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A list of all pages that have property "Extended model description" with value "Landlab component that implements a 1 and 2D lithospheric flexure model.". Since there have been only a few results, also nearby values are displayed.

Showing below up to 26 results starting with #1.

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  • Model:TransportLengthHillslopeDiffuser  + (Hillslope diffusion component in the styleHillslope diffusion component in the style of Carretier et al. (2016, ESurf), and Davy and Lague (2009).</br></br>Works on regular raster-type grid (RasterModelGrid, dx=dy). To be coupled with FlowDirectorSteepest for the calculation of steepest slope at each timestep.lation of steepest slope at each timestep.)
  • Model:TaylorNonLinearDiffuser  + (Hillslope evolution using a Taylor Series Hillslope evolution using a Taylor Series expansion of the Andrews-Bucknam formulation of nonlinear hillslope flux derived following following Ganti et al., 2012. The flux is given as:</br></br>qs = KS ( 1 + (S/Sc)**2 + (S / Sc)**4 + .. + (S / Sc)**2(n - 1) )</br></br>where K is is the diffusivity, S is the slope, Sc is the critical slope, and n is the number of terms. The default behavior uses two terms to produce a flux law as described by Equation 6 of Ganti et al., (2012).bed by Equation 6 of Ganti et al., (2012).)
  • Model:DepthDependentTaylorDiffuser  + (Hillslope sediment flux uses a Taylor SeriHillslope sediment flux uses a Taylor Series expansion of the Andrews-Bucknam formulation of nonlinear hillslope flux derived following following Ganti et al., 2012 with a depth dependent component inspired Johnstone and Hilley (2014). The flux :math:`q_s` is given as:</br>q_s = DSH^* ( 1 + (S/S_c)^2 + (S/Sc_)^4 + .. + (S/S_c)^2(n-1) ) (1.0 - exp( H / H^*)</br></br>where :math:`D` is is the diffusivity, :math:`S` is the slope, :math:`S_c` is the critical slope, :math:`n` is the number of terms, :math:`H` is the soil depth on links, and :math:`H^*` is the soil transport decay depth. The default behavior uses two terms to produce a slope dependence as described by Equation 6 of Ganti et al., (2012).This component will ignore soil thickness located at non-core nodes. soil thickness located at non-core nodes.)
  • Model:HydroCNHS  + (HydroCNHS is an open-source Python package supporting four Application Programming Interfaces (APIs) that enable users to integrate their human decision models, which can be programmed with the agent-based modeling concept, into the HydroCNHS.)
  • Model:HydroPy  + (HydroPy model is a revised version of an eHydroPy model is a revised version of an established global hydrological model (GHM), the Max Planck Institute for Meteorology's Hydrology Model (MPI-HM). Being rewritten in Python, the HydroPy model requires much less effort in maintenance and new processes can be easily implemented.d new processes can be easily implemented.)
  • Model:HydroTrend  + (HydroTrend v.3.0 is a climate-driven hydrological water balance and transport model that simulates water discharge and sediment load at a river outlet.)
  • Model:HSPF  + (Hydrological Simulation Program - FORTRAN Hydrological Simulation Program - FORTRAN (HSPF) is a comprehensive package</br>for simulation of watershed hydrology and water quality for both conventional</br>and toxic organic pollutants (1,2). This model can simulate the hydrologic,</br>and associated water quality, processes on pervious and impervious land</br>surfaces and in streams and well-mixed impoundments. HSPF incorporates the</br>watershed-scale ARM and NPS models into a basin-scale analysis framework that</br>includes fate and transport in one-dimensional stream channels. It is the</br>only comprehensive model of watershed hydrology and water quality that allows</br>the integrated simulation of land and soil contaminant runoff processes with</br>in-stream hydraulic and sediment-chemical interactions.</br></br>The result of this simulation is a time history of the runoff flow rate,</br>sediment load, and nutrient and pesticide concentrations, along with a time</br>history of water quantity and quality at any point in a watershed. HSPF</br>simulates three sediment types (sand, silt, and clay) in addition to a single</br>organic chemical and transformation products of that chemical. The transfer</br>and reaction processes included are hydrolysis, oxidation, photolysis,</br>biodegradation, volatilization, and sorption. Sorption is modeled as a</br>first-order kinetic process in which the user must specify a desorption rate</br>and an equilibrium partition coefficient for each of the three solids types.</br></br>Resuspension and settling of silts and clays (cohesive solids) are defined in</br>terms of shear stress at the sediment water interface. The capacity of the</br>system to transport sand at a particular flow is calculated and resuspension</br>or settling is defined by the difference between the sand in suspension and</br>the transport capacity. Calibration of the model requires data for each of</br>the three solids types. Benthic exchange is modeled as sorption/desorption</br>and deposition/scour with surficial benthic sediments. Underlying sediment</br>and pore water are not modeled.g sediment and pore water are not modeled.)
