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

Showing below up to 244 results starting with #1.

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    • Model:MarshPondModel  + (2D marsh evolution model focused on pond d2D marsh evolution model focused on pond dynamics. Channels are static features. Tidal transport is not directly simulated. Includes the effect of man-made ditches (i.e., localized subsidence).</br>It has companion website with pre-loaded simulations to be used by end-users.oaded simulations to be used by end-users.)
    • Model:2DFLOWVEL  + (2D unsteady nonlinear tidal & wind-driven coastal circulation)
    • Model:Sakura  + (3-equation hyperpycnal flow model.)
    • Model:Dionisos  + (3D basin-scale stratigraphic model)
    • Model:CellularFanDelta  + (3D cellular model simulating delta evolution in coarse grained river dominated systems (e.g. a gravel fan delta).)
    • Model:Cyclopath  + (A 2D or 3D model of carbonate sediment production and transport that generates high-frequency platform top auto and allocycles as well as various aspects of large scale platform geomtry)
    • Model:LakeMapperBarnes  + (A Landlab implementation of the Barnes et A Landlab implementation of the Barnes et al. (2014) lake filling & lake routing algorithms, lightly modified and adapted for Landlab by DEJH. This component is designed as a direct replacement for the LakeMapper as existing pre-Aug 2018, and provides a suite of properties to access information about the lakes created each time it is run. Only significant difference is the way the lakes are coded: this component uses the (unique) ID of the outlet node, whereas DepressionFinderAndRouter uses one of the pit node IDs. Note also this component does not offer the lake_codes or display_depression_map options, for essentially this reason. Use lake_map instead for both. It also uses a much more Landlabbian run_one_step() method as its driver, superceding DepressionFinderAndRouter’s map_depressions().</br></br>A variety of options is provided. Flow routing is route-to-one in this implementation, but can be either D4 (“steepest”) or D8 on a raster. The surface can be filled to either flat or a very slight downward incline, such that subsequent flow routing will run over the lake surface. This incline is applied at machine precision to minimize the chances of creating false outlets by overfill, and note that the gradient as calculated on such surfaces may still appear to be zero. The filling can either be performed in place, or on a new (water) surface distinct from the original (rock) surface. For efficiency, data structures describing the lakes and their properties are only created, and existing flow direction and flow accumulation fields modified, if those flags are set at instantiationified, if those flags are set at instantiation)
    • Model:Lithology  + (A Lithology is a three dimensional represeA Lithology is a three dimensional representation of material operated on by Landlab components. Material can be removed through erosion or added to through deposition. Rock types can have multiple attributes (e.g. age, erodibility or other parameter values, etc).odibility or other parameter values, etc).)
    • Model:NEXRAD-extract  + (A Python tool for extracting and/or plotting data from the NEXRAD (WSR-88D) Doppler weather radar network operated by the US National Weather Service. This can be used for inputs to models that require a meteorologic component.)
    • Model:ZoneTaxon  + (A ``ZoneTaxon`` is composed of members of A ``ZoneTaxon`` is composed of members of a lower taxonomic level that each exists within a ``Zone`` object. Taxonomic rank is not considered by this class despite the use of the term, 'speciation', which is used herein to generally describe creation of a child taxon object.</br></br>All zones of the taxon can be obtained with the attribute, ``zones`` that are the objects that manage the geographic aspect of taxon member populations. The total geographic extent of all populations is depicted by the ``range_mask`` attribute. The zones of a ZoneTaxon instance are created and updated using a ``ZoneController``. At model time steps, the connectivity of zones over time is obtained using attributes of the ``Zone`` object.</br></br>The evolution of this taxon type is carried out in two stages during a model time step. In the first stage, the zones of the taxon are updated as the result of zone connectivity between the prior and current step in the method, ``_update_zones``. This method is the primary implementation of taxon dispersal and it is called in a stage prior to other evolutionary processes so that all taxa are positioned in their landscape locations prior to the other processes.</br></br>In the second stage, processes are carried out in methods that are readily expanded or overridden when needed. The primary methods of second stage macroevolution are ``_evaluate_dispersal``, ``_evaluate_speciation``, and ``_evaluate_extinction``. The evaluate dispersal method is intended to modify dispersal conducted in the first stage and it has no effect unless it is expanded or overridden to have an effect. Processes other than those listed above can be called by expanding or overridding the ``_evolve`` method.</br></br>The taxon is allopatric when it is associated with/exists within multiple zones (signifying multiple member populations). A timer is started when a taxon becomes allopatric. Allopatric speciation occurs once the timer reaches or exceeds the ``time_to_allopatric_speciation`` initialization parameter. If the initialization parameter, ``persists_post_speciation`` is True (default), a child taxon is created in each zone except one zone (the largest by area) that becomes the sole zone of the taxon. If ``persists_post_speciation`` is set to False, a child taxon is created in each and every zone, and the parent no longer occupies any zones, and therefore the parent taxon is no longer extant.</br></br>Extinction occurs when the taxon is no longer associated with any zones. This occurs when zones in the prior time step do not overlap zones in the current time step, signifying the geographic range of the taxon is no more. A taxon can become no longer extant also when the taxon speciates and ``persists_post_speciation`` is False signifying that the parent taxon has evolved into multiple taxon distinct from the original taxon.le taxon distinct from the original taxon.)
    • Model:DECAL  + (A cellular automaton model for simulating the development of aeolian dune landscapes under the influence of vegetation and biota (parabolic dunes, blowouts, foredunes, nebkha dunes).)
    • Model:SpatialPrecipitationDistribution  + (A component to generate a sequence of spatA component to generate a sequence of spatially resolved storms over a grid, following a lightly modified version (see below) of the stochastic methods of Singer & Michaelides, Env Res Lett 12, 104011, 2017, & Singer et al., Geosci. Model Dev., accepted, 10.5194/gmd-2018-86. </br></br>The method is heavily stochastic, and at the present time is intimately calibrated against the conditions at Walnut Gulch, described in those papers. In particular, assumptions around intensity-duration calibration and orographic rainfall are "burned in" for now, and are not accessible to the user. The various probability distributions supplied to the various run methods default to WG values, but are easily modified. This calibration reflects a US desert southwest "monsoonal" climate, and the component distinguishes (optionally) between two seasons, "monsoonal" and "winter". The intensity-duration relationship is shared between the seasons, and so may prove useful in a variety of storm-dominated contexts.</br></br>The default is to disable the orographic rainfall functionality of the component. However, if orographic_scenario == 'Singer', the component requires a 'topographic__elevation' field to already exist on the grid at the time of instantiation.</br></br>The component has two ways of simulating a "year". This choice is controlled by the 'limit' parameter of the yield methods. If limit == 'total_rainfall', the component will continue to run until the total rainfall for the season and/or year exceeds a stochastically generated value. This method is directly comparable to the Singer & Michaelides method, but will almost always result in years which are not one calendar year long, unless the input distributions are very carefully recalibrated for each use case. If limit == 'total_time', the component will terminate a season and/or year once the elapsed time exceeds one year. In this case, the total rainfall will not correspond to the stochastically generated total. You can access the actual total for the last season using the property `(median_)total_rainfall_last_season`.</br></br>Note that this component cannot simulate the occurrence of more than one storm at the same time. Storms that should be synchronous will instead occur sequentially, with no interstorm time. This limitation means that if enough storms occur in a year that numstorms*mean_storm_duration exceeds one year, the number of simulated storms will saturate. This limitation may be relaxed in the future.</br></br>The component offers the option to modify the maximum number of storms simulated per year. If you find simulations encountering this limit too often, you may need to raise this limit. Conversely, it could be lowered to reduce memory usage over small grids. However, in increasing the value, beware - the component maintains two limit*nnodes arrays, which will chew through memory if the limit gets too high. The default will happily simulate grids up to around 50 km * 50 km using the default probability distributions.m * 50 km using the default probability distributions.)
    • Model:MARSSIM  + (A landform evolution model operating at the drainage basin or larger scale. Recent model development has targeted planetary applications.)
    • Model:CSt ASMITA  + (A length-, and time-averaged representatioA length-, and time-averaged representation of coastal system elements including the inner shelf, shoreface, surfzone, inlet, inlet shoals, and estuary channels and tidal flats. The multi-line nature of the morphodynamic model allows it to represent large-scale sediment transport processes with a combination time-average physics empirical relationships. A major use is to represent the interactions between system components to develop with changes in large scale forcing such as accelerated sea level rise, changes in river sediment input (ie. dams), changes in estuary tide prisms (ie. dikes) and the like.uary tide prisms (ie. dikes) and the like.)
    • Model:Marsh column model  + (A marsh column model designed to (ultimateA marsh column model designed to (ultimately) be inserted beneath spatially distributed marsh sedimentation models. Tracks surface biomass, subsurface root mass, carbon accumulation and decay (includes both labile and refractory carbon), inorganic sediments, and sediment compaction.rganic sediments, and sediment compaction.)
    • Model:LateralVerticalIncision  + (A model to explore how increasingly tall vA model to explore how increasingly tall valley walls constrain the river lateral erosion and promote vertical incision. Each run is unique as a random walk controls the lateral migration of the channel. To store and compare repeated runs with identical parameters, there is a built in system to save the results of each run.</br>This model is used to illustrate the wall feedback concept proposed by Malatesta, Prancevic, Avouac; 2017; JGR Eath-Surface; doi:10.1002/2015JF003797JGR Eath-Surface; doi:10.1002/2015JF003797)
    • Model:AgDegNormalGravMixHyd  + (A module that calculates the evolution of a gravel bed river under an imposed cycled hydrograph.)
    • Model:TwoPhaseEulerSedFoam  + (A multi-dimensional numerical model for seA multi-dimensional numerical model for sediment transport based on the two-phase</br>flow formulation is developed. With closures of particle stresses and fluid-particle interaction,</br>the model is able to resolve processes in the concentrated region of sediment</br>transport and hence does not require conventional bedload/suspended load assumptions.</br>The numerical model is developed in three spatial dimensions. However, in this version,</br>the model is only validated for Reynolds-averaged two-dimensional vertical (2DV) formulation</br>(with the k − epsilon closure for carrier flow turbulence) for sheet flow in steady and</br>oscillatory flows. This numerical model is developed via the open-source CFD library of</br>solvers, OpenFOAM and the new solver is called twoPhaseEulerSedFoam.new solver is called twoPhaseEulerSedFoam.)
