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. +
F
This class uses the Braun-Willett Fastscape approach to calculate the amount of erosion at each node in a grid, following a stream power framework. This should allow it to be stable against larger timesteps than an explicit stream power scheme. +
A
This code creates the channel centerline (i.e., the line equidistant between two banks) for a single thread-channel, using a second-order autoregressive model. The code implements a model for random centerlines proposed by Ferguson, R. I. (1976) Disturbed periodic model for river meanders, Earth Surface Processes 1(4), 337-347, doi:10.1002/esp.3290010403. This implementation also includes (1) controls for the node spacing and extent of channels, (2) removal of self-intersecting (cutoff) loops from modeled centerlines, and (3) a wrapper script to sweep model parameter space and generate alternate realizations using different random disturbance series. +
V
This code is based on Cellular Automata Tree Grass Shrub Simulator (CATGraSS). It simulates spatial competition of multiple plant functional types through establishment and mortality. In the current code, tree, grass and shrubs are used. +
H
This component calculates Hack’s law parameters for drainage basins.
Hacks law is given as
L = C * A**h
Where L is the distance to the drainage divide along the channel, A is the drainage area, and C are parameters.
The HackCalculator uses a ChannelProfiler to determine the nodes on which to calculate the parameter fit. +
C
This component calculates chi indices, sensu Perron & Royden, 2013, for a Landlab landscape. +
S
This component calculates steepness indices, sensu Wobus et al. 2006, for a Landlab landscape. Follows broadly the approach used in GeomorphTools, geomorphtools.org. +
F
This component generates random numbers using the Weibull distribution
(Weibull, 1951). No particular units must be used, but it was written with
the fire recurrence units in time (yrs).
Using the Weibull Distribution assumes two things: All elements within the study area have the same fire regime. Each element must have (on average) a constant fire regime during the time span of the study.<br>
As of Sept. 2013, fires are considered instantaneous events independent of
other fire events in the time series. +
D
This component identifies depressions in a topographic surface, finds an outlet for each depression. If directed to do so (default True), and the component is able to find existing routing fields output from the 'route_flow_dn' component, it will then modify the drainage directions and accumulations already stored in the grid to route flow across these depressions. +
This component implements a depth and slope dependent linear diffusion rule in the style of Johnstone and Hilley (2014). Soil moves with a prescribed exponential vertical velocity profile. Soil flux is dictated by a diffusivity, K, and increases linearly with topographic slope. +
E
This component implements exponential weathering of bedrock on hillslopes. Uses exponential soil production function in the style of Ahnert (1976).
Consider that w_0 is the maximum soil production rate and that d* is the characteristic soil production depth. The soil production rate w is given as a function of the soil depth d,
w = w_0^(-d/d*)
The ExponentialWeatherer only calculates soil production at core nodes. +
L
This component is closely related to the FlowAccumulator, in that this is accomplished by first finding flow directions by a user-specified method and then calculating the drainage area and discharge. However, this component additionally requires the passing of a function that describes how discharge is lost or gained downstream, f(Qw, nodeID, linkID, grid). See examples at https://github.com/landlab/landlab/blob/master/landlab/components/flow_accum/lossy_flow_accumulator.py to see how this works in practice. +
F
This components finds the steepest single-path steepest descent flow directions. It is equivalent to D4 method in the special case of a raster grid in that it does not consider diagonal links between nodes. For that capability, use FlowDirectorD8. +
This is a 1DV wave-phase resolving numerical model for fluid mud transport based on mixture theory with boundary layer approximation. The model incorporates turbulence-sediment interaction, gravity-driven flow, mud rheology, bed erodibility and the dynamics of floc break-up and aggregation. +
W
This is a Java Applet that allows the user to change different parameters (such as rainfall, erodibility, tectonic uplift) and watch how the landform evolve over time under different scenarios. It is based on a Cellular Automata algorithm. Two versions are available: linear and non-linear. Details can be found in:
Luo, W., Peronja, E., Duffin, K., Stravers, A. J., 2006, Incorporating Nonlinear Rules in a Web-based Interactive Landform Simulation Model (WILSIM), Computers and Geosciences, v. 32, n. 9, p. 1512-1518 (doi: 10.1016/j.cageo.2005.12.012).
Luo, W., K.L. Duffin, E. Peronja, J.A. Stravers, and G.M. Henry, 2004, A Web-based Interactive Landform Simulation Model (WILSIM), Computers and Geosciences. v. 30, n. 3, p. 215-220. +
G
This is a Landlab wrapper for A Wickert's gFlex flexure model (Wickert et al., submitted to Geoscientific Model Development). The most up-to-date version of his code can be found at github.com/awickert/gFlex.
This Landlab wrapper will use a snapshot of that code, which YOU need to install on your own machine. A stable snapshot of gFlex is hosted on PyPI, which is the recommended version to install.
