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Model:CVFEM Rift2D + (The four primary components of our multi-p … The four primary components of our multi-physics code include geomechanical, hydrologic, solute transport and heat transfer modules. The geomechanical module calculates displacement of an elastic lithosphere disturbed by an ice sheet load. Transient geomechanical deformation is represented by one-dimensional (lateral) viscous asthenosphere flow. Our geomechanical module is partially coupled to the hydrologic module by providing the rate of change in the mean normal stress. Mean normal stress change rate is included as a source term in the groundwater flow equation driving flow. Flow is also influenced by changes in the top specified hydraulic head boundary condition. We implement two-way coupling between fluid flow, solute transport and heat transfer module via density and viscosity equations of state. Three additional modules in our multi-physics code calculate changes to the upper hydraulic and thermal boundary conditions or alter the hydraulic transport properties (permeability) due to hydrogeomechanical failure. These include ice sheet evolution, permafrost, and failure analysis modules. Ice sheet thickness determines both the vertical load in the geomechanical module as well as the hydraulic head boundary condition at the land surface in the hydrologic module. In this study we adopted a simple parabolic polynomial equation to represent the idealized geometry of an ice sheet’s cross section in the ice sheet evolution module. We solved for permafrostformation at and below the land surface using a suite of one-dimensional heat transfer models. We allowed for grid growth within the permafrost module to account for changes in ice sheet thickness. A failure analysis module was used to modify permeability due to hydromechanical failure. We adopted the effective Coulomb’s Failure Stress change criterion from Ge et al.(2009) to assess regions of failure during glaciations.ess regions of failure during glaciations.)
Model:MODFLOW + (The ground-water flow equation is solved u … The ground-water flow equation is solved using the finite-difference approximation. The flow region is subdivided into blocks in which the medium properties are assumed to be uniform. In plan view the blocks are made from a grid of mutually perpendicular lines that may be variably spaced. Model layers can have varying thickness. A flow equation is written for each block, called a cell. Several solvers are provided for solving the resulting matrix problem; the user can choose the best solver for the particular problem. Flow-rate and cumulative-volume balances from each type of inflow and outflow are computed for each time step.d outflow are computed for each time step.)
Model:WASH123D + (The integrated multi-processes include: # … The integrated multi-processes include:# hydrological cycles (evaporation, evapotranspiration, infiltration, and recharges);# fluid flow (surface runoff in land surface, hydraulics and yydrodynamics in river/stream/canal networks;# interflow in vadose zones, and groundwater flow in saturated zones);# salinity transport and thermal transport (in surface waters and groundwater);# sediment transport (in surface waters);# water quality transport (any number of reactive constituents);# biogeochemical cycles (nitrogen, phosphorous, carbon, oxygen, etc.); and# biota kinetics (algae, phyotoplankton, zooplakton, caliform, bacteria, plants, etc.).lakton, caliform, bacteria, plants, etc.).)
Model:CellularFanDelta + (The key processes are 1) topographically-d … The key processes are 1) topographically-driven overland flow and 2) bedload transport by this flow. Through these processes the model self-organizes channels which incise, back-fill, and avulse. Processes are similar to alluvial fans. There are no marine processes besides bedload dumping. marine processes besides bedload dumping.)
Model:TopoFlow-Channels-Kinematic Wave + (The kinematic wave method for flow routing in the channels of a D8-based river network.)
Model:RASCAL + (The main source code calls sub-modules tha … The main source code calls sub-modules that simulate the following processes:- Vegetation community colonization as a function of local water depth. Colonization is deterministic over some ranges and stochastic in others.- Solution of flow field in two dimensions using a cellular automata algorithm (see Larsen and Harvey, 2010, Geomorphology, and Larsen and Harvey, 2010 in press, American Naturalist). The flow field is only simulated during high-flow events that entrain sediment.- Sediment transport by flow according to an advection-dispersion equation. Within each high-flow pulse, steady conditions are assumed.- Evolution of the topography through sediment transport, peat accretion (which is based on Larsen et al., Ecological Monographs, 2007), diffusive erosion of topographic gradients, vegetative propagation, and below-ground biomass expansion.- Adjustment of water levels and high-flow discharge to satisfy a water balance and compensate for the growth of vegetation patches.sate for the growth of vegetation patches.)
Model:Frost Model + (The mean annual temperature of the warmest and coldest months at a given location gives a first-order estimate of distribution of permafrost.)
