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A list of all pages that have property "Extended model description" with value "Storm computes windfield for a cyclone". Since there have been only a few results, also nearby values are displayed.

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  • Model:QUAL2K  + (QUAL2K (or Q2K) is a river and stream wateQUAL2K (or Q2K) is a river and stream water quality model that is intended to represent a modernized version of the QUAL2E (or Q2E) model (Brown and Barnwell 1987). Q2K is similar to Q2E in the following respects:</br>One dimensional. The channel is well-mixed vertically and laterally.</br>* Steady state hydraulics. Non-uniform, steady flow is simulated.</br>* Diurnal heat budget. The heat budget and temperature are simulated as a function of meteorology on a diurnal time scale.</br>* Diurnal water-quality kinetics. All water quality variables are simulated on a diurnal time scale.</br>* Heat and mass inputs. Point and non-point loads and abstractions are simulated.oint loads and abstractions are simulated.)
  • Model:StreamProfilerApp  + (QuickChi enables the rapid analysis of stream profiles at the global scale from SRTM data.)
  • Model:GSFLOW-GRASS  + (Quickly generates input files for and runs GSFLOW, the USGS integrated groundwater--surface-water model, and can be used to visualize the outputs of GSFLOW.)
  • Model:RCPWAVE  + (RCPWAVE is a 2D steady state monocromatic short wave model for simulating wave propagation over arbitrary bahymetry.)
  • Model:REF-DIF  + (REF/DIF is a phase-resolving parabolic refREF/DIF is a phase-resolving parabolic refraction-diffraction model for ocean surface wave propagation. It was originally developed by Jim Kirby and Tony Dalrymple starting in 1982, based on Kirby's dissertation work. This work led to the development of REF/DIF 1, a monochromatic wave model. of REF/DIF 1, a monochromatic wave model.)
  • Model:River Erosion Model  + (REM mechanistically simulates channel bed REM mechanistically simulates channel bed aggradation/degradation and channel widening in river networks. It has successfully been applied to alluvial river systems to simulate channel change over annual and decadal time scales. REM is also capable of running Monte Carlo simulations (in parallel to reduce computational time) to quantify uncertainty in model predictions.quantify uncertainty in model predictions.)
  • Model:RHESSys  + (RHESSys is a GIS-based, hydro-ecological mRHESSys is a GIS-based, hydro-ecological modelling framework designed to simulate carbon, water, and nutrient fluxes. By combining a set of physically-based process models and a methodology for partitioning and parameterizing the landscape, RHESSys is capable of modelling the spatial distribution and spatio-temporal interactions between different processes at the watershed scale.ifferent processes at the watershed scale.)
  • Model:ROMS  + (ROMS is a Free-surface, terrain-following,ROMS is a Free-surface, terrain-following, orthogonal curvilinear, primitive equations ocean model. Its dynamical kernel is comprised of four separate models including the nonlinear, tangent linear, representer tangent linear, and adjoint models. It has multiple model coupling (ESMF, MCT) and multiple grid nesting (composed, mosaics, refinement) capabilities. The code uses a coarse-grained parallelization with both shared-memory (OpenMP) and distributed-memory (MPI) paradigms coexisting together and activated via C-preprocessing.ogether and activated via C-preprocessing.)
  • Model:UMCESroms  + (ROMS is a Free-surface, terrain-following,ROMS is a Free-surface, terrain-following, orthogonal curvilinear, primitive equations ocean model. Its dynamical kernel is comprised of four separate models including the nonlinear, tangent linear, representer tangent linear, and adjoint models. It has multiple model coupling (ESMF, MCT) and multiple grid nesting (composed, mosaics, refinement) capabilities. The code uses a coarse-grained parallelization with both shared-memory (OpenMP) and distributed-memory (MPI) paradigms coexisting together and activated via C-preprocessing.ogether and activated via C-preprocessing.)
  • Model:HydroRaVENS  + (RaVENS: Rain and Variable EvapotranspiratiRaVENS: Rain and Variable Evapotranspiration, Nieve, and Streamflow</br></br>Simple "conceptual" hydrological model that may include an arbitrary number of linked linear reservoirs (soil-zone water, groundwater, etc.) as well as snowpack (accumulation from precipitation with T<0; positive-degree-day melt) and evapotranspiration (from external input or Thorntwaite equation).</br></br>It also includes a water-balance component to adjust ET (typically the least known input) to ensure that P - Q - ET = 0 over the course of a water year.</br></br>Other components plot data and compute the NSE (Nash–Sutcliffe model efficiency coefficient).Nash–Sutcliffe model efficiency coefficient).)
  • Model:Landslides  + (Relative wetness and factor-of-safety are Relative wetness and factor-of-safety are based on the infinite slope stability model driven by topographic and soils inputs and recharge provided by user as inputs to the component. For each node, component simulates mean relative wetness as well as the probability of saturation based on Monte Carlo simulation of relative wetness where the probability is the number of iterations with relative wetness >= 1.0 divided by the number of iterations. Probability of failure for each node is also simulated in the Monte Carlo simulation as the number of iterations with factor-of-safety <= 1.0 divided by the number of iterations.y <= 1.0 divided by the number of iterations.)
  • Model:RouseVanoniEquilibrium  + (Rouse-Vanoni Equilibrium Suspended Sediment Profile Calculator)
  • Model:SLEPIAN Delta  + (Routines pertaining to the paper published as: doi: 10.1073/pnas.1206785109)
  • Model:SLEPIAN Alpha  + (Routines pertaining to the paper published as: doi: 10.1137/S0036144504445765)
  • Model:SLEPIAN Charlie  + (Routines pertaining to the paper published as: doi: 10.1111/j.1365-246X.2008.03854.x)
  • Model:SLEPIAN Echo  + (Routines pertaining to the paper published as: doi: 10.1016/j.acha.2012.12.001)
  • Model:SLEPIAN Bravo  + (Routines pertaining to the paper published as: doi: 10.1111/j.1365-246X.2006.03065.x)
  • Model:Plume  + (Run a hypopycnal sediment plume)
  • Model:Bing  + (Run a submarine debris flow)
  • Model:SBEACH  + (SBEACH is a numerical simulation model forSBEACH is a numerical simulation model for predicting beach, berm, and dune erosion due to storm waves and water levels. It has potential for many applications in the coastal environment, and has been used to determine the fate of proposed beach fill alternatives under storm conditions and to compare the performance of different beach fill cross-sectional designs.ferent beach fill cross-sectional designs.)
  • Model:SEDPAK  + (SEDPAK provides a conceptual framework forSEDPAK provides a conceptual framework for modeling the sedimentary fill of basins by visualizing stratal geometries as they are produced between sequence boundaries. The simulation is used to substantiate inferences drawn about the potential for hydrocarbon entrapment and accumulation within a basin. It is designed to model and reconstruct clastic and carbonate sediment geometries which are produced as a response to changing rates of tectonic movement, eustasy, and sedimentation The simulation enables the evolution of the sedimentary fill of a basin to be tracked, defines the chronostratigraphic framework for the deposition of these sediments, and illustrates the relationship between sequences and systems tracts seen in cores, outcrop, and well and seismic data.cores, outcrop, and well and seismic data.)
