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These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. Digital hydrogeologic surface of the Midway Confining Unit in Alabama, Arkansas, Illinois, Kentucky, Missouri, Mississippi. The hydrogeologic unit dataset contains 414 rows and 394 columns representing 1-mile grid spacing. In general, limitations of data interpolation included areas of sparse geophysical log control points, log datums not clearly defined for some logs, unknown exact extent of each hydrogeologic unit in subcrop, interpolation...
These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. Digital hydrogeologic surface of the Lower Claiborne Confining Unit in Alabama, Arkansas, Louisiana, Mississippi. The hydrogeologic unit dataset contains 414 rows and 394 columns representing 1-mile grid spacing. In general, limitations of data interpolation included areas of sparse geophysical log control points, log datums not clearly defined for some logs, unknown exact extent of each hydrogeologic unit in subcrop, interpolation...
These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. Outcrop and subcrop extent of the Middle Claiborne Aquifer in Alabama, Arkansas, Illinois, Kentucky, Louisiana, Missouri, Mississippi, Tennessee.
These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. Outcrop and subcrop extent of the Mississippi River Valley Alluvial Aquifer in Alabama, Arkansas, Illinois, Kentucky, Louisiana, Mississippi, and Tennessee.
These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. Outcrop and subcrop extent of the Vicksburg-Jackson Confining Unit in Arkansas, Alabama, Louisiana, Missouri, Mississippi, and Tennessee.
These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. This map shows the USGS (United States Geologic Survey), NWIS (National Water Inventory System) Hydrologic Data Sites for Millard County, Utah. The scope and purpose of NWIS is defined on the web site: http://water.usgs.gov/public/pubs/FS/FS-027-98/
These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. This map shows the USGS (United States Geologic Survey), NWIS (National Water Inventory System) Hydrologic Data Sites for Juab County, Utah. The scope and purpose of NWIS is defined on the web site: http://water.usgs.gov/public/pubs/FS/FS-027-98/
Estimation of irrigation water use provides essential information for the management and conservation of agricultural water resources. The blue water evapotranspiration (BWET) raster dataset at 30-meter resolution is created to estimate agricultural irrigation water consumption. The dataset contains seasonal total (1 May to 30 September) BWET time series (1986 – 2020) for the croplands across the U.S. High Plains aquifer region. The BWET estimates are generated by integrating an energy-balance ET model (Operational Simplified Surface Energy Balance model) and a water-balance ET model (Vegetation ET model). BWET in croplands reflects crop consumptive use of irrigation water extracted from surface water and groundwater...
These data were compiled for evaluating plant water use, or river-reach level evapotranspiration (ET) data, in the riparian corridor of the Colorado River delta as specified under Minute 319 of the 1944 Water Treaty. Additionally, these data were compiled for evaluating restoration-level data in Reach 2 and Reach 4, as specified under Minute 323 of the 1944 Water Treaty. Objectives of our study were to measure the peak growing season evapotranspiration (ET) for the average of months in summer-fall (May to October) for the seven reaches, for the full riparian corridor, and for four restoration sites, from 2013 through 2022. The seven reach areas from the Northerly International Boundary (NIB) to the end of the delta...
The U.S. Geological Survey (USGS) developed a systematic, quantitative approach to prioritize candidate basins that can support the assessment and forecasting objectives of the major USGS water science programs. Candidate basins were the level-4 hydrologic units (HUC4) with some of the smaller HUC4s being combined (hereafter referred to as modified HUC4 basins). Candidate basins for the contiguous United States (CONUS) were grouped into 18 hydrologic regions. Thirty-three geospatial variables representing land use, climate change, water use, water-balance components, streamflow alteration, fire risk, and ecosystem sensitivity were initially considered to assist in ranking candidate basins for study. The two highest...
Categories: Data;
Tags: Climatology,
Ecology,
Hydrology,
Integrated Water Science Basins,
Land Use Change,
This community serves to document data and analysis collected by researchers within the Upper Midwest Water Science Center whose mission is to collect high-quality hydrologic data and conduct unbiased, scientifically sound studies of water resources within the Great Lakes and Upper Mississippi Basins. We strive to meet the changing needs of those who use our information—from the distribution, availability, and quality of our water resources to topic-oriented research that addresses current hydrological issues.
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...
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...
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...
These data were compiled to understand the effects of riparian vegetation health on local abundance and species diversity of land birds. The primary objective of our study was to to determine the effects of riparian restoration on birds in the Colorado River delta. These tabular data represent vegetation indices and evapotranspiration (ET) data at varying spatial scales that correspond to avian use circles of 100 to 2000 meters. Three vegetation reflectance indices (VIs): NDVI, EVI, and EVI2 were obtained from Landsat imagery with a biweekly temporal frequency, and covering the entire period of bird surveys (2002-2020). The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) and two-band...
The Ohio-Kentucky-Indiana Water Science Center looks forward to helping you achieve your goals by providing water quantity and quality information, as well as scientific tools and understanding, when and where they are needed by citizens, businesses, and public officials.
This community catalog serves the USGS Pennsylvania Water Science Center. The Water Science Center's mission is to collect, analyze and disseminate the impartial hydrologic data and information needed to wisely manage water resources for the people of the United States and the Commonwealth of Pennsylvania. In Pennsylvania, the USGS's water-resources roots date back to the late 1800's, with the initiation of streamflow gaging on the Delaware and Susquehanna Rivers and the evaluation of groundwater resources in various parts of the Commonwealth. Today, the Pennsylvania Water Science Center's cadre of nearly 80 scientists, technicians, and support staff in New Cumberland, Exton, Pittsburgh, and Williamsport work in...
Observations of irrigated agricultural land within the Willcox Groundwater Basin in Arizona. Digitized field boundaries were used to locate crops for in situ verification twice in 2022; crop verification occurred first on May 17th and again on August 26th. Field boundaries were digitized from U.S. Department of Agriculture, National Agricultural Imagery Program County Mosaic 2021 imagery for Arizona and supplemented with Landsat and Sentinel2 imagery collections accessed via the Sentinel Hub, Sentinel Playground (https://apps.sentinel-hub.com/sentinel-playground). Satellite images were also used to identify the length of the growing season and crop condition. Water withdrawals were calculated using the modified...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Arizona,
Cochise,
Graham,
Land Use Change,
USGS Science Data Catalog (SDC),
Improvements to an existing regional groundwater-flow model of a 160-square mile area of coastal New Hampshire (https://doi.org/10.3133/sir20085222), incorporating MODFLOW-NWT and by more accurately representing stream characteristics, were presented at the MODFLOW and More 2017 conference in an example simulating approximate changes in water use. The groundwater-flow model developed for the previous study incorporated detailed water-use information for 2003-04 and simulated the effects of projected increases in water use. At that time, population growth and increasing water demand prompted concern for the sustainability of the region’s groundwater resources in a fractured-crystalline bedrock-aquifer with little...
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. This data release contains data used in a machine learning model to estimate monthly water use for communities that are supplied by public-supply water systems in the conterminous United States for 2000-2020. This data release also contains associated scripts used to produce input features as well as model output values by 12-digit hydrologic...
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