This data release contains output of the initial calibration of the conterminous United States (CONUS) application of the Precipitation-Runoff Modeling System (PRMS) as implemented in the National Hydrologic Model (NHM) infrastructure (Regan et al, 2018). The PRMS version 5.0.0 hydrologic simulation code was used with the accompanying parameter files in the NHM infrastructure to produce the attached output files. Model input climate drivers include climate data derived from the Daymet gridded data set version 2 (Thornton et al., 2014) with values spatially-distributed to the HRUs using the USGS Geo Data Portal (https://cida.usgs.gov/gdp/; Blodgett et al., 2011). The parameter values are maintained in the National Hydrologic Model Parameter Database (NhmParamDb; Driscoll et al., 2017). The parameter file used to produce these model results is attached (NHM-PRMS.zip). CONUS-scale parameter calibration for the USGS National Hydrologic Model (NHM) infrastructure application of the Precipitation-Runoff Modeling System (NHM-PRMS) was conducted using five baseline data sets derived from multiple sources for each of the NHM’s 109,951 hydrologic response units (HRU) on time scales from annual to daily. A multiple-objective, step-wise, automated calibration procedure was used to identify the ‘optimal’ set of parameters for each HRU. This produced spatially distributed parameters for the CONUS using a calibration procedure termed ‘byHRU’ calibration. The NHM-PRMS simulations, with the byHRU calibrated parameters, were conducted with the same configuration for a time period from October 1, 1980 to December 31, 2016. The first three years of the simulations are should be considered ‘model spin up’ and not included in any subsequent analysis. Table 1 (attached) lists the output variables included in this data release. The individual *.csv files follow a naming convention of using an abbreviation for the spatial dimension of the model output (nhru or nsegment) _variable name.csv. The variable names included are defined further in Table 1. The structure of each output file includes a header line which labels the columns by the spatial unit (hru or stream segment) identification number and each row has the date followed by either 109951 or 56460 values, depending the output variable dimension nhru or nsegment, respectively. See table 1-10 in Regan and LaFontaine (2017) for a description of the variables included in this file. To distribute parameter and output values spatially, a join can be completed by using the nhru_ID or nseg_ID from the variable and the hru_ID from the national-extent Geospatial Fabric. This research used resources provided by the Core Science Analytics, Synthesis, & Libraries (CSASL) Advanced Research Computing (ARC) group at the U.S. Geological Survey.
Blodgett, D.L., Booth, N.L., Kunicki, T.C., Walker, J.I., and Viger, R.J., 2011, Description and testing of the Geo Data Portal—A data integration framework and Web processing services for environmental science collaboration: U.S. Geological Survey Open-File Report 2011–1157, 9 p., accessed March 2, 2017, at https://doi.org/10.3133/ofr20111157.
Driscoll, J.M., Markstrom, S.L., Regan, R.S., Hay, L.E., and Viger, R.J., 2017, National Hydrologic Model Parameter Database—2017-05-08 Download: U.S. Geological Survey database, accessed September 24, 2017, at https://doi.org/10.5066/F7NS0SCW.
Regan, R.S., and LaFontaine, J.H., 2017, Documentation of the dynamic parameter, water-use, stream and lake flow routing, and two summary output modules and updates to surface-depression storage simulation and initial conditions specification options with the Precipitation-Runoff Modeling System (PRMS): U.S. Geological Survey Techniques and Methods, book 6, chap. B8, 60 p., accessed October 27, 2017, at https://doi.org/10.3133/tm6B8.
Regan, R.S., Markstrom, S.L., Hay, L.E., Viger, R.J., Norton, P.A., Driscoll, J.M., LaFontaine, J.H., 2018, Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS): U.S. Geological Survey Techniques and Methods, book 6, chap. B9, 38 p., accessed May 16, 2018, at https://doi.org/10.3133/tm6B9.
Thornton, P.E., Thornton, M.M., Mayer, B.W., Wilhelmi, N., Wei, Y.,Devarakonda, R., and Cook, R.B., 2014, Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2: ORNL DAAC, Oak Ridge, Tennessee, USA, accessed February 21, 2017, at http://dx.doi.org/10.3334/ORNLDAAC/1219.