  • Model:SELFE  + (SELFE is a new unstructured-grid model desSELFE is a new unstructured-grid model designed for the effective simulation of 3D baroclinic circulation across river-to-ocean scales. It uses a semi-implicit finite-element Eulerian-Lagrangian algorithm to solve the shallow water equations, written to realistically address a wide range of physical processes and of atmospheric, ocean and river forcings. of atmospheric, ocean and river forcings.)
  • Model:SIBERIA  + (SIBERIA simulates the evolution of landscapes under the action of runoff and erosion over long times scales.)
  • Model:SICOPOLIS  + (SICOPOLIS (SImulation COde for POLythermalSICOPOLIS (SImulation COde for POLythermal Ice Sheets) is a 3-d dynamic/thermodynamic model that simulates the evolution of large ice sheets and ice caps. It was originally created by Greve (1997a,b) in a version for the Greenland ice sheet. Since then, SICOPOLIS has been developed continuously and applied to problems of past, present and future glaciation of Greenland, Antarctica, the entire northern hemisphere, the polar ice caps of the planet Mars and others.ar ice caps of the planet Mars and others.)
  • Model:SIGNUM  + (SIGNUM (Simple Integrated GeomorphologicalSIGNUM (Simple Integrated Geomorphological Numerical Model) is a TIN-based landscape evolution model: it is capable of simulating sediment transport and erosion by river flow at different space and time scales. It is a multi-process numerical model written in the Matlab high level programming environment, providing a simple and integrated numerical framework for the simulation of some important processes that shape real landscapes.</br></br>Particularly, at the present development stage, SIGNUM is capable of simulating geomorphological processes such as hillslope diffusion, fluvial incision, tectonic uplift or changes in base-level and climate effects in terms of precipitation. A full technical description is reported in Refice et al. 2011 . </br>The software runs under Matlab (it is tested on releases from R2010a to R2011b). It is released under the GPL3 license.b). It is released under the GPL3 license.)
  • Model:SNAC  + (SNAC can solve momentum and heat energy baSNAC can solve momentum and heat energy balance equations in 3D solid with complicated rheology. Lagrangian description of motion adopted in SNAC makes it easy to monitor surface deformation during a crustal or continental scale tectonic event as well as introduce surface processes into a model. introduce surface processes into a model.)
  • Model:SPARROW  + (SPARROW (SPAtially Referenced Regressions SPARROW (SPAtially Referenced Regressions On Watershed attributes) is a watershed modeling technique for relating water-quality measurements made at a network of monitoring stations to attributes of the watersheds containing the stations. The core of the model consists of a nonlinear regression equation describing the non-conservative transport of contaminants from point and diffuse sources on land to rivers and through the stream and river network. The model predicts contaminant flux, concentration, and yield in streams and has been used to evaluate alternative hypotheses about the important contaminant sources and watershed properties that control transport over large spatial scales.ntrol transport over large spatial scales.)
  • Model:SPHYSICS  + (SPHysics is a Smoothed Particle HydrodynamSPHysics is a Smoothed Particle Hydrodynamics (SPH) code written in fortran for the simulation of potentially violent free-surface hydrodynamics. For release version 1.0, the SPHysics code can simulate various phenomena including wave breaking, dam breaks, sloshing, sliding objects, wave impact on a structure, etc. objects, wave impact on a structure, etc.)
  • Model:SRH-1D  + (SRH-1D (Sedimentation and River HydraulicsSRH-1D (Sedimentation and River Hydraulics - One Dimension) is a one-dimensional mobile boundary hydraulic and sediment transport computer model for rivers and manmade canals. Simulation capabilities include steady or unsteady flows, river control structures, looped river networks, cohesive and non-cohesive sediment transport, and lateral inflows. The model uses cross section based river information. The model simulates changes to rivers and canals caused by sediment transport. It can estimate sediment concentrations throughout a waterway given the sediment inflows, bed material, hydrology, and hydraulics of that waterway.ydrology, and hydraulics of that waterway.)
  • Model:STWAVE  + (STWAVE (STeady State spectral WAVE) is an STWAVE (STeady State spectral WAVE) is an easy-to-apply, flexible, robust, half-plane model for nearshore wind-wave growth and propagation. STWAVE simulates depth-induced wave refraction and shoaling, current-induced refraction and shoaling, depth- and steepness-induced wave breaking, diffraction, parametric wave growth because of wind input, and wave-wave interaction and white capping that redistribute and dissipate energy in a growing wave field. dissipate energy in a growing wave field.)
  • Model:SWAN  + (SWAN is a third-generation wave model that computes random, short-crested wind-generated waves in coastal regions and inland waters.)
  • Model:SWAT  + (SWAT is the acronym for Soil and Water AssSWAT is the acronym for Soil and Water Assessment Tool, a river basin, or watershed, scale model developed by Dr. Jeff Arnold for the USDA Agricultural Research Service (ARS). SWAT was developed to predict the impact of land management practices on water, sediment and agricultural chemical yields in large complex watersheds with varying soils, land use and management coditions over long periods of time.ement coditions over long periods of time.)
  • Model:Symphonie  + (SYMPHONIE is a three-dimensional primitive equations coastal ocean model)
  • Model:SedCas  + (SedCas was developed for a debris-flow proSedCas was developed for a debris-flow prone catchment in the Swiss Alps (Illgraben). It consists of two connected sediment reservoirs on the hillslope and in the channel, where sediment transfer is driven by (lumped) hydrological processes at the basin scale. Sediment is stochastically produced by shallow landslides and rock avalanches and delivered to the hillslope and channel reservoirs. From there, it is evacuated out of the basin in the form of debris flows and sediment-laden floods.of debris flows and sediment-laden floods.)
  • Model:SedPlume  + (SedPlume is an integral model, solving theSedPlume is an integral model, solving the conservation equations of volume, momentum, buoyancy and sediment flux along the path of a turbulent plume injected into stably stratified ambient fluid. Sedimentation occurs from the plume when the radial component of the sediment fall velocity exceeds the entrainment velocity. When the plume reaches the surface, it is treated as a radially spreading surface gravity current, for which exact solutions exist for the sediment deposition rate. Flocculation of silt and clay particles is modeled using empirical measurements of particle settling velocities in fjords to adjust the settling velocity of fine-grained sediments.ttling velocity of fine-grained sediments.)
  • Model:Sedflux  + (Sedflux-2.0 is the newest version of the SSedflux-2.0 is the newest version of the Sedflux basin-filling model. Sedflux-2.0 provides a framework within which individual process-response models of disparate time and space resolutions communicate with one another to deliver multi grain sized sediment load across a continental margin.sediment load across a continental margin.)
  • Model:Sedtrans05  + (Sedtrans05 is a sediment transport model fSedtrans05 is a sediment transport model for continental shelf and estuaries. It predicts the sediment transport at one location as function water depth, sediment type, current and waves (single point model). It can be used as sediment transport module for larger 2D models.</br></br>Five different transport equations are available for non-cohesive sediments (sand) and one algorithm for cohesive sediment.) and one algorithm for cohesive sediment.)
