo) on deltaic planform morphological evolution. Future development of the model will focus on critically exploring the interaction between these two key morphodynamic processes along similar natural coastline settings. +
For landscapes to achieve a topographic steady state, they require steady tectonic uplift and climate, and a bedrock that is uniformly erodible in the vertical direction. Basic landscape evolution models predict that incising drainage networks will eventually reach a static geometric equilibrium – that is, the map-view channel pattern will remain constant. In contrast, natural rivers typically incise through heterogeneous bedrock, which can force reorganization of the drainage structure. To investigate how lithological variability can force landscape reorganization, we draw inspiration from formerly glaciated portions of the upper Mississippi Valley. In this region, depth-to-bedrock maps reveal buried dendritic river networks dissecting paleozoic sedimentary rock. During the Pleistocene, ice advance buried the bedrock topography with glacial till, resurfacing the landscape and resetting the landscape evolution clock. As newly formed drainage networks develop and incise into the till-covered surface, they exhume the buried bedrock topography. This then leads to a geomorphic "decision point": Will the rivers follow the course of the bedrock paleodrainage network? Or will they maintain their new pattern? Using a numerical landscape evolution model, we find that two parameters determine this decision: (1) the contrast between the rock erodibility of the glacial till (more erodible) and of the buried sedimentary rock (less erodible) and (2) the orientation of the surface drainage network with respect to the buried network. We find that as the erodibility contrast increases, the drainage pattern is more likely to reorganize to follow the buried bedrock valleys. Additionally, as the alignment of the two networks increases, the surface drainage network also tends to restructure itself to follow the paleodrainage network. However, when there is less contrast and/or alignment, the surface drainage pattern becomes superimposed on the bedrock topography, with streams cutting across buried bedrock ridges. Our results agree with field studies demonstrating that variability in erodibility exerts a first-order control on landscape evolution and morphology. Our findings can provide insight into how lithologic variation affects surface processes, drives drainage reorganization, and creates geopatterns.
For many deltas, their morphology reflects the 100-1000 year balance of wave, tidal, and river-driven sediment fluxes. Human-induced changes to these fluxes can also act on 100-1000 years and therefore influence delta morphology.
Wave, tidal, and river fluxes also change on much shorter (day-to seasonal) timescales. These fluctuations do not work their way into delta morphology immediately, but many studies have indicated substantial relevance, nevertheless.
How to marry these two timescales? In this poster I will investigate the concept of river sediment retention, or trapping efficiency, and its potential to relate seasonality to long-term fluxes. For example, wave, river, and tidal fluxes might each dominate for a few months every year. If the order and respective magnitude of these fluxes throughout the year influence tidal sediment retention, it can affect long-term morphology and make it deviate from a balance based on simple annual averages. +
For paleo environmental studies, a key challenge is to partitioning physical signals operated under multiple spatio-temporal scales. For example, paleo relative sea-level (RSL) data record a combined signal from global ice-ocean mass exchange induced global mean sea-level change and gravitational, rotational and deformational effects, along with regional and local RSL change caused by changing ocean density, groundwater storage and sediment redistribution. Here we present an open-sourced spatio-temporal hierarchical model framework (PaleoSTeHM) that is conceptually suitable for investigating this problem by separating the underlying phenomenon of interest and its variability from the noisy mechanisms by which this underlying process is observed. PaleoSTeHM is built upon a modern, scalable machine-learning framework and offers flexible modelling and analytical choices. In this presentation, we will show some of the modelling choices in PaleoSTeHM along with an example application for Holocene sea level change. Also, we will seek inputs from potential users for this framework in order to make this co-develop framework more sustainable and allows a wide range of paleo-sea level and -climate researchers to easily and robustly incorporate spatio-temporal statistical modeling into their work. +
Fractal geometry is a branch of mathematics pioneered by Benoit Mandelbrot in the 1970's with the goal of finding a mathematically rigorous way to define the geometry found in nature, including what he saw in river networks. Since then, much work on the geometry and structure of river networks has involved fractal method, from passing mention to assumed fractal characteristic's to trying to tie older geomorphic parameters to Mandelbrot's fractal math. However results on the fractal dimensions of river networks have been contradictory and not always well matched to theoretical explanations of fractal geometry. For example, in a 1988 work, Tarboton et al. found that the measured fractal dimension of river networks transitioned from close to 1 at small scales to close to 2 at large scales. They attributed this to switching from a regime where fractal dimension was dominated by Sinuosity to one where it was dominated by the branching characteristics of rivers. Neither of these matches Mandelbrot's prediction of a fractal dimension of 1.2 for river networks, which he derived from a Hack exponent of 0.6, used in the relation between stream length and basin area, which would likely be influenced by river branching. More recent unpublished calculation of the fractal dimension of large North American river basins found a dimension close 1.1, which conveniently would correspond to a Hack exponent of 0.55 which matches more recent empirical work on Hack's law. To better understand the connection between fractal dimension and Hack's Law, in this poster I present work comparing the fractal dimension of modeled river networks to physical ones, and look at what theoretical parameters may explain them variability in measured fractal dimensions of river networks. +
Fresh impetus has been given to efforts for a unified bio+geo understanding of seafloor physical properties. In part the requirement comes from practical needs in: the dependability of automated modules (Autonomous Underwater Vehicles), for object detection (e.g. unexploded ordinance), and for more accurate Acoustic Seafloor Classification in habitat mapping. By the combination of various techniques, and especially new information resources, the opportunities for fresh advancement in the field have recently increased.
The new information resources include semantic structures such as Encyclopedia of Life, WoRMS, Traitbank and others where the characteristics of organisms are described, including their lifecycles, engineering activities, morphologies. They also include environmental databases of ever increasing resolution and scope, such as photosynthetically available radiation, sediment types, water flows, particulate matter and nutrients.
The challenge is a significant one, to combine these factors, but there are some approaches which have been tested and found very promising. Some are described in this poster. They include simulations (rather than analytical models) with data formats derived from the 3D printing industry, agent-based approaches, population models of various types (including cellular models), and more.
Global change, often human-induced, is causing a re-balancing between 'barren' sediment-dominated areas and those which are intensely colonized. Models such as these are required to see ahead to the consequences and management of the changes. +
Freshwater inflow plays a substantial role in the water quality of coastal and estuarine watersheds and ecosystems. The salinity of an estuary can vary depending on the amount of freshwater received. In highly managed systems, such as St. Lucie and Caloosahatchee estuaries in south Florida, USA, understanding total freshwater inflow and the sources of inflow is very important for management decision-making. There is very little information on the quantity of freshwater inflow to St. Lucie and Caloosahatchee estuaries from their ungauged tidal basins. This study examines a linked hydrologic, hydraulic, and watershed water quality model (WaSh) for simulating freshwater inflow to these two systems. The WaSh model is a time-dependent simulation model that represents basic surface hydrology, groundwater flow, surface water flow, and water quality fate and transport. The WaSh model consists of four basic components; a cell-based representation of the watershed basin land surface, a groundwater component, a surface-water drainage system, and a water management component that can consider the effects of reservoirs, stormwater treatment areas, irrigation supply and demand, and land-use changes. The model is capable of simulating hydrology in watersheds with high groundwater tables and dense drainage canal networks, which is typical in South Florida.
The model was developed using long-time series of rainfall, temperature, evapotranspiration, basin boundaries, hydrography including streams and canals features, soils, land use, and land surface elevations. The results indicate that the model accurately simulates the distribution of freshwater over the coastal watersheds and the transport of freshwater through the estuary and that it is a valuable tool for understanding the dynamics of freshwater inflow to estuaries in coastal watersheds.
Keywords: Coastal Hydrology, Ungauged basin, WaSh model, estuary, Salinity, hydrologic and hydraulic model, water quality
Freshwater resources in coastal Bangladesh fluctuate with extreme periods of shortage
and abundance. Bangladeshis have adapted to these alternating periods but are still
plagued with scarce drinking water resources due to pond water pathogens, salinity of
groundwater, and arsenic contamination. The success of attempts to correct the
problem of unsafe drinking water have varied across the southern Bangladesh as a
result of physical and social factors. We use a multicriteria decision analysis (MCDA) to
explore the various physical and social factors that influence decisions about freshwater
technologies and management schemes in southern Bangladesh.
MCDA is a holistic, analytical tool for evaluation of alternatives. MCDA is used to
support public participation and provide structured, rational, and transparent solutions to
complex management problems. To determine the best freshwater technologies and
management schemes, we examine four alternatives, including managed aquifer
recharge (MAR), pond sand filter (PSF), rain water harvesting (RWH), and tubewells
(TW). Criteria are grouped into four categories: environmental, technical, social, and
economic. Weighting of social factors will be determined by community surveys, nongovernmental
organizations (NGO) opinions, and academic interviews. Data
include regional water quality perceptions, perceptions of management/technology
success, MAR community surveys, and interviews with NGO partners. Environmental
and technical feasibility factors are determined from regional water quality data,
geospatial information, land use/land change, and regional stratigraphy.
Survey data suggest a wide range of criteria based on location and stakeholder
perception. MAR and PSF technologies likely have the greatest environmental and
technical potential for success but are highly influenced by community dynamics,
individual perspective, and NGO involvement. RWH solutions are used less frequently
due to quantity limitations but are most successful at reducing the water security threats
of contamination by pathogens, arsenic, and salts. This MCDA informs us of community
and stakeholder water resource decisions, specifically related to their objectives and
values.
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GEOtop 1.145 is used to model the thermal and hydrological state of the subsurface in the Kuparuk basin, Alaska. GEOtop is a distributed hydrological model with coupled water and energy budgets. The surface energy balance scheme includes sensible, latent and radiative heat fluxes at the air-soil or air-snow interface. The subsurface represents heat fluxes in the vertical and water fluxes in the vertical and horizontal directions. The ERA-Interim atmospheric reanalysis product, which is used to force the model, is compared to meteorological and radiation data from the Kuparuk Basin and other stations on the North Slope of Alaska. The use of ERA-Interim reanalysis to force GEOtop enables large-scale simulations to be performed over areas where in situ meteorological data is sparse, such as the North Slope of Alaska. Model simulations forced by ERA-Interim reanalysis data are validated using borehole observations of soil temperature. Model results will be presented demonstrating the interactions between soil properties, snow cover, vegetation and climate. +
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Geophysical datasets, thermal modelling, and drilling data suggest that most Arctic shelves are underlain by submarine permafrost due to their exposure during the glacial low water stands. The degradation of subsea permafrost depends on the duration of inundation, warming rate, the coupling of the seabed to the atmosphere from bottom-fast ice, and brine injections into the seabed. The impact of brine injections on permafrost degradation is dependent on seawater salinity, which changes seasonally in response to salt rejection from sea ice formation and terrestrial freshwater inflows. The relative importance of the upper boundary conditions responsible for permafrost table degradation rates, however, remain poorly understood. This study evaluates the effects of changing upper boundary conditions on subaquatic permafrost thaw rates using CRYOGRID, a one-dimensional heat diffusion model, which was extended to include coupled dissolved salt diffusion. More specifically, the impacts of using a seasonally varying seabed temperature function compared to a mean annual seabed temperature for both freshwater and saline water bodies were assessed. For saline conditions, the effects of different salinity regimes at the seabed, including mean annual concentrations and seasonal variations. Daily observations of seabed temperature and electrical conductivity from 01-09-2008 to 31-08-2009 offshore of Muostakh Island in Siberia were used to set up the upper boundary conditions for the base case model runs. For saline water bodies, sensitivity analyses for mean annual salt concentrations and seabed sediment type were also performed. In all model runs, a steady-state heat conduction function was used to calculate the initial ground thermal regime prior to inundation. The initial state of permafrost was assumed to contain no salt and the ramp-up time from a terrestrial to a sub-aquatic upper boundary condition was one year for all simulations. Generally, it was found that using a mean annual seabed temperature overestimates subaquatic permafrost thaw for shallow freshwater by approximately 2 metres after 65 years of inundation. Seasonal variation of the seabed temperature led to seasonal freezing and thawing of the sea bed. However, for water bodies with high mean annual concentrations of salt (i.e. 420 moles NaCl/m3), it was found that the difference between using mean annual versus seasonally varying seabed temperatures was negligible. Dissolved salts below the seabed depress the pore water freezing point sufficiently to prevent ice formation in the near-surface sediment despite sub-zero winter temperatures. Given the current trend of freshening in the Arctic Ocean, we expect seasonal freezing of the seabed to be more common for newly submerged permafrost caused by coastal erosion, and thus potentially leading to slower permafrost table degradation rates.
Glacial erosion has shaped many high mountain belts during the cold periods of the Late Cenozoic. Theoretical models of glacial erosion generally link the pace of erosion to some subglacial properties including basal sliding, basal thermal regime, and effective water pressure. The energy balance of glaciers is a strong control on these properties and therefore, has a potential impact on glacial erosion. Specifically, the geothermal heat from the bedrock can potentially control the patterns and rates of glacial erosion by changing the basal temperature and the supply of meltwater to the subglacial water system. Here, we investigate the impact of geothermal heat flow on glacial erosion using a coupled model of erosion and ice dynamics. The rate of glacial erosion is modeled as a linear function of the basal sliding velocity. The ice flow is modeled using the Parallel Ice Sheet Model (PISM). PISM solves the conservation of energy using an enthalpy-based scheme, and it links basal sliding to subglacial hydrology through a pseudo-plastic basal resistance model. We model glacial erosion over a synthetic glacial landscape using a range of values for geothermal heat flux. Preliminary results demonstrate that higher geothermal heat flux can increase the total amount of erosion significantly by accelerating the rate of basal sliding and expanding the area of sliding into higher elevations. +
Glacial isostatic adjustment creates characteristic patterns of relative sea level change (RSL) as a function of distance to melting ice sheets (Clark et al., 1978). During the last termination and through the Holocene, regions formerly covered by large ice sheets experienced rapidly falling RSL due to the processes involved in glacial isostatic adjustment (GIA), primarily isostatic uplift. Surrounding this region of uplift is a narrow band that similarly records RSL fall but is interrupted at sometime during the Holocene by a period of sea level rise (i.e. a transgressions) culminating in a high stand. Holocene transgressions and highstands have been well documented in many locations including Norway, Canadian Atlantic coast, the Canadian Pacific coast, Svalbard, the Baltic Sea, and the British Isles (Forman, 2004; Smith et al., 2011; Shugar et al., 2014; Shennan et al., 2018; Vacchi et al., 2018; Rosentau et al., 2021; Creel et al., 2022). We investigate the origins of these Holocene transgressions using GIA/sea level modeling and test the hypothesis that they are the direct result of solid Earth deformation. Our modeling results highlight a unique pattern of solid Earth deformation in which the region of subsidence (peripheral bulge) surrounding the ice sheet migrates first towards and then away from the melted ice mass. We show how this effect, we term ’reverse migration’, is the direct result of the contrast in viscosity between the upper and lower mantle. We compare our GIA model predictions of RSL change to 1) RSL data since the last glacial maximum and 2) constrains on the transgression magnitude in Norway and eastern Canada. Both tests show a preference for GIA models that include a mantle with a substantial (1-2 orders of magnitude) increase in vicosity with depth. This suggests that, in contrast to the conventional view that Holocene transgressions record GMSL temporarily outpacing isostatic uplift, solid Earth deformation and specifically reverse migration played an important role in generating nearfield Holocene transgressions. Finally, by comparing GIA model results to RSL observations, we show how Holocene transgressions can be used to constrain the vertical viscosity structure of the mantle. Our findings suggest that a significant increase in viscosity with depth (1-2 orders of magnitude) likely exists below continents with nearfield transgressions.
Glacial lake outburst floods pose an increasing hazard to communities living downstream of glaciated areas. The Northern Patagonia Icefield has experienced catastrophic glacial lake outburst floods (GLOFs), and understanding past events will help to understand and prepare for future events. This region is vastly understudied, and much research remains to be completed to thoroughly understand such complex phenomena such as GLOFs. Satellite imagery, supplemented by high-resolution UAV imagery derived 3D models, are used to understand the hydrodynamics of a GLOF which took place March 16, 1989, in the Valle Soler of the Northern Patagonia Icefield. Using the 3D model and satellite-derived digital elevation model, flood parameters are calculated in order to describe the 1989 Soler GLOF. The results of this analysis are used to understand mass extraction and gradational fining of moraine material in Valle Soler. Blocks of rock, exceeding 10m, are found throughout the valley and a comparison of peak discharge and the necessary force to deposit the blocks are discussed. +
Glacially-derived debris often blankets alpine streams, yet few models have explicitly linked sediment supply and transport between glacial and fluvial systems. Here, we combine a 1-D river-incision model with a quarrying-dominated glacial erosion model. We link sediment production and supply between the two systems, and include a valley width variable that allows glaciers to widen valleys and temporarily store glacially-derived sediment within those valleys. A lateral erosion factor in the fluvial model re-incorporates this sediment, which is transported using a modified Meyer-Peter and Mueller equation and incorporated into bedrock erosion through a cover effect. We calibrated this model using the DAKOTA calibration software to Holocene glaciated alpine rivers in North America and are able to match observed topography within an acceptable Χ^2 fit of <2. +
Globally, more people are impacted by floods than all other forms of natural disasters combined. In global megacities, defined by the United Nations as cities with a population of over ten million, increased human exposure to flooding is both ubiquitous and extremely difficult to characterize. Over the past three decades, most of these cities have experienced a gradual or very rapid growth as the global population continues to urbanize. As both urban expansion and global climate change contribute to hydrologic intensification, and as globally more people live in urban areas than rural ones, the need to assess both the drivers and magnitude of flood risk associated with rapid growth in megacities is of critical humanitarian concern. Through a multitemporal analysis (2000, 2010, and 2020) of urban growth modes and urban landscape change detection using the Landsat dataset (ETM+, OLI), we estimate the growth rates and development patterns in ten global megacities (Guangzhou, Tokyo, Lagos, Jakarta, Delhi, Manila, Mumbai, Seoul, Mexico City, New York) representing different global climate zones using machine learning. Trends in runoff magnitudes over the time period are quantified and associated with urban expansion and non-stationarity in regional historical precipitation patterns. Preliminary results showed that the ten cities have experienced major flooding within the last ten years resulting mostly as a result of heavy rainfall. +
Globally, the occurrence of extreme hydrologic events such as flooding is known to be the widespread aftermath of torrential rain and the impacts are adverse and devastating in built areas with proximity to water bodies. An example is the 2012 and 2022 flooding along the Niger and Benue rivers in Nigeria. While Nigeria experiences seasonal flooding during the rainy season, the decadal interval between these two catastrophic flood events and the similarities between the natural and anthropogenic conditions responsible for their occurrence prompted this study. Additionally, some hydrologic characteristics and attributes of these flood events are yet to be evaluated. Hence, for the 2012 and 2022 floods, we estimated and compared the floodwater depths at different sections of the Niger and Benue Rivers using the Floodwater Depth Estimation Tool (FwDETv2.0 and FwDETv2.1) implemented in Google Earth Engine, Jupyter Notebook, and ArcGIS Pro. Since this algorithm requires minimal input (flood inundation map and Digital Elevation Model) which favors data-sparse regions such as Nigeria, the potential for the FwDET tool to automatically quantify flood water depths, an important variable in flood intensity estimation was assessed. This tool could be invaluable in flood management and mitigation studies along the rivers. +
Graphics Processing Units (GPUs) have been shown to be very successful in accelerating simulation in many fields. When they are used to accelerate simulation of earthquakes and tsunamis, a big challenge comes from the use of adaptive mesh refinement (AMR) in the code, often necessary for capturing dynamically evolving small-scale features without excessive resolution in other regions of the domain.
