Property:CSDMS meeting abstract
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Understanding gravel bed river morphology over decadal to centennial timescales is vital to making informed stream management and restoration decisions. Factors such as land use change and climate shifts over such timescales may drastically alter river evolution – with major implications for in-channel and riparian habitat. Given these longer timescales of influence, field-based studies may be unable to fully capture such morphologic shifts. Scenario-based morphodynamic modeling is emerging as a means of quantifying gravel bed river evolution, yet current models are unable to predict changes in stream morphology over the timescales in question and with adequate spatial resolution, a problem due largely to the computational overhead they require. Since the computational overhead required to drive sediment transport has hindered previous modeling efforts, field-based research suggests a potential improvement, in that sediment is often mobilized downstream with characteristic step-lengths. Here we introduce a morphodynamic model which drives sediment transport using a step-length based approach. Such a technique negates the need for frequent recalculation of sediment dynamics in the flow, and correspondingly reduces computational overhead. Upon application of this model to the River Feshie (UK), we observe that it accurately reproduces many bed morphologies observed during annual high-resolution topographic surveys. By employing step-length based sediment transport distributions, the formation and preservation of bed morphologies can be accurately predicted with less computational overhead than was available in previous morphodynamic models. Using this new model, a better understanding of gravel-bed river morphodynamics over longer-term timescales (decades to centuries) may aid in the management of gravel bed streams under shifting discharge and sediment regimes. +
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Understanding how channel geometry influences dynamic connectivity in river networks is crucial for predicting environmental flux transport. Here, we investigate the impact of channel link-lengths on the dynamic connectivity time (ΔT) that describes difference between time periods when network is connected by structural extent (DCs) and network connectivity based on total flux aggregation (DCT). We show that the observed exponential link-lengths distribution such that link-lengths decreases with increasing stream order impacts the ΔT. Additionally, these hierarchical variation in link lengths is more evident in humid channels compared to dry channels.
We explicitly analyze the role of this hierarchy in determining ΔT by comparing geometrically derived ΔT_geom (using actual link lengths) and with topologically derived ΔT_topo (assuming uniform link lengths), we find that ΔT_geom is consistently lower than ΔT_topo. The difference between ΔT_geom and ΔT_topo is more evident in humid basins compared to dry. Furthermore, when link lengths are randomized, ΔT_geom converges to ΔT_topo, highlighting the dominant influence of channel geometry on connectivity.
Our findings highlight that the hierarchical distribution of link lengths governs dynamic connectivity time, with humid channels exhibiting more efficient connectivity than dry channels and emphasize the significant role of channel geometry in flux aggregation and transport dynamics. +
Understanding how landscapes acquire their form is complicated by evolution across a large range of spatial and temporal scales. Disentangling causes of landscape evolution should carefully consider scale and scalings, but how best to do so? I summarise the work we have been doing to make use of observations, spectral analyses and forward and inverse modelling to address the following questions. Where and at what scales do fluvial landscapes acquire their physical and chemical properties? How can we use the geometries of landscapes and their compositions to recover information about driving and responsive processes? Demonstrations of how observations of landscape form and chemical concentrations can be combined with simple theory to identify where and how landscapes acquire their geometries and material provenance are given. Spectral analyses of landscape geometries are used to identify scales at which they acquire their form and scaling regimes. Consequently, it is possible to assess whether it is reasonable to ‘stitch together’ observations or theory used to understand geomorphic processes operating at small scales to determine how landscapes acquire their form. In short, that proposition is highly unlikely to be successful because of the existence of erosional ‘shockwaves’ and stochasticity. However, despite local (spatio-temporal) complexity, fluvial landscapes appear to possess emergent, deterministic, simplicity at scales > 100 km, such that processes operating at these scales (e.g. dynamic topography) are manifest in drainage networks with simple, self-similar, scalings (e.g. Brownian noise). The use of upscaling of simple physical models to generate appropriate scaling regimes and statistical insights into how fluvial landscapes acquire their form is explored. Finally, a demonstration of how statistical measures based on Optimal Transport theory can be used to identify optimal landscape evolution models is presented. Wasserstein distances are shown to have significant benefits over more widely used Euclidean measures of misfit, especially when local noise is prevalent.
Understanding sediment dynamics during storms and hurricanes is vital for predicting coastal morphodynamics and improving resilience strategies, especially for the Texas–Louisiana coast.