  • Model:Shoreline  + (Shoreline is a "line model" for modeling tShoreline is a "line model" for modeling the evolution of a coastline as the result of wind/wave-driven longshore sediment transport. It is based on conservation of mass and a semi-empirical sediment transport formula known as the CERC formula. This model was specifically adapted for modeling the evolution of the coastline near Barrow, Alaska.tion of the coastline near Barrow, Alaska.)
  • Model:SiStER  + (SiStER (Simple Stokes solver with Exotic Rheologies) simulates lithosphere and mantle deformation with continuum mechanics: Stokes flow with large strains, strain localization, non-linear rheologies, sharp contrasts in material properties, complex BCs.)
  • Model:SimClast  + (SimClast is a basin-scale 3D stratigraphicSimClast is a basin-scale 3D stratigraphic model, which allows several interacting sedimentary environments. Processes included are; fluvial channel dynamics and overbank deposition, river plume deposition, open marine currents, wave resuspension, nearshore wave induced longshore and crosshore transport. This combined modelling approach allows insight into the processes influencing the flux of energy and clastic material and the effect of external perturbations in all environments. Many governing processes work on relatively small scales, e.g. in fluvial settings an avulsion is a relatively localised phenomenon. Yet, they have a profound effect on fluvial architecture. This means that the model must mimic these processes, but at the same time maintain computational efficiency. Additionally, long-term models use relatively large grid-sizing (km scale), as the area to be modelled is on the scale of continental margins. We solve this problem by implementing the governing processes as sub-grid scale routines into the large-scale basin-filling model. This parameterization greatly refines morphodynamic behaviour and the resulting stratigraphy. This modelling effort recreates realistic geomorphological and stratigraphic delta behaviour in river and wave-dominated settings.iour in river and wave-dominated settings.)
  • Model:MarshMorpho2D  + (Simulate marsh evolution at 10-10000 time Simulate marsh evolution at 10-10000 time scale. Suitable for domains 0.1km2 to 1000 km2.</br>Only simulates tidal flow. Conserve sediment within the domain. Allows to track sediment through the open boundaries. </br>Version 2.0 also included wind waves, ponding, edge erosion</br>Version under construction includes swell waves, cross-shore and along-shore wave-induced transport, secondary flow in channel bends, stratigraphy (sand and mud as separate constituents)hy (sand and mud as separate constituents))
  • Model:OverlandFlowBates  + (Simulate overland flow using Bates et al. Simulate overland flow using Bates et al. (2010).</br></br>Landlab component that simulates overland flow using the Bates et al., (2010) approximations of the 1D shallow water equations to be used for 2D flood inundation modeling.</br></br>This component calculates discharge, depth and shear stress after some precipitation event across any raster grid. Default input file is named “overland_flow_input.txt’ and is contained in the landlab.components.overland_flow folder.e landlab.components.overland_flow folder.)
  • Model:DELTA  + (Simulates circulation and sedimentation in a 2D turbulent plane jet and resulting delta growth)
  • Model:MARM5D  + (Simulates soil evolution on three spatial Simulates soil evolution on three spatial dimensions, explicit particle size distribution and temporal dimension (hence 5D prefix) as a function of:</br>1. Bedrock and soil physical weathering;</br>2. Sediment transport by overland flow;</br>3. Soil Creep (diffusion);</br>4. Aeolian deposition. Creep (diffusion); 4. Aeolian deposition.)
  • Model:RASCAL  + (Simulates the evolution of landscapes consSimulates the evolution of landscapes consisting of patches of high-flow-resistance vegetation and low-flow-resistance vegetation as a result of surface-water flow, peat accretion, gravitationally driven erosion, and sediment transport by flow. Was developed for the freshwater Everglades but could also apply to coastal marshes or floodplains. Described in Larsen and Harvey, Geomorphology, 2010 and Larsen and Harvey, American Naturalist, 2010 in press.arvey, American Naturalist, 2010 in press.)
  • Model:WSGFAM  + (Simulates wave and current supported sediment gravity flows along the seabed offshore of high discharge, fine sediment riverine sources. See Friedrichs & Scully, 2007. Continental Shelf Research, 27: 322-337, for example.)
  • Model:FlowDirectorD8  + (Single-path (steepest direction) flow direction finding on raster grids by the D8 method. This method considers flow on all eight links such that flow is possible on orthogonal and on diagonal links.)
  • Model:Non Local Means Filtering  + (Smoothes noise in a DEM by finding the mean value of neighbouring cells and assigning it to the central cell. This approach deals well with non-gaussian distributed noise.)
  • Model:Kirwan marsh model  + (Spatially explicit model of the development and evolution of salt marshes, including vegetation influenced accretion and hydrodynamic determined channel erosion.)
  • Model:Inflow  + (Steady-state hyperpycnal flow model.)
  • Model:TISC  + (TISC is a computer program that simulates TISC is a computer program that simulates the evolution of 3D large-scale sediment transport together with tectonic deformation and lithospheric vertical movements on geological time scales. Particular attention is given to foreland sedimentary basin settings. TISC (formerly called tao3D) stands for Tectonics, Isostasy, Surface Transport, and Climate.</br></br>*hydrology/climate</br>The drainage river network is calculated following the maximum slope along the evolving topography. Based on the runoff distribution, the water discharge at any cell of the network is calculated as the water collected from tributary cells plus the precipitation at that cell. Lake evaporation is accounted for, enabling the model to study close endorheic basins. Both topography and the network evolves as a result of erosion, sedimentation and tectonic processes. </br></br>*river sediment transport</br>Sediment carrying capacity is a function of water discharge and slope and determines whether a river is eroding or depositing. Suspended sediments resulting from erosion are transported through the fluvial network until they are deposited or they leave the model domain (explicit mass conservation).</br></br>*lithospheric flexure</br>A elastic and/or viscoelastic plate approach is used to calculate the vertical movements of the lithosphere caused by the mass redistribution. In the classical lithospheric flexural model, the lithosphere is assumed to rest on a fluid asthenosphere and behave as a thin plate when submitted to external forces.</br></br>*tectonic deformation</br>Tectonic modification of the relieve and the correspondent loading of the lithosphere are calculated using a cinematic vertical shear approach (preserving the vertical thickness of the moving units during displacement). of the moving units during displacement). )
  • Model:TOPMODEL  + (TOPMODEL is a physically based, distributeTOPMODEL is a physically based, distributed watershed model that simulates hydrologic fluxes of water (infiltration-excess overland flow, saturation overland flow, infiltration, exfiltration, subsurface flow, evapotranspiration, and channel routing) through a watershed. The model simulates explicit groundwater/surface water interactions by predicting the movement of the water table, which determines where saturated land-surface areas develop and have the potential to produce saturation overland flow.ntial to produce saturation overland flow.)