If you have pip (the Python package install tool), simply run 'pip install gFlex' from a command prompt.
Alternatively, you can download and unpack the code (from github, or with PyPI, pypi.python.org/pypi/gFlex/), then run 'python setup.py install'. +
C
This is a special case of the Regional Ocean Modeling System(ROMS). The National Ocean Service presently has an Operational Forecast System (CBOFS) for the Chesapeake Bay which generates only water levels and depth‐integrated currents. As a next generation system, a fully three‐dimensional, baroclinic Forecast System (CBOFS2) was developed, calibrated and validated; this system will produce water levels, currents, temperature and salinity. First, a two‐month tides only simulation was conducted to validate the water levels and currents and thereafter, a synoptic hindcast simulation from June 01, 2003–September 01, 2005 was conducted to validate water levels, currents, temperature and salinity. Upon comparison with observations, CBOFS2 for the most part met the target NOS water level error criteria and for current error, the criteria were met exceptionally well; the temperature and salinity errors were frequently less than 1 C and 3 PSU respectively. Hence, the predictive accuracy of CBOFS2 warranted it being accepted as a suitable three‐dimensional upgrade to CBOFS.
Please see https://csdms.colorado.edu/wiki/Model:ROMS for details. +
N
This is a time-stepping point model which uses linear finite elements to determine the vertical structure of the horizontal components of velocity and density under specified surface forcing. Both a quadratic closure scheme and the level 2.5 closure scheme of Mellor and Yamada are used in this code. +
G
This is a tool that I created to help find knickpoints based on the curvature of a landscape. It provides information about a stream including, knickpoint locations, Elevation/distance that can be used to create longitudinal profiles, XYvalues of all the cells in a stream path, etc. The tool uses built-in tools for ArcGIS 10.x (so you must run this on a machine with ArcGIS 10.x installed), but it is written in python. I used it with a 1m LiDAR DEM, so I'm not totally sure how well it will pick out knickpoints on coarser gridded DEMs. +
T
This model a 1-D numerical model of permafrost and subsidence processes.
It aims to investigate the subsurface thermal impact of thaw lakes of various depths, and to evaluate how this impact might change in a warming climate. +
M
This model accounts for the bed evolution i.e. aggradation/degradation and grain size distribution of surface material in gravel bed rivers under anthropogenic changes such as dam closure and sediment augmentation. This model is developed for an alpine gravel bed river located in SE France (Buech river). +
G
This model calculates the long profile of a river with a gravel-sand transition. The model uses two grain sizes: size Dg for gravel and size Ds for sand. The river is assumed to be in flood for the fraction of time Ifg for the gravel-bed reach and fraction Ifs for the sand-bed reach. All sediment transport is assumed to take place when the river is in flood.
Gravel transport is computed using the Parker (1979) approximation of the Einstein (1950) bedload transport relation. Sand transport is computed using the total bed material transport relation of Engelund and Hansen (1967).
In this simple model the gravel is not allowed to abrade. Both the gravel-bed and sand-bed reaches carry the same flood discharge Qbf.
Gravel is transported as bed material in, and deposits only in the gravel-bed reach. A small residual of gravel load is incorporated into the sand at the gravel-sand transition. Sand is transported as washload in the gravel-bed reach, and as bed material load in the sand-bed reach.
The model allows for depositional widths Bdgrav and Bdsand that are wider than the corresponding bankfull channel widths Bgrav and Bsand of the gravel-bed and sand-bed channels. As the channel aggrades, it is assumed to migrate and avulse to deposit sediment across the entire depositional width. For each unit of gravel deposited in the gravel-bed reach, it is assumed that Lamsg units of sand are deposited. For each unit of sand deposited on the sand-bed reach, it is assumed that Lamms units of mud are deposited.
The gravel-bed reach has sinuosity Omegag and the sand-bed reach has sinuosity Omegas.