Clawpack is an open source library for solving general hyperbolic wave-propagation problems with AMR. It is the basis for the GeoClaw package used for modeling tsunamis, storm surge, and floods. It has also been used for coupled seismic-tsunami simulations. Recently, we have accelerated the library with GPUs and observe a speed-up of 2.5 in a benchmark problem using AMR on a NVIDIA K20 GPU. Many functions that facilitate the execution of computing kernels are added. Customized and CPU thread-safe memory managers are designed to manage GPU and CPU memory pools, which is essential in eliminating overhead of memory allocation and de-allocation. A global reduction is conducted on each AMR grid patch for dynamically adjusting the time step. To avoid copying back fluxes at cell edges from the GPU memory to the CPU memory, the conservation fixes required between patches on different levels are also conducted on the GPU. Some of these kernels are merged into bigger kernels, which greatly reduces the overhead of launching CUDA kernels. +
High quality Digital Elevation Models (DEMs) do not exist in coastal wetlands prior to the widespread use of aerial LiDAR beginning in the early 2000's. This makes it difficult to develop models that capture the historical evolution of specific coastal marshes, creating a challenge in communications between the modeling community and wetland managers who seek to understand model outputs in the context of their experience, observations, history of management decisions, and perception of risk.
The project team is working with managers at four coastal wetlands to advance a method that will fill this data gap using historical remotely sensed imagery, historical in-situ observations, and machine learning. The team will compile Landsat imagery collected within one year of an existing high quality DEM. The suites of Landsat imagery will be processed to produce maps showing inundation frequency based on the Normalized Difference Water Index (NDWI), and these will be used as training data for a deep learning image segmentation model that relates inundation frequency with wetland elevation. The segmentation model will then be validated with observational data and applied to the period before DEMs are widely available but during which Landsat sensors are consistent with today’s standards (i.e. 1984 to the present). +
Hourly precipitation for one historical (1991-2000) and two future periods (2031-2040 and 2071-2079) were generated using the Weather Research and Forecasting (WRF) Regional Climate Model (RCM). The climate simulations were conducted for the Southwest region of the United States using an hourly temporal and 10 km spatial resolution grid. The boundary forcing for the WRF model was developed by the Hadley Centre for Climate Prediction and Research/Met Office’s HadCM3 model with A2 emission scenario. The precipitation from the RCM-WRF model was bias-corrected using the observed data, and then used to quantify the impact of climate change on the magnitude and frequency of flood flow in the upper Santa Cruz River watershed (USCRW) in southern Arizona. The Computational Hydraulics and River Engineering two-dimensional (CHRE2D) model, a two-dimensional hydrodynamic and sediment transport model, was adapted for surface flow routing. The CHRE2D model was first calibrated using a storm event on July 15th, 1999, and then applied to the watershed for three selected periods. The simulated annual maximum discharges in two future periods were added to the historical records to obtain the flood frequency curve. Results indicate the peak discharges of 100-year, 200-year, and 500-year flood only increased slightly, and the increase is within the 90% confidence interval limits. Therefore, the flood magnitude and frequency curve will not change with the inclusion of projected future climate data for the study watershed. +
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Hurricanes are one of the most costly natural disasters impacting US coastal areas. Recent studies point towards an increase in damages caused by hurricanes, resulting from sea-level rise (SLR), possible hurricane intensification due to a warmer climate and increasing coastal populations. The SLR is one of the most significant factors of climate change that will impact coastal areas. Besides geometrical changes in coastal bays (i.e., deeper water depth and larger surface area), SLR is also expected to have substantial impacts on the patterns and process of coastal wetlands, thereby affecting surge generation and propagation inside the bays. We analyzed the impacts of SLR on hurricane storm surges, structural building damage, and population and businesses affected for coastal bays located on the Texas central coast. To evaluate the effects of SLR on surges, we considered its impacts on changes in land cover and bay geometry caused by SLR. The analyses were conducted using the hydrodynamic model ADCIRC and a wind and pressure field model (PBL) representing the physical properties of historical hurricane Bret and hypothetical storms. The effects of land cover change were represented within ADCIRC by the changes in the frictional drag at the sea bottom and changes in momentum transfer from the wind to the water column caused by vegetation losses. Simulations were performed using a high-resolution unstructured numerical mesh to study surge response in communities along the coastal bays of Texas. First, we evaluated the impacts of land cover changes due to SLR on the surge response. Second, we evaluated the impacts of neglecting land cover changes due to SLR on the surge response. Finally, we evaluated the overall effect of SLR on the mean maximum surge and the consequent extent of the flooded areas.
Although the overall impacts of SLR on surge (i.e.: water elevation above mean water level) are highly dependent on storm conditions and specific locations within the study area, we showed that the mean maximum surge (spatial average within each bay) increases with SLR. The overall mean maximum surge within the study area increased on average approximately 0.1 m (SLR of 0.5 m) and 0.7 m (SLR of 2.0 m). Simulations neglecting land cover changes due to SLR did significantly underestimate the expected structural damage for buildings. This difference increased with SLR and was affected by the storm meteorological conditions. Stronger and faster storms were associated with higher underestimation. Although considering land cover changes resulted in an overall damage increase, for SLR below 0.5 m, this increase was almost negligible. As a result, the land cover changes arising from SLR are important for damage estimation considering SLR scenarios over at least 0.5 m. For example, when considering a SLR of 0.6 m, based on the Intergovernmental Panel on Climate Change’s (2007) high emission scenario, we demonstrated a 10% increase in building structural damage. The assimilation of land cover changes is especially important when calculating expected damages from high SLR scenarios. If a SLR of 2.0 m is assumed, a 35% increase in the expected structural damage to buildings is estimated. In summary, the changes in coastal bay geometry and land cover caused by SLR play an important role in the resulting surge response. The variability of the surge response is also greatly affected by location and the characteristics of the storm.
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Hydrologic connectivity can change as climate changes, seasonally, or even after a single rain event. Here, I assess the depression structure of the topography of the United States and determine its capacity to hold surface water in lakes. I provide results from a simulation indicating the pre-industrial water level in these depressions and the resulting degree of hydrologic connectivity. I then share results from a series of experimental simulations to modify water levels and the resulting hydrologic connectivity across the country. +
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IEDA (Integrated Earth Data Applications, www.iedadata.org) is a data facility funded through a contract with the US National Science Foundation to operate data systems and data services for solid earth geoscience data. There are many similarities between IEDA and its community of data producers and users and CSDMS and its community of model creators and users. IEDA has developed a comprehensive suite of data services that are designed to address the concerns and needs of investigators, especially researchers working in the 'Long Tail of Science' (Heidorn 2008). IEDA provides a data publication service, registering data sources (including models) with DOI to ensure their proper citation and attribution. IEDA works with publishers on advanced linkages between datasets in the IEDA repository and scientific online articles to facilitate access to the data, enhance their visibility, and augment their use and citation. IEDA also developed a comprehensive investigator support that includes tools, tutorials, and virtual or face-to-face workshops that guide and assist investigators with data management planning, data submission, and data documentation. A relationship between IEDA and CSDMS benefits the scientists from both communities by providing them with a broader range of tools and data services. +
In Arctic landscapes, modern surface warming has significantly altered geomorphic process rates. Along the Beaufort Sea coastline bounding Alaska’s North Slope, the mean annual coastal erosion rate has doubled from ~7 m/yr for 1955-1979 to ~14 m/yr for 2002-2007. Locally the erosion rate reaches 30 m/yr. A robust understanding of the processes that govern the rate of erosion is required in order to predict the response of the coast and its adjacent landscape to a rapidly changing climate, with implications for sediment and carbon fluxes, oilfield infrastructure, and animal habitat.
On the Beaufort Sea coast, bluffs in regions of ice-rich silt-dominated permafrost are abundant. This type of coast is vulnerable to rapid erosion due to its high ice content and the small grain size of bluff sediment. The bluff material at our study site near Drew Point is 64% ice, making the bluff susceptible to thermal erosion. Liberated sediment is removed from the system in suspension and does not form sheltering beaches or barrier islands which would provide a negative feedback to erosion. During the sea ice-free season, relatively warm waters abut the bluff and ocean water melts a notch into the 4-m tall bluffs. The bluffs ultimately fail by the toppling of polygonal blocks bounded by mechanically weak ice-wedges that are spaced roughly 10-20 m apart. The blocks then temporarily armor the coast against further attack.
We document the style and the drivers of coastal erosion in this region through simultaneous measurements of the oceanic and atmospheric conditions, and time-lapse imagery. We extract proxies for erosion rate from time-lapse imagery of both a degrading block and a retreating bluff from the summer of 2010, and compare the proxy record with environmental conditions and melt rate models. These observations verify that the dominant process by which erosion occurs is thermal insertion of a notch, toppling of blocks, and subsequent melting of the ice in the block. The annual retreat rate is governed by the length of the sea ice-free season, water and air temperatures, and the water level history, including both storm surge and wave height.
Motivated by these observations, we developed a numerical model to capture the evolution of the permafrost bluffs on the North Slope. We honor the high ice content of the bluff materials and the role of the toppled block in temporarily armoring the coast. We employ a positive degree day algorithm to drive subaerial melt, and a modified iceberg melting algorithm to determine rate of notch incision. Our model is first applied to the 2010 coastal retreat history, and is then used to address field and remote sensing observations over a variety of timescales. Finally, we employ the model to explore expected changes in coastal retreat rates in a range of climate scenarios that include increases in the duration of sea-ice free conditions, warming ocean temperatures, and changes in storm frequencies.
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In China, permafrost is mainly underlain on the Qinghai-Tibet Plateau (QTP), which is the largest mid-low latitude permafrost region in the world. Owing to the unique and extremely high altitude, permafrost area on the QTP approximately amounts to 1.06 million km2. Permafrost on the QTP is one of the most sensitive indicators to global climate change, because it is the product between the earth and atmosphere system. The active layer is the interface between the earth and atmosphere. To understand the present condition of active layer and permafrost thermal state is the foundation to learn about the hydrological cycles, infrastructures built on and in permafrost, soil carbon release and uptake, and biogeochemical and ecological processes in cold regions. The observations can depict the present state of permafrost, but models are eventually essential to predict future changes of permafrost. Despite the fact that geophysical surveys and boreholes are the most reliable sources of information about permafrost, they are extremely costly and are mostly available from relatively small regions. I tried to implement the Geophysical Institute Permafrost Lab Version2 (GIPL2) model on the Qinghai-Tibet Plateau (QTP). The GIPL2 model can provide more permafrost thermal state than those of statistical empirical models. I am interested in applying the GIPL2 model to the Qinghai Tibet Plateau in order to know the thermal state of QTP permafrost and its response to recent climate changes. The results of our present work using the original version of GIPL2 indicated that for the whole permafrost area of the QTP, the simulated ALT ranges from 0 to 8 m, with an average of 2.30 m. The simulated 18 ALT sites are generally underestimated compared with the observed values with the MBE value of -0.14 m and the RMSE value of 0.22 m. +
In an ongoing NASA project, our team is producing enhanced global flood hazard maps from advanced modeling, remote sensing and big data analytics. The innovation is that we couple long-term Water Balance Model (WBM) global scale hydrologic flow simulations with the 2-D LISFLOOD-FP model to generate continental scale flood inundation maps that are then integrated with the flood map information from the DFO, including their radiometry-based satellite discharge estimations, i.e. “River Watch”. These remotely sensed discharge stations will be employed to associate flow return periods to the DFO satellite flood maps (up to the 25-year floodplain) that can then be cross-validated with frequencies of inundation from the flood model historic simulations. Furthermore, we collaborate with Google Inc and use their EE platform for big data analytics, such as downscaling our model simulations of flood hazard to adequate resolutions for decision-makers. This poster will present first achievements for Australia, Africa and CONUS, and discuss challenges and perspectives. +
In complex systems, emergence occurs when a ‘new’ property arises at higher levels of organization that cannot be directly deduced from the behavior of constituent elements. While many geomorphic systems exhibit emergence, numerical models of surface processes typically address emergence by carefully selecting the appropriate spatio-temporal scale to parameterize the relevant physics, chemistry, and biology that is occurring at lower levels of organization. This is an effective strategy where finer-scale processes are either poorly constrained or intractable to model numerically. The concept of the geomorphic transport law reifies this strategy by adopting a ‘top down’ approach where surface processes are encoded into the set of partial differential equations chosen. However, as data resolution and computational power increase, there are new opportunities to build models that simulate processes from the ‘bottom up’.
One such opportunity is in the simulation of biologically driven soil production and sediment transport. Biological systems exhibit some of the most compelling examples of emergence (e.g., insect societies, flocking behavior, fairy circles) that are readily simulated using Agent-Based Models (ABMs). Given that biota drive many of the most widely used geomorphic transport laws, it is worth taking stock of whether ABMs can provide new insights into surface process modeling. We present two promising examples where we think ABMs might provide new, testable predictions of soil production and sediment transport. The first example focuses on tree seeding, recruitment, growth, and death. Rules for soil production via tree root growth monotonically decrease with soil depth. However, because soil production in the model depends not only on individual tree root growth but also the probability of an unstressed tree growing at any given location, humped soil production functions emerge over the long-term. The second example focuses on one hypothesized mechanism for mima mound formation. Rules for burrowing organisms allow for preferential upslope transport of sediment into mounds while gravitational processes (i.e., creep) degrade mounds. Both examples highlight how ABMs help make rules for ecological dynamics explicit. Bulk coefficients common to conventional treatments of soil production and sediment transport laws are thus allowed to emerge from the empirically constrained rulesets that are used.
In gravel-bedded rivers, bed material abrasion is a well-recognized control on the balance between fine and coarse sediment fluxes. We suggest that in some landscapes, abrasion may also be an important control on the morphodynamics of sediment pulses. Here, we employ a simple morphodynamic model to explore the extent to which bed material abrasion controls the downstream fate of sediment pulses in terms of transit time and the magnitude of response in channel bed elevation and grain size change. The Network Sediment Transporter (NST) is a Lagrangian 1-D morphodynamic model component that tracks bed sediment moving and interacting on a river network. The NST is implemented in Landlab, a Python-based package for modeling the Earth’s surface. The NST tracks ‘parcels’ of sediment (collections of grains of homogeneous size, density, etc.) as they transport through the network, allowing us to explicitly tag and follow sediment as originating in the mass wasting deposit and give that sediment unique abrasion characteristics. The model requires inputs about channel morphology, flow, and bed sediment attributes. Here, we compare the results of a simple sediment pulse simulation without abrasion of the bed material to an identical pulse with abrasion rates equal to measurements made on a volcanic mass wasting deposit in the Cascade Range of Washington. The differences between pulse behavior with and without abrasion have implications for hazards in volcanic terrains where channels are commonly subject to large mass wasting deposits of heterogeneous sedimentary characteristics. Understanding the fate of these large sediment pulses will increase our understanding of downstream channel aggradation and increases in flood frequency. +
In many areas of the world, the environment has been engineered to reduce variability (increase robustness) for human development. As much of the agricultural land in the middle US is located in arid and semi-arid regions, agricultural practices depend on irrigation. Since the 1960’s thousands of fields are watered using center pivot irrigation, each of which requires about 800 gpm (4,361 m3/day) (New and Fipps, 2017). Groundwater supported irrigation was dependable for decades, but now many areas of the High Plains aquifer, which is partly composed of the Ogallala aquifer, is at risk of depletion, and farming is facing difficult circumstances. On the positive side, western Kansas has very high potential capacity for wind power production, but opportunities to use this locally produced energy to improve prospects for the farming community face scientific and engineering challenges and, communities are not aware of many potentially promising alternatives. The Food-Energy-Water calculator (FEW) is a tool designed to introduce new alternatives to these communities and the scientists, engineers, and governmental entities who support them. In this study, Agent-Based Modeling (ABM) is used to coordinate the many types of actors, information and alternatives relevant to this problem. For more creative agricultural scenarios, a crop model called Decision Support System for Agrotechnology Transfer (DSSAT) can be used to calculate crop yields and income. The resulting ABM based FEW calculator provides a more realistic and effective framework for managing the complexity between the human and natural system dynamics. +
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In most mountainous regions reconstructed glacial histories are the primary record of past climate and are typically based on unsorted accumulations of debris (moraines) deposited at the terminus of glaciers. Former glacier geometries— preserved as moraines and trim lines— are the primary constraint for extracting paleoclimate estimates using either equilibrium-line altitudes or numerical glacier models.
It is an implicit assumption in the glacial geology community that terminal moraines were formed by glaciers responding to the mean value of summer temperature and winter precipitation at the time of formation. In reality glacier termini oscillate around a mean glacial length even in a steady climate, defined by a constant mean and constant standard deviation. These length oscillations are driven by the alignment of more negative (positive) periods of mass balance that arise out of random year-to-year climate variability. Because glaciers that override moraines almost always destroy them, the furthest terminal moraines from the headwall during the time period of interest represent the maximum excursion of the glacier from its mean length. This implies that paleoclimate estimates based upon the furthest terminal moraine are actually maximum estimates of climate change.
We use a linearized glacier model developed by Roe and O’Neal (2009) to determine the mean length of eleven Last Glacial Maximum (LGM) glaciers in the northern Front Range, Colorado. Mean glacier lengths during the LGM were ~15% upvalley from the LGM terminal moraines. In the Colorado Front Range estimating LGM paleoclimate from the furthest terminal moraine rather than the mean length adds an extra ~1°C temperature change or an additional 25% increase in precipitation to estimate of differences from the modern climate. Furthermore, it is possible that ‘recessional’ moraines were formed by length oscillations driven by interannual variability. +
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In recent years a large number of numerical models have been developed and implemented to study basic and applied problems of research moprhodyanmics. Some of these models treat the bed material as uniform; others consider the bed material as a mixture of sand and gravel. The vast majority of the morphodynamic models that account for the non-uniformity of the bed material size are based on the active layer approximation, i.e. the channel bed deposit in two different regions. The active layer, which is the topmost part of the bed deposit, is modeled as mixed layer whose particles can interact with the bed material transport. Particles in the rest of the channel deposit, the substrate, can be exchanged with the bed material transport only when the channel bed aggrades or degrades. Morphdynamic formulations based on the active layer approximation, however, have well known limitations:1) they neglect the vertical fluxes within the deposit associated with e.g. bedform migration, 2) they cannot capture the infiltration of fine sediment and tracer stone dispersal and 3) the statistical nature of sediment entrainment is neglected. To overcome these limitations, Parker and coauthors in 2000 introduced a continuous, i.e. not layer-based, morphodynamic framework based on a stochastic description of the bed surface elevation, of the entrainment and deposition. In this framework particle entrainment rates are computed as a function of the flow and sediment characteristics, while particle deposition is estimated with a step length formulation. However, due to the lack of mathematical functions describing the variability of bed elevation, entrainment and deposition, the continuum framework has never been implemented. Here we present one of the first implementation of the continuum framework at laboratory scale and its validation against laboratory experiments on tracer stones dispersal. The validated model is then used to investigate the dependence of the model results on different particle step lengths.