  • Model:TOPOG  + (TOPOG describes how water moves through laTOPOG describes how water moves through landscapes; over the land surface, into the soil, through the soil and groundwater and back to the atmosphere via evaporation. Conservative solute movement and sediment transport are also simulated.</br></br>The primary strength of TOPOG is that it is based on a sophisticated digital terrain analysis model, which accurately describes the topographic attributes of three-dimensional landscapes. It is intended for application to small catchments (up to 10 km2, and generally smaller than 1 km2).</br></br>We refer to TOPOG as a "deterministic", "distributed-parameter" hydrologic modelling package. The term "deterministic" is used to emphasise the fact that the various water balance models within TOPOG use physical reasoning to explain how the hydrologic system behaves. The term "distributed-parameter" means that the model can account for spatial variability inherent in input parameters such as soil type, vegetation and climate.such as soil type, vegetation and climate.)
  • Model:TUGS  + (TUGS is a 1D model that simulates the tranTUGS is a 1D model that simulates the transport of gravel and sand in rivers. The model predicts the responses of a channel to changes made to the environment (e.g., sediment supply, hydrology, and certain artifical changes made to the river). Output of the model include longitudinal profile, sediment flux, and grain size distributions in bedload, channel surface and subsurface.n bedload, channel surface and subsurface.)
  • Model:TURBINS  + (TURBINS, a highly parallel modular code wrTURBINS, a highly parallel modular code written in C, is capable of modeling gravity and turbidity currents interacting with complex topographies in two and three dimensions. Accurate treatment of the complex geometry, implementation of an efficient and scalable parallel solver, i.e. multigrid solver via PETSc and HYPRE to solve the pressure Poisson equation, and parallel IO are some of the features of TURBINS. </br>TURBINS enables us to tackle problems involving the interaction of turbidity currents with complex topographies. It provides us with a numerical tool for quantifying the flow field properties and sedimentation processes, e.g. energy transfer, dissipation, and wall shear stress, which are difficult to obtain even at laboratory scales. By benefiting from massively parallel simulations, we hope to understand the underlying physics and processes related to the formation and deposition of particles due to the occurrence of turbidity currents.e to the occurrence of turbidity currents.)
  • Model:TauDEM  + (TauDEM provides the following capability: TauDEM provides the following capability: </br></br>•Development of hydrologically correct (pit removed) DEMs using the flooding approach</br></br>•Calculates flow paths (directions) and slopes</br></br>•Calculates contributing area using single and multiple flow direction methods</br></br>•Multiple methods for the delineation of stream networks including topographic form-based methods sensitive to spatially variable drainage density</br></br>•Objective methods for determination of the channel network delineation threshold based on stream drops</br></br>•Delineation of watersheds and subwatersheds draining to each stream segment and association between watershed and segment attributes for setting up hydrologic models</br></br>•Specialized functions for terrain analysis</br></br>Details of new parallel Version 5.0 of TauDEM</br></br>•Restructured into a parallel processing implementation of the TauDEM suite of tools</br></br>•Works on Windows PCs, laptops and UNIX clusters</br></br>•Multiple processes are not required, the parallel approach can run as multiple processes within a single processor</br></br>•Restructured into a set of standalone command line executable programs and an ArcGIS toolbox Graphical User Interface (GUI)</br></br>•Command line executables are:</br> </br>-Written in C++ using Argonne National Laboratory's MPICH2 library to implement message passing between multiple processes</br></br>-Based on single set of source code for the command line execuables that is platform independent and can be compiled for both Window's PC's and UNIX clustersd for both Window's PC's and UNIX clusters)
  • Model:Terrainbento  + (Terrainbento 1.0 is a Python package for mTerrainbento 1.0 is a Python package for modeling the evolution of the surface of the Earth over geologic time (e.g., thousands to millions of years). Despite many decades of effort by the geomorphology community, there is no one established governing equation for the evolution of topography. Terrainbento 1.0 thus provides 28 alternative models that support hypothesis testing and multi-model analysis in landscape evolution.lti-model analysis in landscape evolution.)
  • Model:Terrapin  + (Terrapin (or TerraPIN) stands for "Terraces put into Numerics". It is a module that generates the expected terraces, both strath and fill, from prescribed river aggradation and degradation.)
  • Model:ATS (The Advanced Terrestrial Simulator)  + (The Advanced Terrestrial Simulator (formerThe Advanced Terrestrial Simulator (formerly sometimes known as the Arctic Terrestrial Simulator) is a code for solving ecosystem-based, integrated, distributed hydrology.</br></br>Capabilities are largely based on solving various forms of Richards equation coupled to a surface flow equation, along with the needed sources and sinks for ecosystem and climate models. This can (but need not) include thermal processes (especially ice for frozen soils), evapo-transpiration, albedo-driven surface energy balances, snow, biogeochemistry, plant dynamics, deformation, transport, and much more. In addition, we solve problems of reactive transport in both the subsurface and surface, leveraging external geochemical engines through the Alquimia interface.al engines through the Alquimia interface.)
  • Model:ApsimX  + (The Agricultural Production Systems sIMulaThe Agricultural Production Systems sIMulator (APSIM) is internationally recognized as a highly advanced simulator of agricultural systems. It contains a suite of modules which enable the simulation of systems that cover a range of plant, animal, soil, climate and management interactions. APSIM is undergoing continual development, with new capability added to regular releases of official versions. Its development and maintenance is underpinned by rigorous science and software engineering standards. The APSIM Initiative has been established to promote the development and use of the science modules and infrastructure software of APSIM.ules and infrastructure software of APSIM.)
  • Model:GISS AOM  + (The Atmosphere-Ocean Model is a computer pThe Atmosphere-Ocean Model is a computer program that simulates the Earth's climate in three dimensions on a gridded domain. The Model requires two kinds of input, specified parameters and prognostic variables, and generates two kinds of output, climate diagnostics and prognostic variables. The specified input parameters include physical constants, the Earth's orbital parameters, the Earth's atmospheric constituents, the Earth's topography, the Earth's surface distribution of ocean, glacial ice, or vegetation, and many others. The time varying prognostic variables include fluid mass, horizontal velocity, heat, water vapor, salt, and subsurface mass and energy fields.lt, and subsurface mass and energy fields.)
  • Model:CEM  + (The Coastline Evolution Model (CEM) addresThe Coastline Evolution Model (CEM) addresses predominately sandy, wave-dominated coastlines on time-scales ranging from years to millenia and on spatial scales ranging from kilometers to hundreds of kilometers. Shoreline evolution results from gradients in wave-driven alongshore sediment transport. At its most basic level, the model follows the standard 'one-line' modeling approach, where the cross-shore dimension is collapsed into a single data point. However, the model allows the plan-view shoreline to take on arbitrary local orientations, and even fold back upon itself, as complex shapes such as capes and spits form under some wave climates (distributions of wave influences from different approach angles). The model can also represent the geology underlying the sandy coastline and shoreface in a simplified manner and enables the simulation of coastline evolution when sediment supply from an eroding shoreface may be constrained. CEM also supports the simulation of human manipulations to coastline evolution through beach nourishment or hard structures.ough beach nourishment or hard structures.)