Bed resistance is computed through the use of two specified constant Chezy resistance coefficients; Czg for the gravel-bed reach and Czs for the sand-bed reach. +
H
This model can be used for both transport after sediment failure and for hyperpycnal transport. +
This model evolves a hogback through time. A resistant layer of
rock, which weathers slowly, overlies a softer layer of rock that weathers
quickly. Resistant rock produces "blocks" which land on the adjoining
hillslope. Boundaries incise at a specified rate. User can set hogback
layer thickness, block size, and dip, as well as relative weathering and
incision rates. Trackable metrics included are time and space-averaged
slope, block height, weathering rate, and erosion rate. Parameters that users need to specify are surrounded by many
comment signs. +
F
This model implement the calculation of the 'Frost Number', a dimensionless ratio based on freezing and thawing degree days in the year. Specifically, the 'Air Frost Number' intents to predict the existence of permafrost at a given location based on a cosine-function approximating the annual temperature distribution. +
W
This model is a GUI implementation of a simple cellular automata dune model. The model was originally proposed by Werner (1995, Geology 23) and has seen several extensions. It can simulate basic barchan, transverse, star, and linear dunes. The model is designed to be easy to operate for researchers or students without programming skills. Also included is a tool to operate the model from ArcGIS. +
M
This model is a nonuniform, quasi-unsteady, movable bed, single channel flow model for heterogeneous size-density mixtures +
G
This model is designed to simulate longitudinal profiles with headward advancing headcuts. This model simulates gully erosion on the centennial-scale given information such as average rainfall and infiltration rates. The modeler also specifies a headcut erosion rate and or a rule for headcut retreat (either discharge-dependent or height-dependent retreat). +
R
This model simulates the interaction between suspended sediment, chlorophyll-a, and mussel population density. Discharge is the driver; it modulates suspended sediment and its interactions in the system. The model is suitable for simulating mussel densities at-a-site. It was originally developed to test the hypothesis that increased sediment loads in Minnesota Rivers are a plausible cause of observed mussel population declines. The model and results are described in detail in the following paper: https://doi.org/10.1086/684223 +
L
This model uses a non-dimensional equation for luminescence in a mixing soil that was derived from the Fokker-Plank Equation. +
K
This model uses the Green-Ampt equation to represent infiltration and the kinematic wave equation to represent runoff over a landscape. The effects of rainfall interception can also be included. +
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This module code is inactive. +
1
This module implements a particle-based model of hillslope evolution, which has an associated continuum description (introduced here: https://arxiv.org/abs/1801.02810). The model takes as input a few simple parameters which determine the equilibrium hillslope shape and dynamics, and can be used to produce equilibrium profiles and study the response of the hillslope to perturbations. The model benefits from straightforward implementation, as well as the flexibility to incorporate sophisticated perturbations and to be accessorized by local or nonlocal fluxes. +
S
This module implements sediment flux dependent channel incision following::
E = f(Qs, Qc) * ((a stream power-like term) - (an optional threshold)),
where E is the bed erosion rate, Qs is the volumetric sediment flux into a node, and Qc is the volumetric sediment transport capacity at that node.
This component is under active research and development; proceed with its use at your own risk. +
P
This module uses Taylor Perron’s implicit (2011) method to solve the nonlinear hillslope diffusion equation across a rectangular, regular grid for a single timestep. Note it works with the mass flux implicitly, and thus does not actually calculate it. Grid must be at least 5x5.
Boundary condition handling assumes each edge uses the same BC for each of its nodes. This component cannot yet handle looped boundary conditions, but all others should be fine.
This component has KNOWN STABILITY ISSUES which will be resolved in a future release; use at your own risk. +
E
This numerical 1D research code Elv applied to gravel-sand transitions relates to Blom et al., 2017 "Advance, retreat, and halt of abrupt gravel-sand transitions in alluvial rivers", http://dx.doi.org/10.1002/2017GL074231. +
Z
This object manages ‘zones’ that are used to evaluate the spatial aspect of taxa. A zone represents a portion of a model grid. It is made up of spatially continuous grid nodes. +
T
This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. It uses the "diffusive wave" method to compute flow velocities for all of the channels in a D8-based river network. This method includes a pressure gradient term that is induced by a water-depth gradient in the downstream direction. This means that instead of using bed slope in Manning's equation or the law of the wall, the water-surface slope is used. +
This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. The kinematic wave method (Lighthill and Whitham, 1955) is the simplest method for modeling flow in open channels. This method combines mass conservation with the simplest possible treatment of momentum conservation, namely that all terms in the general momentum equation (pressure gradient, local acceleration and convective acceleration) are neglible except the friction and gravity terms. A flow in which gravitational acceleration is exactly balanced by friction is referred to as steady, uniform flow. For these flows the water surface slope, energy slope and bed slope are all equal. +
This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. TopoFlow supports three different types of flow diversions: sources, sinks and canals. Sources are locations such as natural springs where water enters the watershed at a point by some process other than those that are otherwise modeled. Similarly, sinks are locations where water leaves the watershed at a point. Canals are generally man-made reaches such as tunnels or irrigation ditches that transport water from one point to another, typically without following the natural gradient of the terrain that is indicated by the DEM. The upstream end is essentially a sink and the downstream end a source. +
This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. The dynamic wave method is the most complete and complex method for modeling flow in open channels. This method retains all of the terms in the full, 1D momentum equation, including the gravity, friction and pressure gradient terms (as used by the diffusive wave method) as well as local and convective acceleration (or momentum flux) terms. This full equation is known as the St. Venant equation. In the current version of TopoFlow it is assumed that the flow directions are static and given by a D8 flow grid. In this case, integral vs. differential forms of the conservation equations for mass and momentum can be used. +
This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. +
This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. +
This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. +
This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. +
This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. +
This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. +
This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. +
This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. +
This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. +
This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model. +
B
This program calculates backwater curves over a sand-bed stream with a specified spatially constant bed slope S. The calculation uses the hydraulic resistance formulation of Wright and Parker (2004) (but without the flow stratification correction). +
D
This program calculates the 1D bed evolution of a sand-bed river after installation of a dredge slot. The calculation begins with the assumption of a prevailing mobile-bed normal flow equilibrium before installation of the dredge slot. The flow depth H, volume bedload transport rate per unit width qb and volume suspended transport rate per unit width qs at normal flow are computed based on input values of discharge Qww, channel width B, bed material sizes D50 and D90, sediment submerged specific gravity Rr and bed slope S.