In recent years, seismic signals previously thought of as “noise” have become a subject of study for environmental seismologists. These signals can reveal Critical Zone and geomorphic processes which traditionally are not well-constrained, such as the roles biota play in weathering, movement of mass, and landscape evolution. Wind-driven tree sway is central to conceptual models of physical bedrock weathering and subsequent soil production. However, despite documentation, seismic signals of wind-tree interactions have been largely ignored by surface process researchers. Our work focuses on identifying the seismic signature of tree-captured wind by comparing seismic data in areas with little to no vegetation against heavily vegetated areas. Using meteorological and seismic data from the Transportable Array deployed in Alaska, we isolate this vegetation effect on seismicity by selecting for periods with high-wind events in the absence of rain. We hypothesize that there is a difference in strength of seismicity which scales with percent tree cover. We use a combination of wind speed and seismic data to explore the impact of vegetation on seismic amplitude and examine the spectral signature of wind moving trees in order to better understand its contribution toward soil production and nutrient/carbon cycling in the Critical Zone. +
In terrestrial ecosystems, rock fractures as unsaturated reservoirs for vegetation have been recently recognized as a key ecohydrological process. However, it remains unclear how the coupling between plant water use strategies and rock water storage interplay. We selected Douglas fir and Engelmann spruce trees growing on both soils and exposed limestone cliffs in the Canadian Rockies. We measured sap flow, stem water potential, and superficial fracture substrate moisture for trees growing in rock fractures and glacial till. Isotopic analysis of precipitation, plants, and soil samples revealed that the trees do not have access to any long-term water sources but rather use recent precipitation values. To explore the relationship within the system, we built a stock-flow model with three stocks: the surface fracture, the deep fracture, and the tree itself, and observed that cliff trees respond slightly differently to water replenishment due to the cliff architecture. Plant regulation coupled with rock water storage is crucial to model water movement through plants in highly water-limited environments correctly. Our study highlights the importance of understanding how trees access rock moisture storage in water-limited environments. +
In the same way that watersheds filter precipitation signals into a time series of flow response, watersheds also filter sediment production signals into a time series of bedload transport. Here, we describe the Mass Wasting Router, a new watershed-scale sediment production and transport model written for Landlab that couples an existing shallow landslide hazard model (LandslideProbability) with an existing network-scale bedload transport model (NetworkSedimentTransporter) by (1) delineating hillslope scale landslides from maps of landslide probability, (2) routing the landslides through the watershed using a “precipiton” or “agent” style model and (3) fluvially eroding the mass wasting deposits and creating parcels for the NetworkSedimentTransporter. Preliminary model runs indicate that variation in soil cohesion and precipitation intensity drive landslide-derived hillslope sediment production rates but valley storage processes, driven by debris flow deposition patterns, modulate bedload transport rates at the basin outlet. +
In the southern San Andreas Fault zone, the San Gorgonio Pass (SGP) stands as a region of intricate structural complexity, pivotal for the assessment of seismic hazards due to its potential role in modulating earthquake rupture propagation. This investigation delves into the SGP's crucial function in earthquake dynamics amid ongoing discussions on slip partitioning among its fault strands, aiming to fill a substantial knowledge gap concerning fault activity spanning the last 1 to 100 thousand years. The challenge of estimating slip rates, exacerbated by a dearth of datable materials within the SGP's challenging terrain, calls for innovative methodologies to assess uplift rates along previously overlooked fault segments. In our study, we use thermoluminescence (TL) thermochronology to evaluate differential uplift by analysing bedrock erosion rates. Although AHe dating sheds light on thermal histories and erosion rates across millions of years, it falls short in detailing the recent uplift history vital for grasping Quaternary fault dynamics. In contrast, cosmogenic 10Be dating proves effective in measuring surface erosion rates over millennial timescales, providing insights into contemporary geological activities. TL dating, with its capacity to discern bedrock exhumation over 10-100 ka, acts as a bridge between the temporal scales of AHe thermochronology (Ma) and cosmogenic 10Be denudation rates (ka). By juxtaposing erosion rates across different faults within the SGP, our research aims to pinpoint active fault segments, thereby enriching our understanding of fault dynamics and seismic risk in the southern San Bernardino Mountains. +
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In this study, a methodology based on a multi-resolution wavelet analysis is introduced to extract a regularized topographic index (TI) distribution from a high-resolution DEM (digital elevation model). The methodology is a promising method to deal with common problems in hydrological applications of high-resolution DEMs, which usually contain noise, pits and redundant information. Formation of several unconnected saturated zones is a particular case of such problems when TOPMODEL is employed for simulation of hydrological processes within a basin. The proposed method includes four steps. The first two steps are used for smoothing and de-noising purposes and include decomposition of the original DEM into multi-level sub-signals by 2-dimentional discrete wavelet transform (DWT) and thresholding of the wavelet coefficients. In the next step, the original smoothed and filtered DEM is reconstructed using inverse DWT. Finally, the TI distribution and its information content are computed. The computed information content is used as a metric to identify an optimal TI distribution which contains reasonable topography information in the absence of noise and redundancy. Application of the procedure to 1-m resolution LiDAR (light detection and ranging) DEM of the Elder Creek River watershed via the TOPMODEL framework indicates its filtering ability to smooth and connect the saturated areas during the hydrological process. In addition to the rainfall-runoff modeling, the proposed pre-processing technique may be applied wherever a high-resolution DEM is employed for distributed simulation of hydro-environmental processes. +
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In this study, implicit and explicit spectral solutions are considered for solving the linear diffusion term of a simple 2D loosely coupled landscape evolution model. Spectral methods are powerful tools for solving elliptical partial differential equations and are widely used in other fields, though they have received comparatively little attention in landscape evolution modelling. In the LEM considered, the land surface elevation is altered by three processes: regional uplift, fluvial incision, and linear hillslope diffusion. In the simplest case, these processes act in an undifferentiated way across the entire landscape. While a recent algorithm has provided a powerful implicit solution to for the fluvial incision term, explicit formulations of diffusion remain standard. However, when the desired grid is large, an explicit method may be restricted by stability to a time step too small for the timescales of interest. To solve this problem implicitly, I transform the problem into the spectral domain, solve the 2D diffusion equation with a Crank-Nicholson method, and compare the results to explicit finite difference and explicit spectral methods. In its most simple formulation, the spectral methods require periodic boundary conditions in both dimensions. Resulting from these conditions, I show a tessellating solution where the landscape takes the form of a flat torus. +
Information on flood inundation extent is important for understanding societal exposure, water storage volumes, flood wave attenuation, future flood hazard, and other variables. A number of organizations now provide flood inundation maps based on satellite remote sensing. These data products can efficiently and accurately provide the areal extent of a flood event, but do not provide floodwater depth, an important attribute for first responders and damage assessment. Here we present a new methodology and a GIS-based tool, the Floodwater Depth Estimation Tool (FwDET), for estimating floodwater depth based solely on an inundation map and a digital elevation model (DEM). We compare the FwDET results against water depth maps derived from hydraulic simulation of two flood events, a large-scale event for which we use medium resolution input layer (10 m) and a small-scale event for which we use a high-resolution (LiDAR; 1 m) input. Further testing is per- formed for two inundation maps with a number of challenging features that include a narrow valley, a large reservoir, and an urban setting. The results show FwDET can accurately calculate floodwater depth for diverse flooding scenarios but also leads to considerable bias in locations where the inundation extent does not align well with the DEM. In these locations, manual adjustment or higher spatial resolution input is required. +
Infrequent, large-magnitude discharge (>10^6 m^3/s) outburst floods—megafloods—can play a major role in landscape evolution. Prehistoric glacial lake outburst megafloods transported and deposited large boulders (≥4 m), yet few studies consider their potential lasting impact on river processes and form. We use a numerical model, constrained by observed boulder size distributions, to investigate the fluvial response to boulder deposition by megaflooding in the Yarlung-Siang River, eastern Himalaya. Results show that boulder deposition changes local channel steepness (ksn) up to ∼180% compared to simulations without boulder bars, introducing >100 meter-scale knickpoints to the channel that can be sustained for >20 kyr. Simulations demonstrate that deposition of boulders in a single megaflood can have a greater influence on ksn than another common source of fluvial boulders: incision-rate-dependent delivery of boulders from hillslopes. Through widespread boulder deposition, megafloods leave a lasting legacy of channel disequilibrium that compounds over multiple floods and persists for millennia. +
Inhabitants of Bangladesh and West Bengal rely significantly on groundwater for drinking water. Estimates suggest that 7 to 11 million drinking water wells are contaminated by high concentrations of naturally occurring arsenic. The arsenic likely derives from the pyrite-rich sediment of the Ganges basin, however, the cause and timing of mobilization of the arsenic have been difficult to determine. Generally, shallow and deep aquifers contain low concentrations of arsenic, while mid-depth aquifers (20 to 100 m) are often contaminated. The Ganges river is extremely active and has dissected large portions of previously deposited sediments, introducing significant subsurface heterogeneity and complicating the search for safe drinking water. Here, we have aggregated a variety of datasets into a PostgreSQL database, which we use to build predictive models of arsenic concentration in groundwater. We use the Bangladesh Arsenic Mitigation Water Supply Project (BAMWSP) dataset of ~4.5 million wells to train our models. The predictors for our models are largely based on ~15,000 stratigraphic sediment samples from ~10 transect and ~400 total cores. Approximately 5,000 of these samples have been analyzed for grain size, magnetic susceptibility, chemical composition, and organic matter content. We use elevation and population density as additional predictors. With this database, we will create a regional statistical model that may lead to better prediction of arsenic contaminated wells. By compiling and analyzing these data, we hope to improve water security in this rapidly developing region. +
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Integrated hydrologic models are growing in application and show significant promise in unraveling connections between the surface, subsurface, land-surface and lower atmospheric systems. Recent advances in numerical methods, coupled formulation and computing power have all enabled these simulation advances. Here, I will discuss the modeling platform ParFlow, an integrated hydrologic model that has been coupled to land surface and atmospheric models. I will then discuss a recent application of this model to a large, Continental-Scale domain in North America at high resolution that encompasses both the Mississippi and Colorado watersheds. Details will include techniques for model setup and initialization, in addition to results that focus on understanding fluxes, feedbacks and systems dynamics. Additional anthropogenic complications such as the effects of pumping, irrigation and urbanization will be discussed and a path forward for integrated simulations of the hydrologic cycle will be presented. +
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Integration of humans within landscape evolution models (LEM) as responsive actors in complex human-environmental systems, is still in its infancy. LEMs that included human decision-making have done so either entirely within an agent-based model (ABM) (e.g., CYBEROSION (Wainwright 2008)) or by coupling an ABM with a LEM (e.g., MedLanD (Barton et al. 2012)). These LEM-ABM examples have analyzed the effects of land use and tillage decisions on landscape evolution, but other ways in which humans interact with geomorphic systems have yet to be explored. Our research expands human-environment interaction modeling to landscapes modified by agricultural terraces to explore the long-term geomorphic evolution in these regions.
Agricultural terraces are anthropogenic landforms that have been constructed for centuries in many parts of the world. Despite their widespread distribution and well-known reduction of sediment transport, terraces have rarely been included within LEMs (cf. Lesschen, Schoorl, and Cammeraat 2009). Recent research on agricultural terraces has revealed that terrace abandonment often increases soil erosion and landscape degradation, reversing landscape evolution patterns modified by terrace construction (Tarolli, Preti, and Romano 2014/6; Arnáez et al. 2015/5). We present the Agricultural Terraces Model (AgrTerrModel), which is a coupled LEM-ABM system for analyzing long-term human-environment interactions in terraced landscapes. The LEM component is implemented using the Landlab library and features adjustments to governing landscape evolution equations to reflect changes to geomorphic processes after terrace construction, such as the impact of stone terrace walls that block sediment movement downslope. The ABM component is implemented using the Mesa ABM framework and includes mechanisms for terrace wall collapse and maintenance, as well as agents who determine cultivation and maintenance practices for terraced land. Using the AgrTerrModel, we simulate landscape evolution in Vernazza, Liguria, Italy near Cinque Terre to analyze how the timing and amount of terrace wall maintenance affects sediment transport. The interaction between seasonal precipitation and the timing of terrace wall maintenance is of special interest due to the Mediterranean climate of the study area. This project provides new insights into the evolution of terraced landscapes and an avenue for further research into the complexity of human-environment systems.
References Cited:
Arnáez, J., N. Lana-Renault, T. Lasanta, P. Ruiz-Flaño, and J. Castroviejo. 2015/5. “Effects of Farming Terraces on Hydrological and Geomorphological Processes. A Review.” Catena 128: 122–34.
Barton, C. Michael, Isaac I. T. Ullah, Sean M. Bergin, Helena Mitasova, and Hessam Sarjoughian. 2012. “Looking for the Future in the Past: Long-Term Change in Socioecological Systems.” Ecological Modelling 241 (August): 42–53.
Lesschen, J. P., J. M. Schoorl, and L. H. Cammeraat. 2009. “Modelling Runoff and Erosion for a Semi-Arid Catchment Using a Multi-Scale Approach Based on Hydrological Connectivity.” Geomorphology 109 (3–4): 174–83.
Tarolli, Paolo, Federico Preti, and Nunzio Romano. 2014/6. “Terraced Landscapes: From an Old Best Practice to a Potential Hazard for Soil Degradation due to Land Abandonment.” Anthropocene 6: 10–25.
Wainwright, John. 2008. “Can Modelling Enable Us to Understand the Rôle of Humans in Landscape Evolution?” Geoforum; Journal of Physical, Human, and Regional Geosciences 39 (2): 659–74.
It has been hypothesized that large, rare flooding events in semi-arid to arid climate regimes may do more erosive work than the frequent storm events that occur in humid or temperate climates. Previous work has demonstrated that added variability in modeled climate or water discharges may be linked to changes in landscape form or channel characteristics. Many landscape evolution models do not capture hydrograph dynamics, so they may miss critical aspects linking flood events and erosion. To explore how different climates shape landscapes, this work uses a hydrodynamic model to simulate flooding and erosion processes. Precipitation time series, based on observed event frequency data from NOAA, are used to differentiate modeled wet and dry regimes. The drier regime is characterized by a heavy-tailed flood probability distribution, where the rarest events have a greater magnitude than storms of a similar recurrence in wetter regions. Hydrographs driven by these precipitation time series are used to erode the topography of a synthetic watershed. Simulations are run with and without an incision threshold. After 10^4 modeled years, landscape characteristics such as relief and channel concavity can be compared. Total eroded depths are evaluated for the different storm frequencies to explore how individual floods and the cumulative work of all floods sculpt landscapes. We propose when an incision threshold is considered, the higher magnitude events in arid regimes will be more effective at shaping watersheds than events of the same frequency in temperate climates. These results inform the discussion of how fluvial erosion may change if anthropogenic climate change leads to the aridification of presently temperate regimes. Additionally, this study will illustrate how hydrograph shape and duration impact modeled landforms, processes not captured in traditional landscape evolution models. +
It has been well documented that climate warming was greater in the Arctic than elsewhere. However, it is still poorly understood how climate changed over different permafrost zones and its potential impacts on permafrost thermal dynamics. In this study, we investigated changes in air temperatures, especially seasonal air temperatures, over different permafrost regions in the Northern Hemisphere using the Climate Research Unit (CRU) gridded datasets from 1976-2016. The primary results indicated that permafrost regions as a whole experienced a warming at 0.36, 0.41, and 0.46 °C/decade in mean annual maximum, mean, and minimum air temperature, respectively, which are 16%, 32%, and 44% higher than the corresponding trend in non-permafrost regions. More importantly, strong increases occurred in cold months and nighttime over continuous permafrost zone, exceeding 0.72 °C/decade in Spring and Autumn; while summer air temperature had a relatively small increase or no statistically significant trends. As a result, the decrease of air freezing index by 529 °C-day would result in permafrost temperature increase by 1.43 °C in continuous permafrost zone over the past four decades. This may explain the observed evidence that increase of cold permafrost temperature was greater than that of warm permafrost, while active layer thickness had little or no change during the past several decades. These results suggest that predicted reduction of permafrost area by previous studies might be overestimated. +
Lago Cachet Dos (LC2) is a glacially-dammed lake adjacent to the Northern Patagonian Ice Field (NPIF), formed by the blockage of Cachet Basin (CB) by the Colonia Glacier. This glacier has experienced rapid (~1-2 km) retreat of its terminus as well as ~1-2 m/yr of thinning, documented over the past several decades. Furthermore, the glacier has exhibited a change in hydrologic regime and the frequency of high energy glacial lake outburst flood (GLOF) events since 2008. These historical changes appear to be coupled with regional climate change; summer mean maximum and minimum temperatures in nearby Cochrane show a steady increase since 1971, whereas winter mean maximum temperatures show cooling in the 1970s and 1980s, followed by gradual warming with rapid acceleration in the 2000s-present. Preliminary correlations with a recently installed weather station at Sol de Mayo (~12 km downstream of the Colonia Glacier terminus) show a strong positive correlation with the Cochrane data, indicating these climate changes are regional and not local and thereby have implications for the evolution of other alpine basins of the NPIF and perhaps glaciers on a global scale. Recent observations from unmanned aerial vehicle (UAV) flights, satellite imagery, and geologic mapping suggest unprecedented glacier deterioration near the southern limit of CB. An UAV flight in January 2016 revealed that during GLOF events, the lake drained through a large hole at the base of the glacier. Upon entering this chasm, the water made a sharp east turn (towards the bedrock abutting the glacier’s eastern margin) and appeared to flow beneath the ice at this point. Subsequently, a large (~2km long x 100 m wide) supra-glacial channel has opened directly above the drainage hole, effectively separating the glacier from bedrock. Ice elevation data reveal that healing of this channel may not be possible under the current climate regime, suggesting the basin could be experiencing a long-term (over human timescales) shift to fluvial deposition from a dominantly lacustrine environment, corresponding to an inability to impound water associated with the glacier's retreat. Basin stratigraphy indicates these oscillations between lacustrine and fluvial conditions have occurred repeatedly throughout the Holocene, but the timing of these changes are poorly constrained. Optically stimulated luminescence (OSL) dating of CB sediments will be applied to identify the timing and periodicity of these depositional shifts, with the broader goal of linking these oscillations with local and regional climate and stability of the Colonia Glacier.
