# Property:Extended model description

From CSDMS

This is a property of type Text.

M

"meanderpy" is a Python module that implements a simple numerical model of meandering, the one described by Howard & Knutson in their 1984 paper "Sufficient Conditions for River Meandering: A Simulation Approach" (https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/WR020i011p01659). This is a kinematic model that is based on computing migration rate as the weighted sum of upstream curvatures; flow velocity does not enter the equation. Curvature is transformed into a 'nominal migration rate' through multiplication with a migration rate (or erodibility) constant; in the Howard & Knutson (1984) paper this is a nonlinear relationship based on field observations that suggested a complex link between curvature and migration rate. In the 'meanderpy' module we use a simple linear relationship between the nominal migration rate and curvature, as recent work using time-lapse satellite imagery suggests that high curvatures result in high migration rates (Sylvester et al., 2019). +

B

C

S

K

--- WHEN USING THIS CODE FOR YOUR RESEARCH, PLEASE CITE: ---<br>
Neely, A., Bookhagen B., Burbank, D.W. (2017): An automated knickzone selection algorithm (KZ-Picker) to analyze transient landscapes: Calibration and validation, JGR Earth Surface, doi:10.1002/2017JF004250
available at: http://onlinelibrary.wiley.com/doi/10.1002/2017JF004250/full
<br>
---
The Matlab-based scripts extract several topometrics at the catchment scale based on log area/log slope and chi plots. Topometrics include: steepness index, theta, steepness index with adjusted theta for each drainage basin, specific stream power, curvature, local relief, and others. Detrended and normalized chi-squared plots are used to identify river knickpoints. Output is written as GeoTIFF files, shapefiles, and CSV files.
Additional information, examples, and tutorials are provided on the github page. +

S

M

2D 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).
It has companion website with pre-loaded simulations to be used by end-users. +

2

S

D

C

3D cellular model simulating delta evolution in coarse grained river dominated systems (e.g. a gravel fan delta). +

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 +

L

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().
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 instantiation +

A 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). +

N

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. +

Z

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.
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.
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.
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.
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.
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.

D

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). +

S

A 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.
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.
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.
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`.
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.
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

A landform evolution model operating at the drainage basin or larger scale. Recent model development has targeted planetary applications. +

C

A 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. +

M

A 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. +

L

A 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.
This model is used to illustrate the wall feedback concept proposed by Malatesta, Prancevic, Avouac; 2017; JGR Eath-Surface; doi:10.1002/2015JF003797 +

A

A module that calculates the evolution of a gravel bed river under an imposed cycled hydrograph. +

T

A multi-dimensional numerical model for sediment transport based on the two-phase
flow formulation is developed. With closures of particle stresses and fluid-particle interaction,
the model is able to resolve processes in the concentrated region of sediment
transport and hence does not require conventional bedload/suspended load assumptions.
The numerical model is developed in three spatial dimensions. However, in this version,
the model is only validated for Reynolds-averaged two-dimensional vertical (2DV) formulation
(with the k − epsilon closure for carrier flow turbulence) for sheet flow in steady and
oscillatory flows. This numerical model is developed via the open-source CFD library of
solvers, OpenFOAM and the new solver is called twoPhaseEulerSedFoam. +

G

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. +

O

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 +

L

A 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. +

S

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. +

D

A 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. +

L

P

A 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. +

H

A 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. +

M

A 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. +

P

A stochastic point model for tidal flat evolution to study the influence of tidal currents and wind waves on tidal flat equilibrium. +

B

A 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. +

S

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. +

C

A 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. +

F

A 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. +

W

A

ADCIRC 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:
# modeling tides and wind driven circulation,
# analysis of hurricane storm surge and flooding,
# dredging feasibility and material disposal studies,
# larval transport studies,
# near shore marine operations. +

ALFRESCO 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). +

ANUGA 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.
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.
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). +

ANUGA 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.
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.
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.
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. +

Acronym1D 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). +

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). +

AeoLiS 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. +

F

Allow 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.
Version 2.0 offers improved capabilities in coastal areas. +

A

Alpine3D 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.
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. +

W

An extension of the WBMplus (WBM/WTM) model. Introduce a riverine sediment flux component based on the BQART and Psi models. +

G

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

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.
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.
Dynamic boundary conditions such as climatic changes over time are incorporated by increasing or decreasing discharge and sediment load for each time step. +

B

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. +

BIT 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. +

BRaKE 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. +

Barrier3D 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. +

BarrierBMFT 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.
The use of this coupled model framework requires Barrier3D v2.0 (https://doi.org/10.5281/zenodo.7604068)
and PyBMFT-C v1.0 (https://doi.org/10.5281/zenodo.7853803). +

R

Based on the publication:
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 +

B

Basin 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. +

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.
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.
Possible uses of the model include the study of avulsion, bifurcation stability, and the morphodynamic response of bifurcations to external changes. +

Blocklab 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. +

C

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. +

CHILD computes the time evolution of a topographic surface z(x,y,t) by fluvial and hillslope erosion and sediment transport. +

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. +

CLUMondo 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. +

Caesar 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.
Featuring:
Landscape evolution model simulating erosion and deposition across river reaches and catchments
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)
designed to operate on multiple core processors (parallel processing of core functions)
Operates over a wide range to spatial and time scales (1km2 to 1000km2, <1year to 1000+ years)
Easy to use GUI +

P

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. +

O

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. +

S

Calculates non-equilibrium suspended load transport rates of various size-density fractions in the bed +

B

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. +

S

Calculates the constant terminal settling velocity of each size-density fraction's median size from Dietrich's equation. +

E

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 +

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 +

F

Calculates the flow velocity and depth based on the gradually varied flow equation of an open channel. +

T

Calculates the gaussian or log-gaussian distribution of instantaneous shear stresses on the bed, given a mean and coefficient of variation. +

L

Y

Calculates the total sediment transport rate in an open channel assuming a median bed grain size +

S

Calculation of Density Stratification Effects Associated with Suspended Sediment in Open Channels.
This program calculates the effect of sediment self-stratification on the streamwise velocity and suspended sediment concentration profiles in open-channel flow.
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. +

Calculation of Sediment Deposition in a Fan-Shaped Basin, undergoing Piston-Style Subsidence +

D

Calculator 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. +

Calculator 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. +

C

CarboCAT uses a cellular automata to model horizontal and vertical distributions of carbonate lithofacies +

ChesROMS 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.
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.
http://ches.communitymodeling.org/models/ChesROMS/index.php +

Cliffs features:
Shallow-Water approximation;
Use of Cartesian or spherical (lon/lat) coordinates;
1D and 2D configurations;
Structured co-located grid with (optionally) varying spacing;
Run-up on land;
Initial conditions or boundary forcing;
Grid nesting with one-way coupling;
Parallelized with OpenMP;
NetCDF format of input/output data.
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).
References:
Titov, V.V., and C.E. Synolakis. Numerical modeling of tidal wave runup. J. Waterw. Port Coast. Ocean Eng., 124(4), 157–171 (1998)
Tolkova E. Land-Water Boundary Treatment for a Tsunami Model With Dimensional Splitting.
Pure and Applied Geophysics, 171(9), 2289-2314 (2014) +

B

Coastal barrier model that simulates storm overwash and tidal inlets and estimates coastal barrier transgression resulting from sea-level rise. +

D

Code for estimating long-term exhumation histories and spatial patterns of short-term erosion from the detrital thermochronometric data. +

M

Code functionality and purpose may be found in the following references:
References
# 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.
# 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) +

C

G

Computes 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. +

C

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:
http://ckan.snap.uaf.edu/dataset/historical-monthly-and-derived-temperature-products-771m-cru-ts
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.
The data are monthly average temperatures for each month from January 1901 through December 2009. +

D

DHSVM 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. +

DR3M 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. +

DROG3D tracks passive drogues with given harmonic velocity field(s) in a 3-D finite element mesh +

Dakota 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:
* vector parameter study,
* centered parameter study,
* multidim parameter study,
* sampling,
* polynomial chaos, and
* stochastic collocation. +

C

Data 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. +

D

DeltaRCM 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.
Best usage of DeltaRCM is the investigation of autogenic processes in response to external forcings. +

Demeter 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. +

W

Depth-Discharge and Bedload Calculator, uses:
# Wright-Parker formulation for flow resistance (without stratification correction)
# Ashida-Michiue formulation for bedload transport. +

D

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. +

M

Derived 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. +

D

F

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. +

Directs 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. +

D

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. +

DynEarthSol3D (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. +

E

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. +

EF5 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. +

ELCIRC 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. +

Ecopath 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:
*Address ecological questions;
*Evaluate ecosystem effects of fishing;
*Explore management policy options;
*Evaluate impact and placement of marine protected areas;
*Evaluate effect of environmental changes. +

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). +

Erode-D8-Global is a raster, D8-based fluvial landscape evolution model (LEM) +

L

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). +

S

Extended 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. +

F

FACET 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. +

FUNWAVE is a phase-resolving, time-stepping Boussinesq model for ocean surface wave propagation in the nearshore. +

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. +

Fall velocity for spheres. Uses formulation of Dietrich (1982) +

Z

Finite 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 exercise +

S

Finite element process based simulation model for fluid flow, clastic, carbonate and evaporate sedimentation. +

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. +

M

Fortran 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. +

F

FuzzyReef 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.
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. +

G

GENESIS 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. +

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. +

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. 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. +

GEOMBEST++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. +

GEOtop 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.
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.
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.
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.
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. +

GIPL(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). +

GSFLOW 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. +

A

Generates 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. +

G

Glimmer 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. +

Grain Size Distribution Statistics Calculator +

Gridded 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.
New features of version 2.0 include support for small lakes and detention basins, wetlands, improved sediment transport, and an improved stream flow model.
GSSHA has been successfully used to predict soil moistures as well as runoff and flooding. +

W

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. +

T

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. +

H

HYPE 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. +

E

Here, 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. +

H

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. +

S

High order two dimensional simulations of turbidity currents using DNS of incompressible Navier-Stokes and transport equations. +

T

Hillslope diffusion component in the style of Carretier et al. (2016, ESurf), and Davy and Lague (2009).
Works on regular raster-type grid (RasterModelGrid, dx=dy). To be coupled with FlowDirectorSteepest for the calculation of steepest slope at each timestep. +

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:
qs = KS ( 1 + (S/Sc)**2 + (S / Sc)**4 + .. + (S / Sc)**2(n - 1) )
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). +

D

Hillslope 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:
q_s = DSH^* ( 1 + (S/S_c)^2 + (S/Sc_)^4 + .. + (S/S_c)^2(n-1) ) (1.0 - exp( H / H^*)
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. +

H

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. +

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. +

Hydrological Simulation Program - FORTRAN (HSPF) is a comprehensive package
for simulation of watershed hydrology and water quality for both conventional
and toxic organic pollutants (1,2). This model can simulate the hydrologic,
and associated water quality, processes on pervious and impervious land
surfaces and in streams and well-mixed impoundments. HSPF incorporates the
watershed-scale ARM and NPS models into a basin-scale analysis framework that
includes fate and transport in one-dimensional stream channels. It is the
only comprehensive model of watershed hydrology and water quality that allows
the integrated simulation of land and soil contaminant runoff processes with
in-stream hydraulic and sediment-chemical interactions.
The result of this simulation is a time history of the runoff flow rate,
sediment load, and nutrient and pesticide concentrations, along with a time
history of water quantity and quality at any point in a watershed. HSPF
simulates three sediment types (sand, silt, and clay) in addition to a single
organic chemical and transformation products of that chemical. The transfer
and reaction processes included are hydrolysis, oxidation, photolysis,
biodegradation, volatilization, and sorption. Sorption is modeled as a
first-order kinetic process in which the user must specify a desorption rate
and an equilibrium partition coefficient for each of the three solids types.
Resuspension and settling of silts and clays (cohesive solids) are defined in
terms of shear stress at the sediment water interface. The capacity of the
system to transport sand at a particular flow is calculated and resuspension
or settling is defined by the difference between the sand in suspension and
the transport capacity. Calibration of the model requires data for each of
the three solids types. Benthic exchange is modeled as sorption/desorption
and deposition/scour with surficial benthic sediments. Underlying sediment
and pore water are not modeled.