The sediment is assumed to be sufficiently uniform so that D50 and D90 are unchanging in space and time. The input parameter Inter specifies the fraction of any year for which flood flow prevails. At other times of the year the river is assumed to be morphologically dormant.
The reach is assumed to have length L. The dredge slot is excavated at time t = 0, and then allowed to fill in time with no subsequent excavation. The depth of initial excavation below the bottom of the bed prevailing at normal equilibrium is an input variable with the name Hslot. The dredge slot extends from an upstream point equal to ru*L to a downstream point rd*Hslot, where ru and rd are user-input values.
The porosity lamp of the sediment deposit is a user-input parameter.
The bedload transport relation used in the calculation is that of Ashida and Michiue (1972). The formulation for entrainment of sediment into suspension is that of Wright and Parker (2004). The formulation for flow resistance is that of Wright and Parker (2004). The flow stratification correction of Wright-Parker is not implemented here for simplicity. A quasi-equilibrium formulation is used to computed the transport rate of suspended sediment from the entrainment rate.
A backwater calculation is used to compute the flow. The water surface elevation at the downstream end of the reach is held constant at the value associated with normal flow equilibrium.
Iteration is required to compute: a) the flow depth prevailing at normal flow; b) the friction slope and depth prevailing at normal flow, b) the friction slope and depth associated with skin friction associated with skin friction from any given value of depth, and b) the minimum Shields number below which form drag is taken to vanish.
A
This program computes 1D bed variation in rivers due to differential sediment transport. The sediment is assumed to be uniform with size D. All sediment transport is assumed to occur in a specified fraction of time during which the river is in flood, specified by an intermittency. A Manning-Strickler relation is used for bed resistance. A generic Meyer-Peter Muller relation is used for sediment transport. The flow is computed using a backwater formulation for gradually varied flow. +
This program computes 1D bed variation in rivers due to differential sediment transport in which it is possible to allow the bed to undergo a sudden vertical fault of a specified amount, at a specified place and time. Faulting is realized by moving all notes downstream of the specified point downward by the amount of the faulting.
The sediment is assumed to be uniform with size D. All sediment transport is assumed to occur in a specified fraction of time during which the river is in flood, specified by an intermittency. A Manning-Strickler formulation is used for bed resistance. A generic relation of the general form of that due to Meyer-Peter and Muller is used for sediment transport. The flow is computed using the normal flow approximation. +
B
This program computes fluvial aggradation/degradation with a bedrock-alluvial transition. The bedrock-alluvial transition is located at a point sba(t) which is free to change in time. A bedrock basement channel with slope Sb is exposed from x = 0 to sba(t); it is covered with alluvium from x = sba(t) to x = sd, where sd is fixed. Initially sba = 0. The bedrock basement channel is assumed to undergo no incision on the time scales at which the alluvial reach responds to change. In computing bed level change on the alluvial reach, the normal (steady, uniform) flow approximation is used. Base level is maintained at x = sd, where bed elevation h = 0. The Engelund-Hansen relation is used to compute sediment transport rate, so the analysis is appropriate for sand-bed streams. Resistance is specified in terms of a constant Chezy coefficient Cz. +
A
This program computes gravel bedload and size distribution from specified values for the bed surface size distribution, the sediment specific gravity, and the effective bed shear velocity (based on skin friction only). +
This program computes the time evolution of the long profile of a river of constant width carrying a mixture of gravel sizes, the downstream end of which has a prescribed elevation. In particular, the program computes the time evolution of the spatial profiles of bed elevation, total gravel bedload transport rate and grain size distribution of the surface (active) layer of the bed. The river has constant width. The upstream point, at which sediment is fed, is fixed in the horizontal to be at x = 0. The vertical elevation of the upstream point may change freely as the bed aggrades or degrades. The reach has constant length L, so that the downstream point is fixed in the horizontal at x = L. This downstream point has a user-specified initial elevation hdI.