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Lake records provide a long-term record of climate events and transitions, earthquakes in tectonically active regions, landscape response during and following deglaciation and recent human influenced land use changes. In order to unravel the story preserved in lake sediments, it is necessary to understand the dynamics of the lake system and the source of the sediment coming into the lake. Our study focuses on Lake Ohau, New Zealand, which occupies a fault controlled glacial valley and contains a high resolution sedimentary record of the last ~17 ka. It is presently the focus of a multi-disciplinary studied which aims to recover a long core encompassing the whole ~17 ka record in the next several years.
We use two CSDMS codes: HydroTrend, a climate-driven hydrological model, and Sedflux, a basin filling model, to model sediment flux into Lake Ohau. Using measured climate parameters from the last 60 years, we model water and sediment discharge into the lake and the distribution of sediment through the lake basin. Using a simple conceptual model of the lake dynamics, we produce a series of simulations to examine sediment accumulation at different positions across the lake basin. We then compare these modelled accumulation records to short cores from a number of locations within the lake basin. +
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Landlab is python software framework for the creation of surface dynamics and process models. It provides grid structures, stable and intercompatible process components, and utilities for data input, output and visualization. Here we present two new types of components within the Landlab framework: the FlowAccumulator and the FlowDirectors. These components have been designed to implement one of the basic functions of surface dynamics modeling, the routing and accumulation of water over a surface. These components split up the functionality of the previously implemented FlowRouter component in order to make it easier for the addition of new algorithms for flow direction to Landlab. As part of these components, we include a new algorithm for efficient flow accumulation when flow is routed to multiple neighboring nodes.
Routing of water over a surface can be split into two steps: direction and accumulation. Before outlining these steps, it is useful to state the terminology used to describe the grid. In Landlab the physical processes operate on a model grid which stores information about spatial location and properties that may vary in space (e.g. soil thickness, surface water discharge). The model grid is a dual plane graph in which quantities such as topographic elevation are defined at node points. Between neighboring node points are lines called links on which water, sediment, or other quantities can flow.
To route flow over the surface, flow directions at a given node must first be assigned to indicate which, if any, of the neighboring nodes will receive any flow that arrives in that node. This is typically done using the relative elevations of a node’s neighbors. Previously Landlab supported the steepest descent (or D4) algorithm for both rectilinear and non-rectilinear grids and the D8 algorithms for rectilinear grids. As part of the presented improvement, Landlab includes the Multiple Flow Direction and D infinity algorithms. Each algorithm for directing flow is its own component, but all share core functionality of the FlowDirector class. This shared functionality includes attributes necessary for interacting with other Landlab components, including the FlowAccumulator. This design permits easy addition of new flow direction algorithms while maintaining interoperability with other Landlab components.
Once flow directions have been assigned, surface water discharge and drainage area can be calculated through flow accumulation. This functionality is provided by the FlowAccumulator component which is compatible with all FlowDirector components. Depending on the algorithm chosen, flow accumulation can be computationally inefficient, scaling at a rate greater than O(N). We present a new algorithm for accumulating flow for in the case where flow is directed to more than one receiver that scales with the number of links that flow is directed over.
Landscape evolution is driven by tectonic processes that build up topography and erosional processes that work to tear down that topography and move material out of the landscape. Climate or more specifically water accumulated in rivers as discharge, is an important driver of these erosional processes. Despite its influence in shaping landscapes, there remains much to be learned concerning the relationships between climate, topography and discharge variability in forcing erosion. One reason for this is that climate itself, as well as the relationship between climate and erosion, is difficult to measure. Climate data typically consists of temporally averaged modern measurements of rainfall, which often miss important variability; or spatially inconsistent discharge data from stream gauges. Further, fluvial incision occurs during flood events that overcome a threshold for erosion, the frequency of exceeding this threshold is influenced by both discharge magnitude and variability. In this work we employ a numerical modeling approach to build upon previous research concerning the importance of discharge variability in driving erosion. We couple a landscape evolution model, Landlab, with a high-resolution atmospheric model, WRF (Weather Research and Forecasting), in order to generate high resolution discharge data. In these experiments, we run the WRF model over two artificial topographies with low (100m) and high (4km) elevations and extract discharge data from five drainage basins across the study domain at 10 to 40S. With this experimental setup we are able to analyze how discharge distributions change with topography and across several climate regimes. We find that the presence of high topography results in higher mean discharge across the five domains, particularly at 10, 20, and 30S. Additionally, discharge variability is greatest at 20 and 30S and less variable at 0, 10, and 40S for both the low- and high-elevation experiments. We then use these discharge distributions to drive a 1D river incision model to explore the relationship between discharge variability and erosion between high and low elevation domains and among different climate regimes, particularly in the presence of erosion thresholds. With this modeling approach we aim to gain insight into the influence of discharge variability and erosion thresholds on the relationships between topography, climate and erosion.
Landscape evolution models (LEMs) are a virtual representation of geomorphic processes as observed in the field or in experimental settings. LEMs offer the flexibility to evaluate a range of interactions between surface processes at timescales which cannot be observed. Notwithstanding the added value of LEMs in unravelling the tectonic-climate-erosion enigma at geological timescales, the use of LEMs to explain real-world earth surface processes remains challenging. For a LEM to be representative for a specific area, field data should be used to calibrate and validate the simulated processes. Notwithstanding the continuously growing database on erosion rates at different spatial and temporal scales, the number of datasets and the area they cover is inversely correlated with the timescale considered. Although more data is thus available at shorter timescales, including them into LEMs is not straightforward as short-term observations are known to reflect the stochasticity of earth surface processes.
In this contribution, we focus on the role landslides, a stochastic hillslope processes in steep mountainous mostly not included in long term LEMs, but strongly reflected in short term field data. We first integrate the formation of landslides and the transport of the thereby generated sediments in a previously developed LEM (TTLEM). Landslide initiation is implemented as a stochastic process depending on a landslide failure index whereas landslide size depends on the slope stability calculated using the Cullman index. The updated model (TTLEM_Sed) is thereafter applied to the New Zealand-Alps where long term erosion measurements and landslide inventories allow to calibrate model parameters. Landslide inventories are traditionally analyzed using statistical relationships between slope stability and conditioning factors such as distance to rivers and distance to active faults. However, the use of conditioning factors in landslide hazard maps is based on empirical observations and lacks physical grounding. Indeed, hillslopes closer to rivers should automatically become more prone to landslides as rivers incise and undercut hillslope foots. The integration of landslides in a LEM now allows to simulate this dynamic interplay over different timescales. By varying the simulated timescale over which the model is run, we identify critical timescales at which a-priori imposed statistical relations between landscape characteristics and landslide occurrence are no longer required and represented by the internal dynamics of the evolving landscape.
With TTLEM_Sed, we present an open-source model tool that allows to simulate landslides and sediment propagation. A modelling approach to study landslides is different from classical landslide hazard mapping approaches as it allows to simulate landscapes over longer timescales therefore allowing to identify physical drivers of landslide formation and landslide initiation. Moreover, the explicit integration of landslides in TTLEM_Sed potentially allows for the integration of widely available short-term field data in future model applications.
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Landscape evolution models use mass transport rules to simulate the development of topography over timescales too long for humans to observe. The ability of models to reproduce various attributes of real landscapes must be tested against natural systems in which driving forces, boundary conditions, and timescales of landscape evolution can be well constrained over millennia. We test and calibrate a landscape evolution model by comparing it with a well-constrained natural experiment using a formal inversion method to obtain best-fitting parameter values.
Our case study is the Dragon's Back Pressure Ridge, a region of elevated topography parallel to the south central San Andreas Fault that serves as a natural laboratory for studying how the timing and spatial distribution of uplift affects topography. We apply an optimization procedure to identify the parameter ranges and combinations that best account for the observed topography. Direct-search inversion models can be used to convert observations from such natural systems into inferences of the processes that governed their
formation through the use of repeat forward modeling. Simple inversion techniques have been used before in landscape evolution modeling, but these are imprecise and computationally expensive. We present the application of a more efficient inversion technique, the Neighborhood Algorithm (NA), to optimize the search for the model parameters values that are most consistent with the formation of the Dragon's Back Pressure Ridge through repeat forward modeling using CHILD.
Inversion techniques require the comparison of model results with direct observations to evaluate misfit. For our target landscape, this is done through a series of topographic metrics that include hypsometry, slope-area curves, and channel concavity. NA uses an initial Monte Carlo simulation for which misfits have been calculated to guide a second iteration of forward models. At each iteration, NA uses n-dimensional Voronoi cells to explore the parameter space and find the zones of best-fit, from which it selects new parameter values for the forward models. As it proceeds, the algorithm concentrates sampling around the cells with the best-fit models. The resulting distribution of forward models and misfits in multi-parameter space can then be analyzed to obtain probability density distributions for each parameter.
Preliminary results suggest that, when combined with robust algorithms for the calculation of the misfit, NA quickly centers the parameter search around values that capture the key features of the observed topography. The ability of NA to provide probability distributions for parameter values gives an indication of uncertainty in each, and can be used to guide field measurements for model testing. This application of advanced inversion techniques for landscape evolution modeling is a significant step towards the use of more formal mathematical methods in geomorphology that are already applied by other disciplines in the geosciences.
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Landscape evolution studies typically simulate long-term soil development by varying production rates as a function of the local thickness of soil. Whether this function monotonically decreases with increasing soil depth remains an active source of debate. In modest relief landscapes, the presence of isolated bedrock outcrops called tors are often used to argue for the so-called ‘humped’ soil production function, which hypothesizes that there is an optimal, non-zero soil depth for soil production. Furthermore, in many steep landscapes, the fraction of bedrock exposed at the surface can be very high where cliffs bands form in response to high erosion rates. Yet, numerical models of hillslope evolution struggle to reproduce the continuous transition from fully soil-mantled to bedrock-dominated hillsides within a single framework. To address this, we present a new Agent-Based Model (ABM) of forest dynamics and soil production that is coupled to continuum-based models of hillslope sediment transport (i.e., linear and nonlinear creep). In this model, tors and bedrock cliffs are emergent features that manifest even when maximum possible soil production rates occur at zero soil depth. The intermittency of seed germination and sapling recruitment on bare bedrock surfaces combined with the rapid downslope transport of newly developed soil facilitates the persistence of exposed bedrock. By linking soil development to plant functional type, this work also shows how soil depths and bedrock exposure patterns that evolve over millennia may be mechanistically linked to forest properties that stabilize over shorter timescales. To illustrate model behavior, we use plant parameters inspired by Pinus ponderosa, the dominant species observed at low to intermediate montane forests in the Colorado Front Range. Using this as a baseline, we then test model sensitivity to a variety of tree functional parameters including seed fecundity, seed dispersal distance, maximum rooting depth, and maximum individual lifespans. Our work is the first to couple a NetLogo ABM to Python-based Landlab via the pyNetLogo library. As such, this use-case serves as a template for other landscape evolution studies targeting feedbacks among biological agents, substrate properties, and sediment transport.
Landscapes in a transient state can be described as areas that are undergoing topographical and geomorphological adjustments. In tectonically active areas, it is straightforward to interpret and reconstruct topography using transient geomorphic signals based on stream power theory. However, areas without tectonic activity are also rife with topographic transience but lack a clear trigger. Landscapes with heterogeneous lithological substrates present geomorphic signals of an ongoing transient state even when their geological context implies tectonic and climatic quiescence. Here, I propose to investigate the transient landscape response to the exhumation of heterogenous lithology. The main objective of this project is to quantify the influence of lithology on landscape evolution processes in the absence of tectonic activity. I hypothesize that divide asymmetries are created by the differential incision power each basin has at the lithologic transition. The differences are a function of the drainage area and the distance crossed over the resistant rocks. Our work is based on a LandLab simulation in which the synthetic DEM has a rock in its lower (southern) portion that is more resistant to erosion. The boundary conditions were configured so that only the southern part was open to the river system, which resulted in drainages flowing from north to south. The drainage basins was then analyzed from the same base level, controlled by the exhumation of the most resistant rock. Preliminary results indicate that basins with a smaller drainage area are subject to shrinkage processes after the exhumation of resistant rock in their outlet (base level). While the basins that had the largest drainage area gained area via river capture and divide migration, expanding their total area over time and thus shrinking the adjacent basins. +
Landslides are hazardous phenomena affecting mountainous regions worldwide. Our objective is to develop a Warning System for rainfall-induced shallow landslides in Switzerland, where such a dedicated tool is currently missing. Initially, we focused on empirical rainfall thresholds for landslide triggering based on long-term precipitation data and historical landslide inventories. The results showed that, although precipitation is the main triggering factor, event magnitude (intensity) by itself is not sufficient to explain the occurrence of many landslides. To improve the performance, the antecedent soil moisture prior to the rainfall event has to be taken into account, which we explore using a distributed hydrological model. The overall aim is to understand and quantify (a) the geological and hydrologic conditions critical for landslide initiation and (b) the optimal resolutions for hydrological modelling geared towards landslide prediction.
In fact, while slope stability assessment with a geotechnical model requires high resolution topography, the optimal spatial resolution for the computationally expensive hydrological modeling component remains unknown. To address this question, we conducted numerical experiments for a synthetic digital elevation model (DEM) used to simulate a simplified valley. The DEM is an inclined V-shaped domain and simulations are carried out with the coupled hydrologic-land surface model, ParFlow-CLM, in combination with the infinite slope stability model. We tested different slopes, valley convergence angles, soil layering, and permeability contrasts to assess the effect of spatial resolution on the estimation of antecedent soil moisture and the corresponding Factor of Safety.
These numerical experiments will help inform comparative simulations for real catchments in Switzerland and Colorado, as we explore the potential of using topographic methods for downscaling of the estimated antecedent soil wetness from coarser to fine scales. In particular, we will explore whether or not the soil-topographic index can provide a viable alternative to running the hydrological model at the very high spatial resolutions needed for the geotechnical model.
Landslides are key agents of sediment production and transport. Ongoing efforts to map and simulate landslides continuously improve our knowledge of landslide mechanisms. However, understanding sediment dynamics following landslide events is equally crucial for developing hazard mitigation strategies. An outstanding research challenge is to better constrain the dynamic feedbacks between landslides and fluvial processes. Fluvial processes simultaneously (i) act as conveyor belts evacuating landslide-derived sediment and (ii) lower the hillslope’s base level triggering further landsliding. Landslides in turn can choke river channels with sediment, thereby critically altering fluvial responses to external tectonic or climatic perturbations.
Here, we present HYLANDS, a hybrid landscape evolution model, which is designed to numerically simulate both landslide activity and sediment dynamics following mass failure. The hybrid nature of the model is in its capacity to simulate both erosion and deposition at any place in the landscape. This is achieved by coupling the existing SPACE (Stream Power with Alluvium Conservation and Entrainment) model for channel incision with a new module simulating rapid, stochastic mass wasting (landsliding).
In this contribution, we first illustrate the functionality of HYLANDS to capture river dynamics ranging from detachment-limited to transport-limited configurations. Subsequently, we apply the model to a portion of the Namch-Barwa massive in Eastern Tibet and compare simulated and observed landslide magnitude-frequency and area-volume scaling relationships. Finally, we illustrate the relevance of explicitly simulating stochastic landsliding and sediment dynamics over longer timescales on landscape evolution in general and river dynamics in particular under varying climatologic and tectonic configurations.
With HYLANDS we provide a hybrid tool to understand both the long and short-term coupling between stochastic hillslope processes, river incision and source-to-sink sediment dynamics. We further highlight the unique potential of bridging those timescales to generate better assessments of both on-site and downstream landslide risks.
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Landslides are often assumed to exhibit self-similarity in their failure geometry, and thus a linear scaling between slip depth and rupture length. This assumption has important implications for the prediction of large landslide volumes and for the estimation of erosion budgets by mass-wasting. Nevertheless, some field data indicate a break from self-similarity and imply that, in some circumstances, landslide depth may scale non-linearly with length. Here we test the simple scaling hypothesis by numerical experiment. Modeling is performed with SNAC (StGermaiN Analysis of Continua), a 3D community code originally designed to model viscoelastoplastic deformation on a crustal scale and newly adapted to treating hillslope failure. SNAC employs a parallelized, Lagrangian, explicit finite-difference scheme and dynamic relaxation to solve static, quasi-static and steady-state problems. Landslide rupture is treated as emergent shear localization under strain-weakening Mohr-Coulomb plasticity. We model only the initial slip and early motion of a landslide; granular flow during the runout phase is not considered. A set of 2+1D simulations of failures spanning lengths of 50–400m suffice to vindicate cross-sectional self-similarity—absent any dominant depth scale or trend in the variation of cohesion—and a depth-length ratio of 11–15% is recorded. An interesting by-product of the choice of experimental geometry is some unanticipated complexity in the evolution of the slip plane. Failure initiates at the toe, propagates upslope, and asymptotically parallels the planar upper boundary. However, a connected failure surface is only achieved once a secondary rupture has propagated downwards into this slip plane from the upper breakaway zone. The broader outcome of our numerical experiments is a demonstration of how 3D continuum modeling of soil and rock-slope failure, and the study of their rich behavior, is now feasible using non-commercial code on supercomputing platforms.
