Property:CSDMS meeting abstract
From CSDMS
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Satellite remote sensing is a powerful tool for terrestrial hydrological studies. In particular studies of droughts and floods - hydrological extremes can be well accomplished using remote sensing. In particular, we will use data from the visible-infrared and microwave sensors on NASA platforms to studies the onset and propagation of droughts as well as spatial extent of flooding. In this talk we will present numerous examples of hydrological extreme events and the use of satellite remote sensing as a tool for mapping the spatial extent and the temporal persistence. The droughts of 1988 and 2012 in the United States Midwest, flooding in 1993 and 1998 are strong examples in United States. There have been numerous such events in Asia in India, Pakistan and China which have affected billions of people who depend on the land and agricultural productivity to a much greater degree than in United States. +
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Sea level rise and changes in storm climate will modify the intensity of cross-shore sediment transport processes in the coming decades and centuries. Chief among these processes is the opening of tidal inlets on barrier islands which can affect nearby erosion rates and shoreline positions on a decadal time scale. In addition, shoreline change related to sea level rise and overwash deposition could vary alongshore in ways that could be dynamically coupled to patterns of coastline sculpting from gradients in alongshore sediment flux.
To examine how cross-shore and alongshore patterns interact, we will couple the BarrieR island and Inlet Environment (BRIE) model to the Coastline Evolution Model (CEM). BRIE has also been coupled to Barrier3D, which resolves cross-shore processes at higher resolutions. CEM was previously used to hindcast the component of coastline change patterns arising from alongshore sediment flux gradients, without including the components related to inlets or overwash. Coupled model experiments using BRIE, Barrier3D and CEM exploring how contrasting sets of processes dynamically interact will inform upcoming work to improve long term hindcasting and forecasting of shoreline change on complex coastlines. +
Sea level rise presents an urgent threat to the occupants of river deltas. However, while low lying deltaic landscapes are at risk of significant drowning, the ability to harness a river’s sediment delivery system offers deltaic populations a mechanism to control the location and extent of land loss via land building sediment diversions. Despite their well-recognized importance there are few examples of diversions that have been intensively monitored throughout their development to the extent necessary to support engineering decisions.
In order to guide the operational design of two planned diversions in the Lower Mississippi River, we apply Delft3D to simulate diversion discharge through time as a function of the characteristics of the receiving basin. In both cases the conveyance channel connecting the river to the basin is prevented from eroding.
We find that diversions in basins that offer many outlets for flow are more likely to maintain their discharge over a ten-year time horizon. We also find that diversion performance is not significantly affected by substrate erodibilities in the range of those found in the Mississippi River Delta, but that artificially increased bed strength would lead to decreases in performance. Our work also sheds light on the spatial pattern of erosion near a diversion. We find that very little erosion into the substrate occurs away from the immediate vicinity of the outfall channel, but that the evolution of the proximal scour is a critical control on the sustainability of the diversion. Ecological considerations suggest that operating diversions at low flow might be useful, but this practice increases the risk of back flow from the receiving basin. +
Seagrass provides a wide range of economically and ecologically valuable ecosystem services, with shoreline erosion control often listed as a key service, but can also alter the sediment dynamics and waves within back-barrier bays. Here we incorporate seagrass dynamics into the existing barrier-marsh model GEOMBEST++ to examine the coupled interactions of the back-barrier bay with both adjacent (marsh) and non-adjacent (barrier island) subsystems. In our new integrated model, bay depth and distance from the marsh edge determine the location of suitable seagrass habitat, and the presence or absence, size, and shoot density of seagrass meadows alters the bathymetry of the bay and wave power reaching the marsh edge. While seagrass reduces marsh edge erosion rates and increases progradation rates in many of our model simulations, seagrass surprisingly increases marsh edge erosion rates when sediment export from the back-barrier basin is negligible. Adding seagrass to the bay subsystem leads to increased deposition in the bay, reduced sediment available to the marsh, and enhanced marsh edge erosion until the bay reaches a new, shallower equilibrium depth. In contrast, removing seagrass liberates previously-sequestered sediment that is then delivered to the marsh, leading to enhanced marsh progradation. Lastly, we find that seagrass reduces barrier island migration rates in the absence of back-barrier marsh by filling accommodation space in the bay. These model observations suggest that seagrass meadows operate as dynamic sources and sinks of sediment that can influence the evolution of coupled marsh and barrier island landforms in unanticipated ways. +
Sediment creep is ubiquitous and precedes failure (e.g. landslides) in most landscapes. Accurate modeling of sediment creep is therefore crucial for predicting both the long-term (>10 000 years) evolution of landscapes and the short-term (minute to centuries) evolution of landscapes and infrastructures. Current sediment creep transport laws used in landscape modeling are determined empirically over geological time scales and are diffusion-like (Roering et al,2001); yet the mechanics of sediment creep on all time scales remain poorly understood. As a result, creep models used in civil engineering, materials science, and geomorphology are largely disconnected in time scales, goals, and approaches. In particular, excess porous flow from rain infiltration is currently not a governing parameter of any creep model, while large rain events are known to trigger landscape failures.