Gravel bedload transport of mixtures is computed with a user-specified selection of the Parker (1990), or Wilcock-Crowe (2003) surface-based formulations for gravel transport. Sand and finer material must first be excluded from the grain size distributions, which then must be renormalized for gravel content only, in the case of the Parker (1990) relation. In the case of the Wilcock-Crowe (2003) relation, the sand is retained in the computation. +
This program computes the time evolution of the long profile of a river of constant width carrying a mixture of gravel sizes, the downstream end of which has a prescribed elevation. +
S
This program implements the calculation for steady-state aggradation of a sand-bed river in response to sea level rise at a constant rate, as outlined in Chapter 25 of the e-book. +
R
This program is a companion to the program SteadyStateAg, which computes the steady-state aggradation of a river with a specified base level rise at the downstream end. This program computes the time evolution toward steady-state aggradation.
The calculation assumes a specified, constant Chezy resistance coefficient Cz and floodplain width Bf. The sediment is assumed to be uniform with size D. All sediment transport is assumed to occur in a specified fraction of time during which the river is in flood, specified by an intermittency. If grain size D < 2 mm the Engelund-Hansen (1967) formulation for total bed material transport of sand is used. If grain size D >= 2 mm the Parker (1979) bedload transport formulation for gravel is used. The flow is computed using the normal flow approximation. The reach has downchannel length L, and base level is allowed to rise at a specified rate at the downstream end. +
This program provides two modules for studying the approach to mobile-bed normal equilibrium in recirculating and sediment-feed flumes containing uniform sediment.
The module "Recirc" implements a calculation for the case of a flume that recirculates water and sediment. The module "Feed" implements a calculation for the case of flume which receives water and sediment feed. +
T
This pseudo-2D (cross-section, 1 independent variable x) numerical model permits calculating 1D lithospheric flexure with different rheologies, in combination with faulting, loading, and erosion/deposition. The programs are developed in C for Linux platforms, graphic output is produced using GMT scripts, and standard PCs match the CPU and memory requirements. The software is available for free under a GPL license. +
W
This subroutine computes the deep water significant wave height and period at each point under a hurricane +
S
This tool can be used to map out areas of hillslopes where the emergence of bedrock drives an increase in surface roughness. The tool requires an input DEM in float format and will output the rasters, also in float format, for three eigenvectors that together describe the distribution of normal vectors within a user-defined neighbourhood for each pixel. +
C
This tool is used for examining bedrock channels. The tool is based on the assumption that the stream power incision model (SPIM) adequately describes channel incision. Channels profiles are converted to chi-elevation space, where chi is a transformed longitudinal coordinate that takes drainage area into account. The tool uses a variety of statistical tests to extract the most likely series of segments with distinct steepness in chi-elevation space. It also performs statistical tests to determine the best fit m/n ratio, where m is an area (A) exponent and n is a slope (S) exponent in the SPIM with E = K A^m S^n, where E is an erosion rate and K is an 'erodibility'. +
T
This tool is used to creates a "profile-smoothed" DEM from an input DEM. +
H
This tool produces a flow path for each hilltop pixel on a landscape, generating hillslope length and relief data at a hillslope scale. These data can be used to discriminate between linear and nonlinear sediment flux laws at a landscape scale.
The model requires an input DEM in float format and produces a series raster and plain text output files which can be visualized and analysed using code provided at: https://github.com/sgrieve/LH_Paper_Plotting
For detailed information about how to use this tool please refer to the documentation (http://www.geos.ed.ac.uk/~smudd/LSDTT_docs/html/basin_metrics.html). +
D
This tool provides a method for extracting information on the nature and spatial extent of active geomorphic processes across deltas from the geometry of islands and the channels around them using machine learning.
The method consists of a two-step ensemble unsupervised machine learning algorithm that clusters islands into spatially continuous zones based on morphological metrics computed on remotely sensed imagery +
This tool uses chi river profile analysis to predict channel head locations across a landscape and therefore allow the extraction of river networks. It is most suitable for use with high resolution LiDAR (1m) DEMs. The model requires an input DEM in float format and will output the extracted channel heads and networks, also in float format. For detailed information about how to use this tool please refer to the documentation (http://www.geos.ed.ac.uk/~smudd/LSDTT_docs/html/channel_heads.html)
and to the associated paper (http://onlinelibrary.wiley.com/doi/10.1002/2013WR015167/full). +
R
This toolbox was constructed to help analyze changing river planforms (aerial views). Given a binary mask of a river, tools are provided to efficiently compute
- channel centerline
- banklines
- channel width (two methods)
- centerline direction
- centerline curvature
If multiple input mask images contain georeference information, a tool is provided to "stitch" the masks together--before or after analysis. Stitching can be done for both images and vectors of x,y coordinates. The mapping toolbox is required for this functionality.