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Large blocks of rock are common in steep landscapes developed in the presence of a resistant lithology. However, the influence of blocks on landscape evolution is not well known. We developed a hybrid discrete-continuum coupled numerical model of hillslope and channel evolution in the presence of blocks (BlockLab). The model consists of a horizontal resistant layer of rock overlying softer, more erodible rock. A channel reach, driven by an external base level forcing, incises through the middle of the domain and provides the base level for the hillslopes. The hillslope model uses a continuum approach to treat depth-dependent production and transport of soil. Retreat of the resistant layer, however, is treated discretely. A relief threshold determines release of discrete blocks from the resistant layer onto the hillslope, where each model cell is either filled with blocks or contains no blocks. These blocks are allowed to weather at a constant rate, and are tracked as they move downslope according to a relief threshold related to their diameter. Once blocks enter the channel, they influence channel evolution by covering the bed and reducing available bed shear stress. A force balance on in-channel blocks determines whether they can move downstream. Blocks in the channel are reduced in size by abrasion according to the shear stresses exerted on them. The presence of blocks affects channel incision rates, in turn influencing evolution of the hillslopes. This is the first model to account for the role of blocks in channel hillslope evolution feedbacks (CHEFs), allowing us to better model the evolution of real landscapes. +
Large sediment pulses deposited in river channels can alter channel morphology and amplify downstream flood hazards. In the Suiattle River of Washington State, abrasion controls the downstream impact of sediment supply from Glacier Peak, a stratovolcano that regularly supplies the channel with large sediment pulses. This phenomenon is evident by the persistence of strong volcanic grains on the streambed and the rapid downstream loss of weak volcanic grains to fine sediment. Although cobbles and boulders dominate pulses in the channel, the Suiattle has an unusually high supply of fine sediment and contributes to fine sediment impacts downstream. Despite the evidence that the abrasion of coarse sediment during downstream transport drastically impacts the balance of fine and coarse sediment in the channel and new studies on the variability of abrasion, no work – in the Suiattle or elsewhere – has been done to determine the importance of abrasion on sediment pulse evolution in a highly abrasion-prone setting. Here, we test the extent to which abrasion acts as a control on sediment pulse transport from large mass wasting deposits of heterogeneous sediment characteristics. We employ the use of the Network Sediment Transporter, a 1-D river morphodynamics and Lagrangian modeling component in Landlab, to explore channel response to a large sediment pulse in the Suiattle River basin, tracking bed elevation and grain size changes and compare model results of variable sediment abrasion scenarios. We simulate abrasion as the mass of the grain loss per distance traveled and the scenarios include: no abrasion, a distribution of Schmidt Hammer Rock Strength (SHRS) measurements (a proxy for tumbler-derived abrasion rate), and a doubling of the SHRS proxy to account for the underprediction of the tumbler and a lack of in-place abrasion. We drive the model with a 2-year exceedance flow from discharge data from a distributed hydrology model to account for the complicated rain/snow hydrology of this mountainous region. Our initial results indicate negligible variances in bed elevation solely attributable to abrasion. Instead, our primary findings highlight the importance of the canyon reaches in modulating the coherence of the pulse as it transports downstream. Before the canyon reaches, a coherent wave of bed elevation change is apparent in all model runs, with modest differences between abrasion scenarios. Downstream of this canyon reach, this coherence dissipates.
Large-scale Earth system and land surface models often lack an adequate representation of subgrid-scale processes in permafrost landscapes. Small-scale processes such as thermokarst formation might, however, considerably impact the energy and carbon budgets in way which is not resolved within large-scale models. Since a spatially high-resolved simulation of such processes is not feasible, novel techniques for up-scaling subgrid processes are demanded.
Within this work a one-dimensional model of the ground thermal regime of land surfaces, CryoGrid 3, is employed to conceptually represent small-scale features of permafrost landscapes, particularly those related to thermokarst. For example, the model has been shown to adequately describe the degradation of permafrost underneath waterbodies in a warming climate. Using tiling approaches such point-wise realizations can be up-scaled in a statistical way in order to represent larger land surface units.
The model development is closely linked to field campaigns to the Lena River Delta in Siberia which offers very diverse land surface features such as polygonal tundra and thermos-erosional valleys. These features are related to the region’s diverse soil stratigraphies, in particular the occurrence of ice-rich ground. Combining field measurements with modelling ultimately allows an improvement in the qualitative and quantitative understanding of the typical geomorphological processes in permafrost landscapes and their representation in large-scale land surface models. +
Large-scale flow-routing algorithms efficiently route water to the ocean, neglecting both inland basins that may be able to form lakes and changing groundwater storage. We add these elements of reality in a simplified and computationally-efficient way, combining groundwater and surface-water routing to simulate changing groundwater levels, surface-water flow pathways, and lake locations and extents through time. The groundwater component is based upon a linear-diffusive model for an unconfined aquifer developed by Reinfelder et al (2013), and surface water is routed through a simple downslope-flow algorithm that differs from most flow-routing algorithms in that it takes into account the elevation of the water surface, and not just the land surface. Our model requires as inputs topography, climatic data (P-ET and winter temperature), and an approximation of hydraulic conductivity based on topographic slope and mapped soils. The model outputs grids of depth to water table and thickness of surface water; the latter depicts any lakes that would form under the topographic and climatic conditions. The model can be run to equilibrium, or, if a starting depth to water table input is provided, for any user-selected length of time. Such solutions are transient only with respect to groundwater movement: surface-water flow is significantly faster, so it is always run to equilibrium. The model allows infiltration when surface water flows across cells that are not fully saturated in the groundwater, and it allows exfiltration and the formation of groundwater-fed lakes where convergent groundwater flow raises the water table above the land surface.<br>We show sample results from this model on a test area. Future work using this model will include global runs since the Last Glacial Maximum, with ground truthing possible using past lake shoreline data. Changing depth to water table plus the surface water storage computed using this model allows computation of changing terrestrial water storage volume through time.
Long-term tectonics shape the landscape we live on. Collision over 10s of millions of years has produced the Himalayan mountain chain, the Tibetan Plateau and the atmospheric disturbance that produces the Asian monsoon. But it is the dynamic, short-term manifestations of tectonics and plate boundaries and their aftermath that most dramatically impact people’s lives. The shaking of a large main shock, while overwhelming, is over within minutes but the consequences of the shaking on the landscape can last for years to decades. In particular, in mountainous environments, a sedimentary hazard cascade (SHC) can dominate a region in the decades following a large earthquake. The 1999 Chi-Chi earthquake in Taiwan, the 2008 Wenchuan earthquake in China and most recently the 2016 Kaikioura earthquake in New Zealand provide the opportunity to quantify and model some of these impacts. In particular, improved knowledge of spatial and temporal variations in rock erodibility help us to understand the physical connections between tectonic structure and the Earth surface, both in the short and in the long term. Quantifying rock damage (erodibility) as a result of tectonic processes is an important step in exploring the link between the processes that occur on the timescales of the human dimension and long term tectonics. +
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Low-lying coastal barriers face an uncertain future over the next century, with many projections suggesting end-of-century rates of sea-level rise as high as 1 cm/yr. The hazards associated with this passive inundation can be reasonably estimated using state-of-the-art tools. However, the coast is not a bathtub - increased sea levels enhance the ability for waves to reorganize the coast, typically resulting in increased shoreline retreat by moving sediment either offshore into deeper waters or onshore by overwashing the existing coast.
Although many models of coastal change have been developed, the majority are either highly calibrated and intended to operate at the temporal scales of engineering projects (< ~5 years), offering little possibility of forecasting never-seen behaviors such as barrier drowning, or long-term geologic models, which typically assume that the coast maintains an ‘equilibrium’ configuration that moves with sea level. We aim at bridging the gap between these approaches by constructing a simple model that focuses on dynamical coupling of two primary barrier components: the marine domain represented by the active shoreface, which is constantly affected by transport and reworking by waves, and the backbarrier system, where the infrequent process of overwash controls landward mass fluxes. The model demonstrates that coastal barriers can respond to an accelerated sea-level rise in complex, less predictable manners than suggested by existing conceptual and long-term numerical models. Model behaviors under constant sea-level rise reveal two potential modes of barrier failure: ‘height drowning’, which occurs when overwash fluxes are insufficient to maintain the landward migration rate required to keep in pace with sea-level rise; and ‘width drowning’, which occurs when the shoreface response is insufficient to maintain the barrier geometry during landward migration. We also identify a mode of discontinuous barrier retreat, where barriers can experience punctuated intervals of rapid rollover and shoreline stability, even with constant rates of sea-level rise. We explore the sensitivity of these modes to external and internal variables, including sea-level rise rate, maximum overwash rate, shoreface response rate, and inland topography.
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Low-lying regions of river deltas (marshes, swamps, and tidal flats) are an important part of the delta life cycle. Marsh sedimentation is characterized by non-riverine, low-bulk density material, and interacts with the riverine sediment delivered by distributary channel networks. These two forms of sedimentation interact to produce the channel properties and kinematics observed in the system. Here, we aim to understand this interaction by comparing two physical delta experiments, one with marsh deposition (treatment) and one without (control). We show that the addition of the marsh proxy (kaolinite) alters the channel properties and kinematics of a river delta. Notably, the channels are longer in the treatment experiment and the shoreline roughness is enhanced. The treatment channels have the same width from the entrance to the shoreline, while the control channels get narrower as they approach the shore. Flow is concentrated in the channels in the treatment experiment, as it has about one-fourth the amount of overbank flow as the control experiment. Interestingly, the channel beds in the treatment experiment often exist below sea level in the aerial portion of the delta top, a phenomena observed in global deltas. However, in the control experiment, the channel beds generally exist above relative sea level. The channels in the treatment experiment have a slope break, on average, which is also seen in some global deltaic rivers (e.g., Mississippi River Delta). The difference in channel properties created by the addition of the marsh proxy in the overbank region helps offset the channel bed aggradation rates in the treatment experiment, as the overbank region aggrades faster (relative to the channel) than in the control. This difference in in-channel and far-field aggradation shows a longer channel in-filling time for the treatment as compared to the control. Although the lateral channel mobility statistics are similar in both experiments, there is more area on the delta top in the treatment experiment that is rarely visited by a channel. This suggests that the marsh proxy may buttress the channels in the treatment experiment. Ultimately, marsh sedimentation on the delta top plays a key role in the channel properties and kinematics of a river delta, producing channels which are more analogous to channels in global river deltas, and which cannot be produced solely by increasing cohesion in an experimental river delta.
Marine Hydrokinetic (MHK) technologies provide an opportunity to expand renewable energy by harnessing waves and currents power and converting to electricity for residential and commercial application. Locations with rapid tidal flow, large waves, and large tidal range are being considered for implementation of MHK technologies and extraction of energy. However, little is known about the impact of MHK structures on the surrounding ocean morphology. In this study, the hydrodynamic and morphodynamic numerical model, Delft3d, is used to simulate the erosion and deposition around a bed mounted MHK structure to analyze the impacts of seabed slope, sediment grain size, and wave condition on the long-term stability of the device. We analyzed 10, 15, and 20 degree seabed slopes, and three different sediment grain sizes representing fine, medium, and coarse-grained sand. For wave conditions, we ran storm condition of the frequent 1-2 year recurring storm in North Carolina Coast, which occurred during Hurricane Mathew in 2016. We also tested the mean wave conditions and the extreme 100-year storm for the same location. Our initial results suggest that steeper sloped beds, finer sediment grains, and larger wave heights will be more problematic for increasing total deposition and burial of bed-mounted MHK devices. However, depending on the type of MHK device, this impact may not be as important as potential scour around the MHK leading to toppling and failure of the device. Moreover, for extreme storm conditions (i.e. the 100 year storm), scour and potential collapse of the foundation or anchor of the bed-mounted MHK may be a serious concern. +
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Marine carbonates are created by the metabolism, growth, death and skeletal accumulations of a diverse array of benthic organisms (e.g. corals, bryozoa, molluscs, foraminifera, calcareous algae, and micro-organisms), but carbonate accretion requires a positive net balance among biological growth processes, processes of biological erosion (mainly by fishes, urchins, polychaetes, molluscs, sponges, algae and micro-organisms), and physical processes of destruction, suspension, transport, deposition and cementation. We are creating a knowledge base (KB) containing empirical quantitative data about individual, population and community properties of major calcifying and bio-eroding species to capture the ecological variation inherent in all biological processes, both spatial (e.g. latitude, longitude, habitat, climate, oceanography, depth) and temporal (e.g. diurnal, seasonal, interannual). The KB will provide realistic values for input to a “virtual aquarium” of characteristic organisms at the center of biologically-based carbonate models describing the initiation, growth and maturation through ecological to geological timescales of such formations as shallow and deep-sea coral reefs, Halimeda beds, bryozoan reefs, and maerl deposits. +
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Marshes are highly dynamic landscapes that are shaped through feedbacks between hydrodynamic, morphodynamic, and ecological processes. Future marsh resilience is therefore dependent on the interaction between these different drivers rather than any individual piece. Marshes face a variety of threats, both natural and anthropogenic, resulting in a need for restoration actions that increase survivability. Because many of these threats are unprecedented or acting at unprecedented rates, statistical models do not adequately represent future conditions and require process-based models to better capture the complex interactions between both physical and ecological processes. The comprehensive marsh model integrates tidal flow, morphodynamics, and vegetation growth using the python based Landlab toolkit. This model is then applied at a site within the Seven Mile Island Innovation Laboratory complex in coastal New Jersey. +
Migration is a complex phenomenon that is impacted by economic, social, cultural, and environmental factors. This complexity makes it challenging to study, and especially challenging to understand how future environmental and climatic change may affect mobility and population movements. Agent-based modeling (ABM) is a promising but underutilized method for studying environmental impacts on human migration because of its ability to study connections between large-scale dynamics and individual decision-making. This work presents initial results from an original ABM that simulates household migration decisions in Bangladesh under environmental pressure. The model seeks to understand how riverbank erosion and land inundation impact mobility patterns under varying decision-making frameworks and livelihood opportunities. The model stochastically simulates inundation of land bordering a river. Agents whose land is flooded seek employment in a local labor market. Agents who cannot find employment within the community then face the decision to migrate or remain in the community with limited economic opportunity. We compare several different decision frameworks of varying complexity, in which the probability of choosing to migrate depends upon: household wealth alone, wealth, age, and household size, and finally using the Theory of Planned Behavior, which incorporates interactions between individual-level variables and community-level phenomenon, such as social norms, which are mediated through each agent’s social network. This model serves as a starting point to begin to test how different decision-making frameworks and environmental scenarios may produce different dynamics in the response to environmental stress. +
Mixed sediment beaches are common across the globe, yet despite this, they have not been as extensively studied as sandy coasts. In the UK, these gravel-rich ‘shingle’ beaches are used as a first line of defence against flooding, limiting the amount of overtopping on heavily developed coasts such as those found on the South East coast. The shingle beach at Pevensey Bay, in East Sussex is the UK’s largest natural flood defence and is maintained through publicly funded, long-term beach management activities, recharge, recycling and by-passing of material. Monthly beach surveys, carried out to inform these works, revealed that the foreshore was experiencing chronic erosion with the loss of approximately 8,000 m3 of sediment each year. Whilst changes to the upper beach are constantly tracked and managed changes occurring just below the waterline were practically unknown.
Identifying the pathways for sediment movement across the nearshore zone was a key objective for this study to help understand the continued erosion of the foreshore. Analysis of multibeam bathymetry and X-Band radar reflectance data revealed the presence of transverse finger bars in the nearshore zone. The bars extended up to 700m offshore and were approximately 80-120m wide, with a maximum amplitude of 0.5m. Weekly-averaged reflectance imagery showed the position of the bars, which are orientated at 45o to the coastline, as the surface roughness of the sea was moderated by the seabed. These high temporal frequency roughness signatures showed that the bars were permanent features on the seabed and that they were migrating at a rate of approximately one wavelength a year. The movement of the bars was triggered by excess wave energy; peak migration rates were reached in the 2020 November to December period, whilst virtually no movement occurred between April and September 2021. Similar spatio-temporal patterns have been observed in erosive and accretive pulses in the upper beach and the link between bar movement and beach response is examined. Gaining a clearer understanding of the movement of sediment within the nearshore zone on beaches such as Pevensey will improve our understanding of how mixed sediment beaches function and brings into question whether active upper beach management is the most sustainable long-term option
Models of coastal barrier ecomorphodynamic change are valuable tools for understanding and predicting when, where, and how barriers evolve, which can inform decision-making and hazard mitigation. Present ecomorphodynamic models of barrier systems, however, tend to operate over spatiotemporal scales incongruous with effective management practices (i.e., too fine-scale/event-based or too coarse/long-term). In contrast, we are developing a new model capable of simulating ecomorphologic change of undeveloped barrier systems over several kilometers and decades with a 1-by-1 m planform grid and weekly time step. The model couples aeolian dune growth and vegetation dynamics (DUBEVEG), storm erosion of the beach and foredunes (CDM/SBEACH), storm overwash (Barrier3D), and shoreline/shoreface adjustment (LTA14). We parameterize the model with elevation and vegetation data from North Core Banks, NC, focusing on changes caused by Hurricane Florence (2018). Calibrating free parameters using a genetic algorithm, we find good to excellent agreement with observed and simulated elevation change for representative, small (<1 km alongshore) barrier segments. Future work will include testing the model with multidecadal hindcasts of ecomorphodynamic barrier change; running suites of simulations will allow us to better capture and quantify the probabilistic nature of the dynamic response of barriers to the forces driving coastal evolution. +
Models of landscape evolution provide insight into the geomorphic history of specific field areas, create testable predictions of landform development, demonstrate the consequences of current geomorphic process theory, and spark imagination through hypothetical scenarios. While the last four decades have brought the proliferation of many alternative formulations for the redistribution of mass by Earth surface processes, relatively few studies have systematically compared and tested these alternative equations. We present a new Python package, terrainbento 1.0, that enables multi-model comparison, sensitivity analysis, and calibration of Earth surface process models. terrainbento provides a set of 28 model programs that implement alternative transport laws related to four process elements: hillslope processes, surface-water hydrology, erosion by flowing water, and material properties. The 28 model programs are a systematic subset of the 2048 possible numerical models associated with 11 binary choices. Each binary choice is related to one of these four elements---for example, the use of linear or non-linear hillslope diffusion. terrainbento is an extensible framework: base classes that treat the elements common to all numerical models (such as input/output and boundary conditions) make it possible to create a new numerical model without re-inventing these common methods. terrainbento is built on top of the Landlab framework, such that new Landlab components directly support the creation of new terrainbento model programs. terrainbento is fully documented, has 100% unit test coverage including numerical comparison with analytical solutions for process models, and continuous integration testing. We support future users and developers with introductory Jupyter notebooks and a template for creating new terrainbento model programs. In this paper, we describe the package structure, process theory, and software implementation of terrainbento. Finally, we illustrate the utility of terrainbento with a benchmark example highlighting the differences in steady-state topography between five different numerical models.
Moraines in marine-terminating outlet glacier settings can provide a feedback mechanism for glacier stability or retreat, however, sedimentation dynamics in Greenland are poorly understood. With limited observations, sedimentation contributes to the large uncertainty of ice dynamics in estimating Greenland’s future sea level potential. Recent attempts to couple ice and sedimentation show the importance to include moraine-building processes. To advance our understanding, it is necessary to quantify the impact of sedimentation in Greenland outlet glacier settings on different timescales. We explore the sensitivity of Greenland outlet glaciers to sedimentation dynamics including sediment diffusion (removing sediment from moraines) and glaciofluvial sedimentation (adding sediment to moraines) in a flowline model adapted from Brinkerhoff et al., 2017. We run an ensemble of simulations to investigate these processes on 20 kyr timescales, using different bed topography slopes, surface mass balance scenarios, and with sedimentation coupling turned on versus off. We compare across simulations with parameters like ice volume, sediment volume, ice velocity, and bed topography profiles. We find that sedimentation has a strong control on ice volume change and creates tide water glacier cycles with changes in amplitude over time. In addition, we determine the sensitivity of the tide water glacier cycle to variations in bed topography and surface mass balance. The coupling between sediment and ice dynamics could explain and contribute to the divergent glacier behavior presently seen in Greenland outlet glaciers. This work is important for ice sheet model development and field work efforts to understand the rates and processes driving sedimentation in Greenland. +
Morphological patterns reflect climatic and geomorphic influences throughout a dunefield’s history and can thus be a valuable source for information about past and present environmental conditions. The quantitative assessment and interpretation of such patterns requires precise information about dune locations and arrangements, i.e., dune maps. Mapping dunes based on satellite data has evolved from a simple tool for dryland research to a notable research area. Globally available datasets and the progression of computational infrastructure have facilitated the operation of increasingly elaborate automated algorithms to map spatially extensive areas where manual approaches would be inefficient.
