Population projections, estimated per capita consumption rate, and estimated total annual water demand to 2100 for four future projections based off the IPCC SRES climate scenarios. The estimates for water use are based Bayesian regression analysis on 1985, 1990, 1995, 2005 and 2010 water use from USGS. This dataset is associated with the following publication: Pickard, B., M. Nash, J. Baynes, and M. Mehaffey. Planning for community resilience to future United States domestic water demand. LANDSCAPE AND URBAN PLANNING. Elsevier Science Ltd, New York, NY, USA, 158: 75-86, (2017).

This data release contains projections of future water demand for the Western USA at the county level. This data is part of the project "Changes to Watershed Vulnerability under Future Climates, Fire Regimes, and Population Pressures" (https://www.sciencebase.gov/catalog/item/531dc54de4b04cb293ee7806), and is the product of an analysis that determined where populations are changing, and how that change could affect residential and agricultural water withdraws from surface and ground water. Agricultural water use was derived from the Cropland Data Layer (CDL) of the National Agricultural Statistics Service, while residential water use was drawn from the USGS (Maupin et al. 2014). The scenarios follow four Intergovernmental Panel on Climate Change Special Report on Emission Scenario (IPCC SRES) storylines (A1, A2, B1, B2) and project changes for the periods ending in 2050 and 2100. Integrated Climate and Land Use (ICLUS) Data from Bierwagen et al. (2010) was used to project population change according to the SRES storylines. By using the same storylines, coherent population and climate scenarios can be projected that are the product of both changing populations and future climates. Bierwagen et al. (2010). National housing and impervious surface scenarios for integrated climate impact assessments. DOI: https://doi.org/10.1073/pnas.1002096107 Maupin et al. (2104). United States Geological Survey (USGS) Water-use Intensity Data. DOI: http://dx.doi.org/10.3133/cir1405

This data release contains projections of future water demand for the Western USA at the county level. This data is part of the project "Changes to Watershed Vulnerability under Future Climates, Fire Regimes, and Population Pressures" (https://www.sciencebase.gov/catalog/item/531dc54de4b04cb293ee7806), and is the product of an analysis that determined where populations are changing, and how that change could affect residential and agricultural water withdraws from surface and ground water. Agricultural water use was derived from the Cropland Data Layer (CDL) of the National Agricultural Statistics Service, while residential water use was drawn from the USGS (Maupin et al. 2014). The scenarios follow four Intergovernmental Panel on Climate Change Special Report on Emission Scenario (IPCC SRES) storylines (A1, A2, B1, B2) and project changes for the periods ending in 2050 and 2100. Integrated Climate and Land Use (ICLUS) Data from Bierwagen et al. (2010) was used to project population change according to the SRES storylines. By using the same storylines, coherent population and climate scenarios can be projected that are the product of both changing populations and future climates. Bierwagen et al. (2010). National housing and impervious surface scenarios for integrated climate impact assessments. DOI: https://doi.org/10.1073/pnas.1002096107 Maupin et al. (2104). United States Geological Survey (USGS) Water-use Intensity Data. DOI: http://dx.doi.org/10.3133/cir1405

Urban growth and climate change together complicate planning efforts meant to adapt to increasingly scarce water supplies. Several studies have shown the impacts of urban planning and climate change separately, but little attention has been given to their combined impact on long-term urban water demand forecasting. Here we coupled land and climate change projections with empirically-derived coefficient estimates of urban water use (sum of public supply, industrial, and domestic use) to forecast water demand under scenarios of future population densities and climate warming. We simulated two scenarios of urban growth from 2012 to 2065 using the FUTure Urban-Regional Environment Simulation (FUTURES) framework. FUTURES is an open-source probabilistic land change model designed to address the regional-scale environmental and ecological impacts of urbanization. We simulated an urbanization scenario that continues the historic trend of growth referred to as “Status Quo” and a scenario that simulates patterns of clustered higher density development, referred to as “Urban Infill". We initialized land change projections in 2011 and run forward on an annual time step to 2065. We captured the uncertainty associated with future climate conditions by integrating three Global Climate Models (GCMs), representative of dry, wet, and median future conditions. GCMs follow a continuously increasing greenhouse gas emissions scenario (Representative Concentration Pathway; RCP 8.5). This data release includes: a) land change projections for both urbanization scenarios in a spatial resolution consistent with the National Land Cover Database; b) development-related water demand projections for scenarios of environmental change at the census tract spatial unit summarized by 2030 and 2065; and c) the spatial boundaries of census tracts presented as a shapefile.

