Property:Extended model description

From CSDMS

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Showing 20 pages using this property.
L
Calculates the logrithmic velocity distribution called from TRCALC  +
Y
Calculates the total sediment transport rate in an open channel assuming a median bed grain size  +
S
Calculation of Density Stratification Effects Associated with Suspended Sediment in Open Channels. This program calculates the effect of sediment self-stratification on the streamwise velocity and suspended sediment concentration profiles in open-channel flow. Two options are given. Either the near-bed reference concentration Cr can be specified by the user, or the user can specify a shear velocity due to skin friction u*s and compute Cr from the Garcia-Parker sediment entrainment relation.  +
Calculation of Sediment Deposition in a Fan-Shaped Basin, undergoing Piston-Style Subsidence  +
D
Calculator for 1D Subaerial Fluvial Fan-Delta with Channel of Constant Width. This model assumes a narrowly channelized 1D fan-delta prograding into standing water. The model uses a single grain size D, a generic total bed material load relation and a constant bed resistance coefficient. The channel is assumed to have a constant width. Water and sediment discharge are specified per unit width. The fan builds outward by forming a prograding delta front with an assigned foreset slope. The code employs a full backwater calculation.  +
Calculator for 1D Subaerial Fluvial Fan-Delta with Channel of Constant Width. This model assumes a narrowly channelized 1D fan-delta prograding into standing water. The model uses a single grain size D, a generic total bed material load relation and a constant bed resistance coefficient. The channel is assumed to have a constant width. Water and sediment discharge are specified per unit width. The fan builds outward by forming a prograding delta front with an assigned foreset slope. The code employs the normal flow approximation rather than a full backwater calculation.  +
C
CarboCAT uses a cellular automata to model horizontal and vertical distributions of carbonate lithofacies  +
ChesROMS is a community ocean modeling system for the Chesapeake Bay region being developed by scientists in NOAA, University of Maryland, CRC (Chesapeake Research Consortium) and MD DNR (Maryland Department of Natural Resources) supported by the NOAA MERHAB program. The model is built based on the Rutgers Regional Ocean Modeling System (ROMS, http://www.myroms.org/) with significant adaptations for the Chesapeake Bay. The model is developed to provide a community modeling system for nowcast and forecast of 3D hydrodynamic circulation, temperature and salinity, sediment transport, biogeochemical and ecosystem states with applications to ecosystem and human health in the bay. Model validation is based on bay wide satellite remote sensing, real-time in situ measurements and historical data provided by Chesapeake Bay Program. http://ches.communitymodeling.org/models/ChesROMS/index.php  +
Cliffs features: Shallow-Water approximation; Use of Cartesian or spherical (lon/lat) coordinates; 1D and 2D configurations; Structured co-located grid with (optionally) varying spacing; Run-up on land; Initial conditions or boundary forcing; Grid nesting with one-way coupling; Parallelized with OpenMP; NetCDF format of input/output data. Cliffs utilizes VTCS-2 finite-difference scheme and dimensional splitting as in (Titov and Synolakis, 1998), and reflection and inundation computations as in (Tolkova, 2014). References: Titov, V.V., and C.E. Synolakis. Numerical modeling of tidal wave runup. J. Waterw. Port Coast. Ocean Eng., 124(4), 157–171 (1998) Tolkova E. Land-Water Boundary Treatment for a Tsunami Model With Dimensional Splitting. Pure and Applied Geophysics, 171(9), 2289-2314 (2014)  +
B
Coastal barrier model that simulates storm overwash and tidal inlets and estimates coastal barrier transgression resulting from sea-level rise.  +
D
Code for estimating long-term exhumation histories and spatial patterns of short-term erosion from the detrital thermochronometric data.  +
M
Code functionality and purpose may be found in the following references: References # Zhang L., Parker, G., Stark, C.P., Inoue, T., Viparelli, V., Fu, X.D., and Izumi, N. 2015, "Macro-roughness model of bedrock–alluvial river morphodynamics", Earth Surface Dynamics, 3, 113–138. # Zhang, L., Stark, C.P., Schumer, R., Kwang, J., Li, T.J., Fu, X.D., Wang, G.Q., and Parker, G. 2017, "The advective-diffusive morphodynamics of mixed bedrock-alluvial rivers subjected to spatiotemporally varying sediment supply" (submitted to JGR)  +
C
Compact a sediment column  +
G
Computes transient (semi-implicit numerical) and steady-state (analytical and numerical) solutions for the long-profile evolution of transport-limited gravel-bed rivers. Such rivers are assumed to have an equilibrium width (following Parker, 1978), experience flow resistance that is proportional to grain size, evolve primarily in response to a single dominant "channel-forming" or "geomorphically-effective" discharge (see Blom et al., 2017, for a recent study and justification of this assumption and how it can be applied), and transport gravel following the Meyer-Peter and Müller (1948) equation. This combination of variables results in a stream-power-like relationship for bed-material sediment discharge, which is then inserted into a valley-resolving Exner equation to compute long-profile evolution.  +
C
CruAKtemp is a python 2.7 package that is a data component which serves to provide onthly temperature data over the 20th century for permafrost modeling. The original dataset at higher resolution can be found here: http://ckan.snap.uaf.edu/dataset/historical-monthly-and-derived-temperature-products-771m-cru-ts The geographical extent of this CRUAKtemp dataset has been reduced to greatly reduce the number of ocean or Canadian pixels. Also, the spatial resolution has been reduced by a factor of 13 in each direction, resulting in an effective pixel resolution of about 10km. The data are monthly average temperatures for each month from January 1901 through December 2009.  +
D
DFMFON stands for Delft3D-Flexible Mesh (DFM), and MesoFON (MFON) is an open-source software written in Python to simulate the Mangrove and Hydromorphology development mechanistically. We achieve that by coupling the multi-paradigm of the individual-based mangrove model MFON and process-based hydromorphodynamic model DFM.  +
DHSVM is a distributed hydrology model that was developed at the University of Washington more than ten years ago. It has been applied both operationally, for streamflow prediction, and in a research capacity, to examine the effects of forest management on peak streamflow, among other things.  +
DR3M is a watershed model for routing storm runoff through a Branched system of pipes and (or) natural channels using rainfall as input. DR3M provides detailed simulation of storm-runoff periods selected by the user. There is daily soil-moisture accounting between storms. A drainage basin is represented as a set of overland-flow, channel, and reservoir segments, which jointly describe the drainage features of the basin. This model is usually used to simulate small urban basins. Interflow and base flow are not simulated. Snow accumulation and snowmelt are not simulated.  +
DROG3D tracks passive drogues with given harmonic velocity field(s) in a 3-D finite element mesh  +
Dakota is a software toolkit, developed at Sandia National Laboratories, that provides an interface between models and a library of analysis methods, including support for sensitivity analysis, uncertainty quantification, optimization, and calibration techniques. Dakotathon is a Python package that wraps and extends Dakota’s file-based user interface. It simplifies the process of configuring and running a Dakota experiment, and it allows a Dakota experiment to be scripted. Any model written in Python that exposes a Basic Model Interface (BMI), as well as any model componentized in the CSDMS modeling framework, automatically works with Dakotathon. Currently, six Dakota analysis methods have been implemented from the much larger Dakota library: * vector parameter study, * centered parameter study, * multidim parameter study, * sampling, * polynomial chaos, and * stochastic collocation.  +