    • Model:GNE  + (A multi-element (N, P, Si, C), multi-form A multi-element (N, P, Si, C), multi-form (particulate, dissolved, organic, inorganic) set of biogeochemical sub-models that predicts annual river exports to the coast as a function of basin-aggregated natural and human impact characteristics; GNE is a generic framework used to run the basin models.ic framework used to run the basin models.)
    • Model:OptimalCycleID  + (A numerical method to analyse a vertical succession of strata and identify the most cyclical arrangement of constituent facies using an optimised transition probability matrix approach)
    • Model:LaMEM  + (A parallel 3D numerical code that can be uA parallel 3D numerical code that can be used to model various thermomechanical geodynamical processes such as mantle-lithosphere interaction for rocks that have visco-elasto-plastic rheologies. The code is build on top of PETSc and the current version of the code uses a marker-in-cell approach with a staggered finite difference discretization.taggered finite difference discretization.)
    • Model:SEA  + (A primitive equation ocean general circulation model based on the Bryan--Semtner--Cox formulation and designed to give good performance on clusters of workstations and massively parallel machines using the PVM message passing library.)
    • Model:DeltaSIM  + (A process-response model simulating the evA process-response model simulating the evolution and stratigraphy of fluvial dominated deltaic systems in two dimensions, based on simple approximations of erosion and deposition. The model is called DELTASIM, and was initially presented by Overeem et al. (2003) as AQUATELLUS. DELTASIM has several improvements, the main algorithm has been revised and the output can be presented as probabilistic output. can be presented as probabilistic output.)
    • Model:LONGPRO  + (A program to calculate the dynamical evolution of a stream's longitudinal profile)
    • Model:PyDeCe  + (A python code for modeling the dense endmeA python code for modeling the dense endmember of pyroclastic density currents (PDCs) generated either by impulsive column collapse or sustained fountaining eruptions. Dense, particle rich PDC is modeled as solid-fluid mixture driven by gravity analogous to the granular flow models of Iverson and Denlinger (2001). Flow movement over real topography is realized by using a digital elevation model (DEM) file as one of the model inputs. Other model inputs include simulation time, flow density and viscosity, x and y coordinates (or longitude and latitude) of the source, among others, which are input to the model either using a config file or via command line arguments.config file or via command line arguments.)
    • Model:Hilltop and hillslope morphology extraction  + (A series of tools for extracting a networkA series of tools for extracting a network of hilltops from a landscape, computing curvature, slope and aspect over variable length scales from high resolution topography and performing hillslope traces from hilltops to valley bottoms to sample hilltop curvature, mean hillslope gradient and hillslope length. See Hurst et al. (2012) for full description. Hurst et al. (2012) for full description.)
    • Model:MCPM  + (A stand alone model for an idealized transA stand alone model for an idealized transect across a marsh channel-and-platform. The model simulates morphological evolution from sub-tidal to millennial time scales. In particular, the model explores the effect that soil creep (of both vegetated and unvegetated mud) has on channel bank dynamics, e.g., bank slumping. The model is written in Matlab. slumping. The model is written in Matlab.)
    • Model:Point-Tidal-flat  + (A stochastic point model for tidal flat evolution to study the influence of tidal currents and wind waves on tidal flat equilibrium.)
    • Model:BOM  + (A three-dimensional hydrodynamic multi-purA three-dimensional hydrodynamic multi-purpose model for coastal and shelf seas, which can be coupled to biological, re-suspension and contaminant models. Has been used in a variety of configurations from resolving grain-scale up to seasonal scale processes. Can be run with optional MPI parallelization or run-time visualization via PGPLOT. Programmed with the goal that the same executable can be used for all cases, by using allocatable arrays and cases defined via a single configuration file pointing to input data in files typically in the same directory. in files typically in the same directory.)
    • Model:SedFoam-2.0  + (A three-dimensional two-phase flow solver,A three-dimensional two-phase flow solver, SedFoam-2.0, is presented for sediment transport applications. The solver is extended upon twoPhaseEulerSedFoam (https://csdms.colorado.edu/wiki/Model:TwoPhaseEulerSedFoam). In this approach the sediment phase is modeled as a continuum, and constitutive laws have to be prescribed for the sediment stresses. In the proposed solver, two different inter-granular stress models are implemented: the kinetic theory of granular flows and the dense granular flow rheology μ(I). For the fluid stress, laminar or turbulent flow regimes can be simulated and three different turbulence models are available for sediment transport: a simple mixing length model (one-dimensional configuration only), a k-ϵ and a k-ω model. The numerical implementation is first demonstrated by two validation test cases, sedimentation of suspended particles and laminar bed-load. Two applications are then investigated to illustrate the capabilities of SedFoam-2.0 to deal with complex turbulent sediment transport problems, such as sheet flow and scouring, with different combinations of inter-granular stress and turbulence models.ter-granular stress and turbulence models.)
    • Model:Coastal Landscape Transect Model (CoLT)  + (A transect spanning three coastal ecosysteA transect spanning three coastal ecosystems (bay-marsh-forest) evolves in yearly timesteps to show the evolution of the system. Geomorphic and carbon cycling processes allow for the exchange of material between the adjacent ecosystems. Each landscape unit is on the order of kilometers. Main geomorphic processes are featured in Kirwan et al. 2016 in GRL, and carbon processes track allochthonous and autocthonous carbon with time and depth.d autocthonous carbon with time and depth.)
    • Model:FineSed3D  + (A turbulence-resolving numerical model forA turbulence-resolving numerical model for fine sediment transport in the bottom boundary layer is developed. A simplified Eulerian two-phase flow formulation for the fine sediment transport is adopted. By applying the equilibrium Eulerian approximation, the particle phase velocity is expressed as a vectorial sum of fluid velocity, sediment settling velocity and Stokes number dependent inertia terms. The Boussinesq approximation is applied to simplify the governing equation for the fluid phase. This model utilizes a high accuracy hybrid compact finite difference scheme in the wall-normal direction, and uses the pseudo-spectral scheme in the streamwise and spanwise directions. The model allows a prescribed sediment availability as well as an erosional/depositional bottom boundary condition for sediment concentration. Meanwhile, the model also has the capability to include the particle inertia effect and hindered settling effect for the particle velocity.settling effect for the particle velocity.)
    • Model:WAVEREF  + (A wave refraction program)
    • Model:ADCIRC  + (ADCIRC is a system of computer programs foADCIRC is a system of computer programs for solving time dependent, free surface circulation and transport problems in two and three dimensions. These programs utilize the finite element method in space allowing the use of highly flexible, unstructured grids. Typical ADCIRC applications have included:</br># modeling tides and wind driven circulation,</br># analysis of hurricane storm surge and flooding,</br># dredging feasibility and material disposal studies,</br># larval transport studies,</br># near shore marine operations.t studies, # near shore marine operations.)
    • Model:ALFRESCO  + (ALFRESCO was originally developed to simulALFRESCO was originally developed to simulate the response of subarctic vegetation to a changing climate and disturbance regime (Rupp et al. 2000a, 2000b). Previous research has highlighted both direct and indirect (through changes in fire regime) effects of climate on the expansion rate, species composition, and extent of treeline in Alaska (Rupp et al. 2000b, 2001, Lloyd et al. 2003). Additional research, focused on boreal forest vegetation dynamics, has emphasized that fire frequency changes – both direct (climate-driven or anthropogenic) and indirect (as a result of vegetation succession and species composition) – strongly influence landscape-level vegetation patterns and associated feedbacks to future fire regime (Rupp et al. 2002, Chapin et al. 2003, Turner et al. 2003). A detailed description of ALFRESCO can be obtained from the literature (Rupp et al. 2000a, 200b, 2001, 2002). The boreal forest version of ALFRESCO was developed to explore the interactions and feedbacks between fire, climate, and vegetation in interior Alaska (Rupp et al. 2002, 2007, Duffy et al. 2005, 2007) and associated impacts to natural resources (Rupp et al. 2006, Butler et al. 2007).es (Rupp et al. 2006, Butler et al. 2007).)
    • Model:AnugaSed  + (ANUGA is a hydrodynamic model for simulatiANUGA is a hydrodynamic model for simulating depth-averaged flows over 2D surfaces. This package adds two new modules (operators) to ANUGA. These are appropriate for reach-scale simulations of flows on mobile-bed streams with spatially extensive floodplain vegetation.</br></br>The mathematical framework for the sediment transport operator is described in Simpson and Castelltort (2006) and Davy and Lague (2009). This operator calculates an explicit sediment mass balance within the water column at every cell in order to handle the local disequilibria between entrainment and deposition that arise due to strong spatial variability in shear stress in complex flows.</br></br>The vegetation drag operator uses the mathematical approach of Nepf (1999) and Kean and Smith (2006), treating vegetation as arrays of objects (cylinders) that the flow must go around. Compared to methods that simulate the increased roughness of vegetation with a modified Manning's n, this method better accounts for the effects of drag on the body of the flow and the quantifiable differences between vegetation types and densities (as stem diameter and stem spacing). This operator can simulate uniform vegetation as well as spatially-varied vegetation across the domain. The vegetation drag module also accounts for the effects of vegetation on turbulent and mechanical diffusivity, following the equations in Nepf (1997, 1999).lowing the equations in Nepf (1997, 1999).)