W

I 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. +

C

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. +

I

IDA 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.
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.
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.
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.
Currently only D8 flow directions are supported. Inputs and outputs are raw binary files. +

ISSM 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.
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 Foundation +

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. +

Icepack 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. +

C

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>
'flow__receiver_node'<br>
'flow__link_to_receiver_node'<br>
The ChannelProfiler can work on grids that have used route-to-one or route-to-multiple flow directing. +

H

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. +

W

It 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.
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. +

F

It solves the linearized shallow water equations forced by tidal or other barotropic boundary conditions, wind or a density gradient using linear finite elements. +

A

It tracks any number of different depth-averaged transport variables and is usually used in conjunction with QUODDY simulations. +

L

LEMming 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. +

LEMming2 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.
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. +

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). +

LOAD 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.
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.
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. +

R

Landlab component that computes 1D and 2D total incident shortwave radiation. This code also computes relative incidence shortwave radiation compared to a flat surface. +

L

Landlab component that finds a neighbor node to laterally erode and calculates lateral erosion. +

P

Landlab component that generates precipitation events using the rectangular Poisson pulse model described in Eagleson (1978, Water Resources Research).
No particular units must be used, but it was written with the storm units in hours (hr) and depth units in millimeters (mm). +

F

D

Landlab 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.
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. +

V

Landlab component that simulates net primary productivity, biomass and leaf area index at each cell based on inputs of root-zone average soil moisture. +

S

Landlab component that simulates root-zone average soil moisture at each cell using inputs of potential evapotranspiration, live leaf area index, and vegetation cover.
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. +

L

Landlab 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:
(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.
(2) A set of pre-built COMPONENTS, each of which models a particular process. Components can be combined together to create coupled models.
(3) A library of pre-built MODELS that have been created by combining components together.
To learn more, please visit http://landlab.github.io +

G

Landscape evolution model. Computes evolution of topography under the action of rainfall and tectonics. +

S

Life 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. +

L

LinearDiffuser is a Landlab component that models soil creep using an explicit finite-volume solution to a 2D diffusion equation. +

Lithospheric 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). +

Lithospheric 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. +

C

Long 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.
The CoastMorpho2D model includes the MarshMorpho2D model (which was previously uploaded on CSDMS) +

D

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 +

M

MARSSIM 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 heuristic

MICOM is a primitive equation numerical model that describes the evolution of momentum, mass, heat and salt in the ocean. +

MODFLOW 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. +

MODFLOW 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.
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.
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. +

MOM6 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. +

C

Makes 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. +

M

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). +

R

Measure 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. +

C

Model describing the morphodynamic evolution of vegetated coastal foredunes. +

A

G

ModelE 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. +

L

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. +

G

K

Models 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. +

R

M

Mrip 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. +

N

NearCoM 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. +

R

Network-based modeling framework of Czuba and Foufoula-Georgiou as applied to bed-material sediment transport.
This code is capable of reproducing the results (with some work by the end user) described in the following publications:
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.
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.
Gran, K.B., and J.A. Czuba, (2017), Sediment pulse evolution and the role of network structure,
Geomorphology, 277, 17-30, doi:10.1016/j.geomorph.2015.12.015.
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.
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:
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.
And an application to Clear Creek/Tushar Mountains in Utah is described in:
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.
Note: the application code and data files for Murphy et al., 2019 are included in the repository as example files.
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:
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.
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.

N

Network-based modeling framework of Czuba and Foufoula-Georgiou as applied to nitrate and organic carbon on a wetland-river network.
This code is capable of reproducing the results (with some work of commenting/uncommenting code by the end user) described in the following publication:
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. +

P

Nonlinear three dimensional simulations of miscible Hele-Shaw flows using DNS of incompressible Navier-Stokes and transport equations. +

C

One 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. +

O

One-Dimensional Transport with Equilibrium Chemistry (OTEQ):
A Reactive Transport Model for Streams and Rivers
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.
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.
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.

One-Dimensional Transport with Inflow and Storage (OTIS): A Solute Transport Model for Streams and Rivers
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.
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. +

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. +

Optimization 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. +

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 +

G

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. +

P

PHREEQC 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. +

PIHM 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. +

PISM is a hybrid shallow ice, shallow shelf model. PISM is designed to scale with increasing problem size
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. +

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 +

PSTSWM 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. +

ParFlow 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. +

Physically-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. +

T

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. +

P

Potential 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.
Note: Calling 'PriestleyTaylor' method would generate/overwrite shortwave & longwave radiation fields. +

S

B

Program for backwater calculations in open channel flow +

F

Provides 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. +

Q

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. +

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. +

QUAL2K (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:
One dimensional. The channel is well-mixed vertically and laterally.
* Steady state hydraulics. Non-uniform, steady flow is simulated.
* Diurnal heat budget. The heat budget and temperature are simulated as a function of meteorology on a diurnal time scale.
* Diurnal water-quality kinetics. All water quality variables are simulated on a diurnal time scale.
* Heat and mass inputs. Point and non-point loads and abstractions are simulated. +

S

QuickChi enables the rapid analysis of stream profiles at the global scale from SRTM data. +

G

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. +

R

RCPWAVE is a 2D steady state monocromatic short wave model for simulating wave propagation over arbitrary bahymetry. +

REF/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. +

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. +

RHESSys 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. +

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. +

U

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. +

L

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. +

R

Rouse-Vanoni Equilibrium Suspended Sediment Profile Calculator +

S

Routines pertaining to the paper published as: doi: 10.1073/pnas.1206785109 +

Routines pertaining to the paper published as: doi: 10.1137/S0036144504445765 +

Routines pertaining to the paper published as: doi: 10.1111/j.1365-246X.2008.03854.x +

Routines pertaining to the paper published as: doi: 10.1016/j.acha.2012.12.001 +

Routines pertaining to the paper published as: doi: 10.1111/j.1365-246X.2006.03065.x +

P

B

S

SBEACH 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. +

SEDPAK 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. +

SELFE 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. +

SIBERIA simulates the evolution of landscapes under the action of runoff and erosion over long times scales. +

SICOPOLIS (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. +

SIGNUM (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.
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 .
The software runs under Matlab (it is tested on releases from R2010a to R2011b). It is released under the GPL3 license. +

SNAC 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. +

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. +

SPHysics 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. +

SRH-1D (Sedimentation and River Hydraulics - One Dimension) is a one-dimensional mobile boundary hydraulic and sediment transport computer model for rivers and manmade canals. Simulation capabilities include steady or unsteady flows, river control structures, looped river networks, cohesive and non-cohesive sediment transport, and lateral inflows. The model uses cross section based river information. The model simulates changes to rivers and canals caused by sediment transport. It can estimate sediment concentrations throughout a waterway given the sediment inflows, bed material, hydrology, and hydraulics of that waterway. +

STWAVE (STeady State spectral WAVE) is an easy-to-apply, flexible, robust, half-plane model for nearshore wind-wave growth and propagation. STWAVE simulates depth-induced wave refraction and shoaling, current-induced refraction and shoaling, depth- and steepness-induced wave breaking, diffraction, parametric wave growth because of wind input, and wave-wave interaction and white capping that redistribute and dissipate energy in a growing wave field. +

SWAN is a third-generation wave model that computes random, short-crested wind-generated waves in coastal regions and inland waters. +

SWAT is the acronym for Soil and Water Assessment Tool, a river basin, or watershed, scale model developed by Dr. Jeff Arnold for the USDA Agricultural Research Service (ARS). SWAT was developed to predict the impact of land management practices on water, sediment and agricultural chemical yields in large complex watersheds with varying soils, land use and management coditions over long periods of time. +

SedCas was developed for a debris-flow prone catchment in the Swiss Alps (Illgraben). It consists of two connected sediment reservoirs on the hillslope and in the channel, where sediment transfer is driven by (lumped) hydrological processes at the basin scale. Sediment is stochastically produced by shallow landslides and rock avalanches and delivered to the hillslope and channel reservoirs. From there, it is evacuated out of the basin in the form of debris flows and sediment-laden floods. +

SedPlume is an integral model, solving the conservation equations of volume, momentum, buoyancy and sediment flux along the path of a turbulent plume injected into stably stratified ambient fluid. Sedimentation occurs from the plume when the radial component of the sediment fall velocity exceeds the entrainment velocity. When the plume reaches the surface, it is treated as a radially spreading surface gravity current, for which exact solutions exist for the sediment deposition rate. Flocculation of silt and clay particles is modeled using empirical measurements of particle settling velocities in fjords to adjust the settling velocity of fine-grained sediments. +

Sedflux-2.0 is the newest version of the Sedflux basin-filling model. Sedflux-2.0 provides a framework within which individual process-response models of disparate time and space resolutions communicate with one another to deliver multi grain sized sediment load across a continental margin. +

Sedtrans05 is a sediment transport model for continental shelf and estuaries. It predicts the sediment transport at one location as function water depth, sediment type, current and waves (single point model). It can be used as sediment transport module for larger 2D models.
Five different transport equations are available for non-cohesive sediments (sand) and one algorithm for cohesive sediment. +

Shoreline is a "line model" for modeling the evolution of a coastline as the result of wind/wave-driven longshore sediment transport. It is based on conservation of mass and a semi-empirical sediment transport formula known as the CERC formula. This model was specifically adapted for modeling the evolution of the coastline near Barrow, Alaska. +

SiStER (Simple Stokes solver with Exotic Rheologies) simulates lithosphere and mantle deformation with continuum mechanics: Stokes flow with large strains, strain localization, non-linear rheologies, sharp contrasts in material properties, complex BCs. +

SimClast is a basin-scale 3D stratigraphic model, which allows several interacting sedimentary environments. Processes included are; fluvial channel dynamics and overbank deposition, river plume deposition, open marine currents, wave resuspension, nearshore wave induced longshore and crosshore transport. This combined modelling approach allows insight into the processes influencing the flux of energy and clastic material and the effect of external perturbations in all environments. Many governing processes work on relatively small scales, e.g. in fluvial settings an avulsion is a relatively localised phenomenon. Yet, they have a profound effect on fluvial architecture. This means that the model must mimic these processes, but at the same time maintain computational efficiency. Additionally, long-term models use relatively large grid-sizing (km scale), as the area to be modelled is on the scale of continental margins. We solve this problem by implementing the governing processes as sub-grid scale routines into the large-scale basin-filling model. This parameterization greatly refines morphodynamic behaviour and the resulting stratigraphy. This modelling effort recreates realistic geomorphological and stratigraphic delta behaviour in river and wave-dominated settings. +

M

Simulate marsh evolution at 10-10000 time scale. Suitable for domains 0.1km2 to 1000 km2.
Only simulates tidal flow. Conserve sediment within the domain. Allows to track sediment through the open boundaries.
Version 2.0 also included wind waves, ponding, edge erosion
Version under construction includes swell waves, cross-shore and along-shore wave-induced transport, secondary flow in channel bends, stratigraphy (sand and mud as separate constituents) +

O

Simulate overland flow using Bates et al. (2010).
Landlab component that simulates overland flow using the Bates et al., (2010) approximations of the 1D shallow water equations to be used for 2D flood inundation modeling.
This component calculates discharge, depth and shear stress after some precipitation event across any raster grid. Default input file is named “overland_flow_input.txt’ and is contained in the landlab.components.overland_flow folder. +

D

Simulates circulation and sedimentation in a 2D turbulent plane jet and resulting delta growth +

M

Simulates soil evolution on three spatial dimensions, explicit particle size distribution and temporal dimension (hence 5D prefix) as a function of:
1. Bedrock and soil physical weathering;
2. Sediment transport by overland flow;
3. Soil Creep (diffusion);
4. Aeolian deposition. +

R

Simulates the evolution of landscapes consisting of patches of high-flow-resistance vegetation and low-flow-resistance vegetation as a result of surface-water flow, peat accretion, gravitationally driven erosion, and sediment transport by flow. Was developed for the freshwater Everglades but could also apply to coastal marshes or floodplains. Described in Larsen and Harvey, Geomorphology, 2010 and Larsen and Harvey, American Naturalist, 2010 in press. +

W

Simulates wave and current supported sediment gravity flows along the seabed offshore of high discharge, fine sediment riverine sources. See Friedrichs & Scully, 2007. Continental Shelf Research, 27: 322-337, for example. +

F

Single-path (steepest direction) flow direction finding on raster grids by the D8 method. This method considers flow on all eight links such that flow is possible on orthogonal and on diagonal links. +

N

Smoothes noise in a DEM by finding the mean value of neighbouring cells and assigning it to the central cell. This approach deals well with non-gaussian distributed noise. +

K

Spatially explicit model of the development and evolution of salt marshes, including vegetation influenced accretion and hydrodynamic determined channel erosion. +