If multiple masks (realizations) of the river are available, RivMAP includes tools to
- compute centerline migrated areas
- compute erosional and accretional areas
- identify cutoff areas and quantify cutoff length, chute length, and cutoff area
- generate channel belt boundaries and centerline
- measure and map changes (in width, migration areas or rates, centerline elongation, accreted/eroded areas) in space and time +
A
This workbook computes 1D bed variation in rivers due to differential sediment transport. The sediment is assumed to be uniform with size D. All sediment transport is assumed to occur in a specified fraction of time during which the river is in flood, specified by an intermittency. A Manning-Strickler formulation is used for bed resistance. A generic relation of the general form of that due to Meyer-Peter and Muller is used for sediment transport. The flow is computed using the normal flow approximation. +
This workbook computes the time evolution of a river toward steady state as it flows into a subsiding basin. The subsidence rate s is assumed to be constant in time and space. The sediment is assumed to be uniform with size D. A Manning-Strickler formulation is used for bed resistance. A generic relation of the general form of that due to Meyer-Peter and Muller is used for sediment transport. The flow is computed using the normal flow approximation. The river is assumed to have a constant width. +
G
Three dimensional simulations of the Turbidity currents using DNS of incompressible Navier-Stokes and transport equations. +
T
TopoFlow is a powerful, spatially-distributed hydrologic model with a user-friendly point-and-click interface. Its main purpose is to model many different physical processes in a watershed with the goal of accurately predicting how various hydrologic variables will evolve in time in response to climatic forcings. +
TopoToolbox provides a set of Matlab functions that support the analysis of relief and flow pathways in digital elevation models. The major aim of TopoToolbox is to offer stable and efficient analytical GIS utilities in a non-GIS environment in order to support the simultaneous application of GIS-specific and other quantitative methods. With version 2, TopoToolbox adds various tools specifically targeted at tectonic geomorphologists such as Chiplots and slopearea plots. +
Topography is a Python library to fetch and cache NASA Shuttle Radar Topography Mission (SRTM) and JAXA Advanced Land Observing Satellite (ALOS) land elevation data using the OpenTopography REST API.
The Topography library provides access to the following global raster datasets:
* SRTM GL3 (90m)
* SRTM GL1 (30m)
* SRTM GL1 (30m, Ellipsoidal)
* ALOS World 3D (30m)
* ALOS World 3D (30m, Ellipsoidal)
* Global Bathymetry SRTM15+ V2.1
* NASADEM Global DEM
* Copernicus Global DSM 30m
* Copernicus Global DSM 90m
The library includes an API and CLI that accept the dataset type, a latitude-longitude bounding box, and the output file format. Data are downloaded from OpenTopography and cached locally. The cache is checked before downloading new data. Data from a cached file can optionally be loaded into an xarray DataArray using the experimental open_rasterio method. +
A
Traditionally the Area-Slope equation (S=cA^alpha) is extracted from a catchment area vs. slope plot. This model calculate the Area-Slope constant and coefficient (alpha) for each pixel at the catchment as a function of its downslope neighbor. +
O
Transiently evolving river-channel width as a function of streambank properties, sediment in transport, and the hydrograph.
This model is designed to compute the rates of river-channel widening and narrowing based on changing hydrological regimes. It is currently designed for rivers with cohesive banks, with a critical shear stress for particle detachment and an erosion-rate coefficient.
OTTAR contains:
* The RiverWidth class, which contains methods to evolve the width of an alluvial river.
* The FlowDepthDoubleManning class, which is used to estimate flow depth from discharge, even with an evolving river-channel geometry. +
U
Underworld2 is an open-source, particle-in-cell finite element code tuned for large-scale geodynamics simulations. The numerical algorithms allow the tracking of history information through the high-strain deformation associated with fluid flow (for example, transport of the stress tensor in a viscoelastic, convecting medium, or the advection of fine-scale damage parameters by the large-scale flow). The finite element mesh can be static or dynamic, but it is not contrained to move in lock-step with the evolving geometry of the fluid. This hybrid approach is very well suited to complex fluids which is how the solid Earth behaves on a geological timescale. +
S
Uses the Barnes et al (2014) algorithms to replace pits in a topography with flats, or optionally with very shallow gradient surfaces to allow continued draining.
This component is NOT intended for use iteratively as a model runs; rather, it is to fill in an initial topography. If you want to repeatedly fill pits as a landscape develops, you are after the LakeMapperBarnes component. If you want flow paths on your filled landscape, manually run a FlowDirector and FlowAccumulator for yourself.
