We developed four 2011-2050 land cover change scenarios and modeled the impact of projected land cover change on influent water quality to support long-term planning for the city of Minneapolis, MN. Baseline land cover was from the NLCD2011 database. IPCC SRES scenarios (https://www.ipcc.ch/site/assets/uploads/2018/03/sres-en.pdf) interpreted by Sohl et al. (2014) (https://doi.org/10.1890/13-1245.1) for the conterminous United States were downscaled from 250 meters to 30 meters. The baseline and scenario land cover data were used as input into the Soil Water and Assessment Tool (SWAT) model to assess the effect of outyear projected land cover change on the source of raw water for the city of Minneapolis, MN. SWAT was used to assess the effect of land cover change on raw water concentrations of sediment, total nitrogen, and total phosphorus. The IPCC SRES evaluated were A1B, A2, B1, and B2. The four scenarios were implemented with (A1Bf) and without (A1B) forest recovery (e.g., conversion of cropland (2011) to forest (2050). Units for the MeanDifference variable are different for TN/TP and sediment due to SWAT reporting conventions; TN and TP are in kilograms (kg) and sediment is in megagrams (Mg). 1 Mg = 1,000 kg. Differences are scenario minus baseline; negative values indicate constituent loads were less for the scenario relative to the baseline. NLCD2001 was included as a scenario to assess the effect of land cover change. Negative values for the NLCD2001 scenario indicate that a constituent load was less in 2001 relative to 2011.

We developed four 2011-2050 land cover change scenarios and modeled the impact of projected land cover change on influent water quality to support long-term planning for the city of Minneapolis, MN. Baseline land cover was from the NLCD2011 database. IPCC SRES scenarios (https://www.ipcc.ch/site/assets/uploads/2018/03/sres-en.pdf) interpreted by Sohl et al. (2014) (https://doi.org/10.1890/13-1245.1) for the conterminous United States were downscaled from 250 meters to 30 meters. The baseline and scenario land cover data were used as input into the Soil Water and Assessment Tool (SWAT) model to assess the effect of outyear projected land cover change on the source of raw water for the city of Minneapolis, MN. SWAT was used to assess the effect of land cover change on raw water concentrations of sediment, total nitrogen, and total phosphorus. The IPCC SRES evaluated were A1B, A2, B1, and B2. The four scenarios were implemented with (A1Bf) and without (A1B) forest recovery (e.g., conversion of cropland (2011) to forest (2050). Data on treatment of raw (source) water quality, provided by the city of Minneapolis, MN, were used in autoregressive models to determine if there was a temporal trend in mass of treatment chemicals applied. Models were run separately for each treatment chemical. Data are monthly application rates from 2008 through 2017. The day of the month for the date variable was nominally set to one (1). Data for alum were incomplete from 2008 through 2011, which were set to zero (0) and treated as missing in the autoregressive model. Water volume treated is in megagallons (Mg); 1 Mg = 1000 gallons. A dummy variable for change in management philosphy was included in the model. The dummy variable was set to zero (0) for the period 2008 - 2014 and one (1) afterward. The dummy variable is not included in the file. It had a significant effect only for the CO2 treatment chemical.