    • Model:Anuga  + (ANUGA is a hydrodynamic modelling tool thaANUGA is a hydrodynamic modelling tool that allows users to model realistic flow problems in complex 2D geometries. Examples include dam breaks or the effects of natural hazards such as riverine flooding, storm surges and tsunami. The user must specify a study area represented by a mesh of triangular cells, the topography and bathymetry, frictional resistance, initial values for water level (called stage within ANUGA), boundary conditions and forces such as rainfall, stream flows, windstress or pressure gradients if applicable.</br>ANUGA tracks the evolution of water depth and horizontal momentum within each cell over time by solving the shallow water wave governing equation using a finite-volume method.</br></br>ANUGA also incorporates a mesh generator that allows the user to set up the geometry of the problem interactively as well as tools for interpolation and surface fitting, and a number of auxiliary tools for visualising and interrogating the model output.</br></br>Most ANUGA components are written in the object-oriented programming language Python and most users will interact with ANUGA by writing small Python scripts based on the ANUGA library functions. Computationally intensive components are written for efficiency in C routines working directly with Python numpy structures.ing directly with Python numpy structures.)
    • Model:Acronym1D  + (Acronym1D is an add on to Acronym1R in thaAcronym1D is an add on to Acronym1R in that it adds a flow duration curve to Acronym1R, which computes the volume bedload transport rate per unit width and bedload grain size distribution from a specified surface grain size distribution (with sand removed).ain size distribution (with sand removed).)
    • Model:Acronym1R  + (Acronym1R computes the volume bedload transport rate per unit width and bedload grain size distribution from a specified surface grain size distribution (with sand removed).)
    • Model:AeoLiS  + (AeoLiS is a process-based model for simulaAeoLiS is a process-based model for simulating aeolian sediment transport in situations where supply-limiting factors are important, like in coastal environments. Supply-limitations currently supported are soil moisture contents, sediment sorting and armouring, bed slope effects, air humidity and roughness elements.ects, air humidity and roughness elements.)
    • Model:FwDET  + (Allow for quick estimation of water depthsAllow for quick estimation of water depths within a flooded domain using only the flood extent layer (polygon) and a DEM of the area. Useful for near-real-time flood analysis, especially from remote sensing mapping.</br>Version 2.0 offers improved capabilities in coastal areas.rs improved capabilities in coastal areas.)
    • Model:Alpine3D  + (Alpine3D is a model for high resolution siAlpine3D is a model for high resolution simulation of alpine surface processes, in particular snow processes. The model can be forced by measurements from automatic weather stations or by meteorological model outputs (this is handled by the MeteoIO pre-processing library). The core three-dimensional Alpine3D modules consist of a radiation balance model (which uses a view factor approach and includes shortwave scattering and longwave emission from terrain and tall vegetation) and a drifting snow model solving a diffusion equation for suspended snow and a saltation transport equation. The processes in the atmosphere are thus treated in three dimensions and coupled to a distributed one dimensional model of vegetation, snow and soil model (Snowpack) using the assumption that lateral exchange is small in these media. The model can be used to force a distributed catchment hydrology model (AlpineFlow). The model modules can be run in a parallel mode, using either OpenMP and/or MPI. Finally, the Inishell tool provides a GUI for configuring and running Alpine3D.</br></br>Alpine3D is a valuable tool to investigate surface dynamics in mountains and is currently used to investigate snow cover dynamics for avalanche warning and permafrost development and vegetation changes under climate change scenarios. It could also be used to create accurate soil moisture assessments for meteorological and flood forecasting. for meteorological and flood forecasting.)
    • Model:WBMsed  + (An extension of the WBMplus (WBM/WTM) model. Introduce a riverine sediment flux component based on the BQART and Psi models.)
    • Model:GPM  + (Another derivative of the original SEDSIM,Another derivative of the original SEDSIM, completely rewritten from scratch. It uses finite differences (in addition to the original particle-cell method) to speed up steady flow calculations. It also incorporates compaction algorithms. A general description has been published. A general description has been published.)
    • Model:AquaTellUs  + (AquaTellUs models fluvial-dominated delta AquaTellUs models fluvial-dominated delta sedimentation. AquaTellUS uses a nested model approach; a 2D longitudinal profiles, embedded as a dynamical flowpath in a 3D grid-based space. A main channel belt is modeled as a 2D longitudinal profile that responds dynamically to changes in discharge, sediment load and sea level. Sediment flux is described by separate erosion and sedimentation components. Multiple grain-size classes are independently tracked. Erosion flux depends on discharge and slope, similar to process descriptions used in hill-slope models and is independent of grain-size. Offshore, where we assume unconfined flow, the erosion capacity decreases with increasing water depth. The erosion flux is a proxy for gravity flows in submarine channels close to the coast and for down-slope diffusion over the entire slope due to waves, tides and creep. Erosion is restricted to the main flowpath. This appears to be valid for the river-channel belt, but underestimates the spatial extent and variability of marine erosion processes.</br>Deposition flux depends on the stream velocity and on a travel-distance factor, which depends on grain size (i.e. settling velocity). The travel-distance factor is different in the fluvial and marine domains, which results in a sharp increase of the settling rate at the river mouth, mimicking bedload dumping.</br></br>Dynamic boundary conditions such as climatic changes over time are incorporated by increasing or decreasing discharge and sediment load for each time step.arge and sediment load for each time step.)
    • Model:BatTri  + (BATTRI does the mesh editing, bathymetry incorporation and interpolation, provides the grid generation and refinement properties, prepares the input file to Triangle and visualizes and saves the created grid.)
    • Model:BITM  + (BIT Model aims to simulate the dynamics ofBIT Model aims to simulate the dynamics of the principal processes that govern the formation and evolution of a barrier island. The model includes sea-level oscillations and sediment distribution operated by waves and currents. Each process determines the deposition of a distinct sediment facies, separately schematized in the spatial domain. Therefore, at any temporal step, it is possible to recognize six different stratigraphic units: bedrock, transitional, overwash, shoreface aeolian and lagoonal. overwash, shoreface aeolian and lagoonal.)
    • Model:BRaKE  + (BRaKE is a 1-D bedrock channel profile evoBRaKE is a 1-D bedrock channel profile evolution model. It calculates bedrock erosion in addition to treating the delivery, transport, degradation, and erosion-inhibiting effects of large, hillslope-derived blocks of rock. It uses a shear-stress bedrock erosion formulation with additional complexity related to flow resistance, block transport and erosion, and delivery of blocks from the hillslopes.nd delivery of blocks from the hillslopes.)
    • Model:Barrier3D  + (Barrier3D is an exploratory model that resBarrier3D is an exploratory model that resolves cross-shore and alongshore topographic variations to simulate the morphological evolution of a barrier segment over time scales of years to centuries. Barrier3D tackles the scale separation between event-based and long-term models by explicitly yet efficiently simulating dune evolution, storm overwash, and a dynamically evolving shoreface in response to individual storm events and sea-level rise. Ecological-geomorphological couplings of the barrier interior can be simulated with a shrub expansion and mortality module.th a shrub expansion and mortality module.)
    • Model:BarrierBMFT  + (BarrierBMFT is a coupled model framework fBarrierBMFT is a coupled model framework for exploring morphodynamic interactions across components of the entire coastal barrier system, from the ocean shoreface to the mainland forest. The model framework couples Barrier3D (Reeves et al., 2021), a spatially explicit model of barrier evolution, with the Python version of the Coastal Landscape Transect model (CoLT; Valentine et al., 2023), known as PyBMFT-C (Bay-Marsh-Forest Transect Model with Carbon). In the BarrierBMFT coupled model framework, two PyBMFT-C simulations drive evolution of back-barrier marsh, bay, mainland marsh, and forest ecosystems, and a Barrier3D simulation drives evolution of barrier and back-barrier marsh ecosystems. As these model components simultaneously advance, they dynamically evolve together by sharing information annually to capture the effects of key cross-landscape couplings. BarrierBMFT contains no new governing equations or parameterizations itself, but rather is a framework for trading information between Barrier3D and PyBMFT-C.</br></br>The use of this coupled model framework requires Barrier3D v2.0 (https://doi.org/10.5281/zenodo.7604068)</br> and PyBMFT-C v1.0 (https://doi.org/10.5281/zenodo.7853803). (https://doi.org/10.5281/zenodo.7853803).)
    • Model:RiverSynth  + (Based on the publication: Brown, RA, PastBased on the publication:</br></br>Brown, RA, Pasternack, GB, Wallender, WW. 2013. Synthetic River Valleys: Creating Prescribed Topography for Form-Process Inquiry and River Rehabilitation Design. Geomorphology 214: 40–55. http://dx.doi.org/10.1016/j.geomorph.2014.02.025/dx.doi.org/10.1016/j.geomorph.2014.02.025)
    • Model:Badlands  + (Basin and Landscape Dynamics (Badlands) isBasin and Landscape Dynamics (Badlands) is a parallel TIN-based landscape evolution model, built to simulate topography development at various space and time scales. The model is presently capable of simulating hillslope processes (linear diffusion), fluvial incision ('modified' SPL: erosion/transport/deposition), spatially and temporally varying geodynamic (horizontal + vertical displacements) and climatic forces which can be used to simulate changes in base level, as well as effects of climate changes or sea-level fluctuations.climate changes or sea-level fluctuations.)
    • Model:Bifurcation  + (Bifurcation is a morphodynamic model of a Bifurcation is a morphodynamic model of a river delta bifurcation. Model outputs include flux partitioning and 1D bed elevation profiles, all of which can evolve through time. Interaction between the two branches occurs in the reach just upstream of the bifurcation, due to the development of a transverse bed slope. Aside from this interaction, the individual branches are modeled in 1D. </br></br>The model generates ongoing avulsion dynamics automatically, arising from the interaction between an upstream positive feedback and the negative feedback from branch progradation and/or aggradation. Depending on the choice of parameters, the model generates symmetry, soft avulsion, or full avulsion. Additionally, the model can include differential subsidence. It can also be run under bypass conditions, simulating the effect of an offshore sink, in which case ongoing avulsion dynamics do not occur.</br></br>Possible uses of the model include the study of avulsion, bifurcation stability, and the morphodynamic response of bifurcations to external changes.ponse of bifurcations to external changes.)