Model:Kirwan marsh model + (The model calculates changes in elevation … The model calculates changes in elevation and vegetation growth for a hypothetical salt marsh. In each cell, elevation change is calculated as the difference between accretion and erosion. Accretion rates are a function of inundation depth, vegetation growth, and suspended sediment concentration. Water routed according to Rinaldo et al. (1999) scheme. Erosion rates calculated according to excess sheer stress. Channels widen according to a diffusion-like routine where downslope transport is inversely proportional to vegetation. Vegetation grows according to Morris et al. (2002) where biomass is proportional to inundation depth up until an optimum depth. Episodic vegetation disturbance is simulated by removing vegetation from randomly selected cells (Kirwan et al., 2008). Another version of the model treats wave erosion in a simplistic manner (Kirwan and Murray, 2008).mplistic manner (Kirwan and Murray, 2008).)
Model:ESCAPE + (The model computes flow accumulation using … The model computes flow accumulation using multiple flow direction over unstructured grids based on + an adaptation of the implicit approach proposed by Richardson & Perron (Richardson, Hill, & Perron, 2014). + an extension of the parallel priority-flood depression-filling algorithm from (Barnes, 2016) to unstructured mesh is used to simulate sedimentation in upland areas and internally drained basins. + marine sedimentation is based on a diffusion algorithm similar to the technique proposed in pybadlands (Salles, Ding, & Brocard, 2018).sed in pybadlands (Salles, Ding, & Brocard, 2018).)
Model:HBV + (The model consists of subroutines for mete … The model consists of subroutines for meteorological interpolation, snow accumulation and melt, evapotranspiration estimation, a soil moisture accounting procedure, routines for runoff generation and finally, a simple routing procedure between subbasins and in lakes. It is possible to run the model separately for several subbasins and then add the contributions from all subbasins. Calibration as well as forecasts can be made for each subbasin.s forecasts can be made for each subbasin.)
Model:D'Alpaos model + (The model describes the tidal-network init … The model describes the tidal-network initiation and development, and the vertical accretion of the adjacent marsh platform. Tidal network development is driven by the exceedance of a local hydrodynamic bottom shear stress, controlled by water surface gradients. Marsh vertical growth is modeled by using a sediment balance equation acconting for erosion and deposition terms. The deposition terms account for sediment settling, trapping and organic production.settling, trapping and organic production.)
Model:FUNDY + (The model is forced by tidal or other barotropic boundary conditions, wind, and/or fixed baroclinic pressure gradient, all acting at a single frequency (including zero) and specified by the user.)
Model:Equilibrium Calculator + (The model predicts bankfull geometry of si … The model predicts bankfull geometry of single-thread, sand-bed rivers from first principles, i.e. conservation of channel bed and floodplain sediment, which does not require the a-priori knowledge of the bankfull discharge. Building on previous work on the equilibrium of engineered rivers, i.e. rivers with fixed banks and sinuosity (Blom et al., 2016, 2017, Arkesteijn et al., 2019), as well as formulations for floodplain morphodynamics (Lauer & Parker, 2008, Viparelli et al., 2013, Lauer et al., 2016) and bank migration (Parker et al., 2011, Eke et al., 2014, Davidson & Eaton, 2018, De Rego et al., 2020), we derive equilibrium solutions for channel geometry (width, depth, slope), floodplain sediment size distribution, bankfull discharge, channel migration and overbank deposition rates. ReferencesArkesteijn, L., Blom, A., Czapiga, M. J., Chavarrias, V. & Labeur, R. J. (2019). The quasi-equilibrium longitudinal profile in backwater reaches if the engineered alluvial river: A space-marching method, Journal of Geophysical Research: Earth Surface 124, 2542-2560.Blom, A., Viparelli, E. & Chavarrias, V. (2016). The graded alluvial river: Profile concavity and downstream fining, Geophysical Research Letters 43 (12), 6285-6293.Blom, A., Arkesteijn, L., Chavarrias, V. & Viparelli, E. (2017). The equilibrium alluvial river under variable flow and its channel-forming discharge, Journal of Geophysical Research: Earth Surface 122, 1924-1948.Davidson, S.L. & Eaton, B. C. (2018). Beyond Regime: A stochastic model of floods, bank erosion, and channel migration. Water Resources Research, 54, 6282-6298. De Rego, K., Lauer, J. W., Eaton, B. & Hassan, M. (2020). A decadal-scale numerical model for wandering, cobble-bedded rivers subject to disturbance, Earth Surface Processes and Landforms 45, 912-927. Eke, E., Parker, G. & Shimizu, Y. (2014). Numerical modeling of erosional and depositional bank processes in migrating river bends with self-formed width: Morphodynamics of bar push and bank pull, Journal of Geophysical Research: Earth Surface 119, 1455-1483.Lauer, J. W. & Parker, G. (2008). Modeling framework for sediment deposition, storage, and evacuation in the floodplain of a meandering river: Theory, Water Resources Research 44, W04425, doi: 10.1029/2006WR005528.Lauer, J. W., Viparelli, E. & Piegay, H. (2016). Morphodynamics and sediment tracers in 1-D (MAST-1D): 1-D sediment transport that includes exchange with an off-channel sediment reservoir, Advances in Water Resources 93, 135-149.Parker, G., Shimizu, Y., Wilkerson, G. V., Eke, E. C., Abad, J. D., Lauer, J. W., Paola, C., Dietrich, W. E. & Voller, V. R. (2011). A new framework for modeling the migration of meandering rivers, Earth Surface Processes and Landforms 36, 70-86.Viparelli, E., Lauer, J. W., Belmont, P. & Parker, G. (2013). A numerical model to develop long-term sediment budgets using isotopic sediment fingerprints, Computers & Geosciences 53, 114-122.ediment budgets using isotopic sediment fingerprints, Computers & Geosciences 53, 114-122.)
