Filters: Contacts: Carol L Luukkonen (X)
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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 Public supply refers to water withdrawn by public and private water suppliers that provide water for cities, towns, rural water districts, mobile-home parks, Native American Indian reservations, and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...
A regional groundwater flow model (https://pubs.usgs.gov/sir/2009/5244/) was updated to reflect 2017 pumping conditions in the Tri-County Region covering most of Clinton, Eaton, and Ingham Counties, Michigan. This model was developed to simulate the regional hydrologic system in Tri-County area and continues to be used for planning and protection of area water supplies. Revised contributing area delineations in response to recent pumping conditions were needed for local wellhead protection area programs. The model was calibrated to water level observations for 2017 from well driller logs, average water levels for 2012-17 from active USGS observation wells, and estimated baseflow for 2012-16 from USGS streamgaging...
The U.S. Geological Survey (USGS) National Water Use Program is responsible for compiling and disseminating the Nation's water-use data. Working in cooperation with local, State, and Federal agencies, the USGS has published an estimate of water use in the United States every 5 years, beginning in 1950. These 5-year compilations contain water-use estimates that are aggregated to the county level in the United States. This USGS data release contains summaries of method codes used in the 2015 national compilation of public supply, self-supplied domestic, thermoelectric, and irrigation water-use data. This data release also contains the county-level water-use estimates that support the evaluations in Luukkonen and others...
An inventory of facilities that bottle water or other beverages containing water (including soft drinks, beer, wine, or spirits) or that manufacture ice was compiled by combining available datasets from multiple sources. This water bottling inventory dataset includes facilities within all 50 states of the United States, one federal district (Washington, District of Columbia), and three territories (Guam, Puerto Rico, and Virgin Islands). The inventory focuses on presently active facilities in 2023. Most closed water bottling facilities are not included; however, facilities identified as being a former production site (meaning the facility is still active but the business function has changed) or as closed during...
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...
National watershed boundary (HUC12) dataset for the conterminous United States, retrieved 10/26/2020
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...
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...
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 child item describes R code used to determine water source fractions (groundwater (GW), surface water (SW), or spring (SP)) for public-supply water service areas, counties, and 12-digit hydrologic unit codes (HUC12) using information from a proprietary dataset from the U.S. Environmental Protection Agency. Water-use volumes per source were not available from public-supply systems so water source fractions were calculated by the number of withdrawal source types (GW/SW). For example, for a public supply system with three SW intakes and one GW well, the fractions would be 0.75 SW and 0.25 GW. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic...
The U.S. Geological Survey is developing national water-use models to support water resources management in the United States. Model benefits include a nationally consistent estimation approach, greater temporal and spatial resolution of estimates, efficient and automated updates of results, and capabilities to forecast water use into the future and assess model uncertainty. The term “reanalysis” refers to the process of reevaluating and recalculating water-use data using updated or refined methods, data sources, models, or assumptions. In this data release, water use refers to water that is withdrawn by public and private water suppliers and includes water provided for domestic, commercial, industrial, thermoelectric...
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...
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....
This child item describes a public-supply delivery machine learning model that was developed to estimate public-supply deliveries. Publicly supplied water may be delivered to domestic users or to commercial, industrial, institutional, and irrigation (CII) users. This model predicts total, domestic, and CII per capita rates for public-supply water service areas within the conterminous United States for 2009-2020. This child item contains model input datasets, code used to build the delivery machine learning model, and national predictions. 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...
Monthly water yields for 105,829 catchments and corresponding flows for 107,691 stream segments were estimated for water years 1951-2012 in the United States part of the Great Lakes Basin. Estimates were computed using the AFINCH (Analysis of Flows In Networks of CHannels) application within the NHDPlus geospatial data framework. AFINCH provides an environment to develop constrained regression models to integrate monthly streamflow and water-use data with monthly climatic data and fixed basin characteristics data available within NHDPlus or supplied by the user. Monthly flow time series for individual stream segments can be retrieved and used to approximate monthly flow duration characteristics and to identify possible...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service,
Shapefile;
Tags: AFINCH,
Accountability,
GLRI,
GLRI,
Great Lakes,
This child item describes Python code used to estimate average yearly and monthly tourism per 1000 residents within public-supply water service areas. Increases in population due to tourism may impact amounts of water used by public-supply water systems. This data release contains model input datasets, Python code used to develop the tourism information, and output estimates of tourism. 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 in the public supply delivery and water use machine learning models. This page includes the following files: tourism_input_data.zip...
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