This child item describes Python code used to query census data from the TigerWeb Representational State Transfer (REST) services and the U.S. Census Bureau Application Programming Interface (API). These data were needed as input feature variables for a machine learning model to predict public supply water use for the conterminous United States. Census data were retrieved for public-supply water service areas, but the census data collector could be used to retrieve data for other areas of interest. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Data retrieved by the census data collector code were used as input features in the public supply delivery and water use machine learning models. This page includes the following file: census_data_collector.zip - a zip file containing the census data collector Python code used to retrieve data from the U.S. Census Bureau and a README file.

This child item describes Python code used to query census data from the TigerWeb Representational State Transfer (REST) services and the U.S. Census Bureau Application Programming Interface (API). These data were needed as input feature variables for a machine learning model to predict public supply water use for the conterminous United States. Census data were retrieved for public-supply water service areas, but the census data collector could be used to retrieve data for other areas of interest. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Data retrieved by the census data collector code were used as input features in the public supply delivery and water use machine learning models. This page includes the following file: census_data_collector.zip - a zip file containing the census data collector Python code used to retrieve data from the U.S. Census Bureau and a README file.

This child item describes Python code used to retrieve gridMET climate data for a specific area and time period. Climate data were retrieved for public-supply water service areas, but the climate data collector could be used to retrieve data for other areas of interest. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Data retrieved by the climate data collector code were used as input feature variables in the public supply delivery and water use machine learning models. This page includes the following file: climate_data_collector.zip - a zip file containing the climate data collector Python code used to retrieve climate data and a README file.

This child item describes R code used to determine public supply consumptive use estimates. Consumptive use was estimated by scaling an assumed fraction of deliveries used for outdoor irrigation by spatially explicit estimates of evaporative demand using estimated domestic and commercial, industrial, and institutional deliveries from the public supply delivery machine learning model child item. This method scales public supply water service area outdoor water use by the relationship between service area gross reference evapotranspiration provided by GridMET and annual continental U.S. (CONUS) growing season maximum evapotranspiration. This relationship to climate at the CONUS scale could result in over- or under-estimation of consumptive use at public supply service areas where local variations differ from national variations in climate. This method also assumes that 50% of deliveries for total domestic and commercial, industrial, and institutional deliveries is used for outdoor purposes. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. This page includes the following file: PS_ConsumptiveUse.zip - a zip file containing input datasets, scripts, and output datasets

This data release collates stream water temperature observations from across the United States from four data sources: The U.S. Geological Survey's National Water Information System (NWIS), Water Quality Portal (WQP), Spatial Hydro-Ecological Decision Systems temperature database (EcoSHEDS), and the U.S. Fish and Wildlife's NorWeST stream temperature database. These data were compiled for use in broad scale water temperature models. Observations are included from the contiguous continental US, as well as Alaska, Hawaii, and territories. Temperature monitoring sites were paired to stream segments from the Geospatial Fabric for the National Hydrologic Model. Continuous and discrete data were reduced to daily mean, minimum, and maximum temperatures when more than one measurement was made per site-day. Various quality control checks were conducted including inspecting and converting units, eliminating some duplicate entries, interpreting flags and removing low quality observations, fixing date issues from the WQP, and filtering to expected water temperature ranges. However, we expect data quality issues persist and users should conduct further data quality checks that match the intended use of the data. This data release contains four core files: - site_metadata.csv contains information about each site at which water temperature observations are reported in this dataset. - national_stream_temp_code.zip contains the R code used to derive the data in this data release. - daily_stream_temperature.zip is a compressed comma separated file of observed water temperatures. - spatial.zip contains the geographic information about each site at which water temperature observations are reported in this dataset.

This child item describes a machine learning model that was developed to estimate public-supply water use by water service area (WSA) boundary and 12-digit hydrologic unit code (HUC12) for the conterminous United States. This model was used to develop an annual and monthly reanalysis of public supply water use for the period 2000-2020. This data release contains model input feature datasets, python codes used to develop and train the water use machine learning model, and output water use predictions by HUC12 and WSA. Public supply water use estimates and statistics files for HUC12s are available on this child item landing page. Public supply water use estimates and statistics for WSAs are available in public_water_use_model.zip. This page includes the following files: PS_HUC12_Tot_2000_2020.csv - a csv file with estimated monthly public supply total water use from 2000-2020 by HUC12, in million gallons per day PS_HUC12_GW_2000_2020.csv - a csv file with estimated monthly public supply groundwater use for 2000-2020 by HUC12, in million gallons per day PS_HUC12_SW_2000_2020.csv - a csv file with estimated monthly public supply surface water use for 2000-2020 by HUC12, in million gallons per day Note: 1) Groundwater and surface water fractions were determined using source counts as described in the 'R code that determines groundwater and surface water source fractions for public-supply water service areas, counties, and 12-digit hydrologic units' child item. 2) Some HUC12s have estimated water use of zero because no public-supply water service areas were modeled within the HUC. STAT_PS_HUC12_Tot_2000_2020.csv - a csv file with statistics by HUC12 for the estimated monthly public supply total water use from 2000-2020 STAT_PS_HUC12_GW_2000_2020.csv - a csv file with statistics by HUC12 for the estimated monthly public supply groundwater use for 2000-2020 STAT_PS_HUC12_SW_2000_2020.csv - a csv file with statistics by HUC12 for the estimated monthly public supply surface water use for 2000-2020 public_water_use_model.zip - a zip file containing input datasets, scripts, and output datasets for the public supply water use machine learning model version_history_MLmodel.txt - a txt file describing changes in this version

