The Geospatial Fabric is a dataset of spatial modeling units for use within the National Hydrologic Model that covers Alaska, and most major river basins that flow in from Canada. This U.S. Geological Survey (USGS) data release consists of the geospatial fabric features and other related datasets created to expand the National Hydrologic Model to Alaska. This U.S. Geological Survey (USGS) child item consists of 17 different spatial layers in GeoTIFF format for Alaska. They are 1) average water capacity (awc.zip), 2) percent sand (sand.zip), 3) percent silt (silt.zip), 4) percent clay (clay.zip), 5) soil texture (TEXT_PRMS.zip), 6) land use/land cover (LULC.zip), 7) snow values (snow.zip), 8) summer rain values (SRain.zip), 9) winter rain values (WRain.zip), 10) leaf presence values (keep.zip), 11) leaf loss values (loss.zip), 12) percent tree canopy (CNPY.zip), 13) percent impervious surface (imperv.zip), 14) snow depletion curve numbers (CV_INT.zip), 15) rooting depth (RootDepth.zip), 16) permeability values (Lithology_exp_Konly_Project.zip), and 17) water bodies (wbg.zip). All data cover the National Hydrologic Model's (NHM) Alaskan domain. The 250-meter (m) raster datasets for soils (in sand.zip, silt.zip, clay.zip, TEXT_PRMS.zip) are derived from the Zonodo data (Hengl, 2018). The 30-meter raster of land use and land cover data are a simplified re-classification version of the North American Land-Change Monitoring System (NALCMS, Latifovic and others, 2012) data following the guidance and crosswalk table (crosswalk.csv) in Viger and Leavesley (2007). This layer was used to derive rasters representing dominant vegetative cover type, snow, summer and winter rain interception values, leaf cover and loss, and rooting depth. The impervious data were compiled from the Global Man-made Impervious Surface (GMIS) Dataset from Landsat, v1 (Brown de Colstoun, 2010). The tree canopy data were compiled from MOD44B MODIS/Terra Vegetation Continuous Fields Yearly L3 Global 250m SIN Grid V006, (Sexton and others, 2013). The snow depletion data was compiled from data by Liston (2009) and further processed using methods provided in a snow depletion table (SDC_table.csv) by Sexstone and others (2020). All file formats are in GeoTIFF (Geograhpic Tagged Imaged Format).

This U.S. Geological Survey (USGS) metadata record consists of 17 different spatial layers in GeoTIFF format for the Hawaii. They are: 1) average water capacity (awc.zip), 2) percent sand (sand.zip), 3) percent silt (silt.zip), 4) percent clay (clay.zip), 5) soil texture (TEXT_PRMS.zip), 6) land use/land cover (LULC.zip), 7) snow values (snow.zip), 8) summer rain values (SRain.zip), 9) winter rain values (WRain.zip), 10) leaf presence values (keep.zip), 11) leaf loss values (loss.zip), 12) percent tree canopy (CNPY.zip), 13) percent impervious surface (imperv.zip), 14) snow depletion curve numbers (CV_INT.zip), 15) rooting depth (RootDepth.zip), 16) permeability values (Lithology_exp_Konly_Project.zip), and 17) water bodies. All data cover the National Hydrologic Model's (NHM) version 1.1 Alaskan domain. The NHM is a modeling infrastructure consisting of three main parts: 1) an underlying geospatial fabric of modeling units (hydrologic response units and stream segments) with an associated parameter database, 2) a model input data archive, and 3) a repository of the physical model simulation code bases (Regan and others, 2014). The NHM has been used for a variety of applications since its initial development.The 250-meter (m) raster data sets for soils are derived from the OpenGeoHub's LandGIS data (Hengl, 2018). The 30-meter raster of land use and land cover data are a simplified re-classification version of the North American Land-Change Monitoring System (NALCMS, Latifovic and others, 2012) data following the guidance and crosswalk table (CrossWalk.xslx) in Viger and Leavesley (2007). This layer was used to derive rasters representing dominant vegetative cover type, snow, summer and winter rain interception values, leaf cover and loss, and rooting depth. The impervious data was compiled from the Global Man-made Impervious Surface (GMIS) Dataset from Landsat, v1 (NASA, 2010). The tree canopy data was compiled from MOD44B MODIS/Terra Vegetation Continuous Fields Yearly L3 Global 250m SIN Grid V006, (Carroll and others, 2017). The snow depletion data was compiled from data by Liston and others (2009) and further processed using methods provided in a snow depletion table (SDC.xslx) by Sexstone and others (2020). All file formats are in GeoTIFF (Geograhpic Tagged Imaged Format).

