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U.S. Geological Survey Northeast Region inland bathymetric survey data are compiled to create a survey inventory providing survey records including survey system and product information, and links to survey datasets when available. Dataset footprints including this information and showing the location and extent of surveys can be downloaded as a geodatabase and can be accessed through Spatial Services provided here.
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Acoustic Sonar,
Acoustic Sonar,
Bathymetry,
Bathymetry,
Coastal Zones,
This dataset was developed to estimate point-source total nitrogen and phosphorous loads to streams in the conterminous United States (U.S.) from December 1999 to November 2020. This dataset uses discharge and concentration information from point sources to streams in the conterminous United States from the U.S. Environmental Protection Agency (EPA) Integrated Compliance Information System - Permit Compliance System (ICIS-PCS) database. Nutrient concentrations were used to calculate point source loads. However, measured concentration data was often not available so “typical pollutant concentrations” (TPCs) were developed using concentration data from the same facility but a different time or from similar facilities....
This data release contains phytoplankton data and vertical profile measurements of water quality and light in oligotrophic (low nutrient) lakes within the Adirondack Park, New York State. Data were collected between June and October 2021 at five lakes. Four lake locations (Nearshore, Open Water, Layer, Bloom) were sampled representing one of four sample types (Bottom Sediment, Surface Water, Bloom Material, Layer). Water-quality field parameters (water temperature, dissolved-oxygen concentration and percent saturation, pH, specific conductance, turbidity, chlorophyll fluorescence, phycocyanin fluorescence, and fluorescent dissolved organic material) were measured at each sampling location from the surface to the...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Adirondack Park,
Algal concentration,
Blue Mountain Lake,
Blue-green algae,
Brant Lake,
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 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...
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...
Freshwater salinization is an emerging water quality issue for non-tidal streams and rivers in the Chesapeake Bay watershed (CBW), USA region. A model was developed to predict specific conductance (SC; a proxy for salinity) conditions across the CBW and departures from background SC. Discrete observations of SC from 1999-2016 were acquired from a published SC data inventory and explanatory variables describing sources of SC were compiled from several sources. Random forests modeling was conducted to predict SC at four time periods (1999-2001, 2004-2006, 2009-2011, and 2014-2016) at all non-tidal National Hydrography Dataset Plus Version 2.1 (NHDPlusV2.1; 1:100K scale) stream reaches. These predictions were then...
Categories: Data;
Tags: Chesapeake Bay watershed,
Delaware,
District of Columbia,
Ecology,
Geochemistry,
Geoheritage is a term which lies at the intersection of science, society, and sustainability and is applied to significant geologic features and landforms that have scientific, educational, cultural, economic, and aesthetic value. Many geologic sites have enriched society through the geoheritage values: scientific research and education, cultural significance, economic opportunities, and aesthetic appeal. The Geoheritage Sites of the Nation geodatabase (GDB) provides an initial inventory of geoheritage sites to showcase the geodiversity and natural heritage throughout the United States (U.S.) and its territories. Sites included in this inventory were selected from compiled geosite references of in situ geologic...
Coastal Mean High Water (MHW) is contoured in intertidal zones open to oceans, behind barrier coasts in bays, lagoons, and estuaries, and sometimes where tidal currents reach upstream (landward) of the embayed foreshore water bodies. In the National Geospatial Program (NGP), surface water hydrography is maintained in the National Hydrography Dataset (NHD) Flowline Network projects Mean High Water level (MHW) as the linear-referenced 1:24,000-scale resolution NHD Coastline (http://nhd.usgs.gov/). NHDCoastline Geomorphology and associated Risk line-event feature classes that rank the relative risk of horizontal erosion on a scale of 1 to 5 (least to most risk, respectively) have been developed using the Hydrography...
Categories: Data,
Data Release - In Progress;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Atlantic,
Connecticut,
Delaware,
Florida,
Geomorphology,
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 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 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 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...
Data for Modeling Interbasin Transfers of Water in Colorado and the Northeast Region, United States.
Data used to predict flow characteristics of transfers of water between hydrologic basins at the hydrologic unit code 8 (HUC8 scale) using tree-based ensemble models—random forest models for Colorado and M5 cubist models for the Northeast Region (parts of Pennsylvania, New Jersey, and New York)—are presented and documented in this data release. Interbasin transfers (IBTs) of waters are important components of water balances of basins and can have substantial impact on national and (or) regional water availability for a variety of human uses, such as public supply and irrigation. This data release contains all input files necessary to reproduce the results of the flow prediction models described in the associated...
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