I

S

T

TISC is a computer program that simulates the evolution of 3D large-scale sediment transport together with tectonic deformation and lithospheric vertical movements on geological time scales. Particular attention is given to foreland sedimentary basin settings. TISC (formerly called tao3D) stands for Tectonics, Isostasy, Surface Transport, and Climate.
*hydrology/climate
The drainage river network is calculated following the maximum slope along the evolving topography. Based on the runoff distribution, the water discharge at any cell of the network is calculated as the water collected from tributary cells plus the precipitation at that cell. Lake evaporation is accounted for, enabling the model to study close endorheic basins. Both topography and the network evolves as a result of erosion, sedimentation and tectonic processes.
*river sediment transport
Sediment carrying capacity is a function of water discharge and slope and determines whether a river is eroding or depositing. Suspended sediments resulting from erosion are transported through the fluvial network until they are deposited or they leave the model domain (explicit mass conservation).
*lithospheric flexure
A elastic and/or viscoelastic plate approach is used to calculate the vertical movements of the lithosphere caused by the mass redistribution. In the classical lithospheric flexural model, the lithosphere is assumed to rest on a fluid asthenosphere and behave as a thin plate when submitted to external forces.
*tectonic deformation
Tectonic modification of the relieve and the correspondent loading of the lithosphere are calculated using a cinematic vertical shear approach (preserving the vertical thickness of the moving units during displacement). +

TOPMODEL is a physically based, distributed watershed model that simulates hydrologic fluxes of water (infiltration-excess overland flow, saturation overland flow, infiltration, exfiltration, subsurface flow, evapotranspiration, and channel routing) through a watershed. The model simulates explicit groundwater/surface water interactions by predicting the movement of the water table, which determines where saturated land-surface areas develop and have the potential to produce saturation overland flow. +

TOPOG describes how water moves through landscapes; over the land surface, into the soil, through the soil and groundwater and back to the atmosphere via evaporation. Conservative solute movement and sediment transport are also simulated.
The primary strength of TOPOG is that it is based on a sophisticated digital terrain analysis model, which accurately describes the topographic attributes of three-dimensional landscapes. It is intended for application to small catchments (up to 10 km2, and generally smaller than 1 km2).
We refer to TOPOG as a "deterministic", "distributed-parameter" hydrologic modelling package. The term "deterministic" is used to emphasise the fact that the various water balance models within TOPOG use physical reasoning to explain how the hydrologic system behaves. The term "distributed-parameter" means that the model can account for spatial variability inherent in input parameters such as soil type, vegetation and climate. +

TUGS is a 1D model that simulates the transport of gravel and sand in rivers. The model predicts the responses of a channel to changes made to the environment (e.g., sediment supply, hydrology, and certain artifical changes made to the river). Output of the model include longitudinal profile, sediment flux, and grain size distributions in bedload, channel surface and subsurface. +

TURBINS, a highly parallel modular code written in C, is capable of modeling gravity and turbidity currents interacting with complex topographies in two and three dimensions. Accurate treatment of the complex geometry, implementation of an efficient and scalable parallel solver, i.e. multigrid solver via PETSc and HYPRE to solve the pressure Poisson equation, and parallel IO are some of the features of TURBINS.
TURBINS enables us to tackle problems involving the interaction of turbidity currents with complex topographies. It provides us with a numerical tool for quantifying the flow field properties and sedimentation processes, e.g. energy transfer, dissipation, and wall shear stress, which are difficult to obtain even at laboratory scales. By benefiting from massively parallel simulations, we hope to understand the underlying physics and processes related to the formation and deposition of particles due to the occurrence of turbidity currents. +

TauDEM provides the following capability:
•Development of hydrologically correct (pit removed) DEMs using the flooding approach
•Calculates flow paths (directions) and slopes
•Calculates contributing area using single and multiple flow direction methods
•Multiple methods for the delineation of stream networks including topographic form-based methods sensitive to spatially variable drainage density
•Objective methods for determination of the channel network delineation threshold based on stream drops
•Delineation of watersheds and subwatersheds draining to each stream segment and association between watershed and segment attributes for setting up hydrologic models
•Specialized functions for terrain analysis
Details of new parallel Version 5.0 of TauDEM
•Restructured into a parallel processing implementation of the TauDEM suite of tools
•Works on Windows PCs, laptops and UNIX clusters
•Multiple processes are not required, the parallel approach can run as multiple processes within a single processor
•Restructured into a set of standalone command line executable programs and an ArcGIS toolbox Graphical User Interface (GUI)
•Command line executables are:
-Written in C++ using Argonne National Laboratory's MPICH2 library to implement message passing between multiple processes
-Based on single set of source code for the command line execuables that is platform independent and can be compiled for both Window's PC's and UNIX clusters +

Terrainbento 1.0 is a Python package for modeling the evolution of the surface of the Earth over geologic time (e.g., thousands to millions of years). Despite many decades of effort by the geomorphology community, there is no one established governing equation for the evolution of topography. Terrainbento 1.0 thus provides 28 alternative models that support hypothesis testing and multi-model analysis in landscape evolution. +

Terrapin (or TerraPIN) stands for "Terraces put into Numerics". It is a module that generates the expected terraces, both strath and fill, from prescribed river aggradation and degradation. +

A

The Agricultural Production Systems sIMulator (APSIM) is internationally recognized as a highly advanced simulator of agricultural systems. It contains a suite of modules which enable the simulation of systems that cover a range of plant, animal, soil, climate and management interactions. APSIM is undergoing continual development, with new capability added to regular releases of official versions. Its development and maintenance is underpinned by rigorous science and software engineering standards. The APSIM Initiative has been established to promote the development and use of the science modules and infrastructure software of APSIM. +

G

The Atmosphere-Ocean Model is a computer program that simulates the Earth's climate in three dimensions on a gridded domain. The Model requires two kinds of input, specified parameters and prognostic variables, and generates two kinds of output, climate diagnostics and prognostic variables. The specified input parameters include physical constants, the Earth's orbital parameters, the Earth's atmospheric constituents, the Earth's topography, the Earth's surface distribution of ocean, glacial ice, or vegetation, and many others. The time varying prognostic variables include fluid mass, horizontal velocity, heat, water vapor, salt, and subsurface mass and energy fields. +

C

The Coastline Evolution Model (CEM) addresses predominately sandy, wave-dominated coastlines on time-scales ranging from years to millenia and on spatial scales ranging from kilometers to hundreds of kilometers. Shoreline evolution results from gradients in wave-driven alongshore sediment transport. At its most basic level, the model follows the standard 'one-line' modeling approach, where the cross-shore dimension is collapsed into a single data point. However, the model allows the plan-view shoreline to take on arbitrary local orientations, and even fold back upon itself, as complex shapes such as capes and spits form under some wave climates (distributions of wave influences from different approach angles). The model can also represent the geology underlying the sandy coastline and shoreface in a simplified manner and enables the simulation of coastline evolution when sediment supply from an eroding shoreface may be constrained. CEM also supports the simulation of human manipulations to coastline evolution through beach nourishment or hard structures. +

The Control Volume Permafrost Model (CVPM) is a modular heat-transfer modeling system designed for scientific and engineering studies in permafrost terrain, and as an educational tool. CVPM implements the nonlinear heat-transfer equations in 1-D, 2-D, and 3-D cartesian coordinates, as well as in 1-D radial and 2-D cylindrical coordinates. To accommodate a diversity of geologic settings, a variety of materials can be specified within the model domain, including: organic-rich materials, sedimentary rocks and soils, igneous and metamorphic rocks, ice bodies, borehole fluids, and other engineering materials. Porous materials are treated as a matrix of mineral and organic particles with pore spaces filled with liquid water, ice, and air. Liquid water concentrations at temperatures below 0°C due to interfacial, grain-boundary, and curvature effects are found using relationships from condensed matter physics; pressure and pore-water solute effects are included. A radiogenic heat-production term allows simulations to extend into deep permafrost and underlying bedrock. CVPM can be used over a broad range of depth, temperature, porosity, water saturation, and solute conditions on either the Earth or Mars. The model is suitable for applications at spatial scales ranging from centimeters to hundreds of kilometers and at timescales ranging from seconds to thousands of years. CVPM can act as a stand-alone model, the physics package of a geophysical inverse scheme, or serve as a component within a larger earth modeling system that may include vegetation, surface water, snowpack, atmospheric or other modules of varying complexity. +

The Coupled Routing and Excess STorage (CREST) distributed hydrological model is a hybrid modeling strategy that was recently developed by the University of Oklahoma (http://hydro.ou.edu) and NASA SERVIR Project Team. CREST simulates the spatiotemporal variation of water and energy fluxes and storages on a regular grid with the grid cell resolution being user-defined, thereby enabling global- and regional-scale applications. The scalability of CREST simulations is accomplished through sub-grid scale representation of soil moisture storage capacity (using a variable infiltration curve) and runoff generation processes (using linear reservoirs). The CREST model was initially developed to provide online global flood predictions with relatively coarse resolution, but it is also applicable at small scales, such as single basins. This README file and the accompanying code concentrates on and tests the model at the small scale. The CREST Model can be forced by gridded potential evapotranspiration and precipitation datasets such as, satellite-based precipitation estimates, gridded rain gauge observations, remote sensing platforms such as weather radar, and quantitative precipitation forecasts from numerical weather prediction models. The representation of the primary water fluxes such as infiltration and routing are closely related to the spatially variable land surface characteristics (i.e., vegetation, soil type, and topography). The runoff generation component and routing scheme are coupled, thus providing realistic interactions between atmospheric, land surface, and subsurface water. +

The Cross-Shore Sediment Flux model addresses predominately sandy, wave-dominated coastlines on time-scales ranging from years to millenia and on spatial scales ranging from kilometers to tens of kilometers using a range of wave parameters as inputs. It calculates the cross-shore sediment flux using both shallow water wave assumptions and full Linear Airy wave Theory. An equilibrium profile is also created. Using the Exner equation, we develop an advection diffusion equation that describes the evolution of profile through time. A morphodynamic depth of closure can be estimated for each input wave parameter. +

D

The DLBRM is a distributed, physically based, watershed hydrology model that subdivides a watershed into a 1 km2 grid network and simulates hydrologic processes for the entire watershed sequentially. +

S

The EPA Storm Water Management Model (SWMM) is a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. The runoff component of SWMM operates on a collection of subcatchment areas that receive precipitation and generate runoff and pollutant loads. The routing portion of SWMM transports this runoff through a system of pipes, channels, storage/treatment devices, pumps, and regulators. SWMM tracks the quantity and quality of runoff generated within each subcatchment, and the flow rate, flow depth, and quality of water in each pipe and channel during a simulation period comprised of multiple time steps. +

G

The GeoTiff data component, pymt_geotiff, is a Python Modeling Toolkit (pymt) library for accessing data (and metadata) from a GeoTIFF file, through either a local filepath or a remote URL.
The pymt_geotiff component provides BMI-mediated access to GeoTIFF data as a service, allowing them to be coupled in pymt with other data or model components that expose a BMI. +

The Grain Hill model provides a computational framework with which to study slope forms that arise from stochastic disturbance and rock weathering events. The model operates on a hexagonal lattice, with cell states representing fluid, rock, and grain aggregates that are either stationary or in a state of motion in one of the six cardinal lattice directions. Cells representing near-surface soil material undergo stochastic disturbance events, in which initially stationary material is put into motion. Net downslope transport emerges from the greater likelihood for disturbed material to move downhill than to move uphill. Cells representing rock undergo stochastic weathering events in which the rock is converted into regolith. The model can reproduce a range of common slope forms, from fully soil mantled to rocky or partially mantled, and from convex-upward to planar shapes. An optional additional state represents large blocks that cannot be displaced upward by disturbance events. With the addition of this state, the model captures the morphology of hogbacks, scarps, and similar features. In its simplest form, the model has only three process parameters, which represent disturbance frequency, characteristic disturbance depth, and baselevel lowering rate, respectively. Incorporating physical weathering of rock adds one additional parameter, representing the characteristic rock weathering rate. These parameters are not arbitrary but rather have a direct link with corresponding parameters in continuum theory. The GrainHill model includes the GrainFacetSimulator, which represents an evolving normal-fault facet with a 60-degree-dipping fault. +

The Green-Ampt method of infiltration estimation. +

The GridMET data component is an API, CLI, and BMI for fetching and caching daily gridMET (http://www.climatologylab.org/gridmet.html) CONUS meteorological data. Variables include:
* maximum temperature
* minimum temperature
* precipitation accumulation
GridMET provides BMI-mediated access to gridMET data as a service, allowing it to be coupled with other components that expose a BMI. +

The GroundwaterDupuitPercolator is appropriate for modeling shallow groundwater flow where the vertical component of flow is negligible. Where the groundwater table approaches the land surface, it calculates seepage that can be routed using other Landlab components. It can be implemented on both regular (e.g. rectangular and hexagonal) and irregular grids determined by the user. Recharge, hydraulic conductivity, and porosity may be specified as single values uniform over the model domain, or as vectors on the nodes (recharge, porosity) or links (hydraulic conductivity) of the grid. Link hydraulic conductivity can also be specified from a two-dimensional hydraulic conductivity tensor using an included function. For mass balance calculations, the model includes methods to determine the total groundwater storage on the grid domain, the total recharge flux in, and total groundwater and surface water fluxes leaving through the boundaries. +