Houssais et al. (2021) showed experimentally for the first time, that porous flow can be a leading cause of creep, and ultimately the failure (avalanching) of sediment piles, for flow strength (or pore pressure) far lower than classically admitted. Building on the results from Houssais et al., we propose a new equation for sediment creep consistent with the general formalism of the mechanical creep of disordered materials. In our equation, the creep sediment flux is a function of: topographic slope (similar to the equation from Roering et al.), porous flow intensity, grains and fluid properties, and, importantly, time.
We present here the first results of landscape dynamics from the implementation of our new sediment creep function in landlab, for the case of idealized berms (or coastal natural dams), before they breach. The long-term goal of this effort is to compare the model to our topographic and hydrogeologic observations of berms (pre-)breaching on the coast of Monterey County, CA, that occur each winter, as large rain episodes hit the land. This specific case is a good way to test our model validity over time scales from 1 minute to 1 month. In our presentation, we will show preliminary results of the berms creep (pre-breaching) dynamics, using over-simplified equations for the groundwater flow. In the future, we intend to develop a Landlab component of our new creep function, which could be used with Groundwaterdupuitpercolator, a landlab component recently developed to model groundwater flow while modeling landscape dynamics (Litwin et al., 2020, 2022).
In the end, once this model is validated, it will allow us to model sediment creep at all time and rate scales, and better predict chances of, and monitor, sedimentary failures, such as breaching and landslides. Our new model for sediment creep fundamentally addresses our needs for better understanding and forecasting landscape response to changing climate patterns.
Houssais, M., C. Maldarelli, and J. F. Morris, “Athermal sediment creep triggered by porous flow,” Physical Review Fluids, vol. 6, no. 1, p. L012301, 2021.
Litwin, D. G., G. E. Tucker, K. R. Barnhart, and C. J. Harman, “Groundwaterdupuitpercolator: A landlab component for groundwater flow,” Journal of Open Source Software, vol. 5, no. 46, p. 1935, 2020.
Litwin, D. G., G. E. Tucker, K. R. Barnhart, and C. J. Harman, “Groundwater affects the geomorphic and hydrologic properties of coevolved landscapes,” Journal of Geophysical Research: Earth Surface, vol. 127, no. 1, p. e2021JF006239, 2022.
Roering, J. J., J. W. Kirchner, L. S. Sklar, and W. E. Dietrich, “Hillslope evolution by nonlinear creep and landsliding: An experimental study,” Geology, vol.
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Sediment delivery to low-lying coastal zones must keep pace with, if not exceed, the rate of sea level rise in order to maintain a positive surface elevation. Deltaic lowlands are vulnerable to both sea-level rise and changes in river discharge, but whether the floodplains and coastal areas will ultimately drown depends on a balance of aggradation, eustatic sea level rise and subsidence. The Ganges-Brahmaputra (G-B) Delta is an example of a densely populated coastal system that could be flooded by rapid sea level rise within the next century. Annual monsoonal river flooding and cyclonic storm surges are the principal mechanisms by which sediment is distributed across the G-B floodplain and coastal plain. Stratigraphic reconstructions show that sedimentation in the upper floodplain was more than doubled under the Early Holocene enhanced monsoonal regime, suggesting that the delta may withstand an increase in monsoonal intensity, flooding, and tropical cyclones that are currently predicted in ensemble Community Climate System Model scenarios.
