This data release supports the study by Sexstone and others (2020) and contains simulation output from SnowModel (Liston and Elder, 2006), a well-validated process-based snow modeling system. Simulations are for water years 1984 through 2017 (October 1, 1983 through September 30, 2017) across a 11,200 square kilometer model domain in the San Juan Mountains of southwestern Colorado, United States that encompasses the Rio Grande Basin headwaters (HUC8 13010001). This data release also contains supporting field-based snow and meteorological station observations collected within the model domain during water years 2016 and 2017 that were used to evaluate SnowModel simulations. Sexstone and others (2020) provide details and summarize findings from the SnowModel simulations and supporting observations. SnowModel simulation output provided in this data release are stored in NetCDF files that have spatial (100-meter [m] grid resolution) and temporal (yearly) dimensions. Simulated SnowModel annual snow metrics (water years 1984 through 2017) in the attached NetCDF files include: mean winter (1 October to 31 May) air temperature (T; degrees Celsius [°C]), cumulative winter precipitation (P; millimeters [mm]), peak snow water equivalent (SWE; mm), SWE:P (ratio of peak SWE to winter P; m/m), snow-covered days (days with snow on the ground; days), total snowmelt (surface-water input into the soil that occurs when SWE greater than [>] 0; mm), snowmelt rate (rate the snow melts from peak SWE to melt out; millimeter per day [mm/day]), SM50 (water year day following peak SWE when half of snowpack has melted), peak SWE timing (water year day when peak SWE occurs), melt-out timing (water year day when snow melt out occurs), sublimation (total snow sublimation including surface, canopy, and blowing snow components; mm), sublimation:P (total snow sublimation to winter P ratio; m/m), 1 March SWE (mm), 1 April SWE (mm), 1 May SWE (mm), and 1 June SWE (mm). Supporting observations are provided in this data release in comma separated value (csv) files. Supporting meteorological station observations from three meteorological stations (daily mean values for the previous day) include: air temperature (°C), relative humidity (percent [%]), wind speed (meter per second [m/s]), incoming shortwave radiation (watts per meter squared [W m-2]), net radiation (W m-2), and albedo. Supporting field-based snow observations collected at 73 locations at a daily temporal dimension include: SWE (mm), standard deviation of SWE (mm), snow depth (m), and standard deviation of snow depth (m). An inventory and description of each of the files attached to the data release is provided below. Inventory of data release: URGB_SnowModel_study.xml: FGDC-compliant metadata file for the data release files. melt_doy.nc: NetCDF file of annual melt-out timing (water year day when snow melt out occurs) from SnowModel output . melt_rate.nc: NetCDF file of annual snowmelt rate (rate the snow melts from peak SWE to melt out; mm/day) from SnowModel output. peak_swe.nc: NetCDF file of annual peak SWE (mm) from SnowModel output. peak_swe_doy.nc: NetCDF file of annual peak SWE timing (water year day when peak SWE occurs) from SnowModel output. SM50.nc: NetCDF file of annual SM50 (water year day following peak SWE when half of snowpack has melted) from SnowModel output. snow_days.nc: NetCDF file of annual snow-covered days (days with snow on the ground) from SnowModel output. sub_p.nc: NetCDF file of annual sublimation:P (total snow sublimation to winter P ratio; m/m) from SnowModel output. sum_P_may.nc: NetCDF file of annual cumulative winter P (mm) from SnowModel output. sum_snow_RO.nc: NetCDF file of annual total snowmelt (surface-water input into the soil that occurs when SWE > 0; mm) from SnowModel output. sum_sub.nc: NetCDF file of annual sublimation (total snow sublimation including surface, canopy, and blowing snow components; mm) from SnowModel output. swe_p.nc: NetCDF file of annual