    • Model:Bio  + (Biogenic mixing of marine sediments)
    • Model:BlockLab  + (Blocklab treats landscape evolution in lanBlocklab treats landscape evolution in landscapes where surface rock may be released as large blocks of rock. The motion, degradation, and effects of large blocks do not play nicely with standard continuum sediment transport theory. BlockLab is intended to incorporate the effects of these large grains in a realistic way. of these large grains in a realistic way.)
    • Model:Caesar  + (CAESAR is a cellular landscape evolution model, with an emphasis on fluvial processes, including flow routing, multi grainsize sediment transport. It models morphological change in river catchments.)
    • Model:CHILD  + (CHILD computes the time evolution of a topographic surface z(x,y,t) by fluvial and hillslope erosion and sediment transport.)
    • Model:CICE  + (CICE is a computationally efficient model CICE is a computationally efficient model for simulating the growth, melting, and movement of polar sea ice. Designed as one component of coupled atmosphere-ocean-land-ice global climate models, today’s CICE model is the outcome of more than two decades of community collaboration in building a sea ice model suitable for multiple uses including process studies, operational forecasting, and climate simulation.ional forecasting, and climate simulation.)
    • Model:CLUMondo  + (CLUMondo is based on the land systems apprCLUMondo is based on the land systems approach. Land systems are socio-ecological systems that reflect land use in a spatial unit in terms of land cover composition, spatial configuration, and the management activities employed. The precise definition of land systems depends on the scale of analysis, the purpose of modelling, and the case study region. In contrast to land cover classifications the role of land use intensity and livestock systems are explicitly addressed. Each land system can be characterized in terms of the fractional land covers.<br>Land systems are characterized based on the amount of forest in the landscape mosaic and the management type ranging from swidden cultivation to permanent cultivation and plantations.vation to permanent cultivation and plantations.)
    • Model:CAESAR Lisflood  + (Caesar Lisflood is a geomorphological / LaCaesar Lisflood is a geomorphological / Landscape evolution model that combines the Lisflood-FP 2d hydrodynamic flow model (Bates et al, 2010) with the CAESAR geomorphic model to simulate erosion and deposition in river catchments and reaches over time scales from hours to 1000's of years.</br></br>Featuring:</br>Landscape evolution model simulating erosion and deposition across river reaches and catchments</br></br>A hydrodynamic 2D flow model (based on the Lisflood FP code) that conserves mass and partial momentum. (model can be run as flow model alone)</br></br>designed to operate on multiple core processors (parallel processing of core functions)</br></br>Operates over a wide range to spatial and time scales (1km2 to 1000km2, <1year to 1000+ years)</br></br>Easy to use GUI2, <1year to 1000+ years) Easy to use GUI)
    • Model:PsHIC  + (Calculate the hypsometric integral for each pixel at the catchment. Each pixel is considered a local outlet and the hypsometric integral is calculated according to the characteristics of its contributing area.)
    • Model:OceanWaves  + (Calculate wave-generated bottom orbital velocities from measured surface wave parameters. Also permits calculation of surface wave spectra from wind conditions, from which bottom orbital velocities can be determined.)
    • Model:SUSP  + (Calculates non-equilibrium suspended load transport rates of various size-density fractions in the bed)
    • Model:SVELA  + (Calculates shear velocity associated with grain roughness)
    • Model:BEDLOAD  + (Calculates the bedload transport rates and weights per unit area for each size-density. NB. Bedload transport of different size-densities is proportioned according to the volumes in the bed.)
    • Model:SETTLE  + (Calculates the constant terminal settling velocity of each size-density fraction's median size from Dietrich's equation.)
    • Model:ENTRAINH  + (Calculates the critical Shields Theta for the median size of a distribution and then calculates the critical shear stress of the ith, jth fraction using a hiding function)
    • Model:ENTRAIN  + (Calculates the critical shear stress for entrainment of the median size of each size-density fraction of a bed using Yalin and Karahan formulation, assuming no hiding)
    • Model:FLDTA  + (Calculates the flow velocity and depth based on the gradually varied flow equation of an open channel.)
    • Model:TURB  + (Calculates the gaussian or log-gaussian distribution of instantaneous shear stresses on the bed, given a mean and coefficient of variation.)
    • Model:LOGDIST  + (Calculates the logrithmic velocity distribution called from TRCALC)
    • Model:YANGs  + (Calculates the total sediment transport rate in an open channel assuming a median bed grain size)
    • Model:SuspSedDensityStrat  + (Calculation of Density Stratification EffeCalculation of Density Stratification Effects Associated with Suspended Sediment in Open Channels.</br></br>This program calculates the effect of sediment self-stratification on the streamwise velocity and suspended sediment concentration profiles in open-channel flow.</br></br>Two options are given. Either the near-bed reference concentration Cr can be specified by the user, or the user can specify a shear velocity due to skin friction u*s and compute Cr from the Garcia-Parker sediment entrainment relation.rcia-Parker sediment entrainment relation.)
    • Model:SubsidingFan  + (Calculation of Sediment Deposition in a Fan-Shaped Basin, undergoing Piston-Style Subsidence)
    • Model:DeltaBW  + (Calculator for 1D Subaerial Fluvial Fan-DeCalculator for 1D Subaerial Fluvial Fan-Delta with Channel of Constant Width. This model assumes a narrowly channelized 1D fan-delta prograding into standing water. The model uses a single grain size D, a generic total bed material load relation and a constant bed resistance coefficient. The channel is assumed to have a constant width. Water and sediment discharge are specified per unit width. The fan builds outward by forming a prograding delta front with an assigned foreset slope. The code employs a full backwater calculation.code employs a full backwater calculation.)
    • Model:DeltaNorm  + (Calculator for 1D Subaerial Fluvial Fan-DeCalculator for 1D Subaerial Fluvial Fan-Delta with Channel of Constant Width. This model assumes a narrowly channelized 1D fan-delta prograding into standing water. The model uses a single grain size D, a generic total bed material load relation and a constant bed resistance coefficient. The channel is assumed to have a constant width. Water and sediment discharge are specified per unit width. The fan builds outward by forming a prograding delta front with an assigned foreset slope. The code employs the normal flow approximation rather than a full backwater calculation. rather than a full backwater calculation.)
    • Model:CarboCAT  + (CarboCAT uses a cellular automata to model horizontal and vertical distributions of carbonate lithofacies)
    • Model:ChesROMS  + (ChesROMS is a community ocean modeling sysChesROMS is a community ocean modeling system for the Chesapeake Bay region being developed by scientists in NOAA, University of Maryland, CRC (Chesapeake Research Consortium) and MD DNR (Maryland Department of Natural Resources) supported by the NOAA MERHAB program. The model is built based on the Rutgers Regional Ocean Modeling System (ROMS, http://www.myroms.org/) with significant adaptations for the Chesapeake Bay.</br></br>The model is developed to provide a community modeling system for nowcast and forecast of 3D hydrodynamic circulation, temperature and salinity, sediment transport, biogeochemical and ecosystem states with applications to ecosystem and human health in the bay. Model validation is based on bay wide satellite remote sensing, real-time in situ measurements and historical data provided by Chesapeake Bay Program.</br></br>http://ches.communitymodeling.org/models/ChesROMS/index.phpnitymodeling.org/models/ChesROMS/index.php)
    • Model:Cliffs  + (Cliffs features: Shallow-Water approximatCliffs features: </br>Shallow-Water approximation;</br>Use of Cartesian or spherical (lon/lat) coordinates;</br>1D and 2D configurations;</br>Structured co-located grid with (optionally) varying spacing;</br>Run-up on land;</br>Initial conditions or boundary forcing;</br>Grid nesting with one-way coupling;</br>Parallelized with OpenMP;</br>NetCDF format of input/output data.</br></br>Cliffs utilizes VTCS-2 finite-difference scheme and dimensional splitting as in (Titov and Synolakis, 1998), and reflection and inundation computations as in (Tolkova, 2014). </br></br>References: </br>Titov, V.V., and C.E. Synolakis. Numerical modeling of tidal wave runup. J. Waterw. Port Coast. Ocean Eng., 124(4), 157–171 (1998)</br>Tolkova E. Land-Water Boundary Treatment for a Tsunami Model With Dimensional Splitting.</br>Pure and Applied Geophysics, 171(9), 2289-2314 (2014)plied Geophysics, 171(9), 2289-2314 (2014))
    • Model:Barrier Inlet Environment (BRIE) Model  + (Coastal barrier model that simulates storm overwash and tidal inlets and estimates coastal barrier transgression resulting from sea-level rise.)
    • Model:Detrital Thermochron  + (Code for estimating long-term exhumation histories and spatial patterns of short-term erosion from the detrital thermochronometric data.)
    • Model:MRSAA  + (Code functionality and purpose may be founCode functionality and purpose may be found in the following references:</br></br>References</br># Zhang L., Parker, G., Stark, C.P., Inoue, T., Viparelli, V., Fu, X.D., and Izumi, N. 2015, "Macro-roughness model of bedrock–alluvial river morphodynamics", Earth Surface Dynamics, 3, 113–138.</br># Zhang, L., Stark, C.P., Schumer, R., Kwang, J., Li, T.J., Fu, X.D., Wang, G.Q., and Parker, G. 2017, "The advective-diffusive morphodynamics of mixed bedrock-alluvial rivers subjected to spatiotemporally varying sediment supply" (submitted to JGR)arying sediment supply" (submitted to JGR))
    • Model:Compact  + (Compact a sediment column)
    • Model:GRLP  + (Computes transient (semi-implicit numericaComputes transient (semi-implicit numerical) and steady-state (analytical and numerical) solutions for the long-profile evolution of transport-limited gravel-bed rivers. Such rivers are assumed to have an equilibrium width (following Parker, 1978), experience flow resistance that is proportional to grain size, evolve primarily in response to a single dominant "channel-forming" or "geomorphically-effective" discharge (see Blom et al., 2017, for a recent study and justification of this assumption and how it can be applied), and transport gravel following the Meyer-Peter and Müller (1948) equation. This combination of variables results in a stream-power-like relationship for bed-material sediment discharge, which is then inserted into a valley-resolving Exner equation to compute long-profile evolution.quation to compute long-profile evolution.)