Model:Tracer dispersion calculator + (The model represent the streamwise and vertical dispersal of a patch of tracer stones in an equilibrium gravel bed.)
Model:SWEHR + (The model simulates infiltration, fluid flow, and sediment transport. Fluid behavior is influenced by sediment concentration.)
Model:Meander Centerline Migration Model + (The model simulates the lateral migration of a meandering rivers, allowing the formation of oxbow lakes and scroll bars which may have a different erosional resistance with respect to the pristine floodplain.)
Model:PyDeCe + (The model simulates transport and deposition from the dense endmember of a pyroclastic density currents generated either by impulsive column collapse or sustained fountaining eruptions.)
Model:1DBreachingTurbidityCurrent + (The model solves both Gary Parker's three … The model solves both Gary Parker's three and four equation models for sediment mixtures. A condition was incorporated in the model to solve the equation of conservation of turbulent kinetic energy (fourth equation) and to decide how to estimate the friction coefficients. See also: Eke, E., Viparelli, E., and Parker, G., 2011. Field-scale numerical modeling of breaching as a mechanism for generating continuous turbidity currents. Geosphere, 7, 1063-1076. Doi: 10.1130/GES00607.1ents. Geosphere, 7, 1063-1076. Doi: 10.1130/GES00607.1)
Model:UEB + (The model uses physically-based calculations of radiative, sensible, latent and advective heat exchanges.)
Model:Hilltop flow routing + (The module generates hillslope profiles by routing flow from every point on a drainage divide into a channel.)
Model:Chi analysis tools + (The module performs topographic analysis but the analysis is based on the assumption that the stream power incision model is a good approximation for channel incision.)
Model:FVshock + (The numerical model solves the two-dimensi … The numerical model solves the two-dimensional shallow water equations with different modes of sediment transport. Moreover are presently implemented the Savage-Hutter type model describing avalanches of granular materials (not tested yet) and the equations governing the motion of two layers of immiscible fluid. motion of two layers of immiscible fluid.)
Model:RHESSys + (The original process models include the fo … The original process models include the following:* The MTN-Clim model (Running et al, 1987) uses topography and user supplied base station information to derive spatially variable climate variables such as radiation and to extrapolate input climate variables over topographically varying terrain.* An ecophysiological model is adapted from BIOME-BGC (Running and Coughlan, 1988; Running and Hunt, 1993) to estimate carbon, water and potentially nitrogen fluxes from different canopy cover types.* Distributed hydrologic models – The original RHESSys utilized a single approach, TOPMODEL, to model soil moisture redistribution and runoff production. We now include two approaches:** TOPMODEL (Beven and Kirkby, 1979) is a quasi distributed model. TOPMODEL distributes hillslope soil moisture based on a distribution of a topograhically defined wetness index.** An explicit routing model is adapted from DHSVM (Wigmosta et al., 1994) which models saturated subsurface throughflow and overland flow via explicit connectivity. An important modification from the grid-based routing in DHSVM is the ability to route w ater between arbitrarily shaped surface elements. This allows greater flexibility in defining surface patches and varying shape and density of surface tesselation. shape and density of surface tesselation.)