  • Model:WACCM-EE  + (I am developing a GCM based on NCAR's WACCI am developing a GCM based on NCAR's WACCM model to studied the climate of the ancient Earth. WACCM has been linked with a microphysical model (CARMA). Some important issues to be examined are the climate of the ancient Earth in light of the faint young Sun, reducing chemistry of the early atmosphere, and the production and radiative forcing of Titan-like photochemical hazes that likely enshrouded the Earth at this time. likely enshrouded the Earth at this time.)
  • Model:CAM-CARMA  + (I am developing a recent adaptation of CAM 3.0 that has been converted to Titan by Friedson et al. at JPL. I am adding the aerosol microphysics from CARMA.)
  • Model:IDA  + (IDA formulates the task of determing the dIDA formulates the task of determing the drainage area, given flow directions, as a system of implicit equations. This allows the use of iterative solvers, which have the advantages of being parallelizable on distributed memory systems and widely available through libraries such as PETSc.</br></br>Using the open source PETSc library (which must be downloaded and installed separately), IDA permits large landscapes to be divided among processors, reducing total runtime and memory requirements per processor.</br></br>It is possible to reduce run time with the use of an initial guess of the drainage area. This can either be provided as a file, or use a serial algorithm on each processor to correctly determine the drainage area for the cells that do not receive flow from outside the processor's domain.</br></br>The hybrid IDA method, which is enabled with the -onlycrossborder option, uses a serial algorithm to solve for local drainage on each processor, and then only uses the parallel iterative solver to incorporate flow between processor domains. This generally results in a significant reduction in total runtime.</br></br>Currently only D8 flow directions are supported. Inputs and outputs are raw binary files.. Inputs and outputs are raw binary files.)
  • Model:ISSM  + (ISSM is the result of a collaboration betwISSM is the result of a collaboration between the Jet Propulsion Laboratory and University of California at Irvine. Its purpose is to tackle the challenge of modeling the evolution of the polar ice caps in Greenland and Antarctica.</br>ISSM is open source and is funded by the NASA Cryosphere, GRACE Science Team, ICESat Research, ICESat-2 Research, NASA Sea-Level Change Team (N-SLCT), IDS (Interdisciplinary Research in Earth Science), ESI (Earth Surface and Interior), and MAP (Modeling Analysis and Prediction) programs, JPL R&TD (Research, Technology and Development) and the National Science Foundationvelopment) and the National Science Foundation)
  • Model:IceFlow  + (IceFlow simulates ice dynamics by solving IceFlow simulates ice dynamics by solving equations for internal deformation and simplified basal sliding in glacial systems. It is designed for computational efficiency by using the shallow ice approximation for driving stress, which it solves alongside basal sliding using a semi-implicit direct solver. IceFlow is integrated with GRASS GIS to automatically generate input grids from a geospatial database.te input grids from a geospatial database.)
  • Model:Icepack  + (Icepack is a Python package for simulatingIcepack is a Python package for simulating the flow of glaciers and ice sheets, as well as for solving glaciological data assimilation problems. The main goal for icepack is to produce a tool that researchers and students can learn to use quickly and easily, whether or not they are experts in high-performance computing. Icepack is built on the finite element modeling library firedrake, which implements the domain-specific language UFL for the specification of PDEs.anguage UFL for the specification of PDEs.)
