Data

In crude-oil-contaminant plumes the dissolved organic carbon (DOC) is mainly hydrocarbon degradation intermediates only partly quantified by the diesel range total petroleum hydrocarbon (TPHd) method. To understand potential biological effects of degradation intermediates we tested three fractions of DOC: (1) solid phase extract (HLB); (2) dichloromethane (DCM-total) extract used in TPHd; and (3)

The Bemidji crude oil spill site is a long-term USGS study site to understand the fate of crude oil in the shallow subsurface. A description of the site can be found at https://mn.water.usgs.gov/projects/bemidji. In 2014 concentrations of non-volatile dissolved organic carbon (NVDOC) were three times higher than diesel range organics (DRO) in the contaminant plume*. This is important because most

This data release includes digital orthophotos acquired from a fixed-wing aircraft and field measurements of flow velocity from the Tanana and Nenana Rivers near Nenana, Alaska, obtained on August 18 and 19, 2021.  This parent data release includes links to child pages for two data sets produced during the study: 1. Acoustic Doppler Current Profiler (ADCP) field measurements of flow velocity from

This dataset contains files used in this Monte Carlo simulation study comparing the performance of five statistical models for adjusting design floods for current conditions at sites with known trends. These files include (i) the observed annual peak-flow series in the conterminous US used to inform ranges of known moments and trends used in the simulation experiment, (ii) the 3,000 combinations o

These data are preliminary or provisional and are subject to revision. They are being provided to meet the need for timely best science. The data have not received final approval by the U.S. Geological Survey (USGS) and are provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the data.

Daily lake surface temperatures estimates for 185,549 lakes across the contiguous United States from 1980 to 2020 generated using an entity-aware long short-term memory deep learning model. In-situ measurements used for model training and evaluation are from 12,227 lakes and are included as well as daily meteorological conditions and lake properties. Median per-lake estimated error found through c

This item contains data and code used in experiments that produced the results for Sadler et. al (2022) (see below for full reference). We ran five experiments for the analysis, Experiment A, Experiment B, Experiment C, Experiment D, and Experiment AuxIn. Experiment A tested multi-task learning for predicting streamflow with 25 years of training data and using a different model for each of 101 sit

The US Geological Survey (USGS) conducted a study (Carlisle and others 2017) with a national-scale dataset composed of ecological data from the USGS National Water-Quality Assessment Project and the US Environmental Protection Agency, matched to USGS streamgaging sites. In a follow-up study (Carlisle and others 2019), additional data from three regional assessments conducted by USGS were combined

Empirical models described in previous publications were developed and applied to estimate the probability of streamflow modification for every stream segment in the conterminous United States from 1980-2015. This metadata record documents 6 comma separated tables populated with predictions of streamflow