H

The HBV model (Bergström, 1976, 1992), also known as Hydrologiska Byråns Vattenbalansavdelning, is a rainfall-runoff model, which includes conceptual numerical descriptions of hydrological processes at the catchment scale. There are many versions created over the years in various coding languages. This description points to the work of John Craven, which is a python implementation of the HBV Hydrological Model, based on matlab code of the work of Professor Amir AghaKouchak at the University of California Irvine. +

The HyLands Landscape Evolution Model is built using the Landlab software package. The HyLands model builds on three new components: water and sediment is routed using the PriorityFloodFlowRouter, fluvial erosion and sediment transport is calculated using the SpaceLargeScaleEroder while bedrock landsliding and sediment runout is calculated using the BedrockLandslider. These and all other Landlab components used in this paper are part of the open source Landlab modeling framework, version 2.5.0 (Barnhart et al., 2020a; Hobley et al., 2017), which is part of the Community Surface Dynamics Modeling System (Tucker et al., 2021). Source code for the Landlab project is housed on GitHub: http://github.com/landlab/landlab (last access: 17 August 2022). Documentation, installation, instructions, and software dependencies for the entire Landlab project can be found at http://landlab.github.io/ (last access: 17 August 2022). A user manual with an accompanying Jupyter notebooks is available from https://github.com/BCampforts/hylands_modeling (last access: 17 August 2022). The Landlab project is tested on recent-generation Mac, Linux, and Windows platforms. The Landlab modeling framework is distributed under a MIT open-source license. The latest version of the Landlab software package, including the components developed for the HyLands model is archived at: https://doi.org/10.5281/zenodo.6951444 (last access: 17 August 2022). +

The Hydrologically Enhanced Basin Evolution Model (HEBEM) is a combined hydrologic/geomorphic model. The hydrologic model simulates precipitation with variability, infiltration, evapotranspiration, overland flow, and groundwater flow, thus producing a spatially and temporally varying water discharge Q that drives fluvial processes in the land surface. The geomorphic model accounts for tectonic forcing, hillslope processes, erosion, and sediment transport. The combined model uses multiple time steps for hydrologic and geomorphic processes. Due to its hydrologic representation, the model is able to investigate the interaction between hydrology and geomorpholgy. +

I

The Instructed Glacier Model (IGM) simulates the ice dynamics, surface mass balance, and its coupling through mass conservation to predict the evolution of glaciers and icefields. The specificity of IGM is that it models the ice flow by a neural network, which is trained with ice flow physical models. Doing so permits to speed-up and facilitate considerably the implementation of the forward model and the inverse model required to assimilate data. +

The International Land Model Benchmarking (ILAMB) project is a model-data intercomparison and integration project designed to improve the performance of land models and, in parallel, improve the design of new measurement campaigns to reduce uncertainties associated with key land surface processes. Building upon past model evaluation studies, the goals of ILAMB are to:
* develop internationally accepted benchmarks for land model performance, promote the use of these benchmarks by the international community for model intercomparison,
* strengthen linkages between experimental, remote sensing, and climate modeling communities in the design of new model tests and new measurement programs, and
* support the design and development of a new, open source, benchmarking software system for use by the international community. +

D

The Landlab Drainage Density component calculates landscape-averaged drainage density, defined as the inverse of the mean distance from any pixel to the nearest channel. The component follows the approach defined in Tucker et al (2001, Geomorphology). The drainage density component does not find channel heads, but takes a user-defined channels mask. +

E

The Landlab ErosionDeposition component calculates fluvial erosion and deposition of a single substrate as derived by Davy and Lague (2009, Journal of Geophysical Research). Mass is simultaneously conserved in two reservoirs: the bed and the water column. ErosionDeposition dynamically transitions between detachment-limited and transport-limited behavior, but is limited to erosion of a single substrate (e.g., sediment or bedrock but not both). +

O

The Landlab OverlandFlow component is based on a simplified inertial approximation of the shallow water equations, following the solution of de Almeida et al. (2012). This explicit two-dimensional hydrodynamic algorithm simulates a flood wave across a model domain, where water discharge and flow depth are calculated at all locations within a structured (raster) grid. This component generates a hydrograph at all grid locations, and allows for flow to move in one of the four cardinal directions (D4) into/out of a given model node. +

S

The Landlab SPACE (Stream Power with Alluvium Conservation and Entrainment) enables modeling of bedrock, alluviated, and bedrock-alluvial rivers by simultaneously conserving mass in three reservoirs: the water column, the alluvial bed, and the underlying bedrock. SPACE allows dynamic transitions between detachment-limited, transport-limited, and intermediate states. SPACE calculates sediment fluxes, alluvial layer thickness, and bedrock erosion at all nodes within the model domain. An extended description of the model may be found in Shobe et al (2017, Geoscientific Model Development). +

L

The Larval TRANSport Lagrangian model (LTRANS) is an off-line particle-tracking model that runs with the stored predictions of a 3D hydrodynamic model, specifically the Regional Ocean Modeling System (ROMS). Although LTRANS was built to simulate oyster larvae, it can easily be adapted to simulate passive particles and other planktonic organisms. LTRANS is written in Fortran 90 and is designed to track the trajectories of particles in three dimensions. It includes a 4th order Runge-Kutta scheme for particle advection and a random displacement model for vertical turbulent particle motion. Reflective boundary conditions, larval behavior, and settlement routines are also included. LTRANS was built by Elizabeth North and Zachary Schlag of University of Maryland Center for Environmental Science Horn Point Laboratory. Funding was provided by the National Science Foundation Biological Oceanography Program, Maryland Department of Natural Resources, NOAA Chesapeake Bay Office, and NOAA-funded UMCP Advanced Study Institute for the Environment. Components of LTRANS have been in development since 2002 and are described in the following publications: North et al. 2005, North et al. 2006a, North et al. 2006b, and North et al. 2008. +

M

The MITgcm (MIT General Circulation Model) is a numerical model designed for study of the atmosphere, ocean, and climate. Its non-hydrostatic formulation enables it to simulate fluid phenomena over a wide range of scales; its adjoint capability enables it to be applied to parameter and state estimation problems. By employing fluid isomorphisms, one hydrodynamical kernel can be used to simulate flow in both the atmosphere and ocean. +

The Model Parameter Dictionary is a tool for numerical modelers to
easily read and access model parameters from a simple formatted
input (text) file. Each parameter has a KEY, which identifies the
parameter, and a VALUE, which can be a number or a string. A
ModelParameterDictionary object reads model parameters from an input
file to a Dictionary, and provides functions for the user to look up
particular parameters by key name.
The format of the input file looks like:
PI: the text "PI" is an example of a KEY
3.1416
AVOGADROS_NUMBER: this is another
6.022e23
FAVORITE_FRUIT: yet another
mangoes
NUMBER_OF_MANGO_WALKS: this one is an integer
4
ALSO_LIKES_APPLES: this is a boolean
true
Example code that reads these parameters from a file called
"myinputs.txt":
my_param_dict = ModelParameterDictionary()
my_param_dict.read_from_file( 'myinputs.txt' )
pi = my_param_dict.read_float( 'PI' )
avogado = my_param_dict.read_float( 'AVOGADROS_NUMBER' )
fruit = my_param_dict.read_string( 'FAVORITE_FRUIT' )
nmang = my_param_dict.read_int( 'NUMBER_OF_MANGO_WALKS' )
apples_ok = my_param_dict.read_bool( 'ALSO_LIKES_APPLES' )
As in Python, hash marks (#) denote comments. The rules are that each
key must have one and only one parameter value, and each value must
appear on a separate line immediately below the key line.
Also available are functions to read input parameters from the
command line (e.g., read_float_cmdline( 'PI' ) ) +

P

The Permafrost Benchmark System (PBS) wraps the command-line ILAMB benchmarking system with a customized version of the CSDMS Web Modeling Tool (WMT), and adds tools for uploading CMIP5-compatible model outputs and benchmark datasets. The PBS allows users to access and run ILAMB remotely, without having to install software or data locally; a web browser on a desktop, laptop, or tablet computer is all that’s needed. +

The Princeton Ocean Model (POM), a simple-to-run yet powerful ocean modeling code that is able to simulate a wide-range of problems: circulation and mixing processes in rivers, estuaries, shelf and slope, lakes, semi-enclosed seas and open and global ocean. POM is a sigma coordinate, free surface ocean model with embedded turbulence and wave sub-models, and wet-dry capability. It has been one of the first coastal ocean models freely available to users, with currently over 3000 users from 70 countries.
For more details see: http://www.ccpo.odu.edu/POMWEB/ +

S

The Sea Level Affecting Marshes Model (SLAMM) simulates the dominant processes involved in
wetland conversions and shoreline modifications during long-term sea level rise. Tidal marshes can
be among the most susceptible ecosystems to climate change, especially accelerated sea level rise
(SLR). +

The Sorted Bedform Model (SBM) addresses the formation mechanism for sorted bedforms present on inner continental shelf environments. +

The Spectral Element Ocean Model (SEOM) solves the hydrostatic, and alternatively the non-hydrostatic, primitive equations using a mixed spectral / finite element solution procedure. Potential advantages of the spectral element method include flexible incorporation of complex geometry and spatially dependent resolution, rapid convergence, and attractive performance on parallel computer systems. A 2D version of SEOM, which solves the shallow water equations, has been extensively tested on applications ranging from global tides to the abyssal circulation of the Eastern Mediterranean. The 3D SEOM is undergoing initial testing for later release. +

T

The TELEMAC system is a powerful integrated modeling tool for use in the field of free-surface flows. The various simulation modules use high-capacity algorithms based on the finite-element method. Space is discretised in the form of an unstructured grid of triangular elements, which means that it can be refined particularly in areas of special interest. This avoids the need for systematic use of embedded models, as is the case with the finite-difference method.It has numerous applications in both river and maritime hydraulics. +

U

The Utah Energy Balance (UEB) snow model is an energy balance snowmelt model developed by David Tarboton's research group, first in 1994, and updated over the years. The model uses a lumped representation of the snowpack and keeps track of water and energy balance. The model is driven by inputs of air temperature, precipitation, wind speed, humidity and radiation at time steps sufficient to resolve the diurnal cycle (six hours or less). The model uses physically-based calculations of radiative, sensible, latent and advective heat exchanges. A force-restore approach is used to represent surface temperature, accounting for differences between snow surface temperature and average snowpack temperature without having to introduce additional state variables. Melt outflow is a function of the liquid fraction, using Darcy's law. This allows the model to account for continued outflow even when the energy balance is negative. Because of its parsimony (few state variables - but increasing with later versions) this model is suitable for application in a distributed fashion on a grid over a watershed. +

V

The VIC model is a large-scale, semi-distributed hydrologic model. As such, it shares several basic features with the other land surface models (LSMs) that are commonly coupled to global circulation models (GCMs):
The land surface is modelled as a grid of large (>1km), flat, uniform cells
Sub-grid heterogeneity (e.g. elevation, land cover) is handled via statistical distributions.
Inputs are time series of daily or sub-daily meteorological drivers (e.g. precipitation, air temperature, wind speed).
Land-atmosphere fluxes, and the water and energy balances at the land surface, are simulated at a daily or sub-daily time step
Water can only enter a grid cell via the atmosphere
Non-channel flow between grid cells is ignored
The portions of surface and subsurface runoff that reach the local channel network within a grid cell are assumed to be >> the portions that cross grid cell boundaries into neighboring cells
Once water reaches the channel network, it is assumed to stay in the channel (it cannot flow back into the soil)
This last point has several consequences for VIC model implementation:
Grid cells are simulated independently of each other
Entire simulation is run for each grid cell separately, 1 grid cell at a time, rather than, for each time step, looping over all grid cells
Meteorological input data for each grid cell (for the entire simulation period) are read from a file specific to that grid cell
Time series of output variables for each grid cell (for the entire simulation period) are stored in files specific to that grid cell
Routing of stream flow is performed separately from the land surface simulation, using a separate model (typically the routing model of Lohmann et al., 1996 and 1998) +

W

The Water Erosion Prediction Project (WEPP) model is a process-based, distributed parameter, continuous simulation erosion prediction model for application to hillslope profiles and small watersheds. Interfaces to WEPP allow its application as a stand-alone Windows program, a GIS-system (ArcView, ArcGIS) extension, or in web-based links. WEPP has been developed since 1985 by the U.S. Department of Agriculture for use on croplands, forestlands, rangelands, and other land use types. +

The Weather Research and Forecasting (WRF) Model is a next-generation mesoscale numerical weather prediction system designed to serve both operational forecasting and atmospheric research needs. It features multiple dynamical cores, a 3-dimensional variational (3DVAR) data assimilation system, and a software architecture allowing for computational parallelism and system extensibility. WRF is suitable for a broad spectrum of applications across scales ranging from meters to thousands of kilometers. +