We present a deep learning framework that employs semantic segmentation techniques on optical satellite imagery and medium resolution digital elevation models to map linear dunefields. The workflow includes the access and pre-processing of training and prediction data, with a Neural Network as the centrepiece that is trained and applied to identify dune crests. We conducted a preliminary case study to develop and evaluate the framework on the dunefields of the Kalahari Desert, producing promising results.
Our next step is to leverage the generated dune maps to classify different dune patterns and investigate their relationship with climate and topography. We hope to provide valuable insights into the complex interplay between dunefield morphology and its environmental and climatic drivers. +
Most of the estuaries and lagoons around the globe are unique and have distinct but irregular shorelines and bathymetries and normally surround by highly developed watersheds with expanding agriculture and urbanization in mid and low latitudes. It is important to understand influence of environmental perturbations on the local coastal ecosystems. This project aims to develop a model for water quality and phytoplankton dynamics in the Maryland Coastal Bays during various physical conditions and to provide a prototype to other global estuaries and lagoons. The preliminary results indicated that model was able to well capture the observed seasonal chlorophyll-a and nutrients distribution patterns; and the weak discrepancy in vertical distributions of phytoplankton was mainly caused by dominated wind and tidal mixing effect in the shallow of water column. The research outputs will link modeling with local policymakers for ecological restoration and harmful algal bloom prevention by optimizing the amount of nutrient reduction in freshwater inflow to restore the ecosystem and making timely predictions of harmful algal blooms under different weather conditions. The estimation and discussion towards the spatial and temporal variabilities of phytoplankton distribution under extreme weathers will provide reference for ecological studies in MCBs and other similar lagoon systems around the world. +
Much of modern tectonic geomorphology focuses on interpreting patterns of bedrock river slope and using this information to make tectonic inferences. At its core, this framework often assumes that rivers are readily able to erode bedrock, and that they respond to tectonic and climatic forcing mostly through vertical incision and slope adjustment. However, bedrock rivers must also transport sediment delivered to them by surrounding hillslopes, which may act to amplify or to inhibit incision into bedrock. Rivers also adjust their width in response to climatic and tectonic controls, often much faster than slope adjustments can occur. While the importance of sediment flux and channel width has been understood for some time, these behaviors are hard to predict mechanistically and thus go unaccounted for in many models of landscape evolution. We present a model of river evolution in which channel slope and width freely evolve to optimize sediment transport and bedrock incision in response to stochastic water and sediment discharge. We investigate the impact of both water and sediment discharge variability under varied tectonic forcing and find that equilibrium channel form is controlled by a combination of water and sediment supply variability. We use the model to document measurement biases in rates of river incision (the Sadler effect) which are observed ubiquitously in real landscapes, and to for the first time examine the drivers of variations in this effect. Our results call into question the assumptions underlying the widely used detachment-limited stream power incision model of river evolution and highlight the importance of considering channel width and sediment flux when modeling river behavior and measuring rates of erosion over landscape evolution timescales. +
Much of the estimated 600 Mt of river sediment annually carried by the Ayeyarewady and Thanlwin River system (Myanmar) is delivered to the northern Andaman Sea. This area is influenced by strong tides, monsoon conditions, and periodic cyclones; however the processes that dominate dispersal of riverine material in the coastal ocean of this system have remained largely unquantified. The shelf exhibits a dramatic asymmetry of the surface morphology and sediment texture in the east – to – west direction, and recent field observations indicate that sediment accumulation rates increase toward the west. To explore the role that wave resuspension may play in these patterns, the SWAN (Simulating WAves Nearshore) model was implemented for the northern Andaman Sea, and run to represent both winter and summer time periods. The wave orbital velocities provided by SWAN were then analyzed to estimate the frequency of resuspension of fine-grained sediments throughout the study area. Results showed that wave-driven resuspension is much more frequent during the summer conditions which are characterized by the southwest monsoon; compared to during the northeast winds typical of the winter season. Additionally, the area fronting the Ayeryarwaddy Delta is subjected to energetic waves throughout both the summer and winter conditions, but wave energy decreases dramatically eastward toward the Thanlwin River mouth. +
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NOAA’s National Geophysical Data Center (NGDC) develops and publicly distributes a wide variety of topographic and integrated bathymetric-topographic digital elevation models (DEMs), ranging from the global ETOPO1 and GLOBE, to high-resolution (~10-m cell size) coastal DEMs to support NOAA’s tsunami forecast and warning efforts. We have developed a prototype online tool, using an underlying THREDDs catalog, to view and extract the square-cell models in their native resolution and datums, subset by user extents, and output in netCDF, geotiff, xyz, or ESRI Arc ASCII formats. We have also implemented a command-line get request that bypasses the browser interface. Current models include the 1-minute ETOPO1, 30-second GLOBE topography, the 3 arc-second U.S. Coastal Relief Model (CRM) and Great Lakes Bathymetry, and the 24 arc-second Southern Alaska CRM. In the future, we will be expanding the catalog to include all of NGDC’s public DEMs, and are investigating ways to in-fill gaps between higher-resolution DEMs with data from coarser models. +
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Natural channels are continuously changing their shape, where meanders and other complex configurations appear (e.g. bars, braided rivers, inner confluences, etc.). Channel evolution is strongly determined by the interactions occurring between its banks and the flow. These interactions also determine when a channel stabilizes, i.e. when its width remains constant. Current literature explains the stabilization of channels by the attainment of the equilibrium between sediment diffusion and gravity forces. However, the role of other potentially relevant processes is uncertain and needs to be addressed. Among them are secondary currents close to the banks and the spatial distribution of turbulence. Furthermore, the transition to steady-state banks is not fully understood. We explored these issues aiming to provide a better understanding of bank erosion and channel stability. To do this, we simulated a flatbed channel under 8 conditions, with Shields parameter spanning from 0.03 to 1.78. These simulations solved a 3D turbulent flow by carrying out Large-Eddy Simulations (LES) and the particles’ motion through a Discrete Element Method (DEM). We observed streamwise-aligned vortices appearing close to the banks, which were associated with high levels of TKE and shear stress, as well as flow spanwise velocity fluctuations. These fluctuations were mainly sweeps and ejections, which helped to dislodge sediments from the banks. Once detached, sediments could travel downstream. The role of the turbulence was also observed by separating the diffusive and advective components of the transport, where the initial bank erosion was dominated mainly by the former. Indeed, turbulence roughly explained 90% of sediment flux under erosion and bedload transport conditions. We conclude turbulent events increase shear stress close to the banks, promoting entrainment. Once the flow has transferred enough momentum to sediments, flow mean-velocity and fluctuations decrease. In this manner, shear stress decreases as the channel width increases. Eventually, shear stress reaches the threshold for transport close to the banks. Here, channel stabilization occurs. Notwithstanding that, stresses in the center of the channel are high enough to continue transporting sediments.
Nearshore hydrodynamic modeling necessitates extraordinary computational power to resolve the scales of motions relevant to coastal processes. Thus, coastal models make tradeoffs in the processes resolved. One common tradeoff is wave-averaging, whereby the evolution of bulk properties and statistics of wave fields are modeled. This contrasts the computationally more intensive wave-resolving models, whereby the time-varying motion of individual waves is directly output. However, complex nearshore dynamics are often driven by phenomena that cannot be directly derived from wave-averaged quantities, which limits the breadth of applications for wave-averaged models. Machine learning techniques provide a potential avenue to leverage the power of wave-resolving models for such applications at a lower computational cost. To this end, the wave-resolving, depth-integrated FUNWAVE-TVD modeling based on solving the Boussinesq equation is used in this study. The model was validated against the Dune3 dataset collected at Oregon State University corresponding to wave evolution and breaking in a cross-shore surf zone. A series of similar wave-resolving simulations using the FUNWAVE-TVD model were generated to create a training dataset corresponding to a one-dimensional planar beach under regular wave conditions. Two properties of interest, wave skewness and asymmetry, were calculated from the resulting wave-field and parameterized via the input wave conditions and bathymetry. Preliminary results show that even relatively simple ML models (neural networks and random forests) can provide drastic improvements to commonly used empirical models commonly employed by wave-averaging models, suggesting that ML-based parameterizations of nearshore wave properties provide a viable avenue for improving wave-averaged models. +
North Core Banks, a long (36-km), low (2.6-m mean elevation), narrow (~1200-m) barrier island in the Outer Banks of North Carolina, was inundated from the sound side and severely eroded by outwash during Hurricane Dorian (September 2019). As the fast-moving Category-1 hurricane moved offshore after a brief landfall at Cape Hatteras, winds shifted to the northwest, forcing a ~2.5-m surge onto the back side of the island. Deeply incised drainages were cut into the island as water ran from the washover platform to the ocean through gaps in the primary dune line, removing ~16% of the island volume. This style of storm impact is less common than typical ocean-side attack by waves and storm surge, and rarely modeled. Model simulations may provide insight into the fate of sands eroded during these unusual and difficult-to-measure events. We used the COAWST modeling system to simulate conditions during Dorian for a typical segment of the island using topography and landcover derived from pre-storm mapping using aerial imagery. The high-resolution (~2-m horizontal grid spacing) model was forced by output from a coarser-resolution model that provided water levels, incident waves, and alongshore currents. The model reproduced the steep cross-island water-level gradients inferred from high-water marks and wrack deposits, and generated washout channels ~2 m deep, cut through pre-existing low spots in the primary dune line. We evaluated model performance by comparing the simulated topography with post-storm topography derived from aerial imagery. The location, depth, and width of the simulated channels matched observations well, but the inland portion of the modeled channels were more linear than the observed dendritic drainages. Model simulations were sensitive to water-level forcing, sediment size, and vegetation patterns. The simulated channels extended into the surf zone and deposited sediments in relatively deep water. This transfer of sand from the island core to the nearshore has implications for barrier island evolution, and the ability to model it with COAWST demonstrates the generality of its morphology components.
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Notice: Kim Picard is 1st author; Phil Hill 2nd author; Andrew Wickert 3rd author<br><br>This work aims to improve the late Quaternary stratigraphic framework for the outer shelf and slope of the Beaufort Sea and to assist in the assessment of geohazards, particularly those related to slope instability. Slope failures have been identified on the upper slope, but the age and triggers of slope failure are poorly understood. Existing conceptual models of late Quaternary stratigraphy of the Beaufort shelf and slope are quite generalized and based on a poorly constrained relative sea level curve. Sea level and stratigraphic modeling are used to test the relationships between glaciation, sea level and sedimentation. The results of the work suggest that glacio-isostatic effects cause the relative sea level (RSL) curve to vary significantly across the Beaufort Shelf particularly in the cross-shelf direction. Stratigraphic modeling with a variable RSL input successfully reproduces depositional patterns in the Mackenzie Trough including distinctive highstand and lowstand wedges and a retrogradational transgressive systems tract. However on the eastern shelf, more pronounced isostatic depression is required to match the known stratigraphy, suggesting deviation from the assumed ice loads or crustal properties in the model. Two outburst floods documented to have occurred in the region would have had a marked effect on shelf edge and slope sedimentation. Modeling suggests significant progradation of the shelf edge and rapid deposition on the slope and outer shelf at lowstand and in the early stage of transgression. +
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Numerical models are effective and efficient tools for understanding the interactions among earth surface processes, including hydrological, biogeochemical, geomorphological, and ecological processes. These models with various complexities test hypotheses and make predictions within certain pre-defined model boundaries. These boundaries, on the one hand, reduce the complexity and noise of the system by ignoring the processes outside the boundary, which may only play a minor role in affecting the dynamics of the modeling system. On the other hand, some key processes that have a first-order control on the system dynamics may be unreasonably excluded from the modeling system. With the rapid growth of interdisciplinary researches, there is a more urgent need of revisiting the definition of the boundaries in the current numerical models to understand the gaps in bridging the boundaries between disciplines. This study is developed to meet this need. We investigated the models in the CSDMS model repositories by analyzing the process integration, boundary conditions, and spatial and temporal scales and summarized the potential gaps between boundaries that the current models present. This is the first study that conducts a comprehensive review of the models in the earth system modeling community, which provide insights for future model development and implementation across boundaries. +
Numerical models play a vital role in understanding river channel and floodplain evolution, yet their setup often requires extensive measured data. Maintaining continuity in monitoring fluvial geomorphology and sediment transport globally poses a significant challenge. This study introduced a remote sensing-based methodology for constructing and calibrating a reach scale 1D hydrodynamic numerical model, particularly suited for data-scarce regions. The effectiveness of this approach was assessed on the Elwha River in Washington.
The methodology employed a supervised image classification technique to extract a river mask, especially useful in areas with significant shadow pixels. Subsequently, channel attributes such as width, sinuosity, and slope were derived, and river segments with similar cross-sectional properties were identified using a multivariate change point approach, resulting in delineation of four distinct segments for the Elwha River. Next, hydraulic calibration of the numerical model accurately simulated water surface elevation (NSE: 0.93, PBIAS: -7%, RSR: 0.27). The sediment transport sub-model provided precise estimates of Suspended Sediment Concentration for mid-discharge values of 70 – 100 m3/s, associated with exceedance probabilities ranging from 0.4 to 0.04. Furthermore, the numerical model accurately reproduced channel deposition-erosion patterns estimated using publicly available aerial imagery from 2015 to 2017 (56 m vs. 48 m). These findings demonstrate the successful utilization of remote sensing datasets to supplement data requirements for numerical model setup and calibration, as well as to generate validation datasets. The methodology holds promise for accurately simulating hydromorphodynamic processes in both data-rich and data-scarce regions. +
Numerical simulation of fluvial morphodynamic processes can identify important dynamics at time and space scales difficult to observe in the field. However, simulations involving large spatial scales and/or the long timescales characteristic of morphodynamic processes are often untenable due to long simulation times. The morphological acceleration factor (morfac) applies a scalar multiplier to the sediment continuity equation, and is often applied in morphodynamic simulations to reduce computational time. While the use of morfac in coastal simulations is relatively common, its applicability in field-scale fluvial models is generally confined to steady-flow simulations over reach-scale spatial domains. Here we explore the viability of using morfac to simulate large-scale, long-term morphodynamics in a gravel-bed river. Using Delft3D to simulate a 60-day period with a significant discharge event in the Nooksack River, Washington, we systematically adjust morfac values (ranging from 5 to 20) to compare with a baseline condition of no acceleration. Model results suggest that morfac based modification of the inflow hydrograph time-series significantly alters downstream flood wave propagation. Higher morfac values result in greater flood-wave attenuation and lower celerity, reducing the morphological impact at locations further downstream. In general, relative error compared to the baseline increases farther downstream, due to this altered flood-wave propagation. Furthermore, even for the lowest morfac values absolute cumulative volume change errors are on the order of 10%, indicating that the use of morfac in fluvial simulations is best restricted to short-term and/or smaller-scale modeling efforts. Funded by the National Science Foundation. +
Observations in coastal environments show that seabed resuspension can impact water quality and biogeochemical dynamics by vertically mixing sediment and water, and by redistributing material that has been entrained into the water column. Yet, ocean models that incorporate both sediment transport and biogeochemical processes are rare. The scientific community frequently utilizes hydrodynamic-sediment transport numerical models, but hydrodynamic-biogeochemical models ignore or simplify sediment processes, and have not directly accounted for the effect of resuspension on oxygen and nutrient dynamics.
This presentation focuses on development and implementation of HydroBioSed, a coupled hydrodynamic-sediment transport-biogeochemistry model that was developed within the open-source Regional Ocean Modeling System (ROMS) framework. HydroBioSed can account for processes including advection, resuspension, diffusion within the seabed and at the sediment-water interface, organic matter remineralization, and oxidation of reduced chemical species. Implementation of the coupled HydroBioSed model for different locations, including the Rhone River subaqueous delta and the northern Gulf of Mexico, have helped to quantify the effects of both sediment transport and biogeochemical processes. Results indicate that resuspension-induced exposure of anoxic, ammonium-rich portions of the seabed to the more oxic, ammonium-poor water column can significantly affect seabed-water column fluxes of dissolved oxygen and nitrogen. Also, entrainment of seabed organic matter into the water column may significantly draw down oxygen concentrations in some environments. Ongoing work focuses on how resuspension and redistribution of organic matter and sediment may influence oxygen dynamics in the Chesapeake Bay. +
Observations of the spatial and temporal evolution of thaw and soil moisture changes are needed to understand thermo-hydrologic dynamics in periglacial regions and to inform models that forecast changes in the Arctic. However, obtaining spatially and temporally distributed observations in the Arctic is difficult. Here we develop and investigate the use and accuracy of the parameter estimation algorithm in recovering soil physical properties. We tested our parameter estimation (PE) approach with synthetic data from a continuously modeled electric resistivity tomography transect and co-located synthetic temperature and soil moisture data. The results indicate that developed PE approach is able to identify synthetic porosities and thermal conductivities. +
Ocean waves are key drivers of erosion and cliff retreat along rocky coasts, doing so by delivering energy to the shore upon breaking. Wave energy attenuation increases with increasing distance from the location of breaking. As a result, breaking distance from the shore is one of the most important constraints on wave energy delivery to the coast. A primary factor influencing nearshore wave transformation and energy flux at the shore is shore morphology. We seek to evaluate local morphologic controls to better characterize wave energy delivery to the coast. Local wave climates are characterized utilizing NOAA datasets, and we incorporate the Coastal Relief Model to determine nearshore bathymetry and coastal morphology. We then perform shallow water wave transformations using linear wave theory to specify wave breaking locations along the shore. Here we present preliminary results that suggest that shore morphology, and specifically the gradient of the shore platform, is the dominant control on wave filtering and transformation along the West Coast of the United States. Ascertaining the role of shore morphology in controlling energy delivery to the shore is important for specifying the influence of shore steeping processes on wave transformation and energy delivery, as well as constraining and predicting coastal erosion and cliff retreat. +
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Often a rivers discharge is calculated by constructing an empirical relationship between concurrent, direct measurements of river stage and discharge. In many remote parts of the world however technical and logistical challenges make building of such relationships difficult.