This child item describes R code used to determine whether public-supply water systems buy water, sell water, both buy and sell water, or are neutral (meaning the system has only local water supplies) using water source information from a proprietary dataset from the U.S. Environmental Protection Agency. This information was needed to better understand public-supply water use and where water buying and selling were likely to occur. Buying or selling of water may result in per capita rates that are not representative of the population within the water service area. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Output from this code was used as an input feature variable in the public supply water use machine learning model. This page includes the following files: ID_WSA_04062022_Buyers_Sellers_DR.R - an R script used to determine whether a public-supply water service area buys water, sells water, or is neutral BuySell_readme.txt - a README text file describing the script

This dataset presents the total estimated monthly public-supply water withdrawal by 12-digit hydrologic unit code (HUC12) in the conterminous United States for 2015. Public-supply water use was estimated by spatially and temporally downscaling available data from each state. The total represents combined groundwater and surface water withdrawals for 83,178 watersheds. Public supply refers to water withdrawn by public and private water suppliers that provide water for cities, towns, rural water districts, mobile-home parks, Native American Indian reservations, and military bases. Public-supply facilities are classified under the Standard Industrial Classification (SIC) 4941 and provide water to at least 25 people or have a minimum of 15 connections. Water withdrawals are used mostly for domestic purposes, but also serve other customers such as commercial and industrial establishments. These monthly estimates by HUC12 support USGS National Integrated Water Availability Assessments Water Use Maps.

This dataset, termed "GAGES II", an acronym for Geospatial Attributes of Gages for Evaluating Streamflow, version II, provides geospatial data and classifications for 9,322 stream gages maintained by the U.S. Geological Survey (USGS). It is an update to the original GAGES, which was published as a Data Paper on the journal Ecology's website (Falcone and others, 2010b) in 2010. The GAGES II dataset consists of gages which have had either 20+ complete years (not necessarily continuous) of discharge record since 1950, or are currently active, as of water year 2009, and whose watersheds lie within the United States, including Alaska, Hawaii, and Puerto Rico. Reference gages were identified based on indicators that they were the least-disturbed watersheds within the framework of broad regions, based on 12 major ecoregions across the United States. Of the 9,322 total sites, 2,057 are classified as reference, and 7,265 as non-reference. Of the 2,057 reference sites, 1,633 have (through 2009) 20+ years of record since 1950. Some sites have very long flow records: a number of gages have been in continuous service since 1900 (at least), and have 110 years of complete record (1900-2009) to date. The geospatial data include several hundred watershed characteristics compiled from national data sources, including environmental features (e.g. climate – including historical precipitation, geology, soils, topography) and anthropogenic influences (e.g. land use, road density, presence of dams, canals, or power plants). The dataset also includes comments from local USGS Water Science Centers, based on Annual Data Reports, pertinent to hydrologic modifications and influences. The data posted also include watershed boundaries in GIS format. This overall dataset is different in nature to the USGS Hydro-Climatic Data Network (HCDN; Slack and Landwehr 1992), whose data evaluation ended with water year 1988. The HCDN identifies stream gages which at some point in their history had periods which represented natural flow, and the years in which those natural flows occurred were identified (i.e. not all HCDN sites were in reference condition even in 1988, for example, 02353500). The HCDN remains a valuable indication of historic natural streamflow data. However, the goal of this dataset was to identify watersheds which currently have near-natural flow conditions, and the 2,057 reference sites identified here were derived independently of the HCDN. A subset, however, noted in the BasinID worksheet as “HCDN-2009”, has been identified as an updated list of 743 sites for potential hydro-climatic study. The HCDN-2009 sites fulfill all of the following criteria: (a) have 20 years of complete and continuous flow record in the last 20 years (water years 1990-2009), and were thus also currently active as of 2009, (b) are identified as being in current reference condition according to the GAGES-II classification, (c) have less than 5 percent imperviousness as measured from the NLCD 2006, and (d) were not eliminated by a review from participating state Water Science Center evaluators. The data posted here consist of the following items:- This point shapefile, with summary data for the 9,322 gages.- A zip file containing basin characteristics, variable definitions, and a more detailed report.- A zip file containing shapefiles of basin boundaries, organized by classification and aggregated ecoregion.- A zip file containing mainstem stream lines (Arc line coverages) for each gage.

This child item provides a snapshot of the watershed boundary dataset which consists of a shapefile with 87,020 12-digit hydrologic unit codes (HUC12) for the conterminous United States retrieved 10/26/2020. The National Watershed Boundary Dataset (WBD) is a comprehensive set of digital spatial data that represents the surface drainages areas of the United States. Although versions of the WBD are published as part of U.S. Geological Survey National Hydrography Products, the version used to produce the water-use reanalysis was not archived and is provided here. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Public-supply water use estimates for the HUC12s included in this shapefile are provided on the data release main landing page and on the public supply water use machine learning model child item. This page includes the following file: WBD_HUC12_CONUS_pulled10262020.zip - a zip file containing a shapefile with 12-digit hydrologic units in the conterminous United States