Data

This metadata record describes model outputs and supporting model code for the Data-Driven Drought Prediction project of the Water Resources Mission Area Drought Program. The data listed here include outputs of multiple machine learning model types for predicting hydrological drought at select locations within the conterminous United States. The child items referenced below correspond to different

This data is comprised of representative chloride values Seneca and Cayuga Lakes and their tributaries from many sources.

This USGS data release includes data from experiments conducted with two species of caddisflies (Hydropsyche californica and Arctopsyche grandis (Order: Trichoptera) to quantify copper and cadmium uptake and loss after dissolved and dietary exposures. Both Arctopsyche and Hydropsyche belong to the family Hydropsychidae (O: Trichoptera). They are relatively sessile, net-spinning filter feeders. Dat

Electromagnetic (EM) geophysical methods provide information about the bulk electrical conductivity of the subsurface. EM data has been widely used to investigate aquifers and geologic structures. In the following study, the United States Geological Survey conducted a boat-towed, waterborne transient electromagnetic (FloaTEM) survey to examine conductivity within the subsurface of the main Delawar

The U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board collected produced water samples for analysis of volatile organic compounds (VOCs) in the eight California oil fields of Fruitvale, Lost Hills, North Belridge, Orcutt, Placerita, South Belridge, Midway-Sunset, and Buena Vista from 2016 to 2020. Sampled sites included oil wells; injectate from t

This metadata record describes the observed and estimated hydrologic metrics for the 1980 to 2019 period for U.S. Geological Survey streamgage locations across the Conterminous United States. The datasets are arranged in four files: (1) CONUS_Observed_Estimated_HMs_Annual_Monthly.csv, (2) CONUS_Bootstrap_Validations_for_Models.csv, (3) CONUS_Streamflow_Gages_for_Models.csv, and (4) Data_Dictionary

This metadata record describes observed and predicted baseflow recession characteristics for 300 streamflow gauges in the western United States and 282 streamflow gauges in the eastern United States. Specifically, this record describes (1) the streamflow gauge locations (west or east) in the United States (Location), (2) the U.S. Geological Survey streamflow gauge identification numbers (USGS_Site

This data release has the results of 333 online survey respondents representing 17 federal agencies and 7 Executive Branch departments from March 14 through April 14, 2022 regarding The Federal Priority Streamgage (FPS) network of the U.S. Geological Survey (USGS). The FPS network was created in 1999 as the National Streamflow Information Program and receives congressionally appropriated funding t

This data release and model archive provides all data, code, and modelling results used in Topp et al. (2023) to examine the influence of deep learning architecture on generalizability when predicting stream temperature in the Delaware River Basin (DRB). Briefly, we modeled stream temperature in the DRB using two spatially and temporally aware process guided deep learning models (a recurrent graph

The Sacramento / San Joaquin River Delta (SSJRD) is contaminated with legacy mercury (Hg) from historical mining and mineral processing activities throughout the watershed, as well as from contemporary atmospheric and industrial inputs. The current project was designed for the purpose of developing high-resolution spatial and temporal models for estimating concentrations of mercury species in surf

Human factors that influence water availability in the Basin were discovered by reviewing hundreds of published literature items and articles from the literature following an extensive keyword search. The different factors were drawn from reviewing the literature, and datasets to support the factor were researched across open data catalogs and the world wide web. Data related to the Human Factors