    • Model:CruAKTemp  + (CruAKtemp is a python 2.7 package that is CruAKtemp is a python 2.7 package that is a data component which serves to provide onthly temperature data over the 20th century for permafrost modeling. The original dataset at higher resolution can be found here:</br>http://ckan.snap.uaf.edu/dataset/historical-monthly-and-derived-temperature-products-771m-cru-ts</br>The geographical extent of this CRUAKtemp dataset has been reduced to greatly reduce the number of ocean or Canadian pixels. Also, the spatial resolution has been reduced by a factor of 13 in each direction, resulting in an effective pixel resolution of about 10km.</br>The data are monthly average temperatures for each month from January 1901 through December 2009.h from January 1901 through December 2009.)
    • Model:DFMFON  + (DFMFON stands for Delft3D-Flexible Mesh (DDFMFON stands for Delft3D-Flexible Mesh (DFM), and MesoFON (MFON) is an open-source software written in Python to simulate the Mangrove and Hydromorphology development mechanistically. We achieve that by coupling the multi-paradigm of the individual-based mangrove model MFON and process-based hydromorphodynamic model DFM.rocess-based hydromorphodynamic model DFM.)
    • Model:DHSVM  + (DHSVM is a distributed hydrology model thaDHSVM is a distributed hydrology model that was developed at the University of Washington more than ten years ago. It has been applied both operationally, for streamflow prediction, and in a research capacity, to examine the effects of forest management on peak streamflow, among other things.nt on peak streamflow, among other things.)
    • Model:DR3M  + (DR3M is a watershed model for routing storDR3M is a watershed model for routing storm runoff through a Branched system of pipes and (or) natural channels using rainfall as input. DR3M provides detailed simulation of storm-runoff periods selected by the user. There is daily soil-moisture accounting between storms. A drainage basin is represented as a set of overland-flow, channel, and reservoir segments, which jointly describe the drainage features of the basin. This model is usually used to simulate small urban basins. Interflow and base flow are not simulated. Snow accumulation and snowmelt are not simulated.cumulation and snowmelt are not simulated.)
    • Model:DROG3D  + (DROG3D tracks passive drogues with given harmonic velocity field(s) in a 3-D finite element mesh)
    • Model:Dakotathon  + (Dakota is a software toolkit, developed atDakota is a software toolkit, developed at Sandia National Laboratories, that provides an interface between models and a library of analysis methods, including support for sensitivity analysis, uncertainty quantification, optimization, and calibration techniques. Dakotathon is a Python package that wraps and extends Dakota’s file-based user interface. It simplifies the process of configuring and running a Dakota experiment, and it allows a Dakota experiment to be scripted. Any model written in Python that exposes a Basic Model Interface (BMI), as well as any model componentized in the CSDMS modeling framework, automatically works with Dakotathon. Currently, six Dakota analysis methods have been implemented from the much larger Dakota library:</br></br>* vector parameter study,</br>* centered parameter study,</br>* multidim parameter study,</br>* sampling,</br>* polynomial chaos, and</br>* stochastic collocation.omial chaos, and * stochastic collocation.)
    • Model:CMIP  + (Data component processed from the CRU-NCEPData component processed from the CRU-NCEP Climate Model Intercomparison Project - 5, also called CMIP 5. Data presented include the mean annual temperature for each gridcell, mean July temperature and mean January temperature over the period 1902 -2100. This dataset presents the mean of the CMIP5 models, and the original climate models were run for the representative concentration pathway RCP 8.5.resentative concentration pathway RCP 8.5.)
    • Model:DeltaRCM  + (DeltaRCM is a parcel-based cellular flux rDeltaRCM is a parcel-based cellular flux routing and sediment transport model for the formation of river deltas, which belongs to the broad category of rule-based exploratory models. It has the ability to resolve emergent channel behaviors including channel bifurcation, avulsion and migration. Sediment transport distinguishes two types of sediment: sand and mud, which have different transport and deposition/erosion rules. Stratigraphy is recorded as the sand fraction in layers.</br>Best usage of DeltaRCM is the investigation of autogenic processes in response to external forcings.rocesses in response to external forcings.)
    • Model:Demeter  + (Demeter is an open source Python package tDemeter is an open source Python package that was built to disaggregate projections of future land allocations generated by an integrated assessment model (IAM). Projected land allocation from IAMs is traditionally transferred to Earth System Models (ESMs) in a variety of gridded formats and spatial resolutions as inputs for simulating biophysical and biogeochemical fluxes. Existing tools for performing this translation generally require a number of manual steps which introduces error and is inefficient. Demeter makes this process seamless and repeatable by providing gridded land use and land cover change (LULCC) products derived directly from an IAM—in this case, the Global Change Assessment Model (GCAM)—in a variety of formats and resolutions commonly used by ESMs.ats and resolutions commonly used by ESMs.)
    • Model:WPHydResAMBL  + (Depth-Discharge and Bedload Calculator, uses: # Wright-Parker formulation for flow resistance (without stratification correction) # Ashida-Michiue formulation for bedload transport.)
    • Model:DepDistTotLoadCalc  + (Depth-Discharge and Total Load Calculator, uses: # Wright-Parker formulation for flow resistance, # Ashida-Michiue formulation for bedload transport, # Wright-Parker formulation (without stratification) for suspended load.)
    • Model:Mosartwmpy  + (Derived from MOSART-WM (Model for Scale AdDerived from MOSART-WM (Model for Scale Adaptive River Transport with Water Management), mosasrtwmpy is a large-scale river-routing Python model used to study riverine dynamics of water, energy, and biogeochemistry cycles across local, regional, and global scales. The water management component represents river regulation through reservoir storage and release operations, diversions from reservoir releases, and allocation to sectoral water demands. The model allows an evaluation of the impact of water management over multiple river basins at once (global and continental scales) with consistent representation of human operations over the full domain. of human operations over the full domain.)
    • Model:Diffusion  + (Diffusion of marine sediments)
    • Model:FlowDirectorDinf  + (Directs flow by the D infinity method (Tarboton, 1997). Each node is assigned two flow directions, toward the two neighboring nodes that are on the steepest subtriangle. Partitioning of flow is done based on the aspect of the subtriangle.)
    • Model:FlowDirectorMFD  + (Directs flow by the multiple flow directioDirects flow by the multiple flow direction method. Each node is assigned multiple flow directions, toward all of the N neighboring nodes that are lower than it. If none of the neighboring nodes are lower, the location is identified as a pit. Flow proportions can be calculated as proportional to slope or proportional to the square root of slope, which is the solution to a steady kinematic wave.s the solution to a steady kinematic wave.)
    • Model:Dorado  + (Dorado is a Python package for simulating passive Lagrangian particle transport over flow-fields from any 2D shallow-water hydrodynamic model using a weighted random walk methodology.)
    • Model:DynEarthSol3D  + (DynEarthSol3D (Dynamic Earth Solver in ThrDynEarthSol3D (Dynamic Earth Solver in Three Dimensions) is a flexible, open-source finite element code that solves the momentum balance and the heat transfer in Lagrangian form using unstructured meshes. It can be used to study the long-term deformation of Earth's lithosphere and problems alike.of Earth's lithosphere and problems alike.)
    • Model:ECSimpleSnow  + (ECSimpleSnow is a simple snow model that employs an empirical algorithm to melt or accumulate snow based on surface temperature and precipitation that has fallen since the previous analysis step.)
    • Model:EF5  + (EF5 was created by the Hydrometeorology anEF5 was created by the Hydrometeorology and Remote Sensing Laboratory at the University of Oklahoma. The goal of EF5 is to have a framework for distributed hydrologic modeling that is user friendly, adaptable, expandable, all while being suitable for large scale (e.g. continental scale) modeling of flash floods with rapid forecast updates. Currently EF5 incorporates 3 water balance models including the Sacramento Soil Moisture Accouning Model (SAC-SMA), Coupled Routing and Excess Storage (CREST), and hydrophobic (HP). These water balance models can be coupled with either linear reservoir or kinematic wave routing.inear reservoir or kinematic wave routing.)
    • Model:ELCIRC  + (ELCIRC is an unstructured-grid model desigELCIRC is an unstructured-grid model designed for the effective simulation of 3D baroclinic circulation across river-to-ocean scales. It uses a finite-volume/finite-difference 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. The numerical algorithm is low-order, but volume conservative, stable and computationally efficient. It also naturally incorporates wetting and drying of tidal flats. ELCIRC has been extensively tested against standard ocean/coastal benchmarks, and is starting to be applied to estuaries and continental shelves around the world. and continental shelves around the world.)
    • Model:Ecopath with Ecosim  + (Ecopath with Ecosim (EwE) is an ecologicalEcopath with Ecosim (EwE) is an ecological modeling software suite for personal computers. EwE has three main components: Ecopath – a static, mass-balanced snapshot of the system; Ecosim – a time dynamic simulation module for policy exploration; and Ecospace – a spatial and temporal dynamic module primarily designed for exploring impact and placement of protected areas. The Ecopath software package can be used to:</br>*Address ecological questions;</br>*Evaluate ecosystem effects of fishing;</br>*Explore management policy options;</br>*Evaluate impact and placement of marine protected areas;</br>*Evaluate effect of environmental changes.*Evaluate effect of environmental changes.)
    • Model:Erode  + (Erode is a raster-based, fluvial landscape evolution model. The newest version (3.0) is written in Python and contains html help pages when running the program through the CSDMS Modeling Tool CMT (https://csdms.colorado.edu/wiki/Help:Ccaffeine_GUI).)
    • Model:Erode-D8-Local  + (Erode-D8-Global is a raster, D8-based fluvial landscape evolution model (LEM))
    • Model:LuSS  + (Exposures to heat and sunlight can be simulated and the resulting signals shown. For a detailed description of the underlying luminescence rate equations, or to cite your use of LuSS, please use Brown, (2020).)
