Property:Extended model description
From CSDMS
This is a property of type Text.
S
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 Advanced Terrestrial Simulator (formerly sometimes known as the Arctic Terrestrial Simulator) is a code for solving ecosystem-based, integrated, distributed hydrology.
Capabilities are largely based on solving various forms of Richards equation coupled to a surface flow equation, along with the needed sources and sinks for ecosystem and climate models. This can (but need not) include thermal processes (especially ice for frozen soils), evapo-transpiration, albedo-driven surface energy balances, snow, biogeochemistry, plant dynamics, deformation, transport, and much more. In addition, we solve problems of reactive transport in both the subsurface and surface, leveraging external geochemical engines through the Alquimia interface. +
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 SFINCS model (Super-Fast INundation of CoastS) is developed to efficiently simulate compound flooding events at limited computational cost and good accuracy. SFINCS solves the SSWE and thus includes advection in the momentum equation. However, it can also run using the LIE without advection. Processes such as spatially varying friction, infiltration and precipitation are included. Moreover, SFINCS includes wind-driven shear and an absorbing-generating weakly-reflective boundary is considered which are not included in other reduced-physics models. +
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. +