This data release contains SnowModel snow evolution simulation output on a 100-meter (m) geospatial grid for a 311 kilometer (km) × 300 km model domain in Colorado, United States, encompassing the Colorado and Gunnison River Basin headwaters in the Upper Colorado River Basin. Weather Research and Forecasting (WRF) Model convection-permitting and orography-resolving (4-km grid spacing) regional climate simulations provided the atmospheric forcing conditions to drive SnowModel in both a current and future climate scenario. A pair of continuous 13-water-year (2001-13) WRF model simulations was utilized: (1) a current climate control (CTL) simulation forced using ERA-Interim reanalysis, and (2) a future climate simulation using the pseudo-global-warming (PGW) method that uses the ERA-Interim reanalysis for the same period as (1) and adds an ensemble mean climate delta from 100 years in the future for the most extreme Representative Concentration Pathway (RCP) 8.5 scenario. The six SnowModel simulated outputs provided separately as child items in this data release include (1) air temperature (tair), (2) precipitation (prec), (3) precipitation amount falling as snow (spre), (4) snow water equivalent (swed), (5) liquid water supplied to the soil-snow interface from snowmelt (smlt), and (6) liquid water supplied to the soil-snow or soil-air interface either from snowmelt or rainfall (roff). The simulations used to produce these outputs were conducted on a 100-m geospatial grid. Land cover information (file vege.asc) for the simulation was provided by the 2010 North American Land Change Monitoring System and elevation information (file topo.asc) was provided by the U.S. Geological Survey National Elevation Dataset.

This data release contains SnowModel snow evolution simulation output from water years 2022 to 2023 (October 1, 2021, through September 30, 2023) on a 100-meter (m) geospatial grid for a 3 kilometer (km) × 2 km model domain near Coal Creek off Coal Bank Pass in the San Juan Mountains in southwest Colorado, USA. The three quantities simulated for this release were snow water equivalent for the standard model configuration (swe_standard), snow water equivalent for an open canopy model configuration (swe_open), and incoming shortwave radiation for the open canopy model configuration (qsin_open). The simulation used to produce these outputs was forced using meteorology from the National Land Data Assimilation System (NLDAS-2). Land cover information for the standard simulation was provided by the North American Land Change Monitoring System and land cover for the open canopy model configuration was set to the grassland land cover type. Elevation information was provided by the U.S. Geological Survey (USGS) National Elevation Dataset. This research was funded by the Department of the Interior South Central Climate Adaptation Science Center.

This data release includes simulation output from SnowModel (Liston and Elder, 2006), a well-validated process-based snow modeling system, and supporting snow, meteorological, and streamflow observations from the water years 2011 through 2015 (October 1, 2010, through September 30, 2015) across a 3,600 square kilometer model domain in the north-central Colorado Rocky Mountains. For each water year, SnowModel simulations were completed for a (1) baseline simulation, (2) bark-beetle disturbance condition simulation, (3) 2016 - 2035 future climate condition simulation (S1), and (4) 2046 - 2065 future climate condition simulation (S2). Sexstone and others (2018) provide details and summarize findings from each of the SnowModel simulations. SnowModel simulation output is stored in NetCDF files that have spatial (100-m grid resolution) and temporal (daily) dimensions. Simulated SnowModel outputs in the attached .zip folders include: snow water equivalent (m), snow depth (m), surface sublimation (m/day), canopy sublimation (m/day), blowing sublimation (m/day), cumulative blowing snow transport (m), precipitation (m/day), air temperature (C), surface temperature (C), relative humidity (%), wind speed (m/s), wind direction (degrees from north). Supporting station observations that were collected and used to evaluate SnowModel simulations are also provided in this data release in comma separated value files. Supporting station observations in the attached .zip folders include: daily mean snow sublimation (mm/day), mean daily snow depth (m), mean hourly air temperature (C), mean hourly relative humidity (%), mean hourly wind speed (m/s), and mean daily streamflow normalized to watershed area (mm). An inventory and description of each of the .zip folders attached to the data release are provided below. The purpose of the model simulations and supporting observations provided in this data release are to improve understanding of the importance of snow sublimation to the water balance of this region (Sexstone and others, 2018). Inventory of data release: Model_Runs_WYxxxx.zip (5 zipped folders): Baseline model simulation output (.nc) and associated FGDC-compliant metadata file (.xml) for water years 2011 through 2015. Each of the 5 zipped folders are labeled with the given water year (WY). Model_Runs_Beetle_WYxxxx.zip (5 zipped folders): Bark-beetle disturbance condition model simulation output (.nc) and associated FGDC-compliant metadata file (.xml) for water years 2011 through 2015. Each of the 5 zipped folders are labeled with the given water year (WY). Model_Runs_Climate_WYxxxx_s1.zip (5 zipped folders): Future climate condition (2016 – 2035) simulation (S1) output (.nc) and associated FGDC-compliant metadata file (.xml) for water years 2011 through 2015. Each of the 5 zipped folders are labeled with the given water year (WY). Model_Runs_Climate_WYxxxx_s2.zip (5 zipped folders): Future climate condition (2046 – 2065) simulation (S2) output (.nc) and associated FGDC-compliant metadata file (.xml) for water years 2011 through 2015. Each of the 5 zipped folders are labeled with the given water year (WY). Supporting_observations_WY2011-WY2015.zip (1 zipped folder) Supporting observations of station observations (.csv) and and associated FGDC-compliant metadata file (.xml) for water years 2011 through 2015. References: Liston, G.E., and Elder, K., 2006, A distributed snow-evolution modeling system (SnowModel): Journal of Hydrometeorology, v. 7, no. 6, p. 1259-1276. Sexstone, G.A., Clow, D.W., Fassnacht, S.R., Liston, G.E., Hiemstra, C.A., Knowles, J.F., and Penn, C.A., 2018, Snow sublimation in mountain environments and its sensitivity to forest disturbance and climate warming, Water Resources Research [URL].

