Property:Extended model description
From CSDMS
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C
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. +
