These data were compiled for/to modeling efforts for U.S. Bureau of Reclamation National Environmental Policy Act (NEPA) analyses for the Colorado River in Grand Canyon, Arizona. Objective(s) of our study were to create revised monthly Lake Powell elevations and outflows from Bureau of Reclamation Colorado River Mid-term Modeling System (CRMMS) traces that incorporate the alternatives in the sEIS documents and indicate when potential actions may occur and how that changes water movement and storage. These data represent monthly hydrologies for Lake Powell: inflow, outflow, and elevation forecasts for 2024-2027, as well as volumes of water in outflows for different water mangement strategies in NEPA supplemental environmental impact statement (sEIS) documents from the U.S. Bureau of Reclamation (USBOR). These data were collected in 2023 and 2024. These data were collected from the USBOR CRMMS and used by U.S. Geological Survey-Southwest Biological Science Center-Grand Canyon Monitoring & Research Center modeling. These data can be used to evaluate different water management strategy potential impacts to storage in Lake Powell.

These data were compiled to evaluate impacts of different reservoir management scenarios on sand exposure for aeolian landscape and cultural site resources. Objective of our study was to predict areas of dry, bare Colorado River sand as a function of different management alternative scenarios. These data represent predictions of dry, bare sand for the reach of the Colorado River between Glen Canyon Dam and Bright Angel Creek in Grand Canyon National Park. These data were created during 2023 by the U.S. Geological Survey, Southwest Biological Science Center, Grand Canyon Monitoring and Research Center. These data can be used to understand how the area of sand available for windblown transport might be impacted different reservoir management alternatives and scenarios considered in the Near-term Colorado River Operations Supplemental Environmental Impact Statement (Interim Guidelines sEIS) and the Glen Canyon Dam Long-Term Experimental and Management Plan Supplemental Environmental Impact Statement (LTEMP sEIS).

These data were compiled to evaluate impacts of different reservoir management scenarios on sand exposure for aeolian landscape and cultural site resources. Objective of our study was to predict areas of dry, bare Colorado River sand as a function of different management alternative scenarios. These data represent predictions of dry, bare sand for the reach of the Colorado River between Glen Canyon Dam and Bright Angel Creek in Grand Canyon National Park. These data were created during 2023 by the U.S. Geological Survey, Southwest Biological Science Center, Grand Canyon Monitoring and Research Center. These data can be used to understand how the area of sand available for windblown transport might be impacted different reservoir management alternatives and scenarios considered in the Near-term Colorado River Operations Supplemental Environmental Impact Statement (Interim Guidelines sEIS) and the Glen Canyon Dam Long-Term Experimental and Management Plan Supplemental Environmental Impact Statement (LTEMP sEIS).

These data were compiled for/to modeling to assess impact of management scenarios on Colorado River sediment resources. Objective(s) of our study were to assess impact of management scenarios on Colorado River sediment resources. These data represent model results for high flow experiment timing/duration, sand mass balance, sandbar volume, based on the data in the Interim Guidelines SEIS and LTEMP SEIS folders. These data were generated in 2023-2024 and are model simulations of Colorado River sediment resources downstream of Glen Canyon dam. These data were created by the U.S. Geological Survey, Southwest Biological Science Center, Grand Canyon Monitoring & Research Center with models generated and codes written/adapted by Gerard Salter. These data can be used to assess impact of management scenarios on Colorado River sediment resources.

These data were compiled for/to modeling to assess impact of management scenarios on Colorado River sediment resources. Objective(s) of our study were to assess impact of management scenarios on Colorado River sediment resources. These data represent model results for high flow experiment timing/duration, sand mass balance, sandbar volume, based on the data in the Interim Guidelines SEIS and LTEMP SEIS folders. These data were generated in 2023-2024 and are model simulations of Colorado River sediment resources downstream of Glen Canyon dam. These data were created by the U.S. Geological Survey, Southwest Biological Science Center, Grand Canyon Monitoring & Research Center with models generated and codes written/adapted by Gerard Salter. These data can be used to assess impact of management scenarios on Colorado River sediment resources.

These data were compiled to predict hourly Glen Canyon Dam operations and hydropower impacts. The objective of our study was to estimate hydropower impacts under different future LTEMP sEIS alternatives. These data represent hourly outflow in cubic feet per second, generation in megawatt hours, and economic value of hydropower in nominal dollars. These data were created for operations at Glen Canyon Dam for October 2023 through November 2027. These data were created by the U.S. Geological Survey, Southwest Biological Science Center, Grand Canyon Monitoring and Research Cetner using mathematical modeling methods.