Model:FVCOM + (The present version of FVCOM includes a nu … The present version of FVCOM includes a number of options and components as shown in Figure above. These include:# choice of Cartesian or spherical coordinate system,# a mass-conservative wet/dry point treatment for the flooding/drying process simulation,# the General Ocean Turbulent Model (GOTM) modules (Burchard et al., 1999; Burchard, 2002) for optional vertical turbulent mixing schemes,# a water quality module to simulate dissolved oxygen and other environmental indicators,# 4-D nudging and Reduced/Ensemble Kalman Filters (implemented in collaboration with P. Rizzoli at MIT) for data assimilation,# fully-nonlinear ice models (implemented by F. Dupont),# a 3-D sediment transport module (based on the U.S.G.S. national sediment transport model) for estuarine and near-shore applications, and# a flexible biological module (FBM) for food web dynamics study.FBM includes seven groups: nutrients, autotrophy, heterotrophy, detritus, dissolved organic matter, bacteria, and other. With various pre-built functions and parameters for these groups, GBM allows users to either select a pre-built biological model (such as NPZ, NPZD, etc.) or to build their own biological model using the pre-defined pool of biological variables and parameterization functions. variables and parameterization functions.)
Model:PRMS + (The primary objectives are: (1) simulation … The primary objectives are: (1) simulation of hydrologic processes including evaporation, transpiration, runoff, infiltration, and interflow as determined by the energy and water budgets of the plant canopy, snowpack, and soil zone on the basis of distributed climate information (temperature, precipitation, and solar radiation); (2) simulation of hydrologic water budgets at the watershed scale for temporal scales ranging from days to centuries; (3) integration of PRMS with other models used fornatural-resource management or with models from other scientific disciplines; and (4) providing a modular design that allows for selection of alternative hydrologic-process algorithms from the standard PRMS module library.hms from the standard PRMS module library.)

Model:CVPM + (The primary processes are heat diffusion and phase change.)

Model:DR3M + (The rainfall-excess components include soi … The rainfall-excess components include soil-moisture accounting, pervious-area rainfall excess, impervious-area rainfall excess, and parameter optimization. The Green-Ampt equation is used in the calculations of infiltration and pervious area rainfall excess. A Rosenbrock optimization procedure may be used to aid in calibrating several of the infiltration and soil-moisture accounting parameters. Kinematic wave theory is used for both overland-flow and channel routing. There are three solution techniques available: method of characteristics, implicit finite difference method, and explicit finite difference method. Two soil types may be defined. Overland flow may be defined as turbulent or laminar. Detention reservoirs may be simulated as linear storage or using a modified-Puls method. Channel segments may be defined as gutter, pipe, triangular cross section, or by explicitly specifying the kinematic channel parameters alpha and m. kinematic channel parameters alpha and m.)
Model:TUGS + (The two key elements of TUGS model are a s … The two key elements of TUGS model are a surface-based bedload transport equation that allows for calculation of transport rate and grain size distribution of both gravel and sand (Wilcoco and Crowe 2003), and functions that link bedload grain size distributions with surface and subsurface grain size distributions (Hoey and Ferguson 1994; Toro-Escobar et al. 1996; Cui 2007a).994; Toro-Escobar et al. 1996; Cui 2007a).)
Model:GullyErosionProfiler1D + (This code will erode cells according to a … This code will erode cells according to a shear stress and also deposit sediment based on the concentration of sediment in a modeled water column. Additionally it has a headcut that migrates upstream and as the headcut erodes it deposits sediment downstream that the model must erode.ment downstream that the model must erode.)
Model:DepthDependentDiffuser + (This component calculates the flux of soil on a hillslope according to a soil depth-dependent linear diffusion rule.)
Model:DELTA + (This driver program solves the equations d … This driver program solves the equations describing horizontal velocities in a buoyant, turbulent, plane jet issuing in a normal direction from a coast into a large volume of still fluid. Sedimentation under the jet is modelled using a hemipelagic rain formulation, bedload dumping, and downslope diffusion due to slides, slumps and turbidity currents. to slides, slumps and turbidity currents.)
Model:KWAVE + (This model is designed to represent infilt … This model is designed to represent infiltration (Green-Ampt), rainfall interception, and runoff (kinematic wave). Hydraulic roughness is accounted for using a depth-dependent Manning-type flow resistance equation.For details on the model equations and numerical solution, see the following references:Rengers, F.K., McGuire, L.A., Kean, J.W., Staley, D.M. and Hobley, D.E.J., 2016. Model simulations of flood and debris flow timing in steep catchments after wildfire. Water Resources Research, 52(8), pp.6041-6061.McGuire, L.A. and Youberg, A.M., 2019. Impacts of successive wildfire on soil hydraulic properties: Implications for debris flow hazards and system resilience. Earth Surface Processes and Landforms, 44(11), pp.2236-2250.sses and Landforms, 44(11), pp.2236-2250.)