This metadata record documents a set of 118 comma delimited files and a data dictionary describing the inputs for the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS) which is used to drive the National Hydrologic Model (NHM) for the United States-Canada transboundary domain. The National Hydrologic Model database contains parameters for hydrologic response units (HRUs) and stream segments needed to run the NHM. These parameters are generated using python scripts to process input datasets such as digital elevation models, soil maps, and land cover classifications. Many of the parameters were left at their default model value as they would need to be calibrated as part of the PRMS model development process. Please refer to the Supplemental Information and the Process Description elements of this metadata record for more details on the source datasets and scripts used to generate these parameters.

This U.S. Geological Survey (USGS) data release consists of two hydrographic datasets with spatial modeling units, two sets of spatial data consistent with the National Hydrologic Model (NHM) Geospatial Fabric for National Hydrologic Modeling (abbreviated within this document as GFv1, Viger and Bock, 2014), and a database of 118 parameters used to run the NHM . These datasets are found as subpages to this landing page as 1) the GIS (geographic information system) features of the United States-Canada Transboundary Geospatial Fabric (TGF, added 08/04/2020), 2) the GIS features of the Geospatial Fabric v1.1 (GFv1.1 or v1_1, added 08/04/2020) which is an update to the GF and includes the TGF, 3) Topographic derivative datasets for the United States-Canada transboundary Geospatial Fabric (added 10/28/2020), 4) Data Layers for the National Hydrologic Model, version 1.1, and 5) National Hydrologic Model's United States-Canada Transboundary Geospatial Fabric Parameter Database (added 11/10/2021). See subpages for more details.

This U.S. Geological Survey (USGS) data release record consists of topographic data themes that cover the United States-Canada Transboundary Geospatial Fabric (TGF) domain. The 30-meter (m) raster data sets included under Topographic Derivatives are: 1) digital elevation (dem.tif) , 2) topographic wetness index (TWI, twi100X.tif) ,3) slope (rise over run, slope100X.tif), 4) aspect (asp100X.tif), and flow direction (fdr.tif). In some instances, values were multiplied by 100 and converted from double precision to integer format to reduce file sizes. All file formats are in GeoTIFF (Geographic Tagged Imaged Format).

The Geospatial Fabric for National Hydrologic Modeling (Viger and Bock, 2014; Bock and others, 2020) is a dataset of hydrographic features and spatial data designed for use within the National Hydrologic Model that covers the conterminous United States (CONUS), Hawaii, and most major river basins that flow in from Canada. This U.S. Geological Survey (USGS) data release consists of the geospatial fabric features and other related spatial datasets created to expand the National Hydrologic Model to Alaska. This child item consists of topographic data themes that cover the Geospatial Fabric for National Hydrologic Modeling, Alaska Domain. The 30-meter (m) raster datasets included under Topographic Derivatives are: digital elevation (dem.tif), topographic wetness index (TWI, twiX100.tif), slope (rise over run, slope.tif), aspect (asp.tif), flow accumulation (fac.tif), and flow direction (fdr.tif). All file formats are in GeoTIFF (Geographic Tagged Imaged Format), and are sourced from NHDPlus Version 2.0 raster layers (Environmental Protection Agency, 2019)

This metadata record documents a set of 116 comma delimited files and a data dictionary describing the inputs for the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS) which is used to drive the National Hydrologic Model (NHM) for the Hawaiian domain. The National Hydrologic Model database contains parameters for hydrologic response units (HRUs) and stream segments needed to run the NHM. These parameters are generated using python scripts to process input datasets such as digital elevation models, soil maps, and land cover classifications. Many of the parameters were left at their default model value as they would need to be calibrated as part of the PRMS model development process. Please refer to the Supplemental Information and the Process Description elements of this metadata record for more details on the source datasets and scripts used to generate these parameters.

This data release contains inputs for and outputs from hydrologic simulations for the conterminous United States (CONUS) using the Precipitation Runoff Modeling System (PRMS) version 5.2.1 and the USGS National Hydrologic Model infrastructure (NHM, Regan and others, 2018). These simulations were developed to provide estimates of the water budget for the period 1979 to 2021 for one pre-calibration and three calibration configurations: 1) calibration by hydrologic response unit (byHRU), 2) calibration by select headwaters (byHW), and 3) calibration by select headwaters with streamflow observations (byHWobs). The three versions of model parameters and associated model output included in this data release are described in Hay and others (2023). Specific file types include: 1) input atmospheric forcings of minimum air temperature, maximum air temperature, and daily precipitation accumulation derived from a gridded observation-based dataset developed by Abatzoglou (2013), 2) input parameter files, 3) output files of simulated water budget components for each hydrologic response unit and stream segment, and 4) performance statistics at selected streamgage locations. The first three years of the simulations are considered 'model initialization' and should not be included in any subsequent analysis.