We test and present an alternative approach for use in remote Greenlandic Rivers. We used in-situ stage observations, but converted these measurements into estimates of discharge using a fluid mechanically based model (Kean and Smith, 2005; Kean et al., 2009; Kean and Smith, 2010). We first tested this approach against the one river in Greenland with a well-developed empirical stage- discharge relationship. Modeled relationships agreed well with the empirically derived relationship. We then used this same technique to aid in estimating discharge on two additional rivers in Greenland where only stage measurements were available. This technique presents an alternative option when other methods are logistically prohibitive. In the future this approach may also be useful to aid in estimating river discharge from space. +
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On a broad scale climate controls the distribution of biomes and sets an upper limit for woody plant canopy cover. During last glacial cycle that peaked ~18,000 years (B.P.) in the Late Pleistocene, the southwestern United States was much wetter and cooler than in the Holocene (last 11,000 years) and today. Since the Last Glacial Maximum, wetter and cooler climate in most arid semiarid regions has generally transitioned to drier and warmer conditions, establishing their characteristic (i.e., today’s native) ecosystems and fire regimes 3,000 - 5,000 years B.P. We use the Landlab earth surface modeling toolkit to explore the implications of the climate since the late Pleistocene on ecosystem patterns, using a calibrated model for conditions prior to the Euro-America settlers. Climate is constructed based on paleoclimatic proxies and weather station data. The controls of seedling dispersal strategies of plants and water availability as mediated by aspect are discussed. +
On densely populated deltas, the tendency for river channels to catastrophically avulse poses a hazard to human life and property. Previous work has shown that river avulsions preferentially occur around a spatial node with a distance from the shoreline that is controlled by backwater hydrodynamics, the interplay of dynamic river discharge and standing water near the shoreline. Our ability to forecast the location of future avulsion hazards is limited, however, because avulsions are relatively rare and many deltas are experiencing drastic changes in river discharge and sea level due to land-use and climate change. Building upon previous work, we present a predictive model of delta-lobe morphodynamics and repeated avulsion that is applicable to deltas over a range of spatial scales, sediment supplies, flood regimes, and relative-sea-level-rise conditions. In our model, delta lobes build on top of one another, demonstrating a distribution of avulsion lengths that is sensitive to flow regime and relative sea-level change. Variable flood regimes lead to a consistent avulsion length when low flows (less than bankfull) and high flows (greater than bankfull) compete to intermittently fill and scour portions of the backwater reach. The avulsion node is a spatial maximum in channel superelevation set by the downstream extent of low-flow deposition between erosive high-flows, and in general channels avulse farther upstream when high-flow events are more extreme and more frequent. Relative sea-level rise leads to a more variable avulsion node, driven by intermittent retreat and advance of the delta shoreline as the river periodically shifts the distribution of sediment. If rise rates are sufficiently high to sequester all sediment upstream of the river mouth, avulsions occur progressively farther upstream or not at all. These results have implications for the forecasting of avulsion hazards on modern deltas undergoing relative sea-level rise and human management.
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On earth, landscape morphology is mainly controlled by rivers evolutions and their interactions with hillslopes. But hydrographic network may be re-organized by stream capture and modify deeply the relief. This transition may be induced by several mechanisms (diversion, headward erosion, avulsion, or subterranean filling up). It has interested numerous scientists since a long time (Davis 1895, Blache 1943, Lesson-Quinif 2001 & Le Roux-Harmand 1997-2009…). Here we focus on stream piracies by headward erosion, when an actively eroding low level stream (called the captor) encroaches on the drainage of a nearby stream flowing at a higher level (called the diverter) and diverts part of the water of the higher stream.
During the last decades, several landscapes evolution models (LEM) have been developed to quantify the topography evolution with diffusion and advection equations. These models play an important role in sharpening our thinking to better understand the interaction between landscape evolution processes. LEM were developed basically to simulate erosion, tectonic and climate at different scales of time and space. But, these models were not designed to describe specific mechanisms as the stream capture. It’s one of the aims of this work to evaluate LEM for this purpose.
In this paper, we develop a 1D model based on LEM equations to investigate the stream piracy by headward erosion responses to climatic or tectonic changes. This model incorporates the most common equations used in quantitative geomorphology; diffusion in hillslope, advection in river (detachment-limited mode) and an inequality based on slope and drainage area for the limit between these two domains (Montgomery and Dietrich, 1988). First, simulations on analytical cases highlight the stream head progression mechanism, and the results indicate that this progression rate is mainly controlled by the slope at the captor source. Consequently, the aggradation of the diverter or (and) the incision of the captor accelerate the process. Then, a predictive study with an improved version of GOLEM (software developed by Tucker & Slingerland in 1994) on the Meuse basin shows that several piracies may probably occur in the future. A comparison with the 1D model gives similar results.
The simplicity and the flexibility of the 1D model allow complex simulations in the Meuse basin taking into account: lithological differences of outcropping layers, Meuse deposition tendency, etc. Once the 2D simulations or topography analysis locate potential captures, 1D simulation may intensively be used, as it presents many advantages; weak execution time, simple limits conditions setting, less time for data preparation, etc. Consequently, a sensitivity analysis to estimate piracies ages is realized with the developed 1D model.
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On low-lying coastlines, sand (and/or gravel) washed landward of a beach during storms creates barrier landscapes. This ‘overwashed’ sand also tends to maintain barrier elevation in the face of rising sea level, and barrier width in the face of an eroding shoreline. However, from the point of view of coastal communities, the storm processes that deposit the sand, as well as the sand itself, presents hazards that need to be mitigated, or even disasters that need to be recovered from. The strategies typically chosen to mitigate storm hazards and recover from storm impacts typically involve attempts to prevent overwash processes (e.g. by building and maintaining large dunes) or to undo the effects of overwash processes (e.g. bulldozing overwashed sand off roads and using it to rebuild dunes). Although these mitigation and recovery strategies seem necessary in the short term, they can reduce coastal resiliency in the long term, by tending to make a barrier lower (relative to rising sea level) and narrower (in the case of an eroding shoreline). A lower and narrower barrier is more vulnerable to sunny day flooding and severe storm impacts.
The newly developed CoAStal Community-lAnDscape Evolution (CASCADE) model couples physical processes (storm erosion and sediment redistribution, dune growth, sea-level rise, shoreface and shoreline change, and gradients in alongshore sediment flux) and the effects of management strategies (e.g. overwash removal and dune maintenance, highway relocation, and beach nourishment). Using this model, we examine the outcomes, over decades, of the coupling between natural dynamics and commonly employed management strategies. Modeled outcomes depend on sea-level-rise rate, storm sequences, and initial barrier topography, and they range from developed barrier systems that can be sustained for over a century before becoming uninhabitable (effectively drowned), to scenarios in which highways and/or communities need to be abandoned within decades. Subsequent barrier recovery depends on the final state of the developed system before abandonment, as well as stochasticity in the timing of storms. When different management strategies are employed at different locations alongshore, their effects are coupled via the redistribution of sediment along a curved coastline.
We are also using CASCADE in a participatory modeling collaboration involving managers and planners with the Cape Hatteras National Seashore and the North Carolina Department of Transportation, as well as community representatives. Together, we will examine the range of outcomes, under different climate scenarios, of the strategies being considered for managing a critically threatened transportation corridor along a barrier within the National Seashore.
One possible human response to climate change and other environmental stresses is migration. However, migration is complex, multi-causal phenomenon, and the complexity of human migration poses a challenge for researchers who aim to study the effects of environmental changes on population mobility. This project aims to understand how changing environmental conditions and livelihood opportunities impact migration decisions in coastal Bangladesh. An original agent-based model (ABM) that combines stylized environmental change dynamics with livelihood is developed to understand how these dynamics impact migration decisions as well as what feedbacks may exist between them. The ABM is constructed such that agents represent households, consisting of individuals, within a single origin community. At each step of the model, an agent will first assess the expected utility of its different options within the community, including doing nothing, seeking employment internal to the community, and investing in non-agricultural livelihood options. After assessing livelihood options internal to the community, households with sufficient wealth and a sufficient number of family members will decide whether or not to send a household member as a migrant, also based on expected utility of a migration trip. The model’s representation of natural processes will be simulated in the form of drought, modeled stochastically, that impacts crop yields and crop-associated income. In this initial version of the ABM, agent decision-making is based on simple utility maximization. Future work will incorporate more complex decision-making theories into the model, as well as different destination locations and the possibility of return migration. +
Our understanding of temporal changes in long term regional erosion rates in hundreds of years resolution is currently limited. The existing published research is either restricted in spatial coverage, the time frame is in millions of years, or the erosion rate through time is considered constant. We strive to fill this gap by mapping the regional erosion at a resolution of 3.70° latitude by 3.75° longitude (approximately 412 km x 416 km at the equator) at 500-year resolution for the past 21 ka for all land areas. We employ a transfer function that relates mean annual air temperature (MAAT) with erosion that is derived from published field observations recorded during recent times and transferred through the past 21 ka by using space-for-time substitution with paleo-temperature data from TraCE-21ka, a global climate model. Averaging erosion rates and MAAT by latitudes of the Kӧppen climate zones, a non-linear relationship was established. Among the many findings, the largest variation in erosion rates through time is found in cold regions, such as higher elevations and the Arctic. Furthermore, tropical or sub-tropical regions show minimal variation in erosion through time. +
Outburst floods and debris flows often incorporate large volumes of erodible bed sediment along their runout path. Although this phenomenon is widely recognized and often implicated for volumetric growth of debris flows, the effect of this process on the dynamics and runout extent of large flows has not been directly modeled extensively or systematically. Rather, models that account for this process traditionally utilize simple static volumetric and/or rheological adjustments. However, this process dynamically influences flood and debris-flow evolution in a complex spatiotemporal fashion.
We used D-Claw, a depth-averaged granular-fluid model that accommodates the incorporation of bed material into overlying flow and resultant changes in flow rheology across a wide range of solid concentrations, from dilute suspensions to dense-granular debris flows. We modeled hypothetical lake outburst floods from Spirit Lake, WA into the erodible sediment rich Toutle River Valley. Downstream flood dynamics of clear-water flows were compared to floods that entrain material and transform into down-valley debris flows. We found that while the entrainment of bed material may significantly increase total flow volume (>150%), downstream discharge and runout extent are more similar to clear-water floods than might be expected by volumetric considerations alone. We postulate that the relationship between entrained volume and flow extent depends on complicated site-specific factors such as location of erodible sediment and evolving rheological factors. +
Outlet glaciers convey large quantities of ice, sediment, and water from the interior of ice sheets to the coastal ocean. Beneath ice sheets, sediment is transported by melt water, entrainment in basal ice layers, and deformation of the till layer. Till deformation occurs when the ice sliding velocity exceeds a certain threshold, causing buried clasts to plough the sediment layer (Zoet and Iverson, 2020). Because ice velocity tends to decrease below the ice equilibrium line, but the threshold velocity to induce ploughing stays constant, the glacier will deposit till around the “till equilibrium line,” where the ice sliding velocity drops below the threshold velocity (Alley et al., 1989). Investigating the controls on till equilibrium lines will improve our understanding of erosion and sediment transport beneath glaciers and ice sheets. Here, we implement a numerical model of steady-state till equilibrium line position under a synthetic outlet glacier. We explore the influence of ice sliding velocity, clast sizes and distribution, and effective pressure at the bed. Additionally, we consider the case where the threshold velocity to induce ploughing is not constant, but instead depends on ice and sediment properties.
Zoet, L. K., & Iverson, N. R. (2020). A slip law for glaciers on deformable beds. Science, 368(6486), 76-78.
Alley, R. B., Blankenship, D. D., Rooney, S. T., & Bentley, C. R. (1989). Sedimentation beneath ice shelves—the view from ice stream B. Marine Geology, 85(2-4), 101-120. +
Over 10 percent of the worlds’ population lives less than 10 meters above sea level(McGranahan et al,. 2007), putting them at risk for rising seas and sinking coasts. Additionally, coastal inhabitants preferentially live in locations that are subsiding (Nicholls et al,. 2012), representing a flooding threat to people and infrastructure in coastal cities. Findings from the Intergovernmental Panel on Climate Change (IPCC 2018) outline the risks and impacts of sea level rise on flooding, and go on to identify a knowledge gap regarding the combined effects with coastal subsidence. When drivers of subsidence combine, they can generate sinking rates of 6-100mm/yr, significantly more than the 3-10mm/yr for sea level rise alone (Erkens et al,. 2015), making subsidence an order of magnitude more threatening to coastal cities.
The recent growth in access to C-band Synthetic Aperture Radar (SAR) data through the European Space Agency (ESA) Sentinel-1A/B satellites and the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR) mission provide increased opportunities for differential interferometric synthetic aperture radar (DInSAR) monitoring. Here we developed a dockerized supercomputer workflow that allows us to rapidly generate InSAR pairs from Sentinel 1 imagery using ISCE processing software(Rosen et al., 2012) at ~10 meter resolution.
Results from this workflow are used to create a timeseries of subsidence for Lagos, Nigeria, where rapid urban growth has led to accelerated subsidence throughout the city. This growth has resulted in various flash floods due to infiltration and drainage issues in the last fifteen years(Atufu 2018), and the city is also vulnerable to coastal flooding. Next steps will include inputting our time series to determine how future flood events may impact specific areas of Lagos. Understanding where floods are a higher risk can allow for better distribution of rescue resources, and allow for targeted remediation and recovery efforts.
Particle settling velocity and bed erodibility impact the transport of suspended sediment to the first order, but are especially difficult to parameterize for the muds that often dominate estuarine sediments. For example, fine grained silts and clays typically form loosely bound aggregates (flocs) whose settling velocity can vary widely. Properties of flocculated sediment such as settling velocity and particle density are difficult to prescribe because they change in response to several factors, including salinity, suspended sediment concentration, turbulent mixing, organic content, and mineral composition. Additionally, mud consolidates after deposition, so that its erodibility changes over timescales of days to weeks in response to erosion, deposition, dewatering, and bioturbation. As understanding of flocculation and consolidation grows in response to recent technical advances in field sampling, numerical models describing cohesive behavior have been developed.
For this study, we implement an idealized two-dimensional model that represents a longitudinal section of a partially mixed estuary that mimics the primary features of the York River estuary, VA; and accounts for freshwater input, tides, and estuarine circulation. Suspended transport, erosion, and deposition are calculated using routines from the COAWST (Coupled Ocean-Atmosphere-Wave-and-Sediment Transport) modeling system. Here we evaluate the impact that bed consolidation and flocculation have on suspended sediment dispersal in the idealized model using a series of model runs. The simplest, standard model run neglects flocculation dynamics and consolidation. Next, a size-class-based flocculation model (FLOCMOD) is implemented. The third model run includes bed consolidation processes, but neglects flocculation; while the last model run includes both processes. Differences in tidal and daily averages of suspended load, bulk settling velocity and bed deposition are compared between the four model runs, to evaluate the relative roles of the different cohesive processes in limiting suspension in this partially mixed estuary. With an eye toward implementing these formulations in a realistic-grid model, we also consider the computational cost of including flocculation and consolidation.
Particle-based methods in computational fluid dynamics are capable of characterizing the propagation of the inertial terms and complex behavior of a fluid in low-viscosity systems onto an interface with highly viscous or solid materials, providing a high resolution window into fluid dynamics within environments that are fundamentally defined by fluid-solid interaction. The rate limiting feedbacks of wave action, erosion and sediment transport are a multiscale problem, involving kilometer-scale climate forcing and local, submeter Earth responses. We use real-world inputs of dynamic water levels at the mesoscale to drive local particle-based wave solutions towards natural coastal landforms effectively coupling the multiscale transfer of forces produced by topographic relief, wave action and ice collisions. 3D temporal solutions of nearshore currents at multiple scales make it possible to handle the specifics of fluid-solid interactions as the basis for training algorithms and subsequent expansion to larger regions. +
Passive margin stratigraphy contains time-integrated records of landscapes that have long since vanished. Quantitatively reading the stratigraphic record using coupled landscape evolution and stratigraphic forward models (SFMs) is a promising approach to extracting information about landscape history. However, the most commonly used SFM, which is based on an approximation of local, linear slope-dependent sediment transport, fails to produce diagnostic features of passive margin stratigraphy such as long-distance transport from the continental shelf and slope onto the abyssal plain. There is no consensus about the optimal form of simple SFMs because there has been a lack of direct tests against observed stratigraphy in well constrained test cases. Here we develop a nonlocal, nonlinear one-dimensional SFM that incorporates slope bypass and long-distance sediment transport, both of which have been previously identified as important model components but not thoroughly tested. Our model collapses to the local, linear model under certain parameterizations such that best-fit parameter values can be indicative of optimal model structure. Using seven detailed seismic sections from the South African Margin, we invert the stratigraphic data for best-fit model parameter values and demonstrate that best-fit parameterizations are not compatible with the local, linear diffusion model. Fitting the observed stratigraphy requires parameter values consistent with important contributions from slope bypass and long-distance transport processes. The nonlocal, nonlinear model yields improved fits to the data regardless of whether the model is compared against only the modern bathymetric surface or the full set of seismic reflectors identified in the data. Results suggest that processes of sediment bypass and long-distance transport are required to model realistic passive margin stratigraphy, and are therefore important to consider when inverting the stratigraphic record to infer past perturbations to source regions.
Past decades have seen rapid advancements in the field of soil erosion modelling, with a shift away from lumped empirical models and towards fully-distributed physically-based erosion models. The benefits of this shift is that distributed erosion models facilitate the spatial predictions of erosion and deposition across the landscapes by computing runoff and modelling the subsequent detachment, transport, and deposition of sediments. Despite the ability to represent the physical process of erosion spatially, distributed erosion models are validated to discharge and sediment yield at catchment outlets. Spatial information on erosion and deposition rates are seldom used to validate distributed models; this is because both plot and field-scale data on erosion rates are rare. Structure-from-motion (SfM) and multi-view stereo (MVS) algorithms coupled with the use of unmanned aerial vehicles (UAVs) have become a popular tool in geomorphology for modelling topographic change-detection on complex landscapes. We demonstrate the viability of using these techniques to generate spatial validation data; repeat UAV surveys of an agricultural field are used to identify dominant sediment flow paths, depositional zones, and rill/gully erosion processes. This unique spatial dataset allows us to tackle issues of spatial equifinality, model parameterization, and the accurate discretization of the landscape. +
A
Patterns of sediment transport and particle residence times influence the morphology and ecology of shallow coastal bays in important ways. The Virginia Coast Reserve (VCR), a barrier island-lagoon-marsh system on the Eastern Shore of Virginia, is typical of many shallow coastal bay complexes that lack a significant fluvial source of freshwater and sediment. Sediment redistribution within the bays in response to storms and sea-level rise, together with the dynamics of marsh and lagoon-bottom plants, largely governs the morphological evolution of this system. There are also important feedbacks between sediment and ecosystem dynamics. This is particularly true in the VCR, which is relatively unaffected by human activities. As a step towards evaluating the impact of hydrodynamics on sediment and ecological processes in the VCR, we employ a single unified model that accounts for circulation, surface waves, wave-current interaction, and sediment processes. This three-dimensional unstructured grid finite-volume coastal ocean model (FVCOM) is validated with field observations of wind- and tide-induced water flow (water level and current velocities) in Hog Island Bay, centrally located within the VCR. We present here the resulting patterns of sediment transport and particle residence times over event and seasonal time scales. Water and particle exchange within the VCR and between the VCR and the ocean is examined with the Lagrangian particle-tracking module in FVCOM. We focus on 3 bays with strongly varying bathymetry and coastline geometry, which are also located along a gradient of nitrogen input to the system. The results indicate that residence time of particles within the system vary greatly depending on the location of particle release, bay morphology, and wind conditions. The implications for morphologic evolution and ecosystem response to climate and land-use changes are evaluated. +
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Permafrost thaw is of growing concern due to its potential to weaken slope stability and influence the magnitude and frequency of rapid mass movements in an area. Therefore, modelling of permafrost distribution and dynamics is needed for mountain areas, where such events happened or might happen. For instance in Iceland, permafrost thaw has been recently recognized as a new factor influencing landslide triggering, whereas the instability and slow movement of the unstable rock slope Mannen in southwestern Norway might be connected to permafrost conditions.