The Weather Research and Forecasting Model Hydrological modeling system (WRF-Hydro) was developed as a community-based, open source, model coupling framework designed to link multi-scale process models of the atmosphere and terrestrial hydrology to provide:
An extensible multi-scale & multi-physics land-atmosphere modeling capability for conservative, coupled and uncoupled assimilation & prediction of major water cycle components such as: precipitation, soil moisture, snow pack, ground water, streamflow, and inundation
Accurate and reliable streamflow prediction across scales (from 0-order headwater catchments to continental river basins and from minutes to seasons)
A research modeling testbed for evaluating and improving physical process and coupling representations. +

C

The carbonate production is modelled according to organism growth and survival rates moderated by habitat suitability (chiefly light, temperature, nutrient). The environmental inputs are extracted from global databases. At the seabed the model's vertical zonation allows for underground (diagenetic) processes, bed granular transport, lower stable framework, upper collapsable framework. This voxelation allows for the carbonate to be placed (accumulated) correctly within the bedding and clast fabrics. The stratigraphy and seabed elevation are built in this way. As conditions change (e.g., by shallowing) the biological communities respond in the simulation, and so too do the production rates and clast/binding arrangements. Events punctuate the record, and the organism assemblages adjust according to frequencies and severities. The population stocks are calculated by diffuse competition in a Lotke-Volterra scheme, or via cellular simulations of close-in interactions to represent competition by growth, recruitment. +

B

The code computes the formation of a hillslope profile above an active normal fault. It represents the hillslope as a set of points with vertical and horizontal (fault-perpendicular) coordinates. Points move due to a prescribed erosion rate (which may vary in time) and due to offset during earthquakes with a specified recurrence interval and slip rate.
The model is described and illustrated in the following journal article:
Tucker, G. E., S. W. McCoy, A. C. Whittaker, G. P. Roberts, S. T. Lancaster, and R. Phillips (2011), Geomorphic significance of postglacial bedrock scarps on normal-fault footwalls, J. Geophys. Res., 116, F01022, doi: http://dx.doi.org/10.1029/2010JF001861. +

D

The delta-building model DeltaRCM expanded to included vegetation effects. Vegetation colonizes, grows, and dies, and influences the delta through increasing bank stability and providing resistance to flow. Vegetation was implemented to represent marsh grass type plants, and parameters of stem diameter, carrying capacity, logistic growth rate, and rooting depth can be altered. +

H

The development of the HAMSOM coding goes back to the mid eighties where it emerged from a fruitful co-operation between Backhaus and Maier-Reimer who later called his model 'HOPE'. From the very beginning HAMSOM was designed with the intention to allow simulations of both oceanic and coastal and shelf sea dynamics.
The primitive equation model with a free surface utilises two time-levels, and is defined in Z co-ordinates on the Arakawa C-grid. Stability constraints for surface gravity waves and the heat conduction equation are avoided by the implementation of implicit schemes. With a user defined weighting between future and presence time levels a hierarchy of implicit schemes is provided to solve for the free surface problem, and for the vertical transfer of momentum and water mass properties. In the time domain a scheme for the Coriolis rotation is incorporated which has second order accuracy. Time- and space-dependent vertical exchange and diffusivity coefficients are determined from a simple zero-order turbulence closure scheme which has also been replaced by a higher order closure scheme (GOTM). The resolution of a water column may degenerate to just one grid cell. At the seabed a non-linear (implicit) friction law as well as the full kinematic boundary condition is applied. Seabed cells may deviate from an undisturbed cell height to allow for a better resolution of the topography. The HAMSOM coding excludes any time-splitting, i.e. free surface and internal baroclinic modes are always directly coupled. Simple upstream and more sophisticated advection schemes for both momentum and matter may be run according to directives from the user.
Successful couplings with eco-system models (ECOHAM, ERSEM), an atmospheric model (REMO), and both Lagrangian and Eulerian models for sediment transport are reported in the literature. For polar applications HAMSOM was coupled with a viscous-plastic thermo-hydrodynamic ice model of Hibler type. Since about 15 years in Hamburg, and overseas in more than 30 laboratories, HAMSOM is already being in use as a community model.

N

The fault can have an arbitrary trace given by two points (x1, y1) and (x2, y2) in the fault_trace input parameter. These value of these points is in model-space coordinates and is not based on node id values or number of rows and columns. +

F

The grid contains the value 1 where fractures (one cell wide) exist, and 0 elsewhere. The idea is to use this for simulations based on weathering and erosion of, and/or flow within, fracture networks. +

W

The hydrodynamic module of WWTM solves the shallow water equations modified through the introduction of a refined sub-grid model of topography to deal with flooding and drying processes in irregular domains (Defina, 2000). The numerical model, which uses finite-element technique and discretizes the domain with triangular elements, has been extensively tested in recent years in the Venice lagoon, Italy (D’Alpaos and Defina, 2007, Carniello et al., 2005; Carniello et al., 2009).
For the wind wave modulel the wave action conservation equation is used, solved numerically with a finite volume scheme, and fully coupled with the hydrodynamic module (see Carniello et al. 2005). The two modules share the same computational grid. +

H

The hydromad (Hydrological Model Assessment and Development) package provides a set of functions which work together to construct, manipulate, analyse and compare hydrological models. +

O

The model accounts for glacier geometry (including contributory branches) and includes an explicit ice dynamics module. It can simulate past and future mass-balance, volume and geometry of (almost) any glacier in the world in a fully automated and extensible workflow. Publicly available data is used for calibration and validation. +

G

The model calculates a unique regression equation for each grid-cell between a the relative area of a specific land use (e.g. cropland) and global population. The equation is used to extrapolate that land use are into the future in each grid cell with predicted global population predictions. If the relative area of a land use reach a value of 95%, additional expansion is migrated to neighboring cells thus allowing spatial expansion. Geographic limitations are imposed on land use migration (e.g. no cropland beyond 60 degree latitude).
For more information:
Haney, N., Cohen, S. (2015), Predicting 21st century global agricultural land use with a spatially and temporally explicit regression-based model. Applied Geography, 62: 366-376. +

C

The model calculates the surface energy balance in order to represent energy transfer processes between the atmosphere and the ground. These processes include the radiation balance, the exchange of sensible heat, as well as evaporation and condensation. For a realistic representation of the thermal dynamics of the ground, the model includes processes such as the phase change of soil water and an insulating snow cover during winter. +

S

The model couples the shallow water equations with the Green-Ampt infiltration model and the Hairsine-Rose soil erosion model. Fluid flow is also modified through source terms in the momentum equations that account for changes in flow behavior associated with high sediment concentrations. See McGuire et al. (2016, Constraining the rates of raindrop- and flow-driven sediment transport mechanisms in postwildfire environments and implications for recovery timescales) for a complete model description and details on the numerical solution of the governing equations. +

1

The model evolves a 1D hillslope according to a non-linear diffusion rule (e.g. Roering et al. 1999) for varying boundary conditions idealised as a gaussian pulse of baselevel fall through time. A Markov Chain Monte Carlo inversion finds the most likely boundary condition parameters when compared to a time series of field data on hillslope morphology from the Dragon's Back Pressure Ridge, Carrizo Plain, CA, USA; see Hilley and Arrowsmith, 2008. +

M

The model is developed to simulate the sediment transport and alluvial morphodynamics of bedrock reaches. It is capable of computing the alluvial cover fraction, the alluvial-bedrock transition and flow hydrodynamics over both bedrock and alluvial reaches. This model is now validated against a set of laboratory experiment. Field scale application of the model can also be done using field parameters. +

S

The model is related to the numerical solution of the shallow water equations in spherical geometry. The shallow water equations are used as a kernel for both oceanic and atmospheric general circulation models and are of interest in evaluating numerical methods for weather forecasting and climate modeling. +

Q

The model is three-dimensional and fully nonlinear with a free surface, incorporates advanced turbulence closure, and operates in tidal time. Variable horizontal and vertical resolution are facilitated by the use of unstructured meshes of linear triangles in the horizontal, and structured linear elements in the vertical +

E

The model predicts bankfull geometry of single-thread, sand-bed rivers from first principles, i.e. conservation of channel bed and floodplain sediment, which does not require the a-priori knowledge of the bankfull discharge. +

A

The model reproduce the effect of a variability in soil resistance on salt marsh erosion by wind waves.
The model consists of a two-dimensional square lattice whose elements, i, have randomly distributed resistance, r_i. The critical soil height H_ci for boundary stability is calculated from soil shear strength values and is assumed as representative of soil resistance, as it is a convenient way to take into account general soil and ambient conditions. The erosion rate of each cell, E_i, which represents the erosion of an homogeneous marsh portion, is defined as:
E_i=〖αP〗^β exp (-H_ci/H)
Where α and β are non-dimensional constants set equal to 0.35 and 1.1 respectively, P is the wave power, and H is the mean wave height.
The model follows three rules: i) only neighbors of previously eroded cells can be eroded. Therefore, only cells having at least one side in common with previously eroded elements are susceptible to erosion; ii) at every time step one element is eroded at random with probability p_i=E_i/(∑E_i ); iii) A cell is removed from the domain if it remains isolated from the rest of the boundary (no neighbors). +

W

The model simplifies the geometry of a backbarrier tidal basin with 3 variables: marsh depth, mudflat depth, mudflat width. These 3 variables are evolved by sediment redistribution driven by wave processes. Sediment are exchanged with the open ocean, which is an external reservoir. Organic sediments are produced on the marsh platform. +

S

The model simulates the formation, drift, and melt of a population of icebergs utilizing Monte Carlo based techniques with a number of underlying parametric probability distributions to describe the stochastic behavior of iceberg formation and dynamics. +

M

The model simulates the long-term evolution of meandering rivers above heterogeneous floodplain surfaces, i.e. floodplains that have been reworked by the river itself through the formation of oxbow lakes and point bars. +

C

The model tracks both surface CRN concentration and concentration eroded off hillslopes into fluvial network in a simplified landscape undergoing both landslide erosion and more steady 'diffusive-like' erosion. Sediment mixing is allowed in the fluvial network. Code can be used to help successfully develop CRN sampling procedures in terrains where landslides are important. +

T

The model uses the vertically continuous (not active layer-based), morphodynamic framework proposed by Parker, Paola an Leclair in 2000 to model the streamwise and vertical dispersal of a patch of tracers installed in a equilibrium gravel bed. The model was validated at laboratory and field scales on the mountainous Halfmoon Creek, USA, and on the braided Buech River, France.
Different versions of the model are uploaded in the github folder because the formulaiton for the calculation of the formative bed shear stress varied depending on the available data.
REFERENCE
Parker, G., Paola, C. & Leclair, S. (2000). Probabilistic Exner sediment continuity equation for mixtures with no active layer. Journal of Hydraulic Engineering, 126 (11), 818-826. +

C

The module is designed to calculate morphological changes and water discharge outflow of a crevasse splay that is triggered by a preset flood event and evolves afterwards. The inputs for "mainCS.m" should be daily water discharge and sediment flux series of the trunk channel upstream the crevasse splay. The outputs will be daily series for the cross-sectional parameters of the crevasse splay, and daily water discharge series of the trunk channel downstream the crevasse splay. One limitation of the present version is it only calculates the expanding and healing of a crevasse splay, while ignores the possible morphological change (demise or revival) of the trunk channel downstream the crevasse splay. Another limitation is the codes are originally written for the Lower Yellow River(a suspended load dominated river) for the purpose of calculating sediment budget in the Lower Yellow over a long timescale, say as long as hundreds years, so the present module can not be applied to other alluvial rivers without modifying those lines related to channel geometry, bankfull discharge and bank erosion(deposition). +

F

The numerical model solves the two-dimensional shallow water equations with different modes of sediment transport (bed-load and suspended load) (Canestrelli et al. 2009, Canestrelli et al, 2010). The scheme solves the system of partial differential equations cast in a non-conservative form, but it has the important characteristic of reducing automatically to a conservative scheme if the underlying system of equations is a conservation law. The scheme thus belongs to the so-called category of “shock-capturing” schemes. At the present I am adding a new module for the computation of mud flows, and I want to apply the model to the Fly River (Papua New Guinea) system. +

R

The river water temperature model is designed to be applied in Arctic rivers. Heat energy transfers considered include surface net solar radiation, net longwave radiation, latent heat due to evaporation and condensation, convective heat and the riverbed heat flux. The model is explicitly designed to interact with a permafrost channelbed and frozen conditions through seasonal cycles. In addition to the heat budget, river discharge, or stage, drives the model. +