This study presents preliminary results from an integrated hydrodynamic-sediment transport model of Galveston Bay during Hurricane Harvey. To capture the complex interplay of different hydrological forces, the hydrodynamic model incorporates the combined impacts of wind, precipitation, river, wave, tide, and current. A three-dimensional sediment transport model with a 100-m resolution is developed in the Regional Ocean Modeling System (ROMS) for Galveston Bay. The open boundary conditions are generated from ROMS model (100m) and river discharges of Buffalo Bayou and San Jacinto River will be derived from WRF-Hydro model. The bay bottom sediment input parameters are derived from the Texas Sediment Geodatabase (TxSed), which includes a comprehensive inventory of sediment properties, ensuring simulations with an enhanced level of accuracy and regional specificity. For model modification, river discharge data from the United States Geological Survey (USGS) and/or a WRF-Hydro model will be employed to calibrate and adjust the hydrodynamic model. This study will eventually provide open boundaries and initial sediment conditions for a higher resolution (20m) bayou model focusing on Buffalo Bayou and other rivers feeding into Galveston Bay and will contribute to the development of a detailed river-estuary-ocean continuum model. The outcomes of this research are anticipated to inform future coastal management and resilience planning against storm-induced sediment and contaminant fluxes. +
Understanding the factors that control lateral erosion rates in bedrock channels is a frontier in geomorphology. Lateral erosion rates and the evolution of wide bedrock valleys are linked to bedrock lithology, sediment supply in the stream, and shear stress exerted on channel walls. I use a newly-developed lateral erosion component in the Landlab modeling framework to explore how model results compare with recently published field examples of downstream sweep erosion as a mechanism for gorge eradication and bedrock valley widening. The lateral erosion component dictates that lateral erosion rate is proportional to shear stress exerted on the channel walls in a bend in the river; therefore sharp bends with a smaller radius of curvature will produce faster lateral erosion. Cook et al. (2014) identified a similar mechanism they call downstream sweep erosion (DSE). They suggest that bedrock gorges can be rapidly eroded by DSE when a wide flood plain with a laterally mobile stream exists upstream of the gorge, requiring a sharp bend in the channel to enter the gorge. I set up the model domain to recreate conditions of a low relief area with a mobile channel in the upper part of the model domain and a narrow, high relief gorge in the downstream end of the model domain. I ran modeling experiments under a range of water flux and sediment mobility conditions. The model results show gorge widening that propagates downstream as described by Cook et al. (2014) and preferential erosion of blocks that protrude into the channel. The enhanced lateral erosion at channel bends and the resulting downstream sweep erosion emerge naturally from the models, matching observations in many field areas. Together this suggests that channel curvature is of fundamental importance to lateral erosion rates in bedrock channels. +
Understanding the response of coastal barrier systems to sea level rise is a crucial societal need. Despite the problem having been studied extensively, major knowledge gaps remain. For example, neither the sedimentary record nor existing numerical models have been conclusive in explaining the formation of barrier islands. Here I present a comprehensive 2D model that seamlessly couples cross-shore and along-shore transport, tidal transport, storm surges, and wind waves, and use it to simulate an idealized passive margin during the last 7,000 years. In the early Holocene, when sea level was rising ~20 mm/yr, shoals and ephemeral barrier islands formed, periodically drowned, and then formed again at a landward location. Shoal emergence was triggered by the disequilibrium of the recently submerged shelf, especially for large waves and mild shelf slopes. About 5000 years ago, as sea level rise slowed down to ~1 mm/yr, barriers stabilized and even prograded seaward. The combination of excess sediment in the nearshore and storm surges allowed barriers to accrete above mean high water. When barriers eventually equilibrated to the new sea level rise rate and started to retreat, their retreat rate was highly variable in space and time due to autogenic processes such as inlet formation and backbarrier channel interception. This variability also included multi-decadal periods of localized progradation. Both lag dynamics and autogenic processes confound the relationship between barrier retreat and sea level rise rate. +
Understanding the sensitivities of preserved environmental signals to erosional and transport processes within the sediment generation portion of landscapes is vital in constraining uncertainties within provenance analysis. Here our focus is on populations of detrital zircon U-Pb ages as one of the most ubiquitous sediment provenance methods. Many studies often assume uniform parameters upstream of the sampling site, potentially overlooking variations in erosion rates, zircon size and zircon fertility across landscapes. To tease these uncertainties out, we model synthetic landscapes along with their expected provenance evolution.