  • Model:ChannelProfiler  + (In order to extract channel networks, the In order to extract channel networks, the flow connectivity across the grid must already be identified. This is typically done with the FlowAccumulator component. However, this component does not require that the FlowAccumulator was used. Instead it expects that the following at-node grid fields will be present:<br></br>'flow__receiver_node'<br></br>'flow__link_to_receiver_node'<br></br>The ChannelProfiler can work on grids that have used route-to-one or route-to-multiple flow directing. have used route-to-one or route-to-multiple flow directing.)
  • Model:HIM  + (It is a C-grid, isopycnal coordinate, primitive equation model, simulating the ocean by numerically solving the Boussinesq primitive equations in isopycnal vertical coordinates and general orthogonal horizontal coordinates.)
  • Model:WOFOST  + (It is a mechanistic model that explains crIt is a mechanistic model that explains crop growth on the basis of the underlying processes, such as photosynthesis, respiration and how these processes are influenced by environmental conditions. </br></br>With WOFOST, you can calculate attainable crop production, biomass, water use, etc. for a location given knowledge about soil type, crop type, weather data and crop management factors (e.g. sowing date). WOFOST has been used by many researchers over the World and has been applied for many crops over a large range of climatic and management conditions. WOFOST is one of the key components of the European MARS crop yield forecasting system. In the Global Yield Gap Atlas (GYGA) WOFOST is used to estimate the untapped crop production potential on existing farmland based on current climate and available soil and water resources.te and available soil and water resources.)
  • Model:FUNDY  + (It solves the linearized shallow water equations forced by tidal or other barotropic boundary conditions, wind or a density gradient using linear finite elements.)
  • Model:ACADIA  + (It tracks any number of different depth-averaged transport variables and is usually used in conjunction with QUODDY simulations.)
  • Model:LEMming  + (LEMming tracks regolith and sediment fluxeLEMming tracks regolith and sediment fluxes, including bedrock erosion by streams and rockfall from steep slopes. Initial landscape form and stratigraphic structure are prescribed. Model grid cells with slope angles above a threshold, and which correspond to the appropriate rock type, are designated as candidate sources for rockfall. Rockfall erosion of the cliffband is simulated by instantaneously reducing the height of a randomly chosen grid cell that is susceptible to failure to that of its nearest downhill neighbor among the eight cells bordering it. This volume of rockfall debris is distributed across the landscape below this cell according to rules that weight the likelihood of each downhill cell to retain rockfall debris. The weighting is based on local conditions such as slope angle, topographic curvature, and distance and direction from the rockfall source. Rockfall debris and the bedrock types are each differentiated by the rate at which they weather to regolith and by their fluvial erodibility. Regolith is moved according to transport rules mimicking hillslope processes (dependent on local slope angle), and bedload and suspended load transport (based on stream power). Regolith and sediment transport are limited by available material; bedrock incision occurs (also based on stream power) where bare rock is exposed. stream power) where bare rock is exposed.)
  • Model:LEMming2  + (LEMming2 is a 2D, finite-difference landscLEMming2 is a 2D, finite-difference landscape evolution model that simulates the retreat of hard-capped cliffs. It implements common unit-stream-power and linear/nonlinear-diffusion erosion equations on a 2D regular grid. Arbitrary stratigraphy may be defined. Cliff retreat is facilitated by a cellular algorithm, and rockfall debris is distributed and redistributed to the angle of repose. It is a standalone model written in Matlab with some C components.</br></br>This repo contains the code used and described by Ward (2019) Lithosphere: "Dip, layer spacing, and incision rate controls on the formation of strike valleys, cuestas, and cliffbands in heterogeneous stratigraphy". Given the inputs in that paper it should generate the same results.paper it should generate the same results.)