  • Model:CVPM  + (The Control Volume Permafrost Model (CVPM)The Control Volume Permafrost Model (CVPM) is a modular heat-transfer modeling system designed for scientific and engineering studies in permafrost terrain, and as an educational tool. CVPM implements the nonlinear heat-transfer equations in 1-D, 2-D, and 3-D cartesian coordinates, as well as in 1-D radial and 2-D cylindrical coordinates. To accommodate a diversity of geologic settings, a variety of materials can be specified within the model domain, including: organic-rich materials, sedimentary rocks and soils, igneous and metamorphic rocks, ice bodies, borehole fluids, and other engineering materials. Porous materials are treated as a matrix of mineral and organic particles with pore spaces filled with liquid water, ice, and air. Liquid water concentrations at temperatures below 0°C due to interfacial, grain-boundary, and curvature effects are found using relationships from condensed matter physics; pressure and pore-water solute effects are included. A radiogenic heat-production term allows simulations to extend into deep permafrost and underlying bedrock. CVPM can be used over a broad range of depth, temperature, porosity, water saturation, and solute conditions on either the Earth or Mars. The model is suitable for applications at spatial scales ranging from centimeters to hundreds of kilometers and at timescales ranging from seconds to thousands of years. CVPM can act as a stand-alone model, the physics package of a geophysical inverse scheme, or serve as a component within a larger earth modeling system that may include vegetation, surface water, snowpack, atmospheric or other modules of varying complexity.ic or other modules of varying complexity.)
  • Model:CREST  + (The Coupled Routing and Excess STorage (CRThe Coupled Routing and Excess STorage (CREST) distributed hydrological model is a hybrid modeling strategy that was recently developed by the University of Oklahoma (http://hydro.ou.edu) and NASA SERVIR Project Team. CREST simulates the spatiotemporal variation of water and energy fluxes and storages on a regular grid with the grid cell resolution being user-defined, thereby enabling global- and regional-scale applications. The scalability of CREST simulations is accomplished through sub-grid scale representation of soil moisture storage capacity (using a variable infiltration curve) and runoff generation processes (using linear reservoirs). The CREST model was initially developed to provide online global flood predictions with relatively coarse resolution, but it is also applicable at small scales, such as single basins. This README file and the accompanying code concentrates on and tests the model at the small scale. The CREST Model can be forced by gridded potential evapotranspiration and precipitation datasets such as, satellite-based precipitation estimates, gridded rain gauge observations, remote sensing platforms such as weather radar, and quantitative precipitation forecasts from numerical weather prediction models. The representation of the primary water fluxes such as infiltration and routing are closely related to the spatially variable land surface characteristics (i.e., vegetation, soil type, and topography). The runoff generation component and routing scheme are coupled, thus providing realistic interactions between atmospheric, land surface, and subsurface water.heric, land surface, and subsurface water.)
  • Model:Cross Shore Sediment Flux  + (The Cross-Shore Sediment Flux model addresThe Cross-Shore Sediment Flux model addresses predominately sandy, wave-dominated coastlines on time-scales ranging from years to millenia and on spatial scales ranging from kilometers to tens of kilometers using a range of wave parameters as inputs. It calculates the cross-shore sediment flux using both shallow water wave assumptions and full Linear Airy wave Theory. An equilibrium profile is also created. Using the Exner equation, we develop an advection diffusion equation that describes the evolution of profile through time. A morphodynamic depth of closure can be estimated for each input wave parameter.e estimated for each input wave parameter.)
  • Model:DLBRM  + (The DLBRM is a distributed, physically based, watershed hydrology model that subdivides a watershed into a 1 km2 grid network and simulates hydrologic processes for the entire watershed sequentially.)
  • Model:SWMM  + (The EPA Storm Water Management Model (SWMMThe EPA Storm Water Management Model (SWMM) is a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. The runoff component of SWMM operates on a collection of subcatchment areas that receive precipitation and generate runoff and pollutant loads. The routing portion of SWMM transports this runoff through a system of pipes, channels, storage/treatment devices, pumps, and regulators. SWMM tracks the quantity and quality of runoff generated within each subcatchment, and the flow rate, flow depth, and quality of water in each pipe and channel during a simulation period comprised of multiple time steps.n period comprised of multiple time steps.)
  • Model:GeoTiff Data Component  + (The GeoTiff data component, pymt_geotiff, The GeoTiff data component, pymt_geotiff, is a Python Modeling Toolkit (pymt) library for accessing data (and metadata) from a GeoTIFF file, through either a local filepath or a remote URL.</br></br>The pymt_geotiff component provides BMI-mediated access to GeoTIFF data as a service, allowing them to be coupled in pymt with other data or model components that expose a BMI.ata or model components that expose a BMI.)
  • Model:GrainHill  + (The Grain Hill model provides a computatioThe Grain Hill model provides a computational framework with which to study slope forms that arise from stochastic disturbance and rock weathering events. The model operates on a hexagonal lattice, with cell states representing fluid, rock, and grain aggregates that are either stationary or in a state of motion in one of the six cardinal lattice directions. Cells representing near-surface soil material undergo stochastic disturbance events, in which initially stationary material is put into motion. Net downslope transport emerges from the greater likelihood for disturbed material to move downhill than to move uphill. Cells representing rock undergo stochastic weathering events in which the rock is converted into regolith. The model can reproduce a range of common slope forms, from fully soil mantled to rocky or partially mantled, and from convex-upward to planar shapes. An optional additional state represents large blocks that cannot be displaced upward by disturbance events. With the addition of this state, the model captures the morphology of hogbacks, scarps, and similar features. In its simplest form, the model has only three process parameters, which represent disturbance frequency, characteristic disturbance depth, and baselevel lowering rate, respectively. Incorporating physical weathering of rock adds one additional parameter, representing the characteristic rock weathering rate. These parameters are not arbitrary but rather have a direct link with corresponding parameters in continuum theory. The GrainHill model includes the GrainFacetSimulator, which represents an evolving normal-fault facet with a 60-degree-dipping fault.ault facet with a 60-degree-dipping fault.)
  • Model:GreenAmptInfiltrationModel  + (The Green-Ampt method of infiltration estimation.)
  • Model:GridMET Data Component  + (The GridMET data component is an API, CLI,The GridMET data component is an API, CLI, and BMI for fetching and caching daily gridMET (http://www.climatologylab.org/gridmet.html) CONUS meteorological data. Variables include:</br></br>* maximum temperature</br>* minimum temperature</br>* precipitation accumulation</br></br>GridMET provides BMI-mediated access to gridMET data as a service, allowing it to be coupled with other components that expose a BMI.d with other components that expose a BMI.)
  • Model:GroundwaterDupuitPercolator  + (The GroundwaterDupuitPercolator is approprThe GroundwaterDupuitPercolator is appropriate for modeling shallow groundwater flow where the vertical component of flow is negligible. Where the groundwater table approaches the land surface, it calculates seepage that can be routed using other Landlab components. It can be implemented on both regular (e.g. rectangular and hexagonal) and irregular grids determined by the user. Recharge, hydraulic conductivity, and porosity may be specified as single values uniform over the model domain, or as vectors on the nodes (recharge, porosity) or links (hydraulic conductivity) of the grid. Link hydraulic conductivity can also be specified from a two-dimensional hydraulic conductivity tensor using an included function. For mass balance calculations, the model includes methods to determine the total groundwater storage on the grid domain, the total recharge flux in, and total groundwater and surface water fluxes leaving through the boundaries.ter fluxes leaving through the boundaries.)