In an effort to improve predictions of climatic forcing on aggradation rates in the G-B floodplain and lower delta, direct sedimentation measurements are paired with a series of model components coupled within the CSDMS Modeling Tool (CMT). A sediment flux model, a floodplain sedimentation model and a tidal-plain sedimentation model will be linked to explore the response of the G-B river system to a future sea-level rise and changes in river discharge. Model algorithms will be validated by sedimentation data collected in 2008 and 2012 from the tidal delta (The Sundarbans National Reserve mangrove forest) and the highly cultivated fluvial-dominated delta plain. Field data will also be compared to model outputs by constraining the spatial patterns of sedimentation across the delta front. In this talk, we present initial sedimentation results and discuss controls on heterogeneous patterns of deposition in the tidal versus fluvial dominated parts of the delta. Early results from individual model components will also be discussed in an attempt to integrate current understanding of the G-B System into a numerical modeling framework.
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Sediment dynamics on Arctic shelves can impact coastal geomorphology, habitat suitability, and biogeochemical cycling, and are expected to be sensitive to changes in sea ice extent. Variability in coastal erosion, for example, has been related to variations in waves due to changes in sea ice extent, as well as water temperature. Yet, it remains unclear how changes in sea ice extent will impact hydrodynamic and sediment transport conditions on the continental shelf. To analyze this, we are using a coupled hydrodynamic - sediment transport numerical model, the Regional Ocean Modeling System (ROMS) - Community Sediment Transport Modeling System (CSTMS). The model is implemented for the Alaskan Beaufort Sea shelf and currently accounts for winds, sea ice, offshore currents, rivers, waves, and multiple sediment classes. Ongoing work includes finalizing model inputs. The model is being run for the 2019 open water season when sea ice retreats 100 - 300 km offshore. Analysis will focus on spatial and temporal variations in current velocities, waves, bed shear stresses, and sediment fluxes. Preliminary results show that the time-averaged depth-averaged currents, and likely sediment fluxes, are directed eastward along the shelf. Additionally, the largest bed shear stresses occur near the coast and on the shelf-slope break. Future work includes additional analyses, as well as sensitivity tests to better understand how a lengthening open water season and changing weather conditions may influence shelf sediment dynamics. +
Sediment dynamics on Arctic shelves can impact coastal geomorphology, habitat suitability, and biogeochemical cycling, and are sensitive to changes in sea ice extent. Variability in coastal erosion, for example, has been related to variations in waves due to changes in sea ice extent, as well as water temperature. Yet, it remains unclear how changes in sea ice extent will impact hydrodynamic and sediment transport conditions on the continental shelf, motivating this study. To analyze this, we are using a coupled hydrodynamic-sediment transport numerical model, the Regional Ocean Modeling System (ROMS) - Community Sediment Transport Modeling System (CSTMS). The model is implemented for the Alaskan Beaufort Sea shelf and currently accounts for winds. Ongoing work includes accounting for waves, sea ice, and setting up open boundary conditions. In order to analyze variations in hydrodynamics and sediment transport, the model will be run for two open water seasons representing time periods where sea ice retreats 100-300 km offshore. Analysis will focus on spatial variations in current velocities, waves, and bed shear stresses, as well as how model estimates vary between the two time periods. Future work involves accounting for sediment transport in the model and performing sensitivity analyses to better understand how a lengthening open water season may influence the shelf sediment dynamics. +
Sediment transport is a universal phenomenon responsible for the self-organization of bedforms and dunes seen on the surfaces of many planetary bodies. The smallest of these patterns are wind, or impact ripples. Encoded in the sizes and propagation speeds of impact ripples is direct information about the local transport and environmental conditions: sediment fluxes, wind speeds, grain size, etc. However, to get at this information we must understand the processes that govern ripples dynamics. Because of the complexity of sediment transport, our current understanding of ripples is almost purely empirical, and the parameter space of the system has barely been explored.