This data release contains output from a numerical snow simulation for a 65 kilometer (km) × 81 km model domain in parts of Montana and Wyoming, United States, encompassing the Gallatin River watershed upstream of the U.S. Geological Survey streamgage near Gallatin Gateway, MT (06043500). Weather Research and Forecasting (WRF) Model convection-permitting and orography-resolving regional climate simulations with 4-km horizontal resolution provided the atmospheric forcing conditions to SnowModel in both a historical and future climate scenario. Two continuous, 13-water-year (2001-2013) WRF model simulations were utilized: (1) a historical climate control (CTL) simulation forced using ERA-Interim reanalysis, and (2) a future climate simulation using the pseudo-global-warming (PGW) method that uses the ERA-Interim reanalysis for the same period as (1) and adds an ensemble mean climate delta from the end of the century (2071-2100) for the most extreme 5th Coupled Model Intercomparison Project (CMIP5) Representative Concentration Pathway (RCP) 8.5 scenario. The ten SnowModel simulated outputs provided in this data release include (1) air temperature (tair), (2) precipitation (prec), (3) solid precipitation (spre), (4) liquid precipitation (rpre), (5) liquid water supplied to the soil-snow interface from snowmelt (smlt), (6) snow sublimination (ssub), (7) liquid water supplied to the soil-snow or soil-air interface either from snowmelt or rainfall (roff), (8) snow depth (snod), (9) snow water equivalent depth (swed), and (10) snow density (sden). The simulations used to produce these outputs were conducted on a 30-m geospatial grid. Land cover information for the simulation was provided by the 2010 North American Land Change Monitoring System and elevation information was provided by the U.S. Geological Survey National Elevation Dataset. The historical (CTL) and future climate (PGW) simulations were conducted using annual precipitation bias correction surfaces (prec_cf), which were computed by comparing SnowModel-simulated CTL snow water equivalent to Natural Resources Conservation Service snow telemetry station (SNOTEL) observations to generate a precipitation correction that was interpolated using SnowModel.

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 model parameters from Hay (2019). For each of the model simulations, the calibrated SDCs (Hay, 2019) were replaced with a single derived SDC derived based on a lognormal probability distribution function and assigned snow water equivalent coefficient of variation (CV) value. The seven CV values ranged from 0.1 to 2.0. Each of the simulations were completed at a daily time-step over a 14-year period (water years 2003 – 2016). Detailed methods and results are provided in Sexstone and others (2019). The SDC parameters used in this model experiment are provided by this data release. Furthermore, the attached NHM-PRMS variable table lists the selected output variables included in this data release. The individual *.csv files follow a naming convention of nhru_variable name_CVX.X.csv. The variable names included are defined further in NHM-PRMS variable table. The “CVX.X” denotes the CV value that was used to derive the SDC for the model simulation. The structure of each output file includes a header line which labels the columns by the HRU identification number with each row providing daily outputs. An inventory of the files provided within this data release can be found below. This research used resources provided by the Core Science Analytics, Synthesis, & Libraries (CSASL) Advanced Research Computing (ARC) group at the U.S. Geological Survey. Inventory of data release: NHM-PRMS_SDC_study.xml (1 .xml file): FGDC-compliant metadata file for the data release files. SDC_params.csv (1 .csv file): Table of the seven snow depletion curve parameterizations used in the modeling study. NHM-PRMS_variable_table.docx (1 .docx file): Table describing the selected NHM-PRMS output variables provided in this data release. nhru_gwres_flow_CVX.X.csv (7 .csv files): NHM-PRMS groundwater discharge output for water years 2002 through 2016. Each of the 7 .csv files are labeled with the coefficient of variation (CV) value for the snow depletion curve that was used in the model simulation. nhru_hru_actet_CVX.X.csv (7 .csv files): NHM-PRMS actual evapotranspiration output for water years 2002 through 2016. Each of the 7 .csv files are labeled with the coefficient of variation (CV) value for the snow depletion curve that was used in the model simulation. nhru_hru_outflow_CVX.X.csv (7 .csv files): NHM-PRMS total flow output for water years 2002 through 2016. Each of the 7 .csv files are labeled with the coefficient of variation (CV) value for the snow depletion curve that was used in the model simulation. nhru_hru_ppt_CVX.X.csv (7 .csv files): NHM-PRMS precipitation output for water years 2002 through 2016. Each of the 7 .csv files are labeled with the coefficient of variation (CV) value for the snow depletion curve that was used in the model simulation. nhru_pkwater_equiv_CVX.X.csv (7 .csv files): NHM-PRMS snow water equivalent output for water years 2002 through 2016. Each of the 7 .csv files are labeled with the coefficient of variation (CV) value for the snow depletion curve that was used in the model simulation. nhru_potet_CVX.X.csv (7 .csv files): NHM-PRMS potential evapotranspiration output for water years 2002 through 2016. Each of the 7 .csv files are labeled with the coefficient of variation (CV) value for the snow depletion curve that was

