Property:Extended model description
From CSDMS
This is a property of type Text.
H
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' ) ) +
N
The Numerical model of coastal Erosion by Waves and Transgressive Scarps (NEWTS) model is a framework to simulate the erosion of a closed-basin coastline through time by fetch-dependent erosion or uniform erosion. +
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 Urban Inundation-Drainage Simulator (UIDS) is a new coupled model for simulating urban flooding dynamics, developed as an open-source, MATLAB-based platform. It integrates a rainfall-runoff model with a two-dimensional overland flow model (OFM) and a one-dimensional sewer flow model (SFM). +
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. +