Model:GISKnickFinder + (This tool is used to identify knickpoints using a drainage area threshold and a curvature threshold value)
Model:SurfaceRoughness + (This tool maps out local surface roughness … This tool maps out local surface roughness based on the neighborhood distribution of surface normal vectors. As sediment transport processes in soil mantled landscapes tend to be diffusive, the emergence of bedrock drives an increase in surface roughness that is mapped out by this algorithm.ness that is mapped out by this algorithm.)
Model:DrEICH algorithm + (This tool works under the assumption that the channels incise approximately based on the stream power law. It identifies the channel head as the upstream limit of fluvial incision based on the chi profile of the channel.)
Model:Physprop + (Thus the model yields not only compressional wave speeds, but also shear wave speeds and compressional and shear wave attenuation coefficients.)
Model:CoastMorpho2D + (Tidal currents Sea waves Swell waves Storm surges Tidal dispersion transport Along-wave transport Downslope transport by currents, swell waves, breaking waves, and sea waves Edge erosion Marsh processes Along-shore transport by radiation stresses)
Model:MarshMorpho2D + (Tide-averaged flow (by tidal dispersion) F … Tide-averaged flow (by tidal dispersion)Flow erosion (assuming quasi-static propagation)Sediment depositionSediment transportSoil diffusion (aka creep)Organic sediment productionVegetation effect on drag, settling velocity, soil creepSea level risev.20 also includes:Wind waves (empirical function of speed, water depth, and fetch)Edge erosionIdentification of impounded areasActive pond deepeningActive pond expansionctive pond deepening Active pond expansion)
Model:CSt ASMITA + (Time- and length-averaged sediment transport in shelf, shoreface and surf zone environments combined with morphodynamic-driven sediment flux through inlet, along ebb tide delta and with the bay or estuar.)
Model:QDSSM + (Time-averaged sediment transport by long-r … Time-averaged sediment transport by long-range river transport based on discharge and gradient and on short range diffusive transport based on gradient and diffusion coefficients. Thresholds for slope and discharge can be set and act as a means to keep the flow from spreading over every adjacent grid cell allowing avulsion and bifurcation processes to be modeled.n and bifurcation processes to be modeled.)
Model:ADCIRC + (To many to list, see http://adcirc.org)
Model:WRF + (To simulate real weather and to do simulat … To simulate real weather and to do simulations with coarse resolutions, a minimum set of physics components is required, namely radiation, boundary layer and land-surface parameterization, convective parameterization, subgrid eddy diffusion, and microphysics. Since the model is developed for both research and operational groups, sophisticated physics schemes and simple physics schemes are needed in the model. The objectives of the WRF physics development are to implement a basic set of physics into the WRF model and to design a user friendly physics interface. Since the WRF model is targeted at resolutions of 1-10 km, some of physics schemes might not work properly in this high resolution (e.g. cumulus parameterization). However, at this early stage of model development, only existing physics schemes are implemented, and most of them are taken from current mesoscale and cloud models. In the future, new physics schemes designed for resolutions of 1-10 km should be developed and implemented. See http://www.mmm.ucar.edu/wrf/users/docs/wrf-phy.html#physics_scheme for more informationy.html#physics_scheme for more information)
Model:SWAT + (Too many to describe, see: http://www.brc.tamus.edu/swat/index.html)
Model:DeltaClassification + (Tool is used to regionalize a study area i … Tool is used to regionalize a study area into zones with 'common physical characteristics' with the underlying aim of differentiating areas of influence of various physical processes. Regionalization attempts to aggregate spatial units or observations into clusters based on spatial continuity as well as attribute similarity. Geometry metrics are derived from satellite data analysis and include a.o. island area, island aspect ratio, island fractal dimension, and surrounding channel metric, channel width, channel sinousity, number of outflow channels, convexity.ty, number of outflow channels, convexity.)
Model:CosmoLand + (Tracking of cosmogenic nuclides on surface and in fluvial system of a landslide dominated drainage basin)
Model:GRLP + (Transport-limited equilibrium-width long-profile evolution)
Model:Cliffs + (Tsunami propagation from a source earthquake to a coastal site, land inundation.)
Model:LOGDIST + (Turbulent open channel flow along a rough wall)
Model:GeoClaw + (Two-dimensional depth-averaged flows, particularly suitable for tsunami and storm surge modeling, and has also bee used for dam breaks and flooding of river valleys.)
Model:Non Local Means Filtering + (Uses a non-local means filter image processing technique to perform filtering/smoothing of a DEM.)
Model:NEXRAD-extract + (Uses the Python NetCDF toolkit (see python-netcdf on apt) to pull the desired information out of NetCDF files generated from NEXRAD (WSR-88D) outputs)