The U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) was used to assess the effects of changing climate and land disturbance on seasonal streamflow in the Rio Grande Headwaters (RGHW) region. Three applications of PRMS in the RGHW were used to simulate 1) baseline effects of climate (see RGHW-PRMS_baseline_input.zip), 2) effects of bark-beetle induced tree mortality (see RGHW-PRMS_BB_input.zip), and 3) effects of wildfire (see RGHW-PRMS_fire_input.zip), on components of the hydrologic cycle by hydrologic response unit (HRU) and subsequent seasonal streamflow runoff from April through September for water years 1980 through 2017. PRMS input files (control, climate-by-hru, data, parameter, dynamic parameter, and initial condition, where applicable) for each simulation are contained in this data release. Common input used in each simulation (climate_by_hru, static parameter, and data files) are contained in the RGHW-PRMS_common_input.zip file.

The U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) was used to assess the effects of changing climate and land disturbance on seasonal streamflow in the Rio Grande Headwaters (RGHW) region. Three applications of PRMS in the RGHW were used to simulate 1) baseline effects of climate (see RGHW-PRMS_baseline_input.zip), 2) effects of bark-beetle induced tree mortality (see RGHW-PRMS_BB_input.zip), and 3) effects of wildfire (see RGHW-PRMS_fire_input.zip), on components of the hydrologic cycle by hydrologic response unit (HRU) and subsequent seasonal streamflow runoff from April through September for water years 1980 through 2017. PRMS input files (control, climate-by-hru, data, parameter, dynamic parameter, and initial condition, where applicable) for each simulation are contained in this data release. Common input used in each simulation (climate_by_hru, static parameter, and data files) are contained in the RGHW-PRMS_common_input.zip file.

The U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) was used to assess the effects of changing climate and land disturbance on seasonal streamflow in the Rio Grande Headwaters (RGHW) region. Three applications of PRMS in the RGHW were used to simulate 1) baseline effects of climate (see RGHW-PRMS_baseline_simulation.zip), 2) effects of bark-beetle induced tree mortality (see RGHW-PRMS_BB_simulation.zip), and 3) effects of wildfire (see RGHW-PRMS_fire_simulation.zip), on components of the hydrologic cycle by hydrologic response unit (HRU) and subsequent seasonal streamflow runoff from April through September for water years 1980 through 2017. Select PRMS output variables for each simulation are contained in this data release.

The U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) was used to assess the effects of changing climate and land disturbance on seasonal streamflow in the Rio Grande Headwaters (RGHW) region. Three applications of PRMS in the RGHW were used to simulate 1) baseline effects of climate (see RGHW-PRMS_baseline_simulation.zip), 2) effects of bark-beetle induced tree mortality (see RGHW-PRMS_BB_simulation.zip), and 3) effects of wildfire (see RGHW-PRMS_fire_simulation.zip), on components of the hydrologic cycle by hydrologic response unit (HRU) and subsequent seasonal streamflow runoff from April through September for water years 1980 through 2017. Select PRMS output variables for each simulation are contained in this data release.