G

The term "extended GST model" indicates the combination of an analytical GST migration model combined with closure relations (for slope and surface texture) based on the assumption of quasi-equilibrium conditions. The extended model is described in Blom et al, 2017 "Advance, retreat, and halt of abrupt gravel-sand transitions in alluvial rivers", http://dx.doi.org/10.1002/2017GL074231. +

1

The term “breaching” refers to the slow, retrogressive failure of a steep subaqueous slope, so forming a nearly vertical turbidity current directed down the face. This mechanism, first identified by the dredging industry, has remained largely unexplored, and yet evidence exists to link breaching to the formation of sustained turbidity currents in the deep sea. The model can simulate a breach-generated turbidity current with a layer-averaged formulation that has at its basis the governing equations for the conservation of momentum, water, suspended sediment and turbulent kinetic energy. In particular, the equations of suspended sediment conservation are solved for a mixture of sediment particles differing in grain size. In the model the turbidity current is divided into two regions joined at a migrating boundary: the breach face, treated as vertical, and a quasi-horizontal region sloping downdip. In this downstream region, the bed slope is much lower (but still nonzero), and is constructed by deposition from a quasi-horizontal turbidity current. The model is applied to establish the feasibility of a breach-generated turbidity current in a field setting, using a generic example based on the Monterey Submarine Canyon, offshore California, USA. +

W

Third generation random phase spectral wave model, including shallow water physcis. +

P

This class implements Voller, Hobley, and Paola’s experimental matrix solutions for flow routing. The method works by solving for a potential field at all nodes on the grid, which enforces both mass conservation and flow downhill along topographic gradients. It is order n and highly efficient, but does not return any information about flow connectivity.
Options are permitted to allow “abstract” routing (flow enforced downslope, but no particular assumptions are made about the governing equations), or routing according to the Chezy or Manning equations. This routine assumes that water is distributed evenly over the surface of the cell in deriving the depth, and does not assume channelization. You will need to back- calculate channel depths for yourself using known widths at each node if that is what you want. +

F

This class uses the Braun-Willett Fastscape approach to calculate the amount of erosion at each node in a grid, following a stream power framework. This should allow it to be stable against larger timesteps than an explicit stream power scheme. +

A

This code creates the channel centerline (i.e., the line equidistant between two banks) for a single thread-channel, using a second-order autoregressive model. The code implements a model for random centerlines proposed by Ferguson, R. I. (1976) Disturbed periodic model for river meanders, Earth Surface Processes 1(4), 337-347, doi:10.1002/esp.3290010403. This implementation also includes (1) controls for the node spacing and extent of channels, (2) removal of self-intersecting (cutoff) loops from modeled centerlines, and (3) a wrapper script to sweep model parameter space and generate alternate realizations using different random disturbance series. +

V

This code is based on Cellular Automata Tree Grass Shrub Simulator (CATGraSS). It simulates spatial competition of multiple plant functional types through establishment and mortality. In the current code, tree, grass and shrubs are used. +

H

This component calculates Hack’s law parameters for drainage basins.
Hacks law is given as
L = C * A**h
Where L is the distance to the drainage divide along the channel, A is the drainage area, and C are parameters.
The HackCalculator uses a ChannelProfiler to determine the nodes on which to calculate the parameter fit. +

C

This component calculates chi indices, sensu Perron & Royden, 2013, for a Landlab landscape. +

S

This component calculates steepness indices, sensu Wobus et al. 2006, for a Landlab landscape. Follows broadly the approach used in GeomorphTools, geomorphtools.org. +

F

This component generates random numbers using the Weibull distribution
(Weibull, 1951). No particular units must be used, but it was written with
the fire recurrence units in time (yrs).
Using the Weibull Distribution assumes two things: All elements within the study area have the same fire regime. Each element must have (on average) a constant fire regime during the time span of the study.<br>
As of Sept. 2013, fires are considered instantaneous events independent of
other fire events in the time series. +

D

This component identifies depressions in a topographic surface, finds an outlet for each depression. If directed to do so (default True), and the component is able to find existing routing fields output from the 'route_flow_dn' component, it will then modify the drainage directions and accumulations already stored in the grid to route flow across these depressions. +

This component implements a depth and slope dependent linear diffusion rule in the style of Johnstone and Hilley (2014). Soil moves with a prescribed exponential vertical velocity profile. Soil flux is dictated by a diffusivity, K, and increases linearly with topographic slope. +

E

This component implements exponential weathering of bedrock on hillslopes. Uses exponential soil production function in the style of Ahnert (1976).
Consider that w_0 is the maximum soil production rate and that d* is the characteristic soil production depth. The soil production rate w is given as a function of the soil depth d,
w = w_0^(-d/d*)
The ExponentialWeatherer only calculates soil production at core nodes. +

L

This component is closely related to the FlowAccumulator, in that this is accomplished by first finding flow directions by a user-specified method and then calculating the drainage area and discharge. However, this component additionally requires the passing of a function that describes how discharge is lost or gained downstream, f(Qw, nodeID, linkID, grid). See examples at https://github.com/landlab/landlab/blob/master/landlab/components/flow_accum/lossy_flow_accumulator.py to see how this works in practice. +

F

This components finds the steepest single-path steepest descent flow directions. It is equivalent to D4 method in the special case of a raster grid in that it does not consider diagonal links between nodes. For that capability, use FlowDirectorD8. +

This is a 1DV wave-phase resolving numerical model for fluid mud transport based on mixture theory with boundary layer approximation. The model incorporates turbulence-sediment interaction, gravity-driven flow, mud rheology, bed erodibility and the dynamics of floc break-up and aggregation. +

W

This is a Java Applet that allows the user to change different parameters (such as rainfall, erodibility, tectonic uplift) and watch how the landform evolve over time under different scenarios. It is based on a Cellular Automata algorithm. Two versions are available: linear and non-linear. Details can be found in:
Luo, W., Peronja, E., Duffin, K., Stravers, A. J., 2006, Incorporating Nonlinear Rules in a Web-based Interactive Landform Simulation Model (WILSIM), Computers and Geosciences, v. 32, n. 9, p. 1512-1518 (doi: 10.1016/j.cageo.2005.12.012).
Luo, W., K.L. Duffin, E. Peronja, J.A. Stravers, and G.M. Henry, 2004, A Web-based Interactive Landform Simulation Model (WILSIM), Computers and Geosciences. v. 30, n. 3, p. 215-220. +

G

This is a Landlab wrapper for A Wickert's gFlex flexure model (Wickert et al., submitted to Geoscientific Model Development). The most up-to-date version of his code can be found at github.com/awickert/gFlex.
This Landlab wrapper will use a snapshot of that code, which YOU need to install on your own machine. A stable snapshot of gFlex is hosted on PyPI, which is the recommended version to install.
If you have pip (the Python package install tool), simply run 'pip install gFlex' from a command prompt.
Alternatively, you can download and unpack the code (from github, or with PyPI, pypi.python.org/pypi/gFlex/), then run 'python setup.py install'. +

C

This is a special case of the Regional Ocean Modeling System(ROMS). The National Ocean Service presently has an Operational Forecast System (CBOFS) for the Chesapeake Bay which generates only water levels and depth‐integrated currents. As a next generation system, a fully three‐dimensional, baroclinic Forecast System (CBOFS2) was developed, calibrated and validated; this system will produce water levels, currents, temperature and salinity. First, a two‐month tides only simulation was conducted to validate the water levels and currents and thereafter, a synoptic hindcast simulation from June 01, 2003–September 01, 2005 was conducted to validate water levels, currents, temperature and salinity. Upon comparison with observations, CBOFS2 for the most part met the target NOS water level error criteria and for current error, the criteria were met exceptionally well; the temperature and salinity errors were frequently less than 1 C and 3 PSU respectively. Hence, the predictive accuracy of CBOFS2 warranted it being accepted as a suitable three‐dimensional upgrade to CBOFS.
Please see https://csdms.colorado.edu/wiki/Model:ROMS for details. +

N

This is a time-stepping point model which uses linear finite elements to determine the vertical structure of the horizontal components of velocity and density under specified surface forcing. Both a quadratic closure scheme and the level 2.5 closure scheme of Mellor and Yamada are used in this code. +

G

This is a tool that I created to help find knickpoints based on the curvature of a landscape. It provides information about a stream including, knickpoint locations, Elevation/distance that can be used to create longitudinal profiles, XYvalues of all the cells in a stream path, etc. The tool uses built-in tools for ArcGIS 10.x (so you must run this on a machine with ArcGIS 10.x installed), but it is written in python. I used it with a 1m LiDAR DEM, so I'm not totally sure how well it will pick out knickpoints on coarser gridded DEMs. +

T

This model a 1-D numerical model of permafrost and subsidence processes.
It aims to investigate the subsurface thermal impact of thaw lakes of various depths, and to evaluate how this impact might change in a warming climate. +

M

This model accounts for the bed evolution i.e. aggradation/degradation and grain size distribution of surface material in gravel bed rivers under anthropogenic changes such as dam closure and sediment augmentation. This model is developed for an alpine gravel bed river located in SE France (Buech river). +

G

This model calculates the long profile of a river with a gravel-sand transition. The model uses two grain sizes: size Dg for gravel and size Ds for sand. The river is assumed to be in flood for the fraction of time Ifg for the gravel-bed reach and fraction Ifs for the sand-bed reach. All sediment transport is assumed to take place when the river is in flood.
Gravel transport is computed using the Parker (1979) approximation of the Einstein (1950) bedload transport relation. Sand transport is computed using the total bed material transport relation of Engelund and Hansen (1967).
In this simple model the gravel is not allowed to abrade. Both the gravel-bed and sand-bed reaches carry the same flood discharge Qbf.
Gravel is transported as bed material in, and deposits only in the gravel-bed reach. A small residual of gravel load is incorporated into the sand at the gravel-sand transition. Sand is transported as washload in the gravel-bed reach, and as bed material load in the sand-bed reach.
The model allows for depositional widths Bdgrav and Bdsand that are wider than the corresponding bankfull channel widths Bgrav and Bsand of the gravel-bed and sand-bed channels. As the channel aggrades, it is assumed to migrate and avulse to deposit sediment across the entire depositional width. For each unit of gravel deposited in the gravel-bed reach, it is assumed that Lamsg units of sand are deposited. For each unit of sand deposited on the sand-bed reach, it is assumed that Lamms units of mud are deposited.
The gravel-bed reach has sinuosity Omegag and the sand-bed reach has sinuosity Omegas.
Bed resistance is computed through the use of two specified constant Chezy resistance coefficients; Czg for the gravel-bed reach and Czs for the sand-bed reach. +

H

This model can be used for both transport after sediment failure and for hyperpycnal transport. +

This model evolves a hogback through time. A resistant layer of
rock, which weathers slowly, overlies a softer layer of rock that weathers
quickly. Resistant rock produces "blocks" which land on the adjoining
hillslope. Boundaries incise at a specified rate. User can set hogback
layer thickness, block size, and dip, as well as relative weathering and
incision rates. Trackable metrics included are time and space-averaged
slope, block height, weathering rate, and erosion rate. Parameters that users need to specify are surrounded by many
comment signs. +

F

This model implement the calculation of the 'Frost Number', a dimensionless ratio based on freezing and thawing degree days in the year. Specifically, the 'Air Frost Number' intents to predict the existence of permafrost at a given location based on a cosine-function approximating the annual temperature distribution. +

W

This model is a GUI implementation of a simple cellular automata dune model. The model was originally proposed by Werner (1995, Geology 23) and has seen several extensions. It can simulate basic barchan, transverse, star, and linear dunes. The model is designed to be easy to operate for researchers or students without programming skills. Also included is a tool to operate the model from ArcGIS. +

M

This model is a nonuniform, quasi-unsteady, movable bed, single channel flow model for heterogeneous size-density mixtures +

G

This model is designed to simulate longitudinal profiles with headward advancing headcuts. This model simulates gully erosion on the centennial-scale given information such as average rainfall and infiltration rates. The modeler also specifies a headcut erosion rate and or a rule for headcut retreat (either discharge-dependent or height-dependent retreat). +

R

This model simulates the interaction between suspended sediment, chlorophyll-a, and mussel population density. Discharge is the driver; it modulates suspended sediment and its interactions in the system. The model is suitable for simulating mussel densities at-a-site. It was originally developed to test the hypothesis that increased sediment loads in Minnesota Rivers are a plausible cause of observed mussel population declines. The model and results are described in detail in the following paper: https://doi.org/10.1086/684223 +

L

This model uses a non-dimensional equation for luminescence in a mixing soil that was derived from the Fokker-Plank Equation. +

K

This model uses the Green-Ampt equation to represent infiltration and the kinematic wave equation to represent runoff over a landscape. The effects of rainfall interception can also be included. +