    • Model:SINUOUS  + (Extended description for SINUOUS - MeanderExtended description for SINUOUS - Meander Evolution Model. The basic model simulates planform evolution of a meandering river starting from X,Y coordinates of centerline nodes, with specification of cross-sectional and flow parameters. If the model is intended to simulate evolution of an existing river, the success of the model can be evaluated by the included area between the simulated and the river centerline. In addition, topographic evolution of the surrounding floodplain can be simulated as a function of existing elevation, distance from the nearest channel, and time since the channel migrated through that location. Profile evolution of the channel can also be modeled by backwater flow routing and bed sediment transport relationships. and bed sediment transport relationships.)
    • Model:FACET  + (FACET is a Python tool that uses open sourFACET is a Python tool that uses open source modules to map the floodplain extent and derive reach-scale summaries of stream and floodplain geomorphic measurements from high-resolution digital elevation models (DEMs). Geomorphic measurements include channel width, stream bank height, floodplain width, and stream slope.<br>Current tool functionality is only meant to process DEMs within the Chesapeake Bay and Delaware River watersheds. FACET was developed to batch process 3-m resolution DEMs in the Chesapeake Bay and Delaware River watersheds. Future updates to FACET will allow users to process DEMs outside of the Chesapeake and Delaware basins.<br>FACET allows the user to hydrologically condition the DEM, generate the stream network, select one of two options for stream bank identification, map the floodplain extent using a Height Above Nearest Drainage (HAND) approach, and calculate stream and floodplain metrics using three approaches. stream and floodplain metrics using three approaches.)
    • Model:FUNWAVE  + (FUNWAVE is a phase-resolving, time-stepping Boussinesq model for ocean surface wave propagation in the nearshore.)
    • Model:FVCOM  + (FVCOM is a prognostic, unstructured-grid, FVCOM is a prognostic, unstructured-grid, finite-volume, free-surface, 3-D primitive equation coastal ocean circulation model developed by UMASSD-WHOI joint efforts. The model consists of momentum, continuity, temperature, salinity and density equations and is closed physically and mathematically using turbulence closure submodels. The horizontal grid is comprised of unstructured triangular cells and the irregular bottom is preseented using generalized terrain-following coordinates. The General Ocean Turbulent Model (GOTM) developed by Burchard’s research group in Germany (Burchard, 2002) has been added to FVCOM to provide optional vertical turbulent closure schemes. FVCOM is solved numerically by a second-order accurate discrete flux calculation in the integral form of the governing equations over an unstructured triangular grid. This approach combines the best features of finite-element methods (grid flexibility) and finite-difference methods (numerical efficiency and code simplicity) and provides a much better numerical representation of both local and global momentum, mass, salt, heat, and tracer conservation. The ability of FVCOM to accurately solve scalar conservation equations in addition to the topological flexibility provided by unstructured meshes and the simplicity of the coding structure has make FVCOM ideally suited for many coastal and interdisciplinary scientific applications.interdisciplinary scientific applications.)
    • Model:FallVelocity  + (Fall velocity for spheres. Uses formulation of Dietrich (1982))
    • Model:Zscape  + (Finite difference approximations are greatFinite difference approximations are great for modeling the erosion of landscapes. A paper by Densmore, Ellis, and Anderson provides details on application of landscape evolution models to the Basin and Range (USA) using complex rulesets that include landslides, tectonic displacements, and physically-based algorithms for hillslope sediment transport and fluvial transport. The solution given here is greatly simplified, only including the 1D approximation of the diffusion equation. The parallel development of the code is meant to be used as a class exercisede is meant to be used as a class exercise)
    • Model:SIMSAFADIM  + (Finite element process based simulation model for fluid flow, clastic, carbonate and evaporate sedimentation.)
    • Model:SoilInfiltrationGreenAmpt  + (For each time step, this component calculates an infiltration rate for a given model location and updates surface water depths. Based on the Green-Ampt method, it follows the form of Julien et al., 1995.)
    • Model:Mocsy  + (Fortran 95 routines to model the ocean carFortran 95 routines to model the ocean carbonate system (mocsy). Mocsy take as input dissolved inorganic carbon CT and total alkalinity AT, the only two tracers of the ocean carbonate system that are unaffected by changes in temperature and salinity and conservative with respect to mixing, properties that make them ideally suited for ocean carbon models. With basic thermodynamic equilibria, mocsy compute surface-ocean pCO2 in order to simulate air-sea CO2 fluxes. The mocsy package goes beyond the OCMIP code by computing all other carbonate system variables (e.g., pH, CO32-, and CaCO3 saturation states) and by doing so throughout the water column.d by doing so throughout the water column.)
    • Model:FuzzyReef  + (FuzzyReef is a three-dimensional (3D) numeFuzzyReef is a three-dimensional (3D) numerical stratigraphic model that simulates the development of microbial reefs using fuzzy logic (multi-valued logic) modeling methods. The flexibility of the model allows for the examination of a large number of variables. This model has been used to examine the importance of local environmental conditions and global changes on the frequency of reef development relative to the temporal and spatial constraints from Upper Jurassic (Oxfordian) Smackover reef datasets from two Alabama oil fields.</br></br>The fuzzy model simulates the deposition of reefs and carbonate facies through integration of local and global variables. Local-scale factors include basement relief, sea-level change, climate, latitude, water energy, water depth, background sedimentation rate, and substrate conditions. Regional and global-scale changes include relative sea-level change, climate, and latitude.e sea-level change, climate, and latitude.)
    • Model:GENESIS  + (GENESIS calculates shoreline change producGENESIS calculates shoreline change produced by statial and temporal differences in longshore sand transport produced by breaking waves. The shoreline evolution portion of the numerical modeling system is based on one-line shoreline change theory, which assumes that the beach profile shape remains unchanged, allowing shoreline change to be described uniquely in terms of the translation of a single point (for example, Mean High Water shoreline) on the profile.Mean High Water shoreline) on the profile.)
    • Model:GEOMBEST  + (GEOMBEST is a morphological-behaviour model that simulates the evolution of coastal morphology and stratigraphy resulting from changes in sea level and sediment volume within the shoreface, barrier, and estuary.)
    • Model:GEOMBEST++  + (GEOMBEST++ is a morphological-behaviour moGEOMBEST++ is a morphological-behaviour model that simulates the evolution of coastal morphology and stratigraphy resulting from changes in sea level and sediment volume within the shoreface, barrier, and estuary. GEOMBEST++ builds on previous iterations (i.e. GEOMBEST+) by incorporating the effects of waves into the backbarrier, providing a more physical basis for the evolution of the bay bottom and introducing wave erosion of marsh edges.d introducing wave erosion of marsh edges.)
    • Model:GEOMBEST++Seagrass  + (GEOMBEST++Seagrass is a morphological-behaGEOMBEST++Seagrass is a morphological-behaviour model that simulates the evolution of coastal morphology and stratigraphy resulting from changes in sea level and sediment volume within the shoreface, barrier, and estuary. GEOMBEST++Seagrass builds on previous iterations (i.e. GEOMBEST, GEOMBEST+, and GEOMBEST++) by incorporating seagrass dynamics into the back-barrier bay.agrass dynamics into the back-barrier bay.)
    • Model:GEOtop  + (GEOtop accommodates very complex topographGEOtop accommodates very complex topography and, besides the water balance integrates all the terms in the surface energy balance equation. For saturated and unsaturated subsurface flow, it uses the 3D Richards’ equation. An accurate treatment of radiation inputs is implemented in order to be able to return surface temperature.</br></br>The model GEOtop simulates the complete hydrological balance in a continuous way, during a whole year, inside a basin and combines the main features of the modern land surfaces models with the distributed rainfall-runoff models.</br></br>The new 0.875 version of GEOtop introduces the snow accumulation and melt module and describes sub-surface flows in an unsaturated media more accurately. With respect to the version 0.750 the updates are fundamental: the codex is completely eviewed, the energy and mass parametrizations are rewritten, the input/output file set is redifined.</br></br>GEOtop makes it possible to know the outgoing discharge at the basin's closing section, to estimate the local values at the ground of humidity, of soil temperature, of sensible and latent heat fluxes, of heat flux in the soil and of net radiation, together with other hydrometeorlogical distributed variables. Furthermore it describes the distributed snow water equivalent and surface snow temperature.</br></br>GEOtop is a model based on the use of Digital Elevation Models (DEMs). It makes also use of meteorological measurements obtained thought traditional instruments on the ground. Yet, it can also assimilate distributed data like those coming from radar measurements, from satellite terrain sensing or from micrometeorological models.ensing or from micrometeorological models.)
    • Model:GIPL  + (GIPL(Geophysical Institute Permafrost LaboGIPL(Geophysical Institute Permafrost Laboratory) is an implicit finite difference one-dimensional heat flow numerical model. The GIPL model uses the effect of snow layer and subsurface soil thermal properties to simulate ground temperatures and active layer thickness (ALT) by solving the 1D heat diffusion equation with phase change. The phase change associated with freezing and thawing process occurs within a range of temperatures below 0 degree centigrade, and is represented by the unfrozen water curve (Romanovsky and Osterkamp 2000). The model employs finite difference numerical scheme over a specified domain. The soil column is divided into several layers, each with distinct thermo-physical properties. The GIPL model has been successfully used to map permafrost dynamics in Alaska and validated using ground temperature measurements in shallow boreholes across Alaska (Nicolsky et al. 2009, Jafarov et al. 2012, Jafarov et al. 2013, Jafarov et al. 2014).Jafarov et al. 2013, Jafarov et al. 2014).)
    • Model:GSFLOW  + (GSFLOW was a coupled model based on the inGSFLOW was a coupled model based on the integration of the U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS, Leavesley and others, 1983) and the U.S. Geological Survey Modular Groundwater Flow Model(MODFLOW-2005, Harbaugh, 2005). It was developed to simulate coupled groundwater/surface-water flow in one or more watersheds by simultaneously simulating flow across the land surface, within subsurface saturated and unsaturated materials, and within streams and lakes.d materials, and within streams and lakes.)