The locations and depths etc. of the fills will be tracked, and properties are provided to access this information. +
W
WACCM is NCAR's atmospheric high-altitude model; CARMA is Brian Toon's aerosol microphysical sectional model. I'm studying sulfate aerosols in the UTLS region using this coupled model. +
WASH123D is an integrated multimedia, multi-processes, physics-based computational watershed model of various spatial-temporal scales. The integrated multimedia includes:
# dentric streams/rivers/canal/open channel,
# overland regime (land surface),
# subsurface media (vadose and saturated zones), and
# ponds, lakes/reservoirs (small/shallow).
It also includes control structures such as weirs, gates, culverts, pumps, levees, and storage ponds and managements such as operational rules for pumps and control structures.
The WASH123D code consisted of eight modules to deal with multiple media:
# 1-D River/Stream Networks,
# 2-D Overland Regime,
# 3-D Subsurface Media (both Vadose and Saturated Zones);
# Coupled 1-D River/Stream Network and 2-D Overland Regime,
# Coupled 2-D Overland Regime and 3-D Subsurface,
# Coupled 3-D Subsurface and 1-D River Systems;
# Coupled 3-D Subsurface Media, 2-D Overland, and 1-D River Network; and
# Coupled 0-D Shallow Water Bodies and 1-D Canal Network.
For any of the above eight modules, flow only, transport only, or coupled flow and transport simulations can be carried out using WASH123D. +
C
We have developed a hybrid numerical model at a continental scale via control volume finite element (finite volume) and regular finite element methods to evaluate the stress variation, pore pressure evolution, brine migration, solute transport and heat transfer in the subsurface formations in response to ice sheet loading of multiple glacial cycles. +
Q
We present a geometric model able to track the geomorphic boundaries that delimit the fluvial plain of fluvial-deltas: the shoreline and the alluvial-bedrock transition. By assuming a fluvial profile with a quadratic form, which satisfies the overall mass balance and the boundary conditions dictated by diffusive transport, we are able to provide a solution that accounts for general base-level changes. +
R
When wind blows over snow, it self-organizes. This forms surface features, such as ripples and dunes, that alter the reflectivity and thermal conductivity of the snow.
Studying these features in the field is cold and challenging (we've tried), so we created rescal-snow to enable snow scientists to study snow features in controlled numerical experiments. We hope that this model will be useful to researchers in snow science, geomorphology, and polar climate.
Rescal-snow is able to simulate:
- Snow/sand grain erosion and deposition by wind
- Snowfall
- Time-dependent cohesion (snow sintering)
- Avalanches of loose grains
Rescal-snow is also designed for robust, reproducible science, and contains tools for high-performance computing, data management, and data analysis, including:
- Workflow tools for generating and running many simulations in parallel
- A python-based workflow that manages data and analysis at runtime
These processes, along with model input, output, performance and constraints, are discussed in detail in the project docs and readme. +
W
Whole atmosphere module of sulfate aerosols with emphasis on stratospheric aerosols and dust. +
R
Why ROMSBuilder?
ROMS extensively uses the C preprocessor (cpp) during compilation to replace code statements, insert files into the code, and select relevant parts of the code depending on its directives. There are numerous cpp options that can be activated in header files for your specific application. The preprocessor reads the source file (*.F) and builds a target file (*.f90) according to activated cpp options.
CPP options can be set through the CMT config tab dialogs. ROMSBuilder generates the header file for compiling the new ROMS component from the tab dialog inputs. +
X
Xbeach is a two-dimensional model for wave propagation, long waves and mean flow, sediment transport and morphological changes of the nearshore area, beaches, dunes and backbarrier during storms. It is a public-domain model that has been developed with funding and support by the US Army Corps of Engineers, by a consortium of UNESCO-IHE, Deltares, Delft University of Technology and the University of Miami. +
D
bmi_dbseabed package (https://github.com/gantian127/bmi_dbseabed) provides a set of functions that allows downloading of the dataset from dbSEABED (https://instaar.colorado.edu/~jenkinsc/dbseabed/), a system for marine substrates datasets across the globe. bmi_dbseabed package also includes a Basic Model Interface (BMI), which converts the dbSEABED datasets into a reusable, plug-and-play data component for the PyMT modeling framework developed by Community Surface Dynamics Modeling System (CSDMS). +
E
eSCAPE is a parallel landscape evolution model, built to simulate Earth surface dynamics at global scale and over geological times. The model is primarily designed to address problems related to geomorphology, hydrology, and stratigraphy, but it can also be used in related fields.