A

B

This module code is inactive. +

C

F

This module code is inactive. +

This module code is inactive. +

I

M

This module code is inactive. +

This module code is inactive. +

S

This module code is inactive. +

E

This module code is inactive. +

F

This module code is inactive. +

This module code is inactive. +

This module code is inactive. +

This module code is inactive. +

S

C

This module code is inactive. +

F

This module code is inactive. +

I

This module code is inactive. +

L

This module code is inactive. +

1

This module implements a particle-based model of hillslope evolution, which has an associated continuum description (introduced here: https://arxiv.org/abs/1801.02810). The model takes as input a few simple parameters which determine the equilibrium hillslope shape and dynamics, and can be used to produce equilibrium profiles and study the response of the hillslope to perturbations. The model benefits from straightforward implementation, as well as the flexibility to incorporate sophisticated perturbations and to be accessorized by local or nonlocal fluxes. +

S

This module implements sediment flux dependent channel incision following::
E = f(Qs, Qc) * ((a stream power-like term) - (an optional threshold)),
where E is the bed erosion rate, Qs is the volumetric sediment flux into a node, and Qc is the volumetric sediment transport capacity at that node.
This component is under active research and development; proceed with its use at your own risk. +

P

This module uses Taylor Perron’s implicit (2011) method to solve the nonlinear hillslope diffusion equation across a rectangular, regular grid for a single timestep. Note it works with the mass flux implicitly, and thus does not actually calculate it. Grid must be at least 5x5.
Boundary condition handling assumes each edge uses the same BC for each of its nodes. This component cannot yet handle looped boundary conditions, but all others should be fine.
This component has KNOWN STABILITY ISSUES which will be resolved in a future release; use at your own risk. +

E

This numerical 1D research code Elv applied to gravel-sand transitions relates to Blom et al., 2017 "Advance, retreat, and halt of abrupt gravel-sand transitions in alluvial rivers", http://dx.doi.org/10.1002/2017GL074231. +

Z

This object manages ‘zones’ that are used to evaluate the spatial aspect of taxa. A zone represents a portion of a model grid. It is made up of spatially continuous grid nodes. +

T

This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. It uses the "diffusive wave" method to compute flow velocities for all of the channels in a D8-based river network. This method includes a pressure gradient term that is induced by a water-depth gradient in the downstream direction. This means that instead of using bed slope in Manning's equation or the law of the wall, the water-surface slope is used. +

This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. The kinematic wave method (Lighthill and Whitham, 1955) is the simplest method for modeling flow in open channels. This method combines mass conservation with the simplest possible treatment of momentum conservation, namely that all terms in the general momentum equation (pressure gradient, local acceleration and convective acceleration) are neglible except the friction and gravity terms. A flow in which gravitational acceleration is exactly balanced by friction is referred to as steady, uniform flow. For these flows the water surface slope, energy slope and bed slope are all equal. +

This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. TopoFlow supports three different types of flow diversions: sources, sinks and canals. Sources are locations such as natural springs where water enters the watershed at a point by some process other than those that are otherwise modeled. Similarly, sinks are locations where water leaves the watershed at a point. Canals are generally man-made reaches such as tunnels or irrigation ditches that transport water from one point to another, typically without following the natural gradient of the terrain that is indicated by the DEM. The upstream end is essentially a sink and the downstream end a source. +

This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. The dynamic wave method is the most complete and complex method for modeling flow in open channels. This method retains all of the terms in the full, 1D momentum equation, including the gravity, friction and pressure gradient terms (as used by the diffusive wave method) as well as local and convective acceleration (or momentum flux) terms. This full equation is known as the St. Venant equation. In the current version of TopoFlow it is assumed that the flow directions are static and given by a D8 flow grid. In this case, integral vs. differential forms of the conservation equations for mass and momentum can be used. +

This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. +

This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. +

This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. +

B

This program calculates backwater curves over a sand-bed stream with a specified spatially constant bed slope S. The calculation uses the hydraulic resistance formulation of Wright and Parker (2004) (but without the flow stratification correction). +

D

This program calculates the 1D bed evolution of a sand-bed river after installation of a dredge slot. The calculation begins with the assumption of a prevailing mobile-bed normal flow equilibrium before installation of the dredge slot. The flow depth H, volume bedload transport rate per unit width qb and volume suspended transport rate per unit width qs at normal flow are computed based on input values of discharge Qww, channel width B, bed material sizes D50 and D90, sediment submerged specific gravity Rr and bed slope S.
The sediment is assumed to be sufficiently uniform so that D50 and D90 are unchanging in space and time. The input parameter Inter specifies the fraction of any year for which flood flow prevails. At other times of the year the river is assumed to be morphologically dormant.
The reach is assumed to have length L. The dredge slot is excavated at time t = 0, and then allowed to fill in time with no subsequent excavation. The depth of initial excavation below the bottom of the bed prevailing at normal equilibrium is an input variable with the name Hslot. The dredge slot extends from an upstream point equal to ru*L to a downstream point rd*Hslot, where ru and rd are user-input values.
The porosity lamp of the sediment deposit is a user-input parameter.
The bedload transport relation used in the calculation is that of Ashida and Michiue (1972). The formulation for entrainment of sediment into suspension is that of Wright and Parker (2004). The formulation for flow resistance is that of Wright and Parker (2004). The flow stratification correction of Wright-Parker is not implemented here for simplicity. A quasi-equilibrium formulation is used to computed the transport rate of suspended sediment from the entrainment rate.
A backwater calculation is used to compute the flow. The water surface elevation at the downstream end of the reach is held constant at the value associated with normal flow equilibrium.
Iteration is required to compute: a) the flow depth prevailing at normal flow; b) the friction slope and depth prevailing at normal flow, b) the friction slope and depth associated with skin friction associated with skin friction from any given value of depth, and b) the minimum Shields number below which form drag is taken to vanish.

A

This program computes 1D bed variation in rivers due to differential sediment transport. The sediment is assumed to be uniform with size D. All sediment transport is assumed to occur in a specified fraction of time during which the river is in flood, specified by an intermittency. A Manning-Strickler relation is used for bed resistance. A generic Meyer-Peter Muller relation is used for sediment transport. The flow is computed using a backwater formulation for gradually varied flow. +

This program computes 1D bed variation in rivers due to differential sediment transport in which it is possible to allow the bed to undergo a sudden vertical fault of a specified amount, at a specified place and time. Faulting is realized by moving all notes downstream of the specified point downward by the amount of the faulting.
The sediment is assumed to be uniform with size D. All sediment transport is assumed to occur in a specified fraction of time during which the river is in flood, specified by an intermittency. A Manning-Strickler formulation is used for bed resistance. A generic relation of the general form of that due to Meyer-Peter and Muller is used for sediment transport. The flow is computed using the normal flow approximation. +

B

This program computes fluvial aggradation/degradation with a bedrock-alluvial transition. The bedrock-alluvial transition is located at a point sba(t) which is free to change in time. A bedrock basement channel with slope Sb is exposed from x = 0 to sba(t); it is covered with alluvium from x = sba(t) to x = sd, where sd is fixed. Initially sba = 0. The bedrock basement channel is assumed to undergo no incision on the time scales at which the alluvial reach responds to change. In computing bed level change on the alluvial reach, the normal (steady, uniform) flow approximation is used. Base level is maintained at x = sd, where bed elevation h = 0. The Engelund-Hansen relation is used to compute sediment transport rate, so the analysis is appropriate for sand-bed streams. Resistance is specified in terms of a constant Chezy coefficient Cz. +

A

This program computes gravel bedload and size distribution from specified values for the bed surface size distribution, the sediment specific gravity, and the effective bed shear velocity (based on skin friction only). +

This program computes the time evolution of the long profile of a river of constant width carrying a mixture of gravel sizes, the downstream end of which has a prescribed elevation. In particular, the program computes the time evolution of the spatial profiles of bed elevation, total gravel bedload transport rate and grain size distribution of the surface (active) layer of the bed. The river has constant width. The upstream point, at which sediment is fed, is fixed in the horizontal to be at x = 0. The vertical elevation of the upstream point may change freely as the bed aggrades or degrades. The reach has constant length L, so that the downstream point is fixed in the horizontal at x = L. This downstream point has a user-specified initial elevation hdI.
Gravel bedload transport of mixtures is computed with a user-specified selection of the Parker (1990), or Wilcock-Crowe (2003) surface-based formulations for gravel transport. Sand and finer material must first be excluded from the grain size distributions, which then must be renormalized for gravel content only, in the case of the Parker (1990) relation. In the case of the Wilcock-Crowe (2003) relation, the sand is retained in the computation. +

This program computes the time evolution of the long profile of a river of constant width carrying a mixture of gravel sizes, the downstream end of which has a prescribed elevation. +

S

This program implements the calculation for steady-state aggradation of a sand-bed river in response to sea level rise at a constant rate, as outlined in Chapter 25 of the e-book. +

R

This program is a companion to the program SteadyStateAg, which computes the steady-state aggradation of a river with a specified base level rise at the downstream end. This program computes the time evolution toward steady-state aggradation.
The calculation assumes a specified, constant Chezy resistance coefficient Cz and floodplain width Bf. The sediment is assumed to be uniform with size D. All sediment transport is assumed to occur in a specified fraction of time during which the river is in flood, specified by an intermittency. If grain size D < 2 mm the Engelund-Hansen (1967) formulation for total bed material transport of sand is used. If grain size D >= 2 mm the Parker (1979) bedload transport formulation for gravel is used. The flow is computed using the normal flow approximation. The reach has downchannel length L, and base level is allowed to rise at a specified rate at the downstream end. +

This program provides two modules for studying the approach to mobile-bed normal equilibrium in recirculating and sediment-feed flumes containing uniform sediment.
The module "Recirc" implements a calculation for the case of a flume that recirculates water and sediment. The module "Feed" implements a calculation for the case of flume which receives water and sediment feed. +

T

This pseudo-2D (cross-section, 1 independent variable x) numerical model permits calculating 1D lithospheric flexure with different rheologies, in combination with faulting, loading, and erosion/deposition. The programs are developed in C for Linux platforms, graphic output is produced using GMT scripts, and standard PCs match the CPU and memory requirements. The software is available for free under a GPL license. +

W

This subroutine computes the deep water significant wave height and period at each point under a hurricane +

S

This tool can be used to map out areas of hillslopes where the emergence of bedrock drives an increase in surface roughness. The tool requires an input DEM in float format and will output the rasters, also in float format, for three eigenvectors that together describe the distribution of normal vectors within a user-defined neighbourhood for each pixel. +

C

This tool is used for examining bedrock channels. The tool is based on the assumption that the stream power incision model (SPIM) adequately describes channel incision. Channels profiles are converted to chi-elevation space, where chi is a transformed longitudinal coordinate that takes drainage area into account. The tool uses a variety of statistical tests to extract the most likely series of segments with distinct steepness in chi-elevation space. It also performs statistical tests to determine the best fit m/n ratio, where m is an area (A) exponent and n is a slope (S) exponent in the SPIM with E = K A^m S^n, where E is an erosion rate and K is an 'erodibility'. +

T

This tool is used to creates a "profile-smoothed" DEM from an input DEM. +

H

This tool produces a flow path for each hilltop pixel on a landscape, generating hillslope length and relief data at a hillslope scale. These data can be used to discriminate between linear and nonlinear sediment flux laws at a landscape scale.
The model requires an input DEM in float format and produces a series raster and plain text output files which can be visualized and analysed using code provided at: https://github.com/sgrieve/LH_Paper_Plotting
For detailed information about how to use this tool please refer to the documentation (http://www.geos.ed.ac.uk/~smudd/LSDTT_docs/html/basin_metrics.html). +

D

This tool provides a method for extracting information on the nature and spatial extent of active geomorphic processes across deltas from the geometry of islands and the channels around them using machine learning.
The method consists of a two-step ensemble unsupervised machine learning algorithm that clusters islands into spatially continuous zones based on morphological metrics computed on remotely sensed imagery +

This tool uses chi river profile analysis to predict channel head locations across a landscape and therefore allow the extraction of river networks. It is most suitable for use with high resolution LiDAR (1m) DEMs. The model requires an input DEM in float format and will output the extracted channel heads and networks, also in float format. For detailed information about how to use this tool please refer to the documentation (http://www.geos.ed.ac.uk/~smudd/LSDTT_docs/html/channel_heads.html)
and to the associated paper (http://onlinelibrary.wiley.com/doi/10.1002/2013WR015167/full). +

R

This toolbox was constructed to help analyze changing river planforms (aerial views). Given a binary mask of a river, tools are provided to efficiently compute
- channel centerline
- banklines
- channel width (two methods)
- centerline direction
- centerline curvature
If multiple input mask images contain georeference information, a tool is provided to "stitch" the masks together--before or after analysis. Stitching can be done for both images and vectors of x,y coordinates. The mapping toolbox is required for this functionality.
If multiple masks (realizations) of the river are available, RivMAP includes tools to
- compute centerline migrated areas
- compute erosional and accretional areas
- identify cutoff areas and quantify cutoff length, chute length, and cutoff area
- generate channel belt boundaries and centerline
- measure and map changes (in width, migration areas or rates, centerline elongation, accreted/eroded areas) in space and time +