  • Model:LISFLOOD  + (LISFLOOD is a spatially distributed, semi-LISFLOOD is a spatially distributed, semi-physical hydrological rainfall-runoff model that has been developed by the Joint Research Centre (JRC) of the European Commission in late 90ies. Since then LISFLOOD has been applied to a wide range of applications such as all kind of water resources assessments looking at e.g. the effects of climate and land-use change as well as river regulation measures. Its most prominent application is probably within the European Flood Awareness System (EFAS) operated under Copernicus Emergency Management System (EMS).ernicus Emergency Management System (EMS).)
  • Model:LOADEST  + (LOAD ESTimator (LOADEST) is a FORTRAN progLOAD ESTimator (LOADEST) is a FORTRAN program for estimating constituent loads in streams and rivers. Given a time series of streamflow, additional data variables, and constituent concentration, LOADEST assists the user in developing a regression model for the estimation of constituent load (calibration). Explanatory variables within the regression model include various functions of streamflow, decimal time, and additional user-specified data variables. The formulated regression model then is used to estimate loads over a user-specified time interval (estimation). Mean load estimates, standard errors, and 95 percent confidence intervals are developed on a monthly and(or) seasonal basis.</br></br>The calibration and estimation procedures within LOADEST are based on three statistical estimation methods. The first two methods, Adjusted Maximum Likelihood Estimation (AMLE) and Maximum Likelihood Estimation (MLE), are appropriate when the calibration model errors (residuals) are normally distributed. Of the two, AMLE is the method of choice when the calibration data set (time series of streamflow, additional data variables, and concentration) contains censored data. The third method, Least Absolute Deviation (LAD), is an alternative to maximum likelihood estimation when the residuals are not normally distributed. LOADEST output includes diagnostic tests and warnings to assist the user in determining the appropriate estimation method and in interpreting the estimated loads.</br></br>The LOADEST software and related materials (data and documentation) are made available by the U.S. Geological Survey (USGS) to be used in the public interest and the advancement of science. You may, without any fee or cost, use, copy, modify, or distribute this software, and any derivative works thereof, and its supporting documentation, subject to the USGS software User's Rights Notice.to the USGS software User's Rights Notice.)
  • Model:Radiation  + (Landlab component that computes 1D and 2D total incident shortwave radiation. This code also computes relative incidence shortwave radiation compared to a flat surface.)
  • Model:LateralEroder  + (Landlab component that finds a neighbor node to laterally erode and calculates lateral erosion.)
  • Model:PrecipitationDistribution  + (Landlab component that generates precipitaLandlab component that generates precipitation events using the rectangular Poisson pulse model described in Eagleson (1978, Water Resources Research).</br></br>No particular units must be used, but it was written with the storm units in hours (hr) and depth units in millimeters (mm). (hr) and depth units in millimeters (mm).)
  • Model:Flexure  + (Landlab component that implements a 1 and 2D lithospheric flexure model.)
  • Model:DetachmentLtdErosion  + (Landlab component that simulates detachmenLandlab component that simulates detachment limited sediment transport is more general than the stream power component. Doesn't require the upstream node order, links to flow receiver and flow receiver fields. Instead, takes in the discharge values on NODES calculated by the OverlandFlow class and erodes the landscape in response to the output discharge.</br>As of right now, this component relies on the OverlandFlow component for stability. There are no stability criteria implemented in this class. To ensure model stability, use StreamPowerEroder or FastscapeEroder components instead.der or FastscapeEroder components instead.)
  • Model:Vegetation  + (Landlab component that simulates net primary productivity, biomass and leaf area index at each cell based on inputs of root-zone average soil moisture.)
  • Model:SoilMoisture  + (Landlab component that simulates root-zoneLandlab component that simulates root-zone average soil moisture at each cell using inputs of potential evapotranspiration, live leaf area index, and vegetation cover.</br></br>This component uses a single soil moisture layer and models soil moisture loss through transpiration by plants, evaporation by bare soil, and leakage. The solution of water balance is based on Laio et. al 2001. The component requires fields of initial soil moisture, rainfall input (if any), time to the next storm and potential transpiration.he next storm and potential transpiration.)