To aid at the process of understanding impact ripple dynamics in arbitrary environments we turn to a discrete element model (DEM) of sediment transport. Simulated ripples sizes from the DEM quantitatively agree with wind-tunnel and field data and therefore the DEM can be used as an experimental tool to explore the state space of the system. Preliminary experiments suggest that ripple wavelengths scale with the average hoplength of eroded grains, but only above a threshold. Below this threshold wavelengths stagnate and ripples begin to propagate upwind. These “antiripples” have not previously been predicted or observed. Yet simulations suggest that they are persistent for many planetary conditions such as those on Venus and even Earth (for large enough grain sizes). We present additional findings for a range of environmental conditions found in our solar system and beyond, and thus map out a more complete space of possible states for ripple formation in the Universe. +
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Sedimentary delta formation varies over a wide range of time and space scales. Reduced-complexity models offer a worthwhile means of retaining key dynamics and phenomena in delta morphodynamics through employing approximate but physically reliable descriptions of governing transport equations. To that end, we developed a cellular rule-based model, using a “directed” random-walk to determine the flow field, coupled with empirically based sediment transport schemes, following an Exner equation combining bedload and suspended load. Preliminary results provide physically reasonable 3-dimensional topographical features, as well as dynamic processes like channel avulsions and bifurcations. Stratigraphy is also recorded. The flexibility of the modeling framework makes each building block to be updated separately, which will allow for the ready extension to include additional phenomena such as waves and tides. +
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Sequence is a modular 2D (i.e., profile) sequence stratigraphic model that is written in Python and implemented within the Landlab framework. Sequence represents time-averaged fluvial and marine sediment transport via differential equations. The modular code includes components to deal with sea level changes, sediment compaction, local or flexural isostasy, and tectonic subsidence and uplift. Development of the code was spurred by observations of repetitive stratigraphic sequences in western Turkey that are distorted by tectonics. +
Simulation models are explicit descriptions of the components and interactions of a system, made dynamic in software. In Coupled Human-Earth Systems Science, we most often employ simulation to conduct controlled experiments in which key socio-ecological parameters are varied, and changes to system-level dynamics are observed over time. An interesting emergent property of these kinds of experiments is that they produce a range of possible outcomes for any set of initial conditions. Thus, rather than use simulations to explain particular case studies from the past, they are better suited to examine the dynamics of ancient systems in a more general way. Model parameters need to be determined and model output needs to be validated, however. So, our simulations *do* need to be connected to empirical data; a useful model must be capable of producing the same *kinds* of patterns observed in the archaeological record (but not *only* these patterns). It is often difficult, however, to connect model output to real data. In this presentation I draw upon research and modeling techniques being developed by the Mediterranean Landscape Dynamics Project to explore ways of connecting the output of simulation models to the kinds of proxy records that we typically use to learn about the past, such as the stratigraphic record, human artifact densities, and phytolith and charcoal accumulation. +
Slip at the ice-bed interface (basal motion) dominates the flow of many glaciers, and it is uncertain whether this velocity component will increase or slow in a warmer world. Past results from an idealized flowline glacier model show that declining basal motion induces a two-phase response that initially accelerates glacier retreat in response to climate warming on a multidecadal timescale but lessens centennial-scale retreat and mass loss. In the present work, we utilize existing field-collected and remotely-sensed constraints on ice thickness, ice surface velocity, and the change in each of these terms to constrain the current rate of basal motion and its change over the past ~40 years. We focus our analysis on glaciers with well-constrained ice thickness, mass balance, and velocity records. Utilizing these constraints, we employ a simple flowline model to estimate the contribution of varying basal motion to observed changes in surface velocity across the study glaciers. We then estimate these glaciers’ retreat and thinning responses to changing velocity and compare these with the magnitudes expected from atmospheric warming, constrained by published point measurements, mass balance models, and snowline observations. These results will constrain the extent to which evolving ice dynamics have amplified or mitigated the response of global glaciers to climate change over past decades. Further, this knowledge will provide insight into the potential importance of varying basal motion on projections of future glacier change, with implications for global sea level rise as well as local water resource and ecosystem management. +
Slow-moving arctic soils commonly organize into striking large-scale spatial patterns called solifluction terraces and lobes. Though these features impact hillslope stability, carbon storage and release, and landscape response to climate change, no mechanistic explanation exists for their formation. Everyday fluids—such as paint dripping down walls—produce markedly similar fingering patterns resulting from competition between viscous and cohesive forces. Here we use a scaling analysis to show that soil cohesion and hydrostatic effects can lead to similar large-scale patterns in arctic soils. A large new dataset of high-resolution solifluction lobe spacing and morphology across Norway supports theoretical predictions and indicates a newly observed climatic control on solifluction dynamics and patterns. Our findings provide a quantitative explanation of a common pattern on Earth and other planets, illuminating the importance of cohesive forces in landscape dynamics. These patterns operate at length and time scales previously unrecognized, with implications toward understanding fluid-solid dynamics in particulate systems with complex rheology. +