    • Model:AlluvStrat  + (Generates alluvial stratigraphy by channelGenerates alluvial stratigraphy by channel migration and avulsion. Channel migration is handled via a random walk. Avulsions occur when the channel superelevates. Channels can create levees. Post-avulsion channel locations chosen at random, or based on topography. chosen at random, or based on topography.)
    • Model:Glimmer-CISM  + (Glimmer is an open source (GPL) three-dimeGlimmer is an open source (GPL) three-dimensional thermomechanical ice sheet model, designed to be interfaced to a range of global climate models. It can also be run in stand-alone mode. Glimmer was developed as part of the NERC GENIE project (www.genie.ac.uk). It's development follows the theoretical basis found in Payne (1999) and Payne (2001). Glimmer's structure contains numerous software design strategies that make it maintainable, extensible, and well documented.tainable, extensible, and well documented.)
    • Model:GSDCalculator  + (Grain Size Distribution Statistics Calculator)
    • Model:GSSHA  + (Gridded Surface Subsurface Hydrologic AnalGridded Surface Subsurface Hydrologic Analysis (GSSHA) is a grid-based two-dimensional hydrologic model. Features include 2D overland flow, 1D stream flow, 1D infiltration, 2D groundwater, and full coupling between the groundwater, vadoze zone, streams, and overland flow. GSSHA can run in both single event and long-term modes. The fully coupled groundwater to surfacewater interaction allows GSSHA to model both Hortonian and Non-Hortonian basins.</br>New features of version 2.0 include support for small lakes and detention basins, wetlands, improved sediment transport, and an improved stream flow model.</br>GSSHA has been successfully used to predict soil moistures as well as runoff and flooding. moistures as well as runoff and flooding.)
    • Model:WBM-WTM  + (Gridded water balance model using climate Gridded water balance model using climate input forcings that calculate surface and subsurface runoff and ground water recharge for each grid cell. The surface and subsurface runoff is propagated horizontally along a prescribed gridded network using Musking type horizontal transport.k using Musking type horizontal transport.)
    • Model:TopoFlow-Data-HIS  + (HIS is an internet-based system for sharing hydrologic data. It is comprised of databases and servers, connected through web services, to client applications, allowing for the publication, discovery and access of data.)
    • Model:HYPE  + (HYPE is a semi-distributed hydrological moHYPE is a semi-distributed hydrological model for water and water quality. It simulates water and nutrient concentrations in the landscape at the catchment scale. Its spatial division is related to catchments and sub-catchments, land use or land cover, soil type and elevation. Within a catchment the model will simulate different compartments; soil including shallow groundwater, rivers and lakes. It is a dynamical model forced with time series of precipitation and air temperature, typically on a daily time step. Forcing in the form of nutrient loads is not dynamical. Example includes atmospheric deposition, fertilizers and waste water.c deposition, fertilizers and waste water.)
    • Model:EstuarineMorphologyEstimator  + (Here, we present a Python tool that includHere, we present a Python tool that includes a comprehensive set of relations that predicts the hydrodynamics, bed elevation and the patterns of channels and bars in mere seconds. Predictions are based on a combination of empirical relations derived from natural estuaries, including a novel predictor for cross-sectional depth distributions, which is dependent on the along-channel width profile. Flow velocity, an important habitat characteristic, is calculated with a new correlation between depth below high water level and peak tidal flow velocity, which was based on spatial numerical modelling. Salinity is calculated from estuarine geometry and flow conditions. The tool only requires an along-channel width profile and tidal amplitude, making it useful for quick assessments, for example of potential habitat in ecology, when only remotely-sensed imagery is available.only remotely-sensed imagery is available.)
    • Model:HexWatershed  + (HexWatershed is a mesh independent flow direction model for hydrologic models. It can be run at both regional and global scales. The unique feature of HexWatershed is that it supports both structured and unstructured meshes.)
    • Model:Spbgc  + (High order two dimensional simulations of turbidity currents using DNS of incompressible Navier-Stokes and transport equations.)
    • 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)
    • Model:Kudryavtsev Model  + (Models the temporal and spatial distributiModels the temporal and spatial distribution of the active layer thickness and temperature of permafrost soils. The underlying approximation accounts for effects of air temperature, snow cover, vegatation, soil moisture, soil thermal properties to predict temperature at the ground surface and mean active layer thickness.d surface and mean active layer thickness.)
    • Model:RAFEM  + (Morphodynamic river avulsion model, designed to be coupled with CEM and SEDFLUX3D)
    • Model:Mrip  + (Mrip consists of a matrix representing theMrip consists of a matrix representing the sea floor (25x25 m at this time). Blocks in the matrix are picked up (or deposited) according to transport rules or equations (users choice) and moved with the flow. The user-determined flow is altered, depending on the height and slope of the bed, thus creating feedback. slope of the bed, thus creating feedback.)
    • Model:NearCoM  + (NearCoM predicts waves, currents, sedimentNearCoM predicts waves, currents, sediment transport and bathymetric change in the nearshore ocean, between the shoreline and about 10 m water depth. The model consists of a "backbone", i.e., the master program, handling data input and output as well as internal storage, together with a suite of "modules": wave module, circulation module and sediment transport module.tion module and sediment transport module.)
    • Model:River Network Bed-Material Sediment  + (Network-based modeling framework of Czuba Network-based modeling framework of Czuba and Foufoula-Georgiou as applied to bed-material sediment transport.</br></br>This code is capable of reproducing the results (with some work by the end user) described in the following publications:</br></br>Czuba, J.A., and E. Foufoula-Georgiou (2014), A network-based framework for identifying potential synchronizations and amplifications of sediment delivery in river basins, Water Resources Research, 50(5), 3826–3851, doi:10.1002/2013WR014227.</br></br>Czuba, J.A., and E. Foufoula-Georgiou (2015), Dynamic connectivity in a fluvial network for identifying hotspots of geomorphic change, Water Resources Research, 51(3), 1401-1421, doi:10.1002/2014WR016139.</br></br>Gran, K.B., and J.A. Czuba, (2017), Sediment pulse evolution and the role of network structure,</br>Geomorphology, 277, 17-30, doi:10.1016/j.geomorph.2015.12.015.</br></br>Czuba, J.A., E. Foufoula-Georgiou, K.B. Gran, P. Belmont, and P.R. Wilcock (2017), Interplay between spatially-explicit sediment sourcing, hierarchical river-network structure, and in-channel bed-material sediment transport and storage dynamics, Journal of Geophysical Research - Earth Surface, 122(5), 1090-1120, doi:10.1002/2016JF003965.</br></br>As of 20 March 2019, additional model codes were added to the repository in the folder "Gravel_Bed_Dynamics" that extend the model to gravel bed dynamics. The new methods for gravel bed dynamics are described in:</br></br>Czuba, J.A. (2018), A Lagrangian framework for exploring complexities of mixed-size sediment transport in gravel-bedded river networks, Geomorphology, 321, 146-152, doi:10.1016/j.geomorph.2018.08.031. </br></br>And an application to Clear Creek/Tushar Mountains in Utah is described in:</br></br>Murphy, B.P., J.A. Czuba, and P. Belmont (2019), Post-wildfire sediment cascades: a modeling framework linking debris flow generation and network-scale sediment routing, Earth Surface Processes and Landforms, 44(11), 2126-2140, doi:10.1002/esp.4635.</br></br>Note: the application code and data files for Murphy et al., 2019 are included in the repository as example files.</br></br>As of 24 September 2020, this code has largely been converted to Python and has been incorporated into Landlab version 2.2 as the NetworkSedimentTransporter. See:</br></br>Pfeiffer, A.M., K.R. Barnhart, J.A. Czuba, and E.W.H. Hutton (2020), NetworkSedimentTransporter: A Landlab component for bed material transport through river networks, Journal of Open Source Software, 5(53), 2341, doi:10.21105/joss.02341.</br></br>This initial release is the core code, but development is ongoing to make the data preprocessing, model interface, and exploration of model results more user friendly. All future developments will be in the Landlab/Python version of the code instead of this Matlab version.f the code instead of this Matlab version.)
    • Model:Nitrate Network Model  + (Network-based modeling framework of Czuba Network-based modeling framework of Czuba and Foufoula-Georgiou as applied to nitrate and organic carbon on a wetland-river network.</br></br>This code is capable of reproducing the results (with some work of commenting/uncommenting code by the end user) described in the following publication:</br></br>Czuba, J.A., A.T. Hansen, E. Foufoula-Georgiou, and J.C. Finlay (2018), Contextualizing wetlands within a river network to assess nitrate removal and inform watershed management, Water Resources Research, 54(2), 1312-1337, doi:10.1002/2017WR021859.4(2), 1312-1337, doi:10.1002/2017WR021859.)
    • Model:Pllcart3d  + (Nonlinear three dimensional simulations of miscible Hele-Shaw flows using DNS of incompressible Navier-Stokes and transport equations.)
    • Model:Oceananigans.jl  + (Oceananigans.jl is designed for high-resolution simulations in idealized geometries and supports direct numerical simulation, large eddy simulation, arbitrary numbers of active and passive tracers, and linear and nonlinear equations of state for seawater.)
    • Model:CMFT  + (One dimensional model for the coupled longOne dimensional model for the coupled long-term evolution of salt marshes and tidal flats. The model framework includes tidal currents, wind waves, sediment erosion and deposition, as well as the effect of vegetation on sediment dynamics. The model is used to explore the evolution of the marsh boundary under different scenarios of sediment supply and sea level rise. Time resolution 30 min, simulation length about 100 years.30 min, simulation length about 100 years.)