Employing the Concentration Tracker component, we systematically manipulate erodibility and zircon fertility within synthetic landscapes to simulate sediment provenance evolution and incorporate zircon concentration into a statistical analysis comparing a null hypothesis of an area-dependent contribution to fractions dependent on mass and zircon abundance. While these scenarios do not necessarily reflect “real” landscapes, we use these simple experiments to understand basic controls on the magnitude of potential biases imparted to the simulated detrital zircon U-Pb datasets.
By exploring these potential biases, we provide valuable insights into the uncertainties inherent in provenance analysis and thus their utility and fidelity in reconstructing histories of past landscape evolution. Ultimately, this research contributes to refining the methodologies used in detrital zircon provenance analysis and enriches our understanding of the processes shaping sedimentary records. +
Understanding trends in water table dynamics is critical for closing the global water budget and for water resources management and environmental sustainability. Continental-scale hydrological simulations typically assume that the water table is at steady-state, despite the fact that this is unlikely to be true under changing climate. Here, we present monthly water table fields for the year 2020 across North America based on a simulation using the Water Table Model (WTM). To obtain these, we initialised the WTM using a transiently simulated water table from 500 years before present, and performed a model spin-up to obtain our monthly temporal resolution. The WTM integrates climate variables, topography, and hydrogeological characteristics to simulate depth to the water table, including groundwater and lakes. Our results offer insights into spatial and temporal patterns of water table response to seasonal climatic conditions. Results indicate significant regional variations in water table fluctuations driven by seasonal precipitation and evapotranspiration. This study shows a lag time of approximately 3 to 4 months between measured changes in climate variables and the corresponding response in the water table level. Our study emphasizes the need for targeted, regional management practices to mitigate potential adverse impacts and to optimize water resources under climatic changing conditions. +
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Urbanization and global climate change will severely stress our water resources. One potential unforeseen consequence of these stressors, which is neglected in channel evolution models, is accelerated stream channel erosion due to change in stream water temperature, pH and salinity which affect the surface potential and hence stability of soil colloids. Summer thunderstorms in urban watersheds can increase stream temperature >7 °C and the impact of global warming on average stream temperature is already evident in some stream systems. Initial estimates indicate a 2 °C rise in stream temperature could increase erosion by 30%. Urbanization has significant effects on the pH and salinity of stormwater runoff and as a result on the water quality of headwater streams. Channel erosion and the resulting sediment pollution threaten the sustainability of water resources and urban infrastructure. The goal of this research is to assess the impact of changes in stream water temperature, pH and salinity on stream channel erosion rates and to explore changes in the electrical surface potential of clay colloids as a potential soil stability mechanism. This exploratory research utilizes two reference clays with different permanent surface charges: montmorillonite, and vermiculite. Samples will be eroded in a recirculating sediment flume to determine soil critical shear stress and erodibility. Three water temperatures (12 °C, 20 °C, 27 °C), two pH (5 and 7), and two salinity levels (5 and 50 mg/l NaCl) will be analyzed. Three replicates of each treatment will be conducted for each clay. Additionally, the zeta potential of the clays will be determined under each condition. Research has demonstrated that variations in zeta potential affect liquid limit and shear stress of soil colloids. Results of this research could lead to a reassessment of stream channel stability modelling in urban watersheds and a paradigm shift in urban stormwater management. +
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Variation in bedrock erodibility along a river profile gives rise to differences in vertical incision rate and influences sediment characteristics such as clast lithology, coarse sediment generation rate, and grain size. In rivers whose beds are eroded, in part, through sediment abrasion, these streamwise sediment dynamics are part of a crucial feedback that sets the dominant fluvial erosion process and determines whether a river exhibits transport-limited or detachment-limited behavior. The role that sediment plays in setting the shape of a river profile is of particular interest in the case of a river’s transient response to external forcing.
Here we present a model that explores river profile evolution in a setting with streamwise bedrock variability. Our model combines theory for five interrelated processes: bedload sediment transport in equilibrium gravel-bed channels, channel width adjustment to flow and sediment characteristics, abrasion of bedrock by mobile sediment, plucking of bedrock, and progressive loss of gravel-sized sediment due to grain abrasion. We envision a generic “range-foreland” system that consists of erosion-resistant, crystalline rocks in the upstream reaches, juxtaposed with softer, more erodible rocks downstream. In this setting, coarse sediment generation is confined to the upstream part of the fluvial system. As the sediment is transported downstream, it creates an alluvial blanket across the soft, fine-grained unit. Bedrock erosion is modulated by the thickness of the alluvial layer.