We developed four 2011-2050 land cover change scenarios and modeled the impact of projected land cover change on influent water quality to support long-term planning for the city of Minneapolis, MN. Baseline land cover was from the NLCD2011 database. IPCC SRES scenarios (https://www.ipcc.ch/site/assets/uploads/2018/03/sres-en.pdf) interpreted by Sohl et al. (2014) (https://doi.org/10.1890/13-1245.1) for the conterminous United States were downscaled from 250 meters to 30 meters. The baseline and scenario land cover data were used as input into the Soil Water and Assessment Tool (SWAT) model to assess the effect of outyear projected land cover change on the source of raw water for the city of Minneapolis, MN. SWAT was used to assess the effect of land cover change on raw water concentrations of sediment, total nitrogen, and total phosphorus. The IPCC SRES evaluated were A1B, A2, B1, and B2. The four scenarios were implemented with (A1Bf) and without (A1B) forest recovery (e.g., conversion of cropland (2011) to forest (2050). Data on treatment of raw (source) water quality, provided by the city of Minneapolis, MN, were used in autoregressive models to determine if there was a temporal trend in mass of treatment chemicals applied. Models were run separately for each treatment chemical. Data are monthly application rates from 2008 through 2017. The day of the month for the date variable was nominally set to one (1). Data for alum were incomplete from 2008 through 2011, which were set to zero (0) and treated as missing in the autoregressive model. Water volume treated is in megagallons (Mg); 1 Mg = 1000 gallons. A dummy variable for change in management philosphy was included in the model. The dummy variable was set to zero (0) for the period 2008 - 2014 and one (1) afterward. The dummy variable is not included in the file. It had a significant effect only for the CO2 treatment chemical.

We developed four 2011-2050 land cover change scenarios and modeled the impact of projected land cover change on influent water quality to support long-term planning for the city of Minneapolis, MN. Baseline land cover was from the NLCD2011 database. IPCC SRES scenarios (https://www.ipcc.ch/site/assets/uploads/2018/03/sres-en.pdf) interpreted by Sohl et al. (2014) (https://doi.org/10.1890/13-1245.1) for the conterminous United States were downscaled from 250 meters to 30 meters. The baseline and scenario land cover data were used as input into the Soil Water and Assessment Tool (SWAT) model to assess the effect of outyear projected land cover change on the source of raw water for the city of Minneapolis, MN. SWAT was used to assess the effect of land cover change raw water concentrations of sediment, total nitrogen, and total phosphorus. The IPCC SRES evaluated were A1B, A2, B1, and B2. The four scenarios were implemented with (A1Bf) and without (A1B) forest recovery (e.g., conversion of cropland (2011) to forest (2050) for a total of eight scenarios. The LULC net change file reports total change in hectares between 2011 and 2015 for forest, developed, cropland, pastures, and wetland for the four IPCC SRES scenarios with and without forest recovery.

A monthly water-balance model (MWBM) is applied to simulate components of the water balance for the period 1950-2100 under ssp245, ssp370, and ssp585 scenarios for the Contiguous United States. The statistically downscaled LOCA2 temperature and precipitation projections from 27 GCMs from the Climate Model Intercomparison Program Phase 6 (CMIP6) are use as input to the water balance model. This data set supports the USGS National Climate Change Viewer (ver. 2). The statistically downscaled data set is: CMIP6-LOCA2: Localized Constructed Analogs (Pierce et al. 2023, bias corrected by a modified version of Livneh et al. 2013) Users interested in the downscaled temperature and precipitation files are referred to the data set home page: LOCA: https://loca.ucsd.edu Bias correction data set: https://cirrus.ucsd.edu/~pierce/nonsplit_precip/ The 27 included GCMs are: ACCESS-CM2, ACCESS-ESM1-5, AWI-CM-1-1-MR, BCC-CSM2-MR, CESM2-LENS, CNRM-CM6-1, CNRM-CM6-1-HR, CNRM-ESM2-1, CanESM5, EC-Earth3, EC-Earth3-Veg, FGOALS-g3, GFDL-CM4, GFDL-ESM4, HadGEM3-GC31-LL, HadGEM3-GC31-MM, INM-CM4-8, INM-CM5-0, IPSL-CM6A-LR, KACE-1-0-G, MIROC6, MPI-ESM1-2-HR, MPI-ESM1-2-LR, MRI-ESM2-0, NorESM2-LM, NorESM2-MM, TaiESM1 There are 72 simulations in total (ssp245=24, ssp370=23, ssp585=25). While the LOCA2 data set supports multiple realizations per model; one MWBM realization per model is provided herein (predominately r1i1p1f1, except when this realization was not available).