These data were compiled to predict hourly Glen Canyon Dam operations and hydropower impacts. The objective of our study was to estimate hydropower impacts under different future LTEMP sEIS alternatives. These data represent hourly outflow in cubic feet per second, generation in megawatt hours, and economic value of hydropower in nominal dollars. These data were created for operations at Glen Canyon Dam for October 2023 through November 2027. These data were created by the U.S. Geological Survey, Southwest Biological Science Center, Grand Canyon Monitoring and Research Cetner using mathematical modeling methods.

Lake and landscape data were compiled from the US Environmental Protection Agency National Lakes Assessment 2007 and 2012 surveys and LakeCat geospatial dataset. Additional climate variables were summarized from national PRISM and NOAA data layers following the same geoprocessing steps used in the LakeCat creation. The compiled dataset includes a derived metric that characterizes the degree of human-related water management presence on a lake that has the potential to significantly alter lake hydrology. The HydrAP metric (anthropogenic hydrological-alteration potential) uses information from the National Inventory of Dams and National Land Cover Database and is described in detail in Fergus et al. 2021. The compiled dataset includes all lake sites in the NLA 2007 survey and only new lake sites in NLA 2012 (i.e., not resampled lake sites during the two survey periods). We retained VISIT_NO = 1 observations for the analyses for a total of 1716 observations for unique lake sites distributed across the conterminous US.

Lake and landscape data were compiled from the US Environmental Protection Agency National Lakes Assessment 2007 and 2012 surveys and LakeCat geospatial dataset. Additional climate variables were summarized from national PRISM and NOAA data layers following the same geoprocessing steps used in the LakeCat creation. The compiled dataset includes a derived metric that characterizes the degree of human-related water management presence on a lake that has the potential to significantly alter lake hydrology. The HydrAP metric (anthropogenic hydrological-alteration potential) uses information from the National Inventory of Dams and National Land Cover Database and is described in detail in Fergus et al. 2021. The compiled dataset includes all lake sites in the NLA 2007 survey and only new lake sites in NLA 2012 (i.e., not resampled lake sites during the two survey periods). We retained VISIT_NO = 1 observations for the analyses for a total of 1716 observations for unique lake sites distributed across the conterminous US.

The Water Availability Tool for Environmental Resources (WATER-KY; Williamson and others, 2009) provides the ability to simulate streamflow for ungaged basins. This model integrates TOPMODEL (Beven and Kirkby, 1979) for pervious portions of the landscape with simulation of flow generated from impervious surfaces (USDA, 1986). A restructured version of this decision support tool translates the abilities of WATER to a format that can be used without proprietary software (Williamson and others, 2021). Additional functionality has also been added to include hydrologic response units (HRUs) that are defined based on three fundamental land-use categories: forest, agricultural land, and developed areas, based on subsequent development of WATER for the Delaware River Basin (Williamson and others, 2015). This refinement for agricultural areas, combined with the new software environment that enables easy substitution of precipitation and temperature data was used to develop a method focused on recent conditions in order to simulate daily peak streamflow for forecasted precipitation totals as well as the associated stage in order to identify if flood conditions are possible. Beven, K.J., and Kirkby, M.J., 1979, A physically based, variable contributing area model of basin hydrology / Un modèle à base physique de zone d'appel variable de l'hydrologie du bassin versant: Hydrological Sciences Bulletin v. 24, p. 43-69, https://doi.org/10.1080/02626667909491834. U.S. Department of Agriculture [USDA], 1986, Urban hydrology for small watersheds: Natural Resources Conservation Service, Conservation Engineering Division, Technical Release 55, Revised June 1986, Update of Appendix A January 1999, https://www.nrc.gov/docs/ML1421/ML14219A437.pdf. Williamson, T.N., Hoefling, D.J., Headman, A.O., and Gerzan, M.N., 2021, Water Availability Tool for Environmental Resources for the Commonwealth of Kentucky updated for 2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9AQH027. Williamson, T.N., Lant, J.G., Claggett, P.R., Nystrom, E.A., Milly, P.C.D., Nelson, H.L., Hoffman, S.A., Colarullo, S.J., and Fischer, J.M., 2015, Summary of hydrologic modeling for the Delaware River Basin using the Water Availability Tool for Environmental Resources (WATER): U.S. Geological Survey Scientific Investigations Report 2015–5143, 68 p., https://doi.org/10.3133/sir20155143. Williamson, T.N., Odom, K.R., Newson, J.K., Downs, A.C., Nelson Jr., H.L., Cinotto, P.J., and Ayers, M.A., 2009, The Water Availability Tool for Environmental Resources (WATER)—A water-budget modeling approach for managing water-supply resources in Kentucky—Phase I—Data processing, model development, and application to non-karst areas:U.S. Geological Survey Scientific Investigations Report 2009–5248, 34 p., https://doi.org/10.3133/sir20095248.