We use the model to explore the range of transient forms that can occur in such a setting in response to changes in tectonic or climatic regime. We pay special attention to the conditions under which the upstream gravel source either increases the downstream fluvial gradient (by partially shielding the underlying material from incision) or decreases the gradient (by providing tools that amplify the efficiency of abrasion). We also examine the conditions under which erosion is concentrated at the downstream-most reaches of the river profile, versus at the lithologic boundary.
While our work takes its motivation from the Southern Rocky Mountains and High Plains of North America, the model is applicable generally to settings in which a bedrock-incising river traverses multiple lithologies. This work aims to improve our interpretations of the history of river profiles in lithologically heterogeneous environments and inform our understanding of landscape evolution in these settings.
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Very few in-situ measurements of runoff from the Greenland Ice Sheet (GrIS) exist, though melt water runoff from the GrIS is important to global eustatic sea level, ocean salinity, thermohaline circulation and sea ice dynamics and the transport of sediment and nutrients to fjords and the ocean. We continue to develop the use of NASA MODIS imagery to gauge river discharge of sediment and freshwater into fjords hydrologically linked to the GrIS.
Essential to this remote sensing proxy are accurate models of fjord and plume dynamics. We compare Hutton and Syvitski’s PLUME model results to in situ oceanographic and sedimentological measurements of Greenlandic river sediment/freshwater plumes towards the end goal of exploring the suitability of inverting the PLUME model and combining it with remotely sensed MODIS imagery to estimate river discharge.
Within our study fjords a range of estuarine conditions present a robust test for our plume method, and in turn conditions present a range of complexities to test the suitability of inverting the PLUME model. Fjord conditions range from ocean to river dominated. Some plumes mix very quickly from fresh to near full ocean salinities (22 – 28 PSU). Other plumes maintain low salinities (0 – 10 PSU) to depths exceeding six meters and down fjord over 65 km. Fjord geometries, tidal range, and other conditions impact sediment plume dynamics. These dynamics must be accounted for to link plume imagery to discharge into fjords. +
WBMsed is a spatially and temporally explicit global riverine model predicting suspended and bedload sediment fluxes based on the WBMplus water balance and transport model (part of the FrAMES biogeochemical modeling framework). The model incorporates climate input forcings to calculate surface and subsurface runoff for each grid cell. The prediction of fluvial sediment fluxes is highly dependent on how well its transport medium, riverine water, is simulated. Our analyses indicate that average water discharges are well predicted by the WBMplus model. However, daily freshwater predictions are often over or under predicted by up to an order of magnitude, significantly affecting the accuracy of sediment flux simulation capabilities of WBMsed and indicating that certain hydrological processes are less captured within the model. One of these processes could be temporal storage of water discharge on floodplains, dampening the water hydrograph significantly. In WBMsedv2.0 we incorporate a floodplain reservoir component to improve daily water discharge simulations. The Floodplain reservoir component is used in WBMsedv2.0 to store overbank water flow which are refurbished back to the river once its water level has subsided. Here we compare two methods for determining overbank flow: (1) the log-Pearson III (flood frequency analysis) 5-year maximum discharge recurrence and (2) an empirical relationship between mean river discharge and river width and bank height. +
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Wave Boundary Layer (WBL) plays an important role in sediment offshore transport and material exchange between seafloor and overlying water, especially during strong wave events when fluid mud (concentration > 10g/L) is formed. We incorporated wave-supported fluid mud (WSFM) processes into the Community Sediment Model System (CSTMS) on the platform of the Coupled Ocean-Atmosphere-Wave-and-Sediment Transport Modeling system (COAWST). A new WBL was introduced between the bottom sigma layer (water) and top sediment bed layer, which accounted for the key sediment exchange processes (e.g., resuspension, vertical settling, diffusion, and horizontal advection) at the water-WBL and WBL-sediment bed boundaries. To test its robustness, we adapted the updated model (CSTMS+WBL) to the Atchafalaya Shelf in the northern Gulf of Mexico and successfully reproduced the sediment dynamics in March 2008, during which active WSFM processes were reported. The CSTMS+WBL model simulated a lutocline between the WBL and overlaid water as well as a stronger onshore/offshore erosion/deposition. Sensitivity tests of free settling, flocculation and hindered settling effects suggested sediments were transported further offshore due to reduced settling velocity in the WBL once fluid mud was formed. +
Wave- and current-supported turbidity currents are new class of turbidity flows that has been discovered over the last three decades. Its significance as a carrying agent of fine sediments over low-gradient shelves has been recognized with growing evidence. Due to their vertical length scales, which are on the order of decimeters, understanding the full range of mechanisms that are responsible for and/or affect these currents cannot proceed without turbulence-resolving numerical simulations and/or high-resolution sensor deployment in a laboratory/field experiments. In this talk the culmination of two-phase, turbulence-resolving simulations, i.e. Direct Numerical Simulations (DNS), of wave- and alongshore current-supported fine sediment turbidity currents across mild bathymetric slopes will be presented. Simulation results show that such turbidity currents follow a logarithmic velocity profile across the shelf whose parameters depend on the sediment concentration, across-shore bathymetric slope, and Reynolds number while it is independent of the settling velocity of the sediments. The numerical simulations also provide significant insights on modelling these turbidities in a regional-scale model which can be used to estimate the location of mud depocenters and the dynamics of submarine geomorphology such as in the clinoform development at the continental margin. +
Wave-resolving, Boussinesq nearshore wave models such as FUNWAVE-TVD are capable of providing nonlinear hydrodynamic outputs that wave-averaged models cannot directly provide. Understanding such nonlinear nearshore processes is crucial to deepen our understanding of complex coastal processes, such as morphodynamics and sediment transport. However, the computational cost of wave-resolving models has made them prohibitive to use for many such applications.
