# 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. +

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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) +

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

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

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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) +

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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. +

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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. +

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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. +

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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. +

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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. +

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