A monthly water-balance model (MWBM) is applied to simulate components of the water balance for the period 1950-2100 under ssp245, ssp370, and ssp585 scenarios for the Contiguous United States. The statistically downscaled LOCA2 temperature and precipitation projections from 27 GCMs from the Climate Model Intercomparison Program Phase 6 (CMIP6) are use as input to the water balance model. This data set supports the USGS National Climate Change Viewer (ver. 2). The statistically downscaled data set is: CMIP6-LOCA2: Localized Constructed Analogs (Pierce et al. 2023, bias corrected by a modified version of Livneh et al. 2013) Users interested in the downscaled temperature and precipitation files are referred to the data set home page: LOCA: https://loca.ucsd.edu Bias correction data set: https://cirrus.ucsd.edu/~pierce/nonsplit_precip/ The 27 included GCMs are: ACCESS-CM2, ACCESS-ESM1-5, AWI-CM-1-1-MR, BCC-CSM2-MR, CESM2-LENS, CNRM-CM6-1, CNRM-CM6-1-HR, CNRM-ESM2-1, CanESM5, EC-Earth3, EC-Earth3-Veg, FGOALS-g3, GFDL-CM4, GFDL-ESM4, HadGEM3-GC31-LL, HadGEM3-GC31-MM, INM-CM4-8, INM-CM5-0, IPSL-CM6A-LR, KACE-1-0-G, MIROC6, MPI-ESM1-2-HR, MPI-ESM1-2-LR, MRI-ESM2-0, NorESM2-LM, NorESM2-MM, TaiESM1 There are 72 simulations in total (ssp245=24, ssp370=23, ssp585=25). While the LOCA2 data set supports multiple realizations per model; one MWBM realization per model is provided herein (predominately r1i1p1f1, except when this realization was not available).

Data supporting results presented in "Modeling future land cover change scenarios in Minneapolis, MN, to support drinking water source protection decisions.". This dataset is associated with the following publication: Woznicki, S., G. Kraynick, J. Wickham, M. Nash, and T. Sohl. Modeling future land cover and water quality change in Minneapolis, MN, USA to support drinking water source protection decisions. Global Environmental Change. Elsevier B.V., Amsterdam, NETHERLANDS, 59(4): 726-742, (2023).

This data release provides 64 forecasted water budget simulations for the Mississippi Embayment Regional Aquifer System (MERAS) during the period 2019 to 2055. Gridded daily data (1-kilometer resolution) include net infiltration (potential groundwater recharge), rejected net infiltration, interception, runoff, runoff outside (runoff that cannot be routed downslope), irrigation, actual evapotranspiration, minimum and maximum temperatures, and gross precipitation. The gridded representations of water budget components are output from USGS Soil-Water-Balance (SWB) model (Nielsen and Westenbroek, 2023; Westenbroek and Nielsen, 2023) simulations in netcdf4 format, and all water budget components are in inches. The precipitation, maximum air temperature, and minimum air temperature data used as climatic input to the SWB model application were derived from Coupled Model Intercomparison Project Phase 5 (CMIP5) projections (Brekke and others, 2013), downscaled using Localized Constructed Analogs (LOCA; Pierce and others, 2014) to a 1/16 degree spatial resolution. The SWB model produced output based on 64 CMIP5 climate projections, half of which are Representative Concentration Pathway (RCP) 4.5 and half of which are RCP 8.5 greenhouse gas concentration trajectories. All 64 forecasted climate model outputs can be accessed through the child items: RCP_4_5 and RCP_8_5. Outputs for each climate model scenario are housed in a zipped folder named after the respective climate scenario. Each zipped folder contains ten files: actual_et__2019-01-01_to_2055-12-31__989_by_661.nc, gross_precipitation__2019-01-01_to_2055-12-31__989_by_661.nc, interception__2019-01-01_to_2055-12-31__989_by_661.nc, irrigation__2019-01-01_to_2055-12-31__989_by_661.nc, net_infiltration__2019-01-01_to_2055-12-31__989_by_661.nc, rejected_net_infiltration__2019-01-01_to_2055-12-31__989_by_661.nc, runoff__2019-01-01_to_2055-12-31__989_by_661.nc, runoff_outside__2019-01-01_to_2055-12-31__989_by_661.nc, tmax__2019-01-01_to_2055-12-31__989_by_661.nc, and tmin__2019-01-01_to_2055-12-31__989_by_661.nc. Further details about the SWB model used to produce the water budget forecasts can be found in Nielsen and Westenbroek (2023).