  • Model:Landlab  + (Landlab is a Python software package for cLandlab is a Python software package for creating, assembling, and/or running 2D numerical models. Landlab was created to facilitate modeling in earth-surface dynamics, but it is general enough to support a wide range of applications. Landlab provides three different capabilities:</br></br>(1) A DEVELOPER'S TOOLKIT for efficiently building 2D models from scratch. The toolkit includes a powerful GRIDDING ENGINE for creating, managing, and iterative updating data on 2D structured or unstructured grids. The toolkit also includes helpful utilities to handle model input and output.</br></br>(2) A set of pre-built COMPONENTS, each of which models a particular process. Components can be combined together to create coupled models.</br></br>(3) A library of pre-built MODELS that have been created by combining components together.</br></br> To learn more, please visit http://landlab.github.ioore, please visit http://landlab.github.io)
  • Model:GOLEM  + (Landscape evolution model. Computes evolution of topography under the action of rainfall and tectonics.)
  • Model:SpeciesEvolver  + (Life evolves alongside landscapes by biotiLife evolves alongside landscapes by biotic and abiotic processes under complex dynamics at Earth’s surface. Researchers who wish to explore these dynamics can use this component as a tool for them to build landscape-life evolution models. Landlab components, including SpeciesEvolver are designed to work with a shared model grid. Researchers can build novel models using plug-and-play surface process components to evolve the grid’s landscape alongside the life tracked by SpeciesEvolver. The simulated life evolves following customizable processes. evolves following customizable processes.)
  • Model:LinearDiffuser  + (LinearDiffuser is a Landlab component that models soil creep using an explicit finite-volume solution to a 2D diffusion equation.)
  • Model:LITHFLEX2  + (Lithospheric flexure solution for a brokenLithospheric flexure solution for a broken plate. Load is assumed to be represented by equal width loading elements specified distance from broken edge of plate. Inclusion of sediments as part of the restoring force effect is possible by choice of density assigned to density (2).choice of density assigned to density (2).)
  • Model:LITHFLEX1  + (Lithospheric flexure solution for infiniteLithospheric flexure solution for infinite plate. Load is assumed to be convolved with Greens function (unit load) response in order to calculate the net effect of the load. If desired, inclusion of sediments as part of the restoring force effect can be controlled via density assigned to density (2). Each load element can have specified density and several loadings events can be incorporated.veral loadings events can be incorporated.)
  • Model:CoastMorpho2D  + (Long term 2D morphodynamics of coastal areLong term 2D morphodynamics of coastal areas, including tidal currents, wind waves, swell waves, storm surge, sand, mud, marsh vegetation, edge erosion, marsh ponding, and stratigraphy.</br>The CoastMorpho2D model includes the MarshMorpho2D model (which was previously uploaded on CSDMS)l (which was previously uploaded on CSDMS))
  • Model:D'Alpaos model  + (Long-term ecomorphodynamic model of the initiation and development of tidal networks and of the adjacent marsh platform, accounting for vegetation influence and relative sea level rise effects)
  • Model:MARSSIM V4  + (MARSSIM is a grid based, iterative framewoMARSSIM is a grid based, iterative framework that incorporates selectable modules, including: 1) flow routing, optionally including event-driven flow and evaporation from lakes in depression as a function of relative aridity (Matsubara et al., 2011). Runoff can be spatially uniform or variably distributed. Stream channel morphology (width and depth) is parameterized as a function of effective discharge; 2) bedrock weathering, following Equation 1; 3) spatially variable bedrock resistance to weathering and fluvial erosion, including 3-D stratigraphy and surficial coherent crusts; 4) erosion of bedrock channels using either a stream power relationship (Howard, 1994) or sediment load scour (Sklar and Dietrich, 2004; Chatanantavet and Parker, 2009); 5) sediment routing in alluvial channels including suspended/wash load and a single size of bedload. An optional sediment transport model simulates transport of multiple grain sizes of bedload with sorting and abrasion (Howard et al., 2016); 6) geometric impact cratering modeling optionally using a database of martian fresh crater morphology; 7) vapor sublimation from or condensation on the land surface, with options for rate control by the interaction between incident radiation, reflected light, and local topography; 8) mass wasting utilizing either the Howard (1994) or the Roering et al. (1999, 2001a) rate law. Bedrock can be optionally weathered and mass wasted assuming a critical slope angle steeper than the critical gradient for regolith-mantled slopes. Mass wasted debris is instantaneously routed across exposed bedrock, and the debris flux can be specified to erode the bedrock; 9) groundwater flow using the assumption of hydrostatic pressures and shallow flow relative to cell dimensions. Both recharge and seepage to the surface are modeled. Seepage discharge can be modeled to transport sediment (seepage erosion) or to weather exposed bedrock (groundwater sapping); 10) deep-seated mass flows using either Glen's law or Bingham rheology using a hydrostatic stress assumption; 11) eolian deposition and erosion in which the rate is determined by local topography; 12) lava flow and deposition from one or multiple vents. These model components vary in degree to which they are based on established theory or utilize heuristicon established theory or utilize heuristic)
  • Model:MICOM  + (MICOM is a primitive equation numerical model that describes the evolution of momentum, mass, heat and salt in the ocean.)