A

This workbook computes 1D bed variation in rivers due to differential sediment transport. The sediment is assumed to be uniform with size D. All sediment transport is assumed to occur in a specified fraction of time during which the river is in flood, specified by an intermittency. A Manning-Strickler formulation is used for bed resistance. A generic relation of the general form of that due to Meyer-Peter and Muller is used for sediment transport. The flow is computed using the normal flow approximation. +

This workbook computes the time evolution of a river toward steady state as it flows into a subsiding basin. The subsidence rate s is assumed to be constant in time and space. The sediment is assumed to be uniform with size D. A Manning-Strickler formulation is used for bed resistance. A generic relation of the general form of that due to Meyer-Peter and Muller is used for sediment transport. The flow is computed using the normal flow approximation. The river is assumed to have a constant width. +

G

Three dimensional simulations of the Turbidity currents using DNS of incompressible Navier-Stokes and transport equations. +

T

TopoFlow is a powerful, spatially-distributed hydrologic model with a user-friendly point-and-click interface. Its main purpose is to model many different physical processes in a watershed with the goal of accurately predicting how various hydrologic variables will evolve in time in response to climatic forcings. +

TopoToolbox provides a set of Matlab functions that support the analysis of relief and flow pathways in digital elevation models. The major aim of TopoToolbox is to offer stable and efficient analytical GIS utilities in a non-GIS environment in order to support the simultaneous application of GIS-specific and other quantitative methods. With version 2, TopoToolbox adds various tools specifically targeted at tectonic geomorphologists such as Chiplots and slopearea plots. +

Topography is a Python library to fetch and cache NASA Shuttle Radar Topography Mission (SRTM) and JAXA Advanced Land Observing Satellite (ALOS) land elevation data using the OpenTopography REST API.
The Topography library provides access to the following global raster datasets:
* SRTM GL3 (90m)
* SRTM GL1 (30m)
* SRTM GL1 (Ellipsoidal)
* ALOS World 3D (30m)
* ALOS World 3D (30m, Ellipsoidal)
The library includes an API and CLI that accept the dataset type, a latitude-longitude bounding box, and the output file format. Data are downloaded from OpenTopography and cached locally. The cache is checked before downloading new data. Data from a cached file can optionally be loaded into an xarray DataArray using the experimental open_rasterio method. +

A

Traditionally the Area-Slope equation (S=cA^alpha) is extracted from a catchment area vs. slope plot. This model calculate the Area-Slope constant and coefficient (alpha) for each pixel at the catchment as a function of its downslope neighbor. +

O

Transiently evolving river-channel width as a function of streambank properties, sediment in transport, and the hydrograph.
This model is designed to compute the rates of river-channel widening and narrowing based on changing hydrological regimes. It is currently designed for rivers with cohesive banks, with a critical shear stress for particle detachment and an erosion-rate coefficient.
OTTAR contains:
* The RiverWidth class, which contains methods to evolve the width of an alluvial river.
* The FlowDepthDoubleManning class, which is used to estimate flow depth from discharge, even with an evolving river-channel geometry. +

U

Underworld2 is an open-source, particle-in-cell finite element code tuned for large-scale geodynamics simulations. The numerical algorithms allow the tracking of history information through the high-strain deformation associated with fluid flow (for example, transport of the stress tensor in a viscoelastic, convecting medium, or the advection of fine-scale damage parameters by the large-scale flow). The finite element mesh can be static or dynamic, but it is not contrained to move in lock-step with the evolving geometry of the fluid. This hybrid approach is very well suited to complex fluids which is how the solid Earth behaves on a geological timescale. +

S

Uses the Barnes et al (2014) algorithms to replace pits in a topography with flats, or optionally with very shallow gradient surfaces to allow continued draining.
This component is NOT intended for use iteratively as a model runs; rather, it is to fill in an initial topography. If you want to repeatedly fill pits as a landscape develops, you are after the LakeMapperBarnes component. If you want flow paths on your filled landscape, manually run a FlowDirector and FlowAccumulator for yourself.
The locations and depths etc. of the fills will be tracked, and properties are provided to access this information. +

W

WACCM is NCAR's atmospheric high-altitude model; CARMA is Brian Toon's aerosol microphysical sectional model. I'm studying sulfate aerosols in the UTLS region using this coupled model. +

WASH123D is an integrated multimedia, multi-processes, physics-based computational watershed model of various spatial-temporal scales. The integrated multimedia includes:
# dentric streams/rivers/canal/open channel,
# overland regime (land surface),
# subsurface media (vadose and saturated zones), and
# ponds, lakes/reservoirs (small/shallow).
It also includes control structures such as weirs, gates, culverts, pumps, levees, and storage ponds and managements such as operational rules for pumps and control structures.
The WASH123D code consisted of eight modules to deal with multiple media:
# 1-D River/Stream Networks,
# 2-D Overland Regime,
# 3-D Subsurface Media (both Vadose and Saturated Zones);
# Coupled 1-D River/Stream Network and 2-D Overland Regime,
# Coupled 2-D Overland Regime and 3-D Subsurface,
# Coupled 3-D Subsurface and 1-D River Systems;
# Coupled 3-D Subsurface Media, 2-D Overland, and 1-D River Network; and
# Coupled 0-D Shallow Water Bodies and 1-D Canal Network.
For any of the above eight modules, flow only, transport only, or coupled flow and transport simulations can be carried out using WASH123D. +

C

We have developed a hybrid numerical model at a continental scale via control volume finite element (finite volume) and regular finite element methods to evaluate the stress variation, pore pressure evolution, brine migration, solute transport and heat transfer in the subsurface formations in response to ice sheet loading of multiple glacial cycles. +

Q

We present a geometric model able to track the geomorphic boundaries that delimit the fluvial plain of fluvial-deltas: the shoreline and the alluvial-bedrock transition. By assuming a fluvial profile with a quadratic form, which satisfies the overall mass balance and the boundary conditions dictated by diffusive transport, we are able to provide a solution that accounts for general base-level changes. +

R

When wind blows over snow, it self-organizes. This forms surface features, such as ripples and dunes, that alter the reflectivity and thermal conductivity of the snow.
Studying these features in the field is cold and challenging (we've tried), so we created rescal-snow to enable snow scientists to study snow features in controlled numerical experiments. We hope that this model will be useful to researchers in snow science, geomorphology, and polar climate.
Rescal-snow is able to simulate:
- Snow/sand grain erosion and deposition by wind
- Snowfall
- Time-dependent cohesion (snow sintering)
- Avalanches of loose grains
Rescal-snow is also designed for robust, reproducible science, and contains tools for high-performance computing, data management, and data analysis, including:
- Workflow tools for generating and running many simulations in parallel
- A python-based workflow that manages data and analysis at runtime
These processes, along with model input, output, performance and constraints, are discussed in detail in the project docs and readme. +

W

Whole atmosphere module of sulfate aerosols with emphasis on stratospheric aerosols and dust. +

R

Why ROMSBuilder?
ROMS extensively uses the C preprocessor (cpp) during compilation to replace code statements, insert files into the code, and select relevant parts of the code depending on its directives. There are numerous cpp options that can be activated in header files for your specific application. The preprocessor reads the source file (*.F) and builds a target file (*.f90) according to activated cpp options.
CPP options can be set through the CMT config tab dialogs. ROMSBuilder generates the header file for compiling the new ROMS component from the tab dialog inputs. +

X

Xbeach is a two-dimensional model for wave propagation, long waves and mean flow, sediment transport and morphological changes of the nearshore area, beaches, dunes and backbarrier during storms. It is a public-domain model that has been developed with funding and support by the US Army Corps of Engineers, by a consortium of UNESCO-IHE, Deltares, Delft University of Technology and the University of Miami. +

E

eSCAPE is a parallel landscape evolution model, built to simulate Earth surface dynamics at global scale and over geological times. The model is primarily designed to address problems related to geomorphology, hydrology, and stratigraphy, but it can also be used in related fields.
eSCAPE accounts for both hillslope processes (soil creep using linear diffusion) and fluvial incision (stream power law). It can be forced using spatially and temporally varying tectonics (vertical displacements) and climatic conditions (precipitation changes and/or sea-level fluctuations). +

G

gospl is able to simulate global-scale forward models of landscape evolution, dual-lithology (coarse and fine) sediment routing and stratigraphic history forced with deforming plate tectonics, paleotopographies and paleoclimate reconstructions. It relates the complexity of the triggers and responses of sedimentary processes from the complete sediment routing perspective accounting for different scenarii of plate motion, tectonic uplift/subsidence, climate, geodynamic and sedimentary conditions. +

N

nwis package provides a set of functions that allows downloading of the National Water Information System (NWIS) for data analysis and visualization. nwis package includes a Basic Model Interface (BMI), which converts the NWIS dataset into a reusable, plug-and-play data component for Community Surface Dynamics Modeling System (CSDMS) modeling framework. +

nwm package provides a set of functions that allows downloading of the National Water Model (NWM) time series datasets for a river reach or a model grid. nwm package also includes a Basic Model Interface (BMI), which converts the dataset into a reusable, plug-and-play data component for the CSDMS modeling framework. +

O

olaFlow (formerly known as olaFoam) is a numerical model conceived as a continuation of the work in IHFOAM. Its development has been continuous from ihFoam (Jul 8, 2014 - Feb 11, 2016) and olaFoam (Mar 2, 2016 - Nov 25, 2017).
This free and open source project is committed to bringing the latest advances in the simulation of wave dynamics to the OpenFOAM® and FOAM-extend communities.
olaFlow includes a set of solvers and boundary conditions to generate and absorb water waves actively at the boundaries and to simulate their interaction with porous coastal structures. +

P

placeholder +

pyDeltaRCM is the Python version of DeltaRCM (https://csdms.colorado.edu/wiki/Model:DeltaRCM) by Man Liang (also available from the CSDMS model repository). This version is a WMT component but can also be run as a stand-alone model (see README.md).
DeltaRCM 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.
Best usage of DeltaRCM is the investigation of autogenic processes in response to external forcings. +

E

pymt_era5 is a package that converts ERA5 datasets (https://confluence.ecmwf.int/display/CKB/ERA5) into a reusable, plug-and-play data component for PyMT modeling framework developed by Community Surface Dynamics Modeling System (CSDMS). This allows ERA5 datasets (currently support 3 dimensional data) to be easily coupled with other datasets or models that expose a Basic Model Interface. +

R

pymt_roms is a package that converts the ROMS model (https://www.myroms.org/) datasets into a reusable, plug-and-play data component for PyMT modeling framework developed by Community Surface Dynamics Modeling System (CSDMS). This allows ROMS model datasets to be easily coupled with other datasets or models that expose a Basic Model Interface. +

S

soilgrids package provides a set of functions that allow downloading of the global gridded soil information from SoilGrids https://www.isric.org/explore/soilgrids, a system for global digital soil mapping to map the spatial distribution of soil properties across the globe. soilgrids package includes a Basic Model Interface (BMI), which converts the SoilGrids dataset into a reusable, plug-and-play data component for Community Surface Dynamics Modeling System (CSDMS) modeling framework. +

stream_power_smooth_threshold.py: Defines the StreamPowerSmoothThresholdEroder, which is derived from FastscapeEroder. StreamPowerSmoothThresholdEroder uses a mathematically smooth threshold formulation, rather than one with a singularity. +

D

wave-current interaction, (non) hydrostatic flow (2D/3D), salinity, temperature, (non) cohesive sediment transport, morphology, bed stratigraphy, water quality, ecology, structures & control, particle tracking, curvilinear multi-domain mesh in cartesian or spheric coord., online visualization, GUI. +

G

“GEOMBEST-Plus” (Geomorphic Model of Barrier, Estuarine, and Shoreface Translations) is a new 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-Plus differs from other large-scale behaviour models (e.g. Bruun, 1962; Dean and Maumeyer, 1983; Cowell et al., 1995; Niedoroda et al., 1995, Stive & de Vriend, 1995 and Storms et al., 2002) by relaxing the assumption that the initial substrate (i.e stratigraphy) is comprised of an unlimited supply of unconsolidated material (typically sand). The substrate is instead defined by distinct stratigraphic units characterized by their erodibility and sediment composition. Additionally, GEOMBEST-Plus differs from its predecessor (GEOMBEST) by adding in a dynamic stratigraphic unit for a backbarrier marsh. Accordingly, the effects of geological framework on morphological evolution and shoreline translation can be simulated. +