Skip to main content
Advanced Search

Filters: partyWithName: Joshua D. Larsen (X) > partyWithName: U.S. Geological Survey, MIDCONTINENT REGION (X) > Categories: Data (X)

3 results (38ms)   

View Results as: JSON ATOM CSV
thumbnail
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....
thumbnail
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...
thumbnail
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 In this data release, water use refers to water that is withdrawn by public and private water suppliers and includes water provided for domestic, commercial, industrial, thermoelectric...


    map background search result map search result map Machine learning model that estimates total monthly and annual per capita public-supply water use (version 2.0) Public supply water use reanalysis for the 2000-2020 period by HUC12, month, and year for the conterminous United States (ver. 2.0, August 2024) R code that determines groundwater and surface water source fractions for public-supply water service areas, counties, and 12-digit hydrologic units Machine learning model that estimates total monthly and annual per capita public-supply water use (version 2.0) Public supply water use reanalysis for the 2000-2020 period by HUC12, month, and year for the conterminous United States (ver. 2.0, August 2024) R code that determines groundwater and surface water source fractions for public-supply water service areas, counties, and 12-digit hydrologic units