  • Model:MODFLOW 6  + (MODFLOW 6 is an object-oriented program anMODFLOW 6 is an object-oriented program and framework developed to provide a platform for supporting multiple models and multiple types of models within the same simulation. This version of MODFLOW is labeled with a "6" because it is the sixth core version of MODFLOW to be released by the USGS (previous core versions were released in 1984, 1988, 1996, 2000, and 2005). In the new design, any number of models can be included in a simulation. These models can be independent of one another with no interaction, they can exchange information with one another, or they can be tightly coupled at the matrix level by adding them to the same numerical solution. Transfer of information between models is isolated to exchange objects, which allow models to be developed and used independently of one another. Within this new framework, a regional-scale groundwater model may be coupled with multiple local-scale groundwater models. Or, a surface-water flow model could be coupled to multiple groundwater flow models. The framework naturally allows for future extensions to include the simulation of solute transport.nclude the simulation of solute transport.)
  • Model:MODFLOW  + (MODFLOW is a three-dimensional finite-diffMODFLOW is a three-dimensional finite-difference ground-water model that was first published in 1984. It has a modular structure that allows it to be easily modified to adapt the code for a particular application. Many new capabilities have been added to the original model. OFR 00-92 (complete reference below) documents a general update to MODFLOW, which is called MODFLOW-2000 in order to distinguish it from earlier versions.</br></br>MODFLOW-2000 simulates steady and nonsteady flow in an irregularly shaped flow system in which aquifer layers can be confined, unconfined, or a combination of confined and unconfined. Flow from external stresses, such as flow to wells, areal recharge, evapotranspiration, flow to drains, and flow through river beds, can be simulated. Hydraulic conductivities or transmissivities for any layer may differ spatially and be anisotropic (restricted to having the principal directions aligned with the grid axes), and the storage coefficient may be heterogeneous. Specified head and specified flux boundaries can be simulated as can a head dependent flux across the model's outer boundary that allows water to be supplied to a boundary block in the modeled area at a rate proportional to the current head difference between a "source" of water outside the modeled area and the boundary block. MODFLOW is currently the most used numerical model in the U.S. Geological Survey for ground-water flow problems.</br></br>In addition to simulating ground-water flow, the scope of MODFLOW-2000 has been expanded to incorporate related capabilities such as solute transport and parameter estimation.solute transport and parameter estimation.)
  • Model:MOM6  + (MOM6 is the latest generation of the ModulMOM6 is the latest generation of the Modular Ocean Model which is a numerical model code for simulating the ocean general circulation. MOM6 represents a major algorithmic departure from the previous generations of MOM (up to and including MOM5). Most notably, it uses the Arbitrary-Lagrangian-Eulerian (ALE) algorithm in the vertical direction to allow the use of any vertical coordinate system including, geo-potential coordinates (z or z*), isopycnal coordinates, terrain-following coordinates and hybrid-/user-defined coordinates. It is also based on the horizontal C-grid stencil, rather than the B-grid used by earlier MOM versions.n the B-grid used by earlier MOM versions.)