  • Model:HBV  + (The HBV model (Bergström, 1976, 1992), alsThe HBV model (Bergström, 1976, 1992), also known as Hydrologiska Byråns Vattenbalansavdelning, is a rainfall-runoff model, which includes conceptual numerical descriptions of hydrological processes at the catchment scale. There are many versions created over the years in various coding languages. This description points to the work of John Craven, which is a python implementation of the HBV Hydrological Model, based on matlab code of the work of Professor Amir AghaKouchak at the University of California Irvine.ak at the University of California Irvine.)
  • Model:HyLands  + (The HyLands Landscape Evolution Model is bThe HyLands Landscape Evolution Model is built using the Landlab software package. The HyLands model builds on three new components: water and sediment is routed using the PriorityFloodFlowRouter, fluvial erosion and sediment transport is calculated using the SpaceLargeScaleEroder while bedrock landsliding and sediment runout is calculated using the BedrockLandslider. These and all other Landlab components used in this paper are part of the open source Landlab modeling framework, version 2.5.0 (Barnhart et al., 2020a; Hobley et al., 2017), which is part of the Community Surface Dynamics Modeling System (Tucker et al., 2021). Source code for the Landlab project is housed on GitHub: http://github.com/landlab/landlab (last access: 17 August 2022). Documentation, installation, instructions, and software dependencies for the entire Landlab project can be found at http://landlab.github.io/ (last access: 17 August 2022). A user manual with an accompanying Jupyter notebooks is available from https://github.com/BCampforts/hylands_modeling (last access: 17 August 2022). The Landlab project is tested on recent-generation Mac, Linux, and Windows platforms. The Landlab modeling framework is distributed under a MIT open-source license. The latest version of the Landlab software package, including the components developed for the HyLands model is archived at: https://doi.org/10.5281/zenodo.6951444 (last access: 17 August 2022).odo.6951444 (last access: 17 August 2022).)
  • Model:HEBEM  + (The Hydrologically Enhanced Basin EvolutioThe Hydrologically Enhanced Basin Evolution Model (HEBEM) is a combined hydrologic/geomorphic model. The hydrologic model simulates precipitation with variability, infiltration, evapotranspiration, overland flow, and groundwater flow, thus producing a spatially and temporally varying water discharge Q that drives fluvial processes in the land surface. The geomorphic model accounts for tectonic forcing, hillslope processes, erosion, and sediment transport. The combined model uses multiple time steps for hydrologic and geomorphic processes. Due to its hydrologic representation, the model is able to investigate the interaction between hydrology and geomorpholgy.action between hydrology and geomorpholgy.)
  • Model:Instructed Glacier Model  + (The Instructed Glacier Model (IGM) simulatThe Instructed Glacier Model (IGM) simulates the ice dynamics, surface mass balance, and its coupling through mass conservation to predict the evolution of glaciers and icefields. The specificity of IGM is that it models the ice flow by a neural network, which is trained with ice flow physical models. Doing so permits to speed-up and facilitate considerably the implementation of the forward model and the inverse model required to assimilate data.inverse model required to assimilate data.)
  • Model:ILAMB  + (The International Land Model Benchmarking The International Land Model Benchmarking (ILAMB) project is a model-data intercomparison and integration project designed to improve the performance of land models and, in parallel, improve the design of new measurement campaigns to reduce uncertainties associated with key land surface processes. Building upon past model evaluation studies, the goals of ILAMB are to:</br></br>* develop internationally accepted benchmarks for land model performance, promote the use of these benchmarks by the international community for model intercomparison,</br>* strengthen linkages between experimental, remote sensing, and climate modeling communities in the design of new model tests and new measurement programs, and</br>* support the design and development of a new, open source, benchmarking software system for use by the international community.em for use by the international community.)
  • Model:Drainage Density  + (The Landlab Drainage Density component calThe Landlab Drainage Density component calculates landscape-averaged drainage density, defined as the inverse of the mean distance from any pixel to the nearest channel. The component follows the approach defined in Tucker et al (2001, Geomorphology). The drainage density component does not find channel heads, but takes a user-defined channels mask.s, but takes a user-defined channels mask.)
  • Model:ErosionDeposition  + (The Landlab ErosionDeposition component caThe Landlab ErosionDeposition component calculates fluvial erosion and deposition of a single substrate as derived by Davy and Lague (2009, Journal of Geophysical Research). Mass is simultaneously conserved in two reservoirs: the bed and the water column. ErosionDeposition dynamically transitions between detachment-limited and transport-limited behavior, but is limited to erosion of a single substrate (e.g., sediment or bedrock but not both). (e.g., sediment or bedrock but not both).)
  • Model:OverlandFlow  + (The Landlab OverlandFlow component is baseThe Landlab OverlandFlow component is based on a simplified inertial approximation of the shallow water equations, following the solution of de Almeida et al. (2012). This explicit two-dimensional hydrodynamic algorithm simulates a flood wave across a model domain, where water discharge and flow depth are calculated at all locations within a structured (raster) grid. This component generates a hydrograph at all grid locations, and allows for flow to move in one of the four cardinal directions (D4) into/out of a given model node.tions (D4) into/out of a given model node.)
  • Model:SPACE  + (The Landlab SPACE (Stream Power with AlluvThe Landlab SPACE (Stream Power with Alluvium Conservation and Entrainment) enables modeling of bedrock, alluviated, and bedrock-alluvial rivers by simultaneously conserving mass in three reservoirs: the water column, the alluvial bed, and the underlying bedrock. SPACE allows dynamic transitions between detachment-limited, transport-limited, and intermediate states. SPACE calculates sediment fluxes, alluvial layer thickness, and bedrock erosion at all nodes within the model domain. An extended description of the model may be found in Shobe et al (2017, Geoscientific Model Development).l (2017, Geoscientific Model Development).)
  • Model:LTRANS  + (The Larval TRANSport Lagrangian model (LTRThe Larval TRANSport Lagrangian model (LTRANS) is an off-line particle-tracking model that runs with the stored predictions of a 3D hydrodynamic model, specifically the Regional Ocean Modeling System (ROMS). Although LTRANS was built to simulate oyster larvae, it can easily be adapted to simulate passive particles and other planktonic organisms. LTRANS is written in Fortran 90 and is designed to track the trajectories of particles in three dimensions. It includes a 4th order Runge-Kutta scheme for particle advection and a random displacement model for vertical turbulent particle motion. Reflective boundary conditions, larval behavior, and settlement routines are also included. LTRANS was built by Elizabeth North and Zachary Schlag of University of Maryland Center for Environmental Science Horn Point Laboratory. Funding was provided by the National Science Foundation Biological Oceanography Program, Maryland Department of Natural Resources, NOAA Chesapeake Bay Office, and NOAA-funded UMCP Advanced Study Institute for the Environment. Components of LTRANS have been in development since 2002 and are described in the following publications: North et al. 2005, North et al. 2006a, North et al. 2006b, and North et al. 2008.North et al. 2006b, and North et al. 2008.)