Soil creeps imperceptibly downhill, but also fails catastrophically to create landslides. Despite the importance of these processes as hazards and in sculpting landscapes, there is no agreed upon model that captures the full range of behavior. Here we examine the granular origins of hillslope soil transport by Discrete Element Method simulations, and re-analysis of measurements in natural landscapes. We find creep for slopes below a critical gradient, where average particle velocity (sediment flux) increases exponentially with friction coefficient (gradient). At critical there is a continuous transition to a dense-granular flow rheology. Slow earthflows and landslides thus exhibit glassy dynamics characteristic of a wide range of disordered materials; they are described by a two-phase flux equation that emerges from grain-scale friction alone. This glassy model reproduces topographic profiles of natural hillslopes, showing its promise for predicting hillslope evolution over geologic timescales. +
Soil moisture state has a critical role on subsurface-land surface-atmosphere energy and water balance. Yet, there is still no consensus on how to initialize atmospheric-hydrologic models to improve the representation of soil moisture content. Lack of accurate observational soil moisture data is the root of this issue. Although there has been progress in providing remotely sensed soil moisture data (e.g., Soil Moisture Active Passive (SMAP) data), their resolution is not adequate for high-resolution simulations. As an alternative approach, many atmospheric-hydrological simulations use various spin-up periods prior to the start of their analysis to perturb and improve the low-resolution soil moisture with precipitation. It has been shown that such method can improve soil moisture distribution in some studies in comparison to observational data. However, starting simulations from earlier times can cause divergence from accurate initial atmospheric conditions, which were obtained from observational data when simulation reaches the analysis period of interest. Therefore, there is a tradeoff between starting several days or hours before the analysis period in accurate representation of atmospheric data versus soil moisture input. In this study, we evaluated the sensitivity of a high-resolution (150-m) Weather Research and Forecasting (WRF) model to initialization starting point. We ran five nested domains with 12150-, 4050-, 1350-, 450-, and 150-m resolutions to downscale NCEP North American Regional Reanalysis (NARR) to our domain of interest encompassing Baltimore-Washington metropolitan area. The five domains were run in three scenarios starting 4, 7, and 14 days before the analysis period. Land surface temperature (LST) output was compared to LandSat data to investigate the impact of initialization starting point on model’s LST predictability. Results indicate that while the three scenarios underperformed in prediction of the urban heat island, there was no significant difference among the three scenarios. We determined that one of WRF’s thermal roughness parameterizations, which improves LST simulation over nonurban areas, caused significant errors in LST prediction over urban areas. Further simulations and analysis are underway to improve urban LST prediction. The three case scenarios will be compared against LandSat again when urban LST prediction is improved.
Son alluvial fan system, a megafan situated at the foothills of Vindhyans, is governed by the endogenic and exogenic process operating in the Ganga foreland basin. The megafan is interspersed with a number of structural features in the bedrock overlain by quaternary alluvial cover viz., Munger Saharsa Ridge Fault (MSRF), East Patna fault (EPF), and West Patna fault (WPF), some other reported tectonic features. A number of studies have attempted to decipher the recorded signatures of these underlying bedrock structural features and related tectonoclimatic activities in in the form of geomorphic anomalies and sedimentological evidences. In this study, χ‐transform index and χ‐anomalies, in combination with stream channel sinuosity, channel steepness index (ksn), channel concavity index (θ), geomorphology, and field evidences, have been used to examine if these structural features be highlighted on the low relief megafan surface with bedrock-alluvial mixed to thick alluvial cover (upto 1000 m thick). Drainage basin divide (in)stability measured through across divide χ‐anomaly map which proven to be an important tool for quantification of basin and channel network geometry behaviour, has been found to highlight the areas with active structural activities around the reported bedrock structures in the experimental study. Geomorphology and field evidences corroborate the findings of this study. +
Source-to-sink (S2S) studies seek to explicitly link the denudation of continents with the building of basin stratigraphy in an effort to infer tectonic and climatic drivers of surface change. Quantitative models for S2S systems must incorporate geomorphic processes at both source and sink, yet more effort has been devoted to developing landscape evolution models in source terranes than equivalent models for sedimentation in marine basins. In particular, most marine sedimentation models use local linear diffusion approximations for sediment transport, which have been shown to yield reasonable stratigraphy in shallow marine environments but struggle to reproduce diagnostic features of deep marine deposits. The lack of model predictive power in deep marine environments precludes the full closure of S2S sediment budgets.