To bridge this gap, a machine learning model trained on thousands of FUNWAVE-TVD models using synthetic, experimental, and field data was developed to estimate nonlinear nearshore wave statistics. Given boundary conditions and forcing terms, the model can “learn” the statistics associated with nonlinear nearshore processes. Such a model is broadly useful for other coastal models that rely on accurate measures of these nonlinear wave properties to parameterize other processes of interest. +
We are advancing dynamic multi-hazard risk assessment (MHRA) methods for human ecology, using the Kutupalong Rohingya Refugee Camp (KTP) in southeastern Bangladesh as a case study. KTP, home to over 1.1 million refugees within a 15 km² area, represents one of the world’s most densely populated and hazard-prone humanitarian settlements. This research investigates hydro-meteorological risks—primarily shallow landslides and flash floods—before and after refugee settlement, with a focus on landscape changes driven by both anthropogenic and natural processes. We formulated two core hypotheses. The first posits that dynamic hazard modeling, incorporating both geological and anthropogenic factors, more accurately captures the cascading effects of landslides and flash floods than traditional static models. The second hypothesis suggests that hydro-meteorological risk at KRC has declined due to the incremental implementation of slope stabilization and restoration measures.
We began with a landslide hazard assessment using a sloped unit (SU)-based approach, building upon previous grid-based models employed at KTP. Our dynamic, time-lapse assessment, which examines pre- and post-refugee influx scenarios, identifies slope units with increasing, decreasing, or unchanged susceptibility over time. A Generalized Additive Model (GAM) applied at the SU scale outperforms conventional machine learning (ML) methods, providing a robust framework for surface hazard modeling. In parallel, we evaluated landscape degradation and recovery through above-ground biomass (AGB) estimation using Sentinel-2A imagery, NASA GEDI LiDAR, and ESA Biomass products. We estimated AGB for 2017 (pre-influx), 2019 (early restoration), and 2023 (ongoing recovery) using Random Forest, SVM, and XGBoost regression models. This integration of remote sensing and ML demonstrates the utility of multi-source data for tracking dynamic land-use change.
Further fieldwork is required to collect more geotechnical soil samples and detailed information on the geometry of the failure plane in selected large landslides. This will enable us to assess the interaction between slope-forming materials and the underlying bedrock interface, as well as model the velocity and volume of sliding materials in the form of run-out. Like landslides, we will dynamically simulate flash flood inundation to extract critical hydrodynamic parameters, including peak flow height, flow velocity, discharge, and flood arrival time, particularly for the 2017 and 2021 monsoon events at KTP. Multi-temporal DEM generation and land cover mapping will be the key in this regard.
A key contribution of this research lies in the integration of landslide and flash flood risk data to assess their cascading impacts on human ecology. This integrated risk information will be combined with engineering measures and economic modeling to assess the effectiveness and feasibility of the existing mitigation measures. Risk estimation will be conducted under changing hazard scenarios, comparing conditions immediately before the major refugee influx (2018 and earlier) with those in the post-intervention period (2022–2023). A similar modeling framework will also be applied to explore potential future hazard scenarios under evolving landscape and climate conditions.