    • Model:OTEQ  + (One-Dimensional Transport with EquilibriumOne-Dimensional Transport with Equilibrium Chemistry (OTEQ):</br>A Reactive Transport Model for Streams and Rivers</br></br>OTEQ is a mathematical simulation model used to characterize the fate and transport of waterborne solutes in streams and rivers. The model is formed by coupling a solute transport model with a chemical equilibrium submodel. The solute transport model is based on OTIS, a model that considers the physical processes of advection, dispersion, lateral inflow, and transient storage. The equilibrium submodel is based on MINTEQ, a model that considers the speciation and complexation of aqueous species, acid-base reactions, precipitation/dissolution, and sorption.</br></br>Within OTEQ, reactions in the water column may result in the formation of solid phases (precipitates and sorbed species) that are subject to downstream transport and settling processes. Solid phases on the streambed may also interact with the water column through dissolution and sorption/desorption reactions. Consideration of both mobile (waterborne) and immobile (streambed) solid phases requires a unique set of governing differential equations and solution techniques that are developed herein. The partial differential equations describing physical transport and the algebraic equations describing chemical equilibria are coupled using the sequential iteration approach. The model's ability to simulate pH, precipitation/dissolution, and pH-dependent sorption provides a means of evaluating the complex interactions between instream chemistry and hydrologic transport at the field scale.</br></br>OTEQ is generally applicable to solutes which undergo reactions that are sufficiently fast relative to hydrologic processes ("Local Equilibrium"). Although the definition of "sufficiently fast" is highly solute and application dependent, many reactions involving inorganic solutes quickly reach a state of chemical equilibrium. Given a state of chemical equilibrium, inorganic solutes may be modeled using OTEQ's equilibrium approach. This equilibrium approach is facilitated through the use of an existing database that describes chemical equilibria for a wide range of inorganic solutes. In addition, solute reactions not included in the existing database may be added by defining the appropriate mass-action equations and the associated equilibrium constants. As such, OTEQ provides a general framework for the modeling of solutes under the assumption of chemical equilibrium. Despite this generality, most OTEQ applications to date have focused on the transport of metals in streams and small rivers. The OTEQ documentation is therefore focused on metal transport. Potential model users should note, however, that additional applications are possible.that additional applications are possible.)
    • Model:OTIS  + (One-Dimensional Transport with Inflow and One-Dimensional Transport with Inflow and Storage (OTIS): A Solute Transport Model for Streams and Rivers</br></br>OTIS is a mathematical simulation model used to characterize the fate and transport of water-borne solutes in streams and rivers. The governing equation underlying the model is the advection-dispersion equation with additional terms to account for transient storage, lateral inflow, first-order decay, and sorption. This equation and the associated equations describing transient storage and sorption are solved using a Crank-Nicolson finite-difference solution.</br></br>OTIS may be used in conjunction with data from field-scale tracer experiments to quantify the hydrologic parameters affecting solute transport. This application typically involves a trial-and-error approach wherein parameter estimates are adjusted to obtain an acceptable match between simulated and observed tracer concentrations. Additional applications include analyses of nonconservative solutes that are subject to sorption processes or first-order decay. OTIS-P, a modified version of OTIS, couples the solution of the governing equation with a nonlinear regression package. OTIS-P determines an optimal set of parameter estimates that minimize the squared differences between the simulated and observed concentrations, thereby automating the parameter estimation process.tomating the parameter estimation process.)
    • Model:OpenFOAM  + (OpenFOAM (Open Field Operation and Manipulation) is a toolbox for the development of customized numerical solvers, and pre-/post-processing utilities for the solution of continuum mechanics problems, including computational fluid dynamics.)
    • Model:OTTER  + (Optimization Technique in Transient EvolutOptimization Technique in Transient Evolution of Rivers (OTTER). This models a 1D river profile while incorporating a algorithm for dynamic channel width. The channel width algorithm dynamically adjusts channel geometry in response to values of water discharge, rock-uplift/erosion, and sediment supply. It operates by calculating the current shear stress (no wide channel assumption), the shear stress if channel width is slightly larger, and shear stress for a slightly narrower channel. Using these values, erosion potential is calculated for all three scenarios (no change in width, slightly wider, slightly narrower) and the one that generates the maximum erosion rate dictates the direction of channel change. See Yanites, 2018 JGR for further information.Yanites, 2018 JGR for further information.)
    • Model:OrderID  + (OrderID is a method that takes thickness and facies data from a vertical succession of strata and tests for the presence of order in the strata)
    • Model:GeoClaw  + (Originally developed for modeling tsunami Originally developed for modeling tsunami generation, propagation, and inundation. Also used for storm surge modeling and overland flooding (e.g. dam break problems). Uses adaptive mesh refinement to allow much greater spatial resolutions in some regions than others, and to automatically follow dynamic evolution of waves or floods. Uses high-resolution finite volume methods that robustly handle wetting and drying. The package also includes tools for working with geophysical data including topography DEMs, earthquake source models for tsunami generation, and observed gauge data. The simulation code is in Fortran with OpenMP for shared memory parallelization, and Python for the user interface, visualization, and data tools. interface, visualization, and data tools.)
    • Model:PHREEQC  + (PHREEQC implements several types of aqueouPHREEQC implements several types of aqueous models: two ion-association aqueous models (the Lawrence Livermore National Laboratory model and WATEQ4F), a Pitzer specific-ion-interaction aqueous model, and the SIT (Specific ion Interaction Theory) aqueous model. Using any of these aqueous models, PHREEQC has capabilities for (1) speciation and saturation-index calculations; (2) batch-reaction and one-dimensional (1D) transport calculations with reversible and irreversible reactions, which include aqueous, mineral, gas, solid-solution, surface-complexation, and ion-exchange equilibria, and specified mole transfers of reactants, kinetically controlled reactions, mixing of solutions, and pressure and temperature changes; and (3) inverse modeling, which finds sets of mineral and gas mole transfers that account for differences in composition between waters within specified compositional uncertainty limits.pecified compositional uncertainty limits.)
    • Model:PIHM  + (PIHM is a multiprocess, multi-scale hydrolPIHM is a multiprocess, multi-scale hydrologic model where the major hydrological processes are fully coupled using the semi-discrete finite volume method. PIHM is a physical model for surface and groundwater, “tightly-coupled” to a GIS interface. PIHMgis which is open source, platform independent and extensible. The tight coupling between GIS and the model is achieved by developing a shared data-model and hydrologic-model data structure.model and hydrologic-model data structure.)
    • Model:PISM  + (PISM is a hybrid shallow ice, shallow shelPISM is a hybrid shallow ice, shallow shelf model. PISM is designed to scale with increasing problem size</br>by harnessing the computational power of supercomputing systems and by leveraging the scalable software libraries that have been developed by the high-performance computing research community. The model combines two shallow (small depth-to-width ratio) stress balances, namely the shallow-ice approximation (SIA) and the shallow-shelf approximation (SSA), which are computationally efficient schemes to simulate ice flow by internal deformation and ice-stream flow, respectively. In PISM, deformational velocities from the SIA and sliding velocities from the SSA are weighted and averaged to achieve a smooth transition from shearing flow to sliding flow.sition from shearing flow to sliding flow.)
    • Model:PRMS  + (PRMS is a modular-design modeling system that has been developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff, sediment yields, and general basin hydrology)
    • Model:PSTSWM  + (PSTSWM is a message-passing benchmark codePSTSWM is a message-passing benchmark code and parallel algorithm testbed that solves the nonlinear shallow water equations on a rotating sphere using the spectral transform method. It is a parallel implementation of STSWM to generate reference solutions for the shallow water test cases.olutions for the shallow water test cases.)
    • Model:ParFlow  + (ParFlow is an open-source, object-orientedParFlow is an open-source, object-oriented, parallel watershed flow model. It includes fully-integrated overland flow, the ability to simulate complex topography, geology and heterogeneity and coupled land-surface processes including the land-energy budget, biogeochemistry and snow (via CLM). It is multi-platform and runs with a common I/O structure from laptop to supercomputer. ParFlow is the result of a long, multi-institutional development history and is now a collaborative effort between CSM, LLNL, UniBonn and UCB. ParFlow has been coupled to the mesoscale, meteorological code ARPS and the NCAR code WRF.rological code ARPS and the NCAR code WRF.)
    • Model:PIHMgis  + (Physically-based fully-distributed hydroloPhysically-based fully-distributed hydrologic models try to simulate hydrologic state variables in space and time while using information regarding heterogeneity in climate, land use, topography and hydrogeology. However incorporating a large number of physical data layers in the hydrologic model requires intensive data development and topology definitions.data development and topology definitions.)
    • Model:TreeThrow  + (Plot scale, spatially implicit model of tree throw on hillslopes. We couple an existing forest growth model with a couple simple equations for the transport of sediment caused by tree fall.)
    • Model:PotentialEvapotranspiration  + (Potential Evapotranspiration Component calPotential Evapotranspiration Component calculates spatially distributed potential evapotranspiration based on input radiation factor (spatial distribution of incoming radiation) using chosen method such as constant or Priestley Taylor. Ref: Xiaochi et. al. 2013 for 'Cosine' method and ASCE-EWRI Task Committee Report Jan 2005 for 'PriestleyTaylor' method.</br>Note: Calling 'PriestleyTaylor' method would generate/overwrite shortwave & longwave radiation fields.ite shortwave & longwave radiation fields.)
    • Model:STVENANT  + (Predicts 1D, unsteady, nonlinear, gradually varied flow)
    • Model:BackwaterCalculator  + (Program for backwater calculations in open channel flow)
    • Model:FlowAccumulator  + (Provides the FlowAccumulator component whiProvides the FlowAccumulator component which accumulates flow and calculates drainage area. FlowAccumulator supports multiple methods for calculating flow direction. Optionally a depression finding component can be specified and flow directing, depression finding, and flow routing can all be accomplished together. routing can all be accomplished together.)
    • Model:QDSSM  + (QDSSM is a 3D cellular, forward numerical QDSSM is a 3D cellular, forward numerical model coded in Fortran90 that simulates landscape evolution and stratigraphy as controlled by changes in sea-level, subsidence, discharge and bedload flux. The model includes perfect and imperfect sorting modules of grain size and allows stratigraphy to be build over time spans of 1000 to million of years.er time spans of 1000 to million of years.)
    • Model:QTCM  + (QTCMs are models of intermediate complexity suitable for the modeling of tropical climate and its variability. It occupies a niche among climate models between complex general circulation models and simple models.)
    • 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.)