  • Model:MITgcm  + (The MITgcm (MIT General Circulation Model)The MITgcm (MIT General Circulation Model) is a numerical model designed for study of the atmosphere, ocean, and climate. Its non-hydrostatic formulation enables it to simulate fluid phenomena over a wide range of scales; its adjoint capability enables it to be applied to parameter and state estimation problems. By employing fluid isomorphisms, one hydrodynamical kernel can be used to simulate flow in both the atmosphere and ocean.ate flow in both the atmosphere and ocean.)
  • Model:ModelParameterDictionary  + (The Model Parameter Dictionary is a tool fThe Model Parameter Dictionary is a tool for numerical modelers to</br>easily read and access model parameters from a simple formatted </br>input (text) file. Each parameter has a KEY, which identifies the</br>parameter, and a VALUE, which can be a number or a string. A</br>ModelParameterDictionary object reads model parameters from an input </br>file to a Dictionary, and provides functions for the user to look up </br>particular parameters by key name.</br></br>The format of the input file looks like:</br></br>PI: the text "PI" is an example of a KEY</br>3.1416</br>AVOGADROS_NUMBER: this is another</br>6.022e23</br>FAVORITE_FRUIT: yet another</br>mangoes</br>NUMBER_OF_MANGO_WALKS: this one is an integer</br>4</br>ALSO_LIKES_APPLES: this is a boolean</br>true</br></br>Example code that reads these parameters from a file called</br>"myinputs.txt":</br></br> my_param_dict = ModelParameterDictionary()</br> my_param_dict.read_from_file( 'myinputs.txt' )</br> pi = my_param_dict.read_float( 'PI' )</br> avogado = my_param_dict.read_float( 'AVOGADROS_NUMBER' )</br> fruit = my_param_dict.read_string( 'FAVORITE_FRUIT' )</br> nmang = my_param_dict.read_int( 'NUMBER_OF_MANGO_WALKS' )</br> apples_ok = my_param_dict.read_bool( 'ALSO_LIKES_APPLES' )</br></br>As in Python, hash marks (#) denote comments. The rules are that each</br>key must have one and only one parameter value, and each value must</br>appear on a separate line immediately below the key line.</br></br>Also available are functions to read input parameters from the </br>command line (e.g., read_float_cmdline( 'PI' ) )d line (e.g., read_float_cmdline( 'PI' ) ))
  • Model:Permafrost Benchmark System  + (The Permafrost Benchmark System (PBS) wrapThe Permafrost Benchmark System (PBS) wraps the command-line ILAMB benchmarking system with a customized version of the CSDMS Web Modeling Tool (WMT), and adds tools for uploading CMIP5-compatible model outputs and benchmark datasets. The PBS allows users to access and run ILAMB remotely, without having to install software or data locally; a web browser on a desktop, laptop, or tablet computer is all that’s needed., or tablet computer is all that’s needed.)
  • Model:Princeton Ocean Model (POM)  + (The Princeton Ocean Model (POM), a simple-The Princeton Ocean Model (POM), a simple-to-run yet powerful ocean modeling code that is able to simulate a wide-range of problems: circulation and mixing processes in rivers, estuaries, shelf and slope, lakes, semi-enclosed seas and open and global ocean. POM is a sigma coordinate, free surface ocean model with embedded turbulence and wave sub-models, and wet-dry capability. It has been one of the first coastal ocean models freely available to users, with currently over 3000 users from 70 countries.</br></br>For more details see: http://www.ccpo.odu.edu/POMWEB/tails see: http://www.ccpo.odu.edu/POMWEB/)
  • Model:SFINCS  + (The SFINCS model (Super-Fast INundation ofThe SFINCS model (Super-Fast INundation of CoastS) is developed to efficiently simulate compound flooding events at limited computational cost and good accuracy. SFINCS solves the SSWE and thus includes advection in the momentum equation. However, it can also run using the LIE without advection. Processes such as spatially varying friction, infiltration and precipitation are included. Moreover, SFINCS includes wind-driven shear and an absorbing-generating weakly-reflective boundary is considered which are not included in other reduced-physics models. included in other reduced-physics models.)
  • Model:SLAMM 6.7  + (The Sea Level Affecting Marshes Model (SLAThe Sea Level Affecting Marshes Model (SLAMM) simulates the dominant processes involved in</br>wetland conversions and shoreline modifications during long-term sea level rise. Tidal marshes can</br>be among the most susceptible ecosystems to climate change, especially accelerated sea level rise</br>(SLR).pecially accelerated sea level rise (SLR).)
  • Model:SBM  + (The Sorted Bedform Model (SBM) addresses the formation mechanism for sorted bedforms present on inner continental shelf environments.)
  • Model:SEOM  + (The Spectral Element Ocean Model (SEOM) soThe Spectral Element Ocean Model (SEOM) solves the hydrostatic, and alternatively the non-hydrostatic, primitive equations using a mixed spectral / finite element solution procedure. Potential advantages of the spectral element method include flexible incorporation of complex geometry and spatially dependent resolution, rapid convergence, and attractive performance on parallel computer systems. A 2D version of SEOM, which solves the shallow water equations, has been extensively tested on applications ranging from global tides to the abyssal circulation of the Eastern Mediterranean. The 3D SEOM is undergoing initial testing for later release.ergoing initial testing for later release.)
  • Model:The TELEMAC system  + (The TELEMAC system is a powerful integrateThe TELEMAC system is a powerful integrated modeling tool for use in the field of free-surface flows. The various simulation modules use high-capacity algorithms based on the finite-element method. Space is discretised in the form of an unstructured grid of triangular elements, which means that it can be refined particularly in areas of special interest. This avoids the need for systematic use of embedded models, as is the case with the finite-difference method.It has numerous applications in both river and maritime hydraulics.ons in both river and maritime hydraulics.)
  • Model:UEB  + (The Utah Energy Balance (UEB) snow model iThe Utah Energy Balance (UEB) snow model is an energy balance snowmelt model developed by David Tarboton's research group, first in 1994, and updated over the years. The model uses a lumped representation of the snowpack and keeps track of water and energy balance. The model is driven by inputs of air temperature, precipitation, wind speed, humidity and radiation at time steps sufficient to resolve the diurnal cycle (six hours or less). The model uses physically-based calculations of radiative, sensible, latent and advective heat exchanges. A force-restore approach is used to represent surface temperature, accounting for differences between snow surface temperature and average snowpack temperature without having to introduce additional state variables. Melt outflow is a function of the liquid fraction, using Darcy's law. This allows the model to account for continued outflow even when the energy balance is negative. Because of its parsimony (few state variables - but increasing with later versions) this model is suitable for application in a distributed fashion on a grid over a watershed.ibuted fashion on a grid over a watershed.)
