Property:Extended model description
From CSDMS
This is a property of type Text.
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Code for estimating long-term exhumation histories and spatial patterns of short-term erosion from the detrital thermochronometric data. +
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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) +
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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. +
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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. +
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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. +
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Data component processed from the CRU-NCEP Climate Model Intercomparison Project - 5, also called CMIP 5. Data presented include the mean annual temperature for each gridcell, mean July temperature and mean January temperature over the period 1902 -2100. This dataset presents the mean of the CMIP5 models, and the original climate models were run for the representative concentration pathway RCP 8.5. +
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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. +
Demeter is an open source Python package that was built to disaggregate projections of future land allocations generated by an integrated assessment model (IAM). Projected land allocation from IAMs is traditionally transferred to Earth System Models (ESMs) in a variety of gridded formats and spatial resolutions as inputs for simulating biophysical and biogeochemical fluxes. Existing tools for performing this translation generally require a number of manual steps which introduces error and is inefficient. Demeter makes this process seamless and repeatable by providing gridded land use and land cover change (LULCC) products derived directly from an IAM—in this case, the Global Change Assessment Model (GCAM)—in a variety of formats and resolutions commonly used by ESMs. +
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Depth-Discharge and Bedload Calculator, uses:
# Wright-Parker formulation for flow resistance (without stratification correction)
# Ashida-Michiue formulation for bedload transport. +
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Depth-Discharge and Total Load Calculator, uses:
# Wright-Parker formulation for flow resistance,
# Ashida-Michiue formulation for bedload transport,
# Wright-Parker formulation (without stratification) for suspended load. +
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Derived from MOSART-WM (Model for Scale Adaptive River Transport with Water Management), mosasrtwmpy is a large-scale river-routing Python model used to study riverine dynamics of water, energy, and biogeochemistry cycles across local, regional, and global scales. The water management component represents river regulation through reservoir storage and release operations, diversions from reservoir releases, and allocation to sectoral water demands. The model allows an evaluation of the impact of water management over multiple river basins at once (global and continental scales) with consistent representation of human operations over the full domain. +
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Directs flow by the D infinity method (Tarboton, 1997). Each node is assigned two flow directions, toward the two neighboring nodes that are on the steepest subtriangle. Partitioning of flow is done based on the aspect of the subtriangle. +
Directs flow by the multiple flow direction method. Each node is assigned multiple flow directions, toward all of the N neighboring nodes that are lower than it. If none of the neighboring nodes are lower, the location is identified as a pit. Flow proportions can be calculated as proportional to slope or proportional to the square root of slope, which is the solution to a steady kinematic wave. +
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