CryoGrid is a suite of permafrost models for solving different problems related to permafrost processes. This presentation will show examples of application of the two model schemes, the one-dimensional model CryoGrid 2 (Westermann et al., 2013) and the two-dimensional model CryoGrid 2D (Myhra et al., 2017). Both models solve the transient heat diffusion equation that additionally accounts for the latent heat effects due to ground freezing or thawing. The CryoGrid 2 model is forced with time series of air/ground surface temperature and snow depth data, whereas the CryoGrid 2D model is forced with ground surface temperature.
We applied CryoGrid 2 to the regional modelling of permafrost dynamics in Iceland for the last six decades. To account for snow redistribution, we ran the model for three scenarios of the snow depth, having a large impact on the modelled permafrost distribution.
CryoGrid 2D was employed to model ground temperature in the Mannen rock slope since the 1860s. Our preliminary results show that permafrost can occur in the Mannen slope in areas with considerably reduced snow depth, i.e. under steep parts of the slope.
REFERENCES
Myhra, K. S., Westermann, S., & Etzelmüller, B. (2017). Modelled distribution and temporal evolution of permafrost in steep rock walls along a latitudinal transect in Norway by CryoGrid 2D. Permafrost and Periglacial Processes, 28(1), 172-182. DOI: 10.1002/ppp.1884
Westermann, S., Schuler, T., Gisnås, K., & Etzelmüller, B. (2013). Transient thermal modeling of permafrost conditions in Southern Norway. The Cryosphere, 7(2), 719-739. DOI: 10.5194/tc-7-719-2013
Planktic foraminifera abundances and distributions, i.e. faunal assemblages, have been used to reconstruct oceanographic conditions from Earth's ancient past. Here we examine the utility of Species Distribution Models (SDMs) in characterizing the ecology of modern foraminifera and how this can inform reconstructions of past oceanographic states from Earth’s climatic history. Standard faunal assemblage proxy reconstructions often reduce multidimensional environmental data into a single variable, typically temperature. However, when environmental covariates feature strong spatial autocorrelation, these traditional methods may incorrectly interpret information from other variables as a temperature signal. Using modern machine learning-based SDMs we show that while temperature is an unquestionably important control on foraminifera distribution, other environmental factors appear to play a non-trivial role. This has implications not only for temperature values derived from standard assemblage-based reconstructions, but also may help reconcile apparent mismatches between proxies and climate model simulations +
Post-fire debris flow is a common hazard in the western United States. However, after decades of efforts in the debris flow research community, universally applicable post-fire debris flow predict methods are still lacking. Large discrepancies in the post-fire debris flow initiation mechanism are the main source that limits the predictive accuracy of debris flow. Improve and understanding these discrepancies is significant to possibly improve the debris flow modeling. In this work, we propose a data-driven, physics-informed machine learning approach for reconstructing and predicting debris flows. By using a classic supervising modern learning technique based on logistics regression, the logistics regression functions are trained by existing direct field measurements and debris flow numerical simulations from Las Lomas after 2016 Fish fire and then used to predict debris flow in different drainage basin where data are not available. The proposed method is evaluated by two classes of simulations: sediment transport model and runoff model. In runoff simulations, five drainage basins are considered: Las Lomas, Arroyo Seco, Dunsmore 1, Dunsmore 2, Big Tujunga. In sediment transport model, Las Lomas and Arroyo Seco watersheds are applied. Excellent predictive performances were observed in both scenarios, demonstrating the capabilities of the proposed method. +
Post-wildfire debris flows are a major source of geomorphic change that by nature of the large amounts of mass they mobilize can be deadly and destructive. These landslides are triggered by the interaction of fire-induced changes to both hydrologic and geomorphic responses. Representing the cascading effects of fire on landslides requires linking information from hydrologic models and debris flow models and presents both technical and theoretical challenges. Statistical models of debris flows have been used successfully for decades to assist in disaster prevention and mitigation. However, physically-based models that may provide additional insight into underlying processes and behavior under extreme conditions are rarely used.
We present a case study to begin addressing these challenges, focusing on a basin burned by the Thomas Fire in southern California in 2017. Soil water content maps and sediment fluxes produced by the Distributed Hydrology Soil Vegetation Model (DHSVM) in areas at risk for debris flows are compared with times and locations of known landslides. The degree of correspondence between modelled debris flow risk factors is compared for different potential methods of representing fire in DHSVM, including: changes to soil depth, soil infiltration characteristics, vegetation cover, and vegetation properties. Finally, future challenges of linking information across hydrologic and landslide models are discussed, towards more accurately representation of the spectrum of debris flow processes. +
Predicting river hydrodynamics through computational models is critical for advancing science and engineering practices to manage rivers and floodplains. Traditional hydrodynamic models pose computational challenges, often demanding extensive processing time for large-scale 2D flood simulations. While data-driven algorithms have shown promise in improving simulation efficiency, existing efforts have primarily concentrated on generating inundation maps only at event peaks. In this research, we introduce a novel deep learning model designed to provide accurate and rapid simulation of the temporal evolution of floods, providing 2D prediction of both water depth and flood inundation maps across an entire event. We trained and evaluated this model based on a dataset that was developed using HEC-RAS, a physics-based model, for a segment of Ninnescah River, in Kansas. This was done using a deep learning model to integrate the spatial advantages of a convolutional neural network along with the temporal sequence capabilities of a long-short term memory network. The hybrid model demonstrates remarkable proficiency in capturing the dynamic nature of flood events. Evaluation of the inundation maps, at the highest testing peak, exhibited exceptional performance, with precision exceeding 0.99 and an F1-score approaching 0.98. Moreover, this hybrid model showed robust performance in predicting water depth maps, with RMSE values of 0.03 m on average during testing and 0.08 m at the highest peak time-step. This study represents a significant advancement in our ability to conduct long-term simulations of hydrodynamics and sediment transport. +
Predictive understanding of the variation and distribution of substrates at large spatial extents in aquatic systems is severely lacking. This hampers efforts to numerically predict the occurrence and distribution of specific benthic habitats, which must be observed in the field. Existing survey methods are limited in scale, require heavy and technically sophisticated survey equipment, or are prohibitively expensive for surveying and mapping. Recreation-grade side scan sonar (SSS) instruments, or fishfinders, have demonstrated their unparalleled value in a lightweight and easily-to-deploy system to image benthic habitats efficiently at the landscape-level. Existing methods for generating geospatial datasets from these sonar systems require a high-level of interaction from the user and are primarily closed-source, limiting opportunities for community-driven enhancements. We introduce PING-Mapper, an open-source and freely available Python-based software for generating geospatial benthic datasets from recreation-grade SSS systems. PING-Mapper is an end-to-end framework for surveying and mapping aquatic systems at large spatial extents reproducibly, with minimal intervention from the user. Version 1.0 of the software (Summer 2022) decodes sonar recordings from any existing Humminbird® side imaging system, export plots of sonar intensities and sensor-derived bedpicks and generates georeferenced mosaics of geometrically corrected sonar imagery. Version 2.0 of the software, to be released Summer 2023, extends PING-Mapper functionality by incorporating deep neural network models that automatically locate and mask sonar shadows, calculate independent bedpicks from both side scan channels, and classify substrates at the pixel level. The widespread availability of substrate information in aquatic systems will facilitate development of the next generation of in-stream models for routing flows of sediment and water, as well as more sophisticated simulations of specific habitats.
Preserved in the morphology of bedrock river valleys is a recorded history of geologic and climactic conditions experienced by that river over time. A deep, narrow valley suggests that conditions favored vertical incision over lateral erosion, and the presence of a wide bedrock valley indicates that lateral erosion and valley widening outpaced vertical incision. While vertical incision and the rates and mechanisms by which it operates are relatively well understood, the processes of lateral erosion and valley widening remain more enigmatic. Utilizing bedrock valley morphology as an interpretive tool is impossible without first improving our knowledge of the valley widening process. For a bedrock valley to widen the river must first laterally erode the bedrock wall until the overlying stresses cause the wall to collapse into a talus pile on the valley bottom. Once the material has collapsed, it then must be transported away from the bedrock wall so that the river can regain access to the wall and lateral erosion can continue. In this two-step conceptual model of valley widening, the size of the individual talus blocks and the volume of the pile itself plays a large role in the rate of valley widening over time. In this study, I use numerical modeling to estimate the long-term breakdown and removal of talus material in a river through chemical and physical weathering. Inputs for the model include measured talus pile characteristics from a bedrock river with wide and narrow bedrock valleys (Buffalo River) and long-term flood simulations generated by the LandLab tool, Random Precipitation Distribution Generator. Model results may offer some insight into the potential role of talus in the bedrock valley widening process and improve our understanding of the conditions favorable for the development of wide bedrock river valleys. +
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Previous studies have found that the ratio between valley spacing and mountain range width is relatively constant across the globe, but the processes responsible for its uniformity are not well understood. To determine the reasons for this uniform ratio, we firstly need to explore why valleys are evenly distributed in a mountain range, and what factors can impact valley spacing. Recent research has found that the critical length between hillslope and fluvial processes is an important control on the valley spacing of first order fluvial channels. In this study, we use the CHILD landscape evolution model to explore how the critical length affects valley spacing in higher order fluvial channels, and we use these results to help explain the narrow range of observations in the valley spacing ratio. We find that valley spacing has a linear relationship with critical length in higher order channels and, for a given order channel, the ratio between valley spacing and critical length is relatively constant. This relationship demonstrates that the competition between hillslope and fluvial processes influences the distribution of higher order channels across the landscape. However, we also find that valley spacing is influenced by model initial conditions and variability across the landscape, such as orographic precipitation patterns. Moreover, for a fixed domain in our model, although the critical length may vary, the ratio between the valley spacing of trunk channels and mountain width remains in the range observed in real landscapes. The reason for this is that the order of trunk channels varies with the critical length. Therefore, for a given domain size (or mountain range width), a larger critical length can produce lower order trunk channels but with the same spacing value as higher order trunk channels with a smaller critical length. This may be one of the reasons why the spacing ratio is relatively constant across diverse natural settings. +
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Proper quantification of sediment flux has always been an area of interest both for scientist and engineers involved in hydraulic engineering and management of rivers, estuaries and coastal waters. In spite of the importance of bedload flux globally, either for monitoring water quality, maintaining coastal and marine ecology or during dam construction or even for food security, bedload data, especially for large rivers, extremely scarce. This is due to the fact that bedload flux measurements are relatively expensive and time consuming and introduce large spatial and temporal uncertainties. Lack of adequate and continuous field observation is a hindrance to developing a globally accepted numerical model. We developed a new global riverine bedload flux model as an extension of the WBMsed framework. Here we present an evaluation of the model predictions using over eighty field observations for large rivers (over 1000 km2), collected from different sources. This model will be used to study various aspects of fluvial geomorphology globally, which is most common interest area for the researcher to see the impacts of different issues at global scale. Also, considering the contribution of bedload as sediment in the global level, it will elucidate the relationship between suspended sediment and bedload. The observational dataset we compiled is in itself a unique product that can be instrumental for future studies. +
Quantifying the spatial distribution of vegetation on coastal dunes is critical for understanding their morphological evolution and ecological functioning. However, effective large-scale mapping of dune vegetation presents a challenge for coastal managers at the resolution suitable for detailed analysis of these berm-dune systems. This study presents an integrated machine learning and geographic information system (GIS) methodology to accurately classify vegetation, sand, and shadows from high-resolution unmanned aerial vehicle (UAV) imagery of an undeveloped dune system in Long Branch, New Jersey. Using a Zenmuse X5S 3-band multispectral sensor and a Zenmuse X5 RGB sensor, we collected data from a single survey in October, 2023. We then combined the band data from this flight in order to develop additional model inputs of normalized difference vegetation index (NDVI) and green NDVI (gNDVI). Thirteen model runs were performed and compared using 3 to 8 inputs including spectral bands of Red, Green, Blue, and near-infrared (NIR). The spectral indices of NDVI and gNDVI, were developed using Red, Green, and NIR band data. In our research, the random forest machine learning algorithm was employed, with optimal hyperparameters determined through empirical testing. Classifiers with 350 decision trees were found to yield highest accuracy on the training data across different spectral indices combinations. The trained random forest models were then applied to map vegetation distribution on an unseen "training grid" area. Results show that model runs containing the NDVI and gNDVI yielded higher accuracy in classification than model runs only containing a combination of R, G, B, and NIR bands. Incorporating additional Red and Green bands from our multispectral sensor produced less accurate model classification as these additional inputs lead to overfitting and increased misclassification of vegetation and shadows. Incorporating NDVI and gNDVI indices significantly improved classification performance compared to model runs that only used spectral band information. The classified vegetation, sand, and shadow maps were integrated into ArcPro GIS software for visualization and validation against other established methods of manual class identification and map digitization. Rigorous accuracy assessments confirmed the robustness of the machine learning approach that can be used to quickly and accurately identify vegetation distribution in a dune complex.
Quantitative constraints on the frequency of hazards is vital to risk assessments and appropriate mitigation strategies. The frequency of landslides, a common hazard in steep landscapes, is difficult to quantify for a number of reasons including: (1) infrequent occurrence; (2) rapid deterioration of the morphological signature of a landslide event; (3) expensive geochronological approaches are often require to obtain the age of a single event. Through the use of numerical modeling, I propose that more careful approach of using cosmogenic nuclide concentrations of alluvial sediment sourced in landslide dominated drainage basins can alleviate many of these hurdles and provide regional constraints on landslide frequency. This suggestion stems from new development of an old numerical code that quantifies the impacts of landslides on CRN concentrations in alluvial sediment. The modeling shows that quantitative insight can be obtained by measuring CRN concentrations (1) of multiple nuclides (10Be and 14C), (2) of multiple grain sizes (i.e. coarse material sourced from depth in the hillslope), and (3) over time. I will present the new model developments and results as well as discuss some strategies towards applying this in field settings. +
A
Reactive Transport Modeling (RTM) has been developed in the past decades and used extensively to understand the coupling between fluid flow, diffusive and dispersive transport, and biogeochemical processes in the natural subsurface in a wide range of applications relevant to earth and environmental sciences. Reactive transport modeling solves conservation equations of mass, momentum, and energy. Process-based reactive transport modeling allows the regeneration of spatial and temporal propagation of tightly coupled subsurface processes at spatial scales ranging from single pores (microns) to watershed scales (kilometers). RTM can keep track of evolving porous medium properties including porosity, permeability, surface area, and mineralogical composition. In this presentation I will introduce the general framework of RTM together with its advantages and challenges. The use of RTM at different spatial and temporal scales will be illustrated using two examples. A one-dimensional chemical weathering model for soil formation in Marcellus Shale will illustrate its use in Critical Zone (CZ) processes at the time scales of tens of thousands of years. A two dimensional biogeochemical transport model will exemplify its use in understanding engineered bioremediation processes in natural, heterogeneous porous media at the time scale of months to years. +
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Recent discovery of a well-preserved drowned bald cypress forest offshore Alabama has spurred the search for analogous sites, as they provide valuable paleoclimate proxies and potential paleohuman habitats. However, drowned forests are difficult to detect when buried beneath the seabed, and degrade rapidly when exposed to the water column.
In this study, various machine learning algorithms within NRL's Global Predictive Seabed Model (GPSM) are used to geospatially predict the location of buried ancient forests offshore Mississippi. Subsurface sediment cores containing evidence of ancient forests (wood debris) are used as training and validation data, and feature layers include modern bathymetry, paleo-topographic surfaces, and seabed substrate. The resulting maps of probability of encountering wood-bearing sediments will be used to guide future data acquisition efforts. +
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Recent morphodynamic modeling of non-uniform turbulent transport and deposition of sediment in a standing body of water devoid of tides and waves shows that sediment caliber plays a major role in determining the shapes, cumulative number of distributaries, and wetland areas of river-dominated deltas. In this study we introduce metrics for quantifying delta shoreline rugosity and foreset dip (clinoform) variability, and explore their variation with sediment caliber. Delta shoreline rugosity is calculated using the isoperimetric quotient, IP = 4 pi A / P2, where a circle has a value of one. Clinoform complexity is calculated using the uniformity test in circular statistics wherein clinoform dip direction uniformity is the sum of the deviations of dip azimuths from a theoretical uniform distribution. Analysis of fifteen simulated deltas shows that IP increases from 0.1 to 0.5 as the normalized shear stress for re-erosion of cohesive sediment, τn, increases from 0.65 to 1. Clinoform dip azimuth uniformity decreases from 300 to 130 with increasing τn. Preliminary analysis of data from outcrops of the Cretaceous Ferron Delta and ground penetrating radar data of the Pleistocene Weber and Brigham City Deltas are consistent with these trends. These results imply that changes in sediment caliber delivered to a deltaic coastal system will profoundly change its wetland area, bathymetric hypsometry, ecological function, and interior stratigraphy. +
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Recent post-tsunami field surveys show that sandy tsunami deposits usually cannot cover all of the tsunami flow inundation areas. The difference between the sandy tsunami deposits inland extent and the flow inundation limit can be used to estimate tsunami magnitude. However, the relationship between tsunami deposit inland extent and inundation limit is still not fully understood. This paper focuses on studying the relationship and its control factors by using a parameter study and field measurements. Deposition ratio is a ratio between the sediment layer inland extent and the tsunami inundation limit to quantify this relationship. In the parameter study carried by a state-of-the-art sediment transport model (GeoClaw-STRICHE), we change grain size, offshore wave height, and onshore slope. The deposition ratio for tsunami deposit extent ($\xi_0$) is not sensitive to the grain size. However, the deposition ratios for observable sediment layer inland extent ($\xi_{0.5}$ and $\xi_{1}$) are affected by the grain size, offshore wave height, and onshore slope. The deposition ratios for a 0.5 cm thick sediment layer from parameter study are consistent with field measurements from the 2011 T\={o}hoku-oki tsunami on Sendai Plain. The topography, especially onshore slope, strongly influences the deposition ratio in this case. The combination of different deposition ratios can be used to estimate tsunami inundation area from tsunami deposits and improve tsunami hazard assessments. +