eSCAPE accounts for both hillslope processes (soil creep using linear diffusion) and fluvial incision (stream power law). It can be forced using spatially and temporally varying tectonics (vertical displacements) and climatic conditions (precipitation changes and/or sea-level fluctuations). +
G
gospl is able to simulate global-scale forward models of landscape evolution, dual-lithology (coarse and fine) sediment routing and stratigraphic history forced with deforming plate tectonics, paleotopographies and paleoclimate reconstructions. It relates the complexity of the triggers and responses of sedimentary processes from the complete sediment routing perspective accounting for different scenarii of plate motion, tectonic uplift/subsidence, climate, geodynamic and sedimentary conditions. +
N
nwis package provides a set of functions that allows downloading of the National Water Information System (NWIS) for data analysis and visualization. nwis package includes a Basic Model Interface (BMI), which converts the NWIS dataset into a reusable, plug-and-play data component for Community Surface Dynamics Modeling System (CSDMS) modeling framework. +
nwm package provides a set of functions that allows downloading of the National Water Model (NWM) time series datasets for a river reach or a model grid. nwm package also includes a Basic Model Interface (BMI), which converts the dataset into a reusable, plug-and-play data component for the CSDMS modeling framework. +
O
olaFlow (formerly known as olaFoam) is a numerical model conceived as a continuation of the work in IHFOAM. Its development has been continuous from ihFoam (Jul 8, 2014 - Feb 11, 2016) and olaFoam (Mar 2, 2016 - Nov 25, 2017).
This free and open source project is committed to bringing the latest advances in the simulation of wave dynamics to the OpenFOAM® and FOAM-extend communities.
olaFlow includes a set of solvers and boundary conditions to generate and absorb water waves actively at the boundaries and to simulate their interaction with porous coastal structures. +
P
placeholder +
pyDeltaRCM is the Python version of DeltaRCM (https://csdms.colorado.edu/wiki/Model:DeltaRCM) by Man Liang (also available from the CSDMS model repository). This version is a WMT component but can also be run as a stand-alone model (see README.md).
DeltaRCM is a parcel-based cellular flux routing and sediment transport model for the formation of river deltas, which belongs to the broad category of rule-based exploratory models. It has the ability to resolve emergent channel behaviors including channel bifurcation, avulsion and migration. Sediment transport distinguishes two types of sediment: sand and mud, which have different transport and deposition/erosion rules. Stratigraphy is recorded as the sand fraction in layers.
Best usage of DeltaRCM is the investigation of autogenic processes in response to external forcings. +
E
pymt_era5 is a package that converts ERA5 datasets (https://confluence.ecmwf.int/display/CKB/ERA5) into a reusable, plug-and-play data component for PyMT modeling framework developed by Community Surface Dynamics Modeling System (CSDMS). This allows ERA5 datasets (currently support 3 dimensional data) to be easily coupled with other datasets or models that expose a Basic Model Interface. +
R
pymt_roms is a package that converts the ROMS model (https://www.myroms.org/) datasets into a reusable, plug-and-play data component for PyMT modeling framework developed by Community Surface Dynamics Modeling System (CSDMS). This allows ROMS model datasets to be easily coupled with other datasets or models that expose a Basic Model Interface. +
S
soilgrids package provides a set of functions that allow downloading of the global gridded soil information from SoilGrids https://www.isric.org/explore/soilgrids, a system for global digital soil mapping to map the spatial distribution of soil properties across the globe. soilgrids package includes a Basic Model Interface (BMI), which converts the SoilGrids dataset into a reusable, plug-and-play data component for Community Surface Dynamics Modeling System (CSDMS) modeling framework. +
stream_power_smooth_threshold.py: Defines the StreamPowerSmoothThresholdEroder, which is derived from FastscapeEroder. StreamPowerSmoothThresholdEroder uses a mathematically smooth threshold formulation, rather than one with a singularity. +
D
wave-current interaction, (non) hydrostatic flow (2D/3D), salinity, temperature, (non) cohesive sediment transport, morphology, bed stratigraphy, water quality, ecology, structures & control, particle tracking, curvilinear multi-domain mesh in cartesian or spheric coord., online visualization, GUI. +
G
“GEOMBEST-Plus” (Geomorphic Model of Barrier, Estuarine, and Shoreface Translations) is a new morphological-behaviour model that simulates the evolution of coastal morphology and stratigraphy, resulting from changes in sea level, and sediment volume within the shoreface, barrier and estuary. GEOMBEST-Plus differs from other large-scale behaviour models (e.g. Bruun, 1962; Dean and Maumeyer, 1983; Cowell et al., 1995; Niedoroda et al., 1995, Stive & de Vriend, 1995 and Storms et al., 2002) by relaxing the assumption that the initial substrate (i.e stratigraphy) is comprised of an unlimited supply of unconsolidated material (typically sand). The substrate is instead defined by distinct stratigraphic units characterized by their erodibility and sediment composition. Additionally, GEOMBEST-Plus differs from its predecessor (GEOMBEST) by adding in a dynamic stratigraphic unit for a backbarrier marsh. Accordingly, the effects of geological framework on morphological evolution and shoreline translation can be simulated. +