This data release provides 64 forecasted water budget simulations for the Mississippi Embayment Regional Aquifer System (MERAS) during the period 2019 to 2055. Gridded daily data (1-kilometer resolution) include net infiltration (potential groundwater recharge), rejected net infiltration, interception, runoff, runoff outside (runoff that cannot be routed downslope), irrigation, actual evapotranspiration, minimum and maximum temperatures, and gross precipitation. The gridded representations of water budget components are output from USGS Soil-Water-Balance (SWB) model (Nielsen and Westenbroek, 2023; Westenbroek and Nielsen, 2023) simulations in netcdf4 format, and all water budget components are in inches. The precipitation, maximum air temperature, and minimum air temperature data used as climatic input to the SWB model application were derived from Coupled Model Intercomparison Project Phase 5 (CMIP5) projections (Brekke and others, 2013), downscaled using Localized Constructed Analogs (LOCA; Pierce and others, 2014) to a 1/16 degree spatial resolution. The SWB model produced output based on 64 CMIP5 climate projections, half of which are Representative Concentration Pathway (RCP) 4.5 and half of which are RCP 8.5 greenhouse gas concentration trajectories. All 64 forecasted climate model outputs can be accessed through the child items: RCP_4_5 and RCP_8_5. Outputs for each climate model scenario are housed in a zipped folder named after the respective climate scenario. Each zipped folder contains ten files: actual_et__2019-01-01_to_2055-12-31__989_by_661.nc, gross_precipitation__2019-01-01_to_2055-12-31__989_by_661.nc, interception__2019-01-01_to_2055-12-31__989_by_661.nc, irrigation__2019-01-01_to_2055-12-31__989_by_661.nc, net_infiltration__2019-01-01_to_2055-12-31__989_by_661.nc, rejected_net_infiltration__2019-01-01_to_2055-12-31__989_by_661.nc, runoff__2019-01-01_to_2055-12-31__989_by_661.nc, runoff_outside__2019-01-01_to_2055-12-31__989_by_661.nc, tmax__2019-01-01_to_2055-12-31__989_by_661.nc, and tmin__2019-01-01_to_2055-12-31__989_by_661.nc. Further details about the SWB model used to produce the water budget forecasts can be found in Nielsen and Westenbroek (2023).

We apply a monthly water-balance model (MWBM) to simulate components of the water balance for the period 1950-2099 under RCP4.5 and RCP8.5 for the Contiguous United States. We use the statistically downscaled MACAv2-METDATA temperature and precipitation data from 20 General Circulation Models (GCMs) from the Climate Model Intercomparison Program Phase 5 (CMIP5) as input to the water balance model. This dataset supports the USGS National Climate Change Viewer. The statistically downscaled dataset is: MACAv2-METDATA: Multivariate Adaptive Constructed Analogs (Abatzoglou & Brown, 2012, bias corrected by METDATA, Abatzoglou, 2013) Users interested in the downscaled temperature and precipitation files are referred to the dataset home page: MACAv2-METDATA: http://maca.northwestknowledge.net The 20 included GCMs are: bcc-csm1-1-m, bcc-csm1-1, BNU-ESM, CanESM2, CCSM4, CNRM-CM5, CSIRO-Mk3-6-0, GFDL-ESM2G, GFDL-ESM2M, HadGEM2 CC365, HadGEM2-ES365, inmcm4,IPSL-CM5A-LR, IPSL CM5A-MR, IPSL-CM5B-LR, MIROC5, MIROC-ESM, MIROC ESM CHEM, MRI-CGCM3, NorESM1-M