  • Model:CASCADE  + (Makes use of fast Delaunay triangulation aMakes use of fast Delaunay triangulation and Voronoi diagram calculations to represent surface processes on an irregular, dynamically evolving mesh. Processes include fluvial erosion, transport and deposition, hillslope (diffusion) processes, flexural isostasy, orographic precipitation. Designed to model processes at the orogenic scale. Can be easily modified for other purposes by changing process laws.r other purposes by changing process laws.)
  • Model:Manningseq-bouldersforpaleohydrology  + (Matlab® code for paleo-hydrological flood Matlab® code for paleo-hydrological flood flow reconstruction in a fluvial channel: first-order magnitude estimations of maximum average flow velocity, peak discharge, and maximum flow height from boulder size and topographic input data (channel cross-section & channel bed slope).hannel cross-section & channel bed slope).)
  • Model:Reservoir  + (Measure single reservoir performance usingMeasure single reservoir performance using resilience, reliability, and vulnerability metrics; compute storage-yield-reliability relationships; determine no-fail Rippl storage with sequent peak analysis; optimize release decisions using determinisitc and stochastic dynamic programming; evaluate inflow characteristics.gramming; evaluate inflow characteristics.)
  • Model:Coastal Dune Model  + (Model describing the morphodynamic evolution of vegetated coastal foredunes.)
  • Model:Sun fan-delta model  + (Model for fluvial fan-delta evolution, oriModel for fluvial fan-delta evolution, originally described by Sun et al. (2002) and later adapted by Limaye et al. (2023). The model routes water and sediment across a grid from a single inlet and via a self-formed channel network, where local divergence in sediment flux drives bed elevation change. The model represents hydrodynamics using rules for flow routing and stress partitioning. At large scales, other heuristics determine how channels branch and avulse, distributing water and sediment. The original model, designed for fluvial fan-deltas that debouch into standing water, is extended to allow deposition of an alluvial fan in the absence of standing water.</br></br>References: </br>Limaye, A. B., Adler, J. B., Moodie, A. J., Whipple, K. X., & Howard, A. D. (2023). Effect of standing water on formation of fan-shaped sedimentary deposits at Hypanis Valles, Mars. Geophysical Research Letters, 50(4), e2022GL102367. https://doi.org/10.1029/2022GL102367</br></br>Sun, T., Paola, C., Parker, G., & Meakin, P. (2002). Fluvial fan deltas: Linking channel processes with large-scale morphodynamics. Water Resources Research, 38(8), 26-1-26–10. https://doi.org/10.1029/2001WR000284, 26-1-26–10. https://doi.org/10.1029/2001WR000284)
  • Model:Avulsion  + (Model stream avulsion as random walk)
  • Model:GISS GCM ModelE  + (ModelE is the GISS series of coupled atmosModelE is the GISS series of coupled atmosphere-ocean models, which provides the ability to simulate many different configurations of Earth System Models - including interactive atmospheric chemsitry, aerosols, carbon cycle and other tracers, as well as the standard atmosphere, ocean, sea ice and land surface components.cean, sea ice and land surface components.)
  • Model:Lake-Permafrost with Subsidence  + (Models temperature of 1-D lake-permafrost Models temperature of 1-D lake-permafrost system through time, given input surface temperature and solar radiation. Model is fully implicit control volume scheme, and cell size can vary with depth. Thermal conductivity and specific heat capacity are dependent on cell substrate (% soil and % ice) and temperature using the apparent heat capacity scheme where freezing/thawing occurs over a finite temperature range and constants are modified to account for latent heat. Lake freezes and thaws depending on temperature; when no ice is present lake is fully mixed and can absorb solar radiation. Upper 10 m substrate contains excess ice and, if thawed, can subside by this amount (lake then deepens by amount of subsidence). "Cell type" controls whether cell has excess ice, only pore space ice, or is lake water.ce, only pore space ice, or is lake water.)
  • Model:Gc2d  + (Models the growth and evolution of valley glaciers and ice sheets)