We develop a hydroclimatological approach to modeling regional shallow landslide initiation by integrating spatial and temporal dimensions of parameter uncertainty to estimate an annual probability of landslide initiation based on Monte Carlo simulations. The physically based model couples the infinite-slope stability model with a steady-state subsurface flow representation and operates in a digital elevation model. Spatially distributed gridded data for soil properties and vegetation classification are used for parameter estimation of probability distributions that characterize model input uncertainty. Hydrologic forcing to the model is through annual maximum daily recharge to subsurface flow obtained from a macroscale hydrologic model. We demonstrate the model in a steep mountainous region in northern Washington, USA, over 2700 km2. The influence of soil depth on the probability of landslide initiation is investigated through comparisons among model output produced using three different soil depth scenarios reflecting the uncertainty of soil depth and its potential long-term variability. We found elevation-dependent patterns in probability of landslide initiation that showed the stabilizing effects of forests at low elevations, an increased landslide probability with forest decline at midelevations (1400 to 2400 m), and soil limitation and steep topographic controls at high alpine elevations and in post-glacial landscapes. These dominant controls manifest themselves in a bimodal distribution of spatial annual landslide probability. Model testing with limited observations revealed similarly moderate model confidence for the three hazard maps, suggesting suitable use as relative hazard products. The model is available as a component in Landlab, an open-source, Python-based landscape earth systems modeling environment, and is designed to be easily reproduced utilizing HydroShare cyberinfrastructure. +
We have developed a simple approach to modeling how coastal marshes respond to changes in the rate of sea level rise (SLR) and sediment concentration. This approach, rooted in detailed numerical modeling and in field and remotely sensed observations, produces plan view distributions of elevations and the densities of multiple marsh species and bare soil. This modelling approach can be applied to specific marshes, to forecast marsh configurations for any combination of SLR rate and suspended sediment concentration in a channel network.
The approach involves techniques to detect the spatial distributions of fractional cover and biomass densities of multiple marsh species from satellite observations. These techniques were developed using a combination of field observations and drone and airborne lidar and multispectral data from the East Coast of the United States and the Venice Lagoon, and can be applied to any coastal environment with similar mixes of vegetation types. Biomass density can be treated as a function of elevation, representing the realized niches of observed vegetation species, or mixtures of species.
The approach also involves modeling demonstrating that, within marsh basins, tidal current velocities and rates of inorganic sediment deposition do not depend on vegetation properties. Given this simplification, and the relationship between biomass density and elevation (realized niches), solving for equilibrium depths and biomass densities as a function of distance from the nearest channel becomes straightforward (Figure 1).
The rate of change of depth D (below high-water level) is given by:
∂D/∂t = R - A_inorg - A_org
where R is the rate of SLR, A_inorg and A_org are the rates of accretion of inorganic and organic sediment, respectively. A_inorg is equal to DC, where C is sediment concentration. In Figure 1, equilibrium depths (∂D/∂t=0; R - A_inorg = A_org) are graphically determined.
Acknowledgments
Supported by the US NSF Geomorphology and Land Use Dynamics program (2016068), and AA, MM, and SS were also supported by the RETURN Extended Partnership and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005).
We have implemented algorithms for simulating fine and cohesive sediment in the Regional Ocean Modeling System (ROMS). These include: floc dynamics (aggregation and disaggregation in the water column); changes in floc characteristics in the seabed; erosion and deposition of cohesive and mixed (cohesive and non-cohesive) sediment; and biodiffusive mixing of bed sediment. These routines supplement existing non-cohesive sediment routines in ROMS, thereby increasing the model ability to represent fine-grained environments where aggregation, disaggregation, and consolidation may be important. Additionally, we describe changes to the sediment bed layering scheme that improve the fidelity of the modeled stratigraphic record. This poster provides examples of these modules implemented in idealized test cases and a real-world application. +
A
We present a method that reconstructs daily snow thermal conductivities using air and ground temperature measurements. The method recovers the daily snow thermal conductivities over the entire snow season. By using reconstructed snow conductivities we can improve modeling of ground surface temperatures. Simulation of the ground surface temperatures by using changing in time snow thermal conductivities could potentially reduce ground temperature modeling uncertainty.
The developed method was applied to four permafrost observation stations in Alaska. Reconstructed snow thermal conductivity time series for the interior stations in Alaska revealed low conductivity values that reach their maximum towards the end of the snow season, while the northern stations showed high conductivity values that reach their maximum towards the middle of the snow season. The differences in snow conductivities between interior and northern stations are most likely due to wind compaction which is more pronounced in the Northern Arctic lowlands of Alaska. +
