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Person

Jessica M Driscoll

Hydrologist

Office of the Chief Operating Officer

Email: jdriscoll@usgs.gov
Office Phone: 303-236-4979
ORCID: 0000-0003-3097-9603

Location
Box 25046
Denver Federal Center
Denver , CO 80225-0046
US

Supervisor: Julie E Kiang
The files contained on this site are for use with the National Hydrologic Model (NHM) for the Precipitation Runoff Modeling System (PRMS), developed by the Modeling of Watershed Systems (MoWS) group of the U.S. Geological Survey. PRMS is a daily deterministic watershed-scale model (Markstrom and others, 2015), and can be used at a conterminous United States (CONUS) extent with on the Geospatial Fabric (Viger and Bock, 2014) in the NHM infrastructure (Regan and others, 2018). The NHM-PRMS is the sum of three parts: the source code, parameter values, geospatial fabric (Regan and others, in press). These components are used to generate the simlation output files. Child items of this page include all or parts of these...
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This is accompanying data produced for the study "Implications of Model Selection: Inter-Comparison of Publicly-Available, CONUS-Extent Hydrologic Component Estimates". These datasets were converted from their primary structures (rasters and shapefiles) to EPA Ecoregions Level I. Conversion was performed by averaging timestep layers via mean area weight to produce a single vector of monthly values for each ecoregion, for each of the following hydrologic cycle components: precipitation (P), actual evapotranspiration (AET), runoff (R), snow water equivalent (SWE), rootzone soil moisture in equivalent water depth (RZSME), and rootzone soil moisture in volumetric water content (RZSMV).
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Models that predict the flow of rivers and streams are critically important for planning flood control, hydropower, and reservoir operations, as well as for management of fish and wildlife populations. As temperatures and precipitation regimes change globally, the need to improve and develop these models for a wider spatial coverage and higher spatial fidelity becomes more imperative. Currently, one of the biggest impediments to developing robust streamflow knowledge is incomplete understanding of the range of timescales over which water is stored (e.g., in snowpack, soils, and groundwater) in watersheds, as well as the processes and factors that control those storage timescales. This working group will address...
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This data release supports the study by Sexstone and others (2019) and contains simulation output from a hydrological modeling experiment using a specific calibration of the conterminous United States (CONUS) application of the Precipitation-Runoff Modeling System (PRMS) (Hay, 2019) as implemented in the National Hydrologic Model (NHM) infrastructure (Regan and others, 2018). The by hydrologic response unit (byHRU) calibrated, baseline version of the NHM-PRMS (Hay, 2019) was used to evaluate the sensitivity of simulated runoff to the representation of snow depletion curves (SDCs) within the NHM-PRMS across the CONUS. The model experiment consisted of seven NHM-PRMS model simulations using the calibrated NHM-PRMS...
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This data release contains input data for hydrologic simulations of the Alaska Domain application of the U.S. Geological Survey (USGS) Precipitation Runoff Modelling System (PRMS) as implemented in the National Hydrologic Model (NHM) infrastructure (Regan and others, 2018). The NHM Alaska Domain parameter database consists of 114 parameter files in ASCII format (CSV), two files needed to run the Alaska Domain PRMS (control.fy19deliverable and fy19_deliv.param), two xml files (dimensions.xml and parameters.xml) containing descriptive information about the parameters, and a table that defines each parameter (AK_paramDB_datadictionary.csv). The Entity and Attribute element of this metadata record describe the data...
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