Urban growth and climate change together complicate planning efforts meant to adapt to increasingly scarce water supplies. Several studies have shown the impacts of urban planning and climate change separately, but little attention has been given to their combined impact on long-term urban water demand forecasting. Here we coupled land and climate change projections with empirically-derived coefficient estimates of urban water use (sum of public supply, industrial, and domestic use) to forecast water demand under scenarios of future population densities and climate warming. We simulated two scenarios of urban growth from 2012 to 2065 using the FUTure Urban-Regional Environment Simulation (FUTURES) framework. FUTURES is an open-source probabilistic land change model designed to address the regional-scale environmental and ecological impacts of urbanization. We simulated an urbanization scenario that continues the historic trend of growth referred to as “Status Quo” and a scenario that simulates patterns of clustered higher density development, referred to as “Urban Infill". We initialized land change projections in 2011 and run forward on an annual time step to 2065. We captured the uncertainty associated with future climate conditions by integrating three Global Climate Models (GCMs), representative of dry, wet, and median future conditions. GCMs follow a continuously increasing greenhouse gas emissions scenario (Representative Concentration Pathway; RCP 8.5). This data release includes: a) land change projections for both urbanization scenarios in a spatial resolution consistent with the National Land Cover Database; b) development-related water demand projections for scenarios of environmental change at the census tract spatial unit summarized by 2030 and 2065; and c) the spatial boundaries of census tracts presented as a shapefile.

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.

This dataset contains csv files in support of the conclusions published in "Water use demand in Mediterranean California under multiple scenarios of developed and agricultural land use " in the journal PLOS One. We used the USGS's LUCAS model to examine a broad suite of spatially explicit future land use scenarios and their associated county-level water use demand, including the historical (1992-2011) and projected periods (2012-2062) across 40 Monte Carlo simulations.We examined a range of potential water demand futures sampled from a 20-year record of historical (1992-2012) data to develop a suite of potential future land change scenarios from 2012-2062. These scenario simulations include a 1) business-as-usual (BAU), 2) low agriculture (LA), 3) high agriculture (HU), 4) low urban (LU), 5) high urban (HU), 6) lowest of the low (LL), and 7) highest of the high (HH) anthropogenic use scenarios.

This dataset contains raster image files in support of the conclusions published in "Water use demand in Mediterranean California under multiple scenarios of developed and agricultural land use " in the journal PLOS One. We used the USGS's LUCAS model to examine a broad suite of spatially explicit future land use scenarios and their associated county-level water use demand, including the historical (1992-2011) and projected periods (2012-2062) across 40 Monte Carlo simulations.We examined a range of potential water demand futures sampled from a 20-year record of historical (1992-2012) data to develop a suite of potential future land change scenarios from 2012-2062. These scenario simulations include a 1) business-as-usual (BAU), 2) low agriculture (LA), 3) high agriculture (HA), 4) low urban (LU), 5) high urban (HU), 6) lowest of the low (LL), and 7) highest of the high (HH) anthropogenic use scenarios.

This dataset contains csv files in support of the conclusions published in "Water use demand in Mediterranean California under multiple scenarios of developed and agricultural land use " in the journal PLOS One. We used the USGS's LUCAS model to examine a broad suite of spatially explicit future land use scenarios and their associated county-level water use demand, including the historical (1992-2011) and projected periods (2012-2062) across 40 Monte Carlo simulations.We examined a range of potential water demand futures sampled from a 20-year record of historical (1992-2012) data to develop a suite of potential future land change scenarios from 2012-2062. These scenario simulations include a 1) business-as-usual (BAU), 2) low agriculture (LA), 3) high agriculture (HU), 4) low urban (LU), 5) high urban (HU), 6) lowest of the low (LL), and 7) highest of the high (HH) anthropogenic use scenarios.