Data

The purpose of this data release is to provide the original data, analysis methods, and nitrogen loading models in support of a study of the upper South Platte River annual total nitrogen loads attributed to atmospheric deposition of reactive nitrogen during 2017-2018. The data release includes water-quality and stream discharge data and associated predictive regression models used in the estimat

This data release is associated with a journal article titled, "Aquatic-Terrestrial Linkages Control Metabolism and Carbon Dynamics in a Mid-sized, Urban Stream Influenced by Snowmelt." The data were collected adjacent to USGS stream gage 06730200 and include observed and modeled values. Dissolved oxygen, dissolved carbon dioxide, stream depth, water temperature, and light intensity were collected

A three-dimensional groundwater-flow model of a 73.2 square mile area in southeastern Albuquerque, New Mexico was designed and coupled to a regional (parent) model of the Middle Rio Grande Basin with the local-grid refinement numerical code MODFLOW-LGR2. This fine-gridded local (child) model was designed to simulate the response of the aquifer to pumping stresses and simulate advective groundwat

Surface water, pore water, pond bottom sediments, and groundwater were sampled within and downgradient from five groundwater flow-through ponds that ranged from oligotrophic to eutrophic in Cape Cod, Massachusetts during different seasons from 2015 – 2018. The sampled ponds included Ashumet, Santuit, Snake, Shubael, and Longs. Pore water was collected between 15 to 100 cm below the pond bottoms on

The Tenaya Lake Water Budget Study seeks to quantify and understand the water balance within the principal snow accumulation and runoff yielding zone in the Sierra Nevada Mountains. The Study operates stage sensors and data loggers to record Tenaya Lake inflows, water surface elevation, and outflow, with continuous annual data collection for the 21 square-kilometer watershed located in the alpine

This dataset consists of a series of 1-kilometer rasters which provide a mapping of the estimated use of 101 agricultural pesticide compounds for the conterminous United States. Each compound is mapped annually for the years 2013 through 2017, thus there are 505 rasters posted (101 compounds x 5 years). The datasets were created by taking previously-published county-level estimates of kilograms of

This product consists of pesticide detections and benchmark exceedances in surface waters. These are time series data representing water years 2013 - 2017 for river sites associated with the U.S. Geological Survey National Water Quality Pesticide Monitoring Program.

This dataset contains passive seismic data collected using a three-component seismometer during 2018-2020 at Pinnacles National Park, California. The data were acquired for the purpose of estimating depth to the bedrock surface underlying alluvial deposits, using the horizontal-to-vertical spectral ratio (HVSR) technique. Data were collected along ten transects, with 3 to 14 points collected along

This data release includes a video acquired from a satellite and field measurements of flow velocity from the Tanana River in Alaska that were used to derive remotely sensed estimates of surface flow velocities via particle image velocimetry (PIV). The field data were collected on July 24, 2019, in cooperation with the USGS Alaska Science Center, and the satellite video was obtained on July 14, 2

Santa Rosa Island, part of Channel Islands National Park off the coast of California, has a undergone a history of ecologic degradation due to introduced ungulate grazing for ranching (cattle and sheep) and hunting (deer and elk) purposes. Grazing in many parts of the island has resulted in widespread vegetation loss and subsequent erosion presumably causing changes in infiltration/runoff relation

Phytoplankton is an important and limiting food source in the Sacramento-San Joaquin Delta and San Francisco Bay; the decline of phytoplankton biomass is one possible factor in the pelagic organism decline and specifically in the decline of the protected delta smelt. The bivalves Corbicula fluminea and Potamocorbula amurensis (hereafter Corbicula and Potamocorbula, respectively) have been shown to

This data release provides all data and code used in Rahmani et al. (2020) to model stream temperature and assess results. Briefly, we used a subset of the USGS GAGES-II dataset as a test case for temperature prediction using deep learning methods. The associated manuscript explores the value of including stream discharge as a predictor in the temperature models, including the value of predicted d