  • Model:VIC  + (The VIC model is a large-scale, semi-distrThe VIC model is a large-scale, semi-distributed hydrologic model. As such, it shares several basic features with the other land surface models (LSMs) that are commonly coupled to global circulation models (GCMs):</br></br>The land surface is modelled as a grid of large (>1km), flat, uniform cells</br>Sub-grid heterogeneity (e.g. elevation, land cover) is handled via statistical distributions.</br>Inputs are time series of daily or sub-daily meteorological drivers (e.g. precipitation, air temperature, wind speed).</br>Land-atmosphere fluxes, and the water and energy balances at the land surface, are simulated at a daily or sub-daily time step</br>Water can only enter a grid cell via the atmosphere</br>Non-channel flow between grid cells is ignored</br>The portions of surface and subsurface runoff that reach the local channel network within a grid cell are assumed to be >> the portions that cross grid cell boundaries into neighboring cells</br>Once water reaches the channel network, it is assumed to stay in the channel (it cannot flow back into the soil)</br>This last point has several consequences for VIC model implementation:</br></br>Grid cells are simulated independently of each other</br>Entire simulation is run for each grid cell separately, 1 grid cell at a time, rather than, for each time step, looping over all grid cells</br>Meteorological input data for each grid cell (for the entire simulation period) are read from a file specific to that grid cell</br>Time series of output variables for each grid cell (for the entire simulation period) are stored in files specific to that grid cell</br>Routing of stream flow is performed separately from the land surface simulation, using a separate model (typically the routing model of Lohmann et al., 1996 and 1998)the routing model of Lohmann et al., 1996 and 1998))
  • Model:WEPP  + (The Water Erosion Prediction Project (WEPPThe Water Erosion Prediction Project (WEPP) model is a process-based, distributed parameter, continuous simulation erosion prediction model for application to hillslope profiles and small watersheds. Interfaces to WEPP allow its application as a stand-alone Windows program, a GIS-system (ArcView, ArcGIS) extension, or in web-based links. WEPP has been developed since 1985 by the U.S. Department of Agriculture for use on croplands, forestlands, rangelands, and other land use types.nds, rangelands, and other land use types.)
  • Model:WRF  + (The Weather Research and Forecasting (WRF)The Weather Research and Forecasting (WRF) Model is a next-generation mesoscale numerical weather prediction system designed to serve both operational forecasting and atmospheric research needs. It features multiple dynamical cores, a 3-dimensional variational (3DVAR) data assimilation system, and a software architecture allowing for computational parallelism and system extensibility. WRF is suitable for a broad spectrum of applications across scales ranging from meters to thousands of kilometers.ng from meters to thousands of kilometers.)
  • Model:WRF-Hydro  + (The Weather Research and Forecasting ModelThe Weather Research and Forecasting Model Hydrological modeling system (WRF-Hydro) was developed as a community-based, open source, model coupling framework designed to link multi-scale process models of the atmosphere and terrestrial hydrology to provide:</br></br>An extensible multi-scale & multi-physics land-atmosphere modeling capability for conservative, coupled and uncoupled assimilation & prediction of major water cycle components such as: precipitation, soil moisture, snow pack, ground water, streamflow, and inundation</br>Accurate and reliable streamflow prediction across scales (from 0-order headwater catchments to continental river basins and from minutes to seasons)</br>A research modeling testbed for evaluating and improving physical process and coupling representations.ing physical process and coupling representations.)
  • Model:CarboLOT  + (The carbonate production is modelled accorThe carbonate production is modelled according to organism growth and survival rates moderated by habitat suitability (chiefly light, temperature, nutrient). The environmental inputs are extracted from global databases. At the seabed the model's vertical zonation allows for underground (diagenetic) processes, bed granular transport, lower stable framework, upper collapsable framework. This voxelation allows for the carbonate to be placed (accumulated) correctly within the bedding and clast fabrics. The stratigraphy and seabed elevation are built in this way. As conditions change (e.g., by shallowing) the biological communities respond in the simulation, and so too do the production rates and clast/binding arrangements. Events punctuate the record, and the organism assemblages adjust according to frequencies and severities. The population stocks are calculated by diffuse competition in a Lotke-Volterra scheme, or via cellular simulations of close-in interactions to represent competition by growth, recruitment.resent competition by growth, recruitment.)
  • Model:Bedrock Fault Scarp  + (The code computes the formation of a hillsThe code computes the formation of a hillslope profile above an active normal fault. It represents the hillslope as a set of points with vertical and horizontal (fault-perpendicular) coordinates. Points move due to a prescribed erosion rate (which may vary in time) and due to offset during earthquakes with a specified recurrence interval and slip rate.</br></br>The model is described and illustrated in the following journal article:</br></br>Tucker, G. E., S. W. McCoy, A. C. Whittaker, G. P. Roberts, S. T. Lancaster, and R. Phillips (2011), Geomorphic significance of postglacial bedrock scarps on normal-fault footwalls, J. Geophys. Res., 116, F01022, doi: http://dx.doi.org/10.1029/2010JF001861.i: http://dx.doi.org/10.1029/2010JF001861.)
  • Model:DeltaRCM Vegetation  + (The delta-building model DeltaRCM expandedThe delta-building model DeltaRCM expanded to included vegetation effects. Vegetation colonizes, grows, and dies, and influences the delta through increasing bank stability and providing resistance to flow. Vegetation was implemented to represent marsh grass type plants, and parameters of stem diameter, carrying capacity, logistic growth rate, and rooting depth can be altered.th rate, and rooting depth can be altered.)
  • Model:HAMSOM  + (The development of the HAMSOM coding goes The development of the HAMSOM coding goes back to the mid eighties where it emerged from a fruitful co-operation between Backhaus and Maier-Reimer who later called his model 'HOPE'. From the very beginning HAMSOM was designed with the intention to allow simulations of both oceanic and coastal and shelf sea dynamics.</br></br>The primitive equation model with a free surface utilises two time-levels, and is defined in Z co-ordinates on the Arakawa C-grid. Stability constraints for surface gravity waves and the heat conduction equation are avoided by the implementation of implicit schemes. With a user defined weighting between future and presence time levels a hierarchy of implicit schemes is provided to solve for the free surface problem, and for the vertical transfer of momentum and water mass properties. In the time domain a scheme for the Coriolis rotation is incorporated which has second order accuracy. Time- and space-dependent vertical exchange and diffusivity coefficients are determined from a simple zero-order turbulence closure scheme which has also been replaced by a higher order closure scheme (GOTM). The resolution of a water column may degenerate to just one grid cell. At the seabed a non-linear (implicit) friction law as well as the full kinematic boundary condition is applied. Seabed cells may deviate from an undisturbed cell height to allow for a better resolution of the topography. The HAMSOM coding excludes any time-splitting, i.e. free surface and internal baroclinic modes are always directly coupled. Simple upstream and more sophisticated advection schemes for both momentum and matter may be run according to directives from the user.</br></br>Successful couplings with eco-system models (ECOHAM, ERSEM), an atmospheric model (REMO), and both Lagrangian and Eulerian models for sediment transport are reported in the literature. For polar applications HAMSOM was coupled with a viscous-plastic thermo-hydrodynamic ice model of Hibler type. Since about 15 years in Hamburg, and overseas in more than 30 laboratories, HAMSOM is already being in use as a community model.already being in use as a community model.)