We present a model for marine sedimentation with two simple modifications allowing non-local sediment transport: 1) a mechanism for sediment bypass on steep topographic slopes, and 2) a parameter allowing long-distance transport over vanishingly gentle slopes. We use Bayesian inference techniques to constrain four model parameters against the stratigraphy of the Orange Basin in southern Africa. We compare modeled against observed stratigraphy over 130 Ma of margin evolution. Our best-fit simulations capture the broad structure of the observed record, and imply non-negligible roles for both non-local model elements: sediment bypass at steep slopes and long-distance runout over gentle slopes. Residual misfit between our best-fit simulations and the stratigraphic data indicate that additional components of transport dynamics—likely hemipelagic sedimentation, grain size variations, or ocean bottom currents—might be required to achieve the longest transport distances observed in the sedimentary record. Results suggest that full closure of Earth’s sediment mass balance for S2S studies requires moving beyond local diffusion approximations, even at the longest timescales. Relatively simple modifications to modeled transport dynamics can lead to better agreement between modeled and observed stratigraphy, and may enable improved inference of landscape perturbations from the stratigraphic record.
Stream channels that cross strike-slip faults play an essential role in the long-term landscape response. So far, numerical models of strike-slip faults have simulated fluvial erosion assuming purely detachment-limited conditions. The detachment-limited theory assumes that the erosion is controlled by material that is detached from the channel bed and is always transported by the flow. As an alternative, erosion in channels can be represented by the transport-limited theory, which assumes that sediment is always available but may or not be transportable depending on the flow capacity. Extreme environments such as the Atacama Desert in Northern Chile, are evidence of strike-slip faulting with channels covered by alluvial deposits, suggesting that the landscape is best represented by a combination of detachment-limited and transport-limited conditions. Based on the most recent strike-slip fault model we incorporate and couple the effect of the SPACE (stream power with alluvium conservation and entrainment) 1.0 Landlab component in Python. The SPACE component can freely transition between detachment-limited and transport-limited conditions offering a closer representation of what is observed in the natural world. The results of coupling SPACE with strike-slip faults models are contrasted against the models that apply only detachment-limited conditions, to identify the action of a layer of sediment in landscape modification under variable strike-slip fault conditions. The concluding remarks of this work contribute to testing the accuracy of simplifying channel erosion processes to the commonly used stream power equation in strike-slip fault settings. +
Stream discharge is often used to drive sediment transport models across channel networks. Because sediment transport is nonlinear, discharge arising from precipitation resolved at 1-hr resolution may simulate bedload differently than discharge arising from daily total precipitation distributed evenly over 24-hrs. In this study, we quantify the bias introduced into a network-scale bedload transport model due to this simplification in forcing. Specifically, we examine the difference between bedload transport capacity driven by 1- vs 24-hr precipitation derived stream hydrographs at channel network locations varying from lowland pool-riffle channels to upland colluvial channels in a watershed where snow accumulation and melt can affect runoff processes. Bedload transport error is expressed as the ratio of cumulative transport capacity driven by 1-h to the 24-h hyetographs. We find that, depending on channel network location, cumulative error can range from 10-20% to more than two orders of magnitude. Surprisingly, variation in flow rates due to differences in hillslope and channel runoff do not seem to dictate the network locations where the largest errors in predicted bedload transport capacity occur. Rather, spatial variability of the magnitude of the bankfull-excess shear stress and changes in runoff due to snow accumulation and melt exert the greatest influence. As bankfull-excess shear stress decreases in the upstream direction, the largest bedload transport capacity errors occur in upland channels. These findings have implications for flood-hazard and aquatic habitat models that rely on modeled sediment transport driven by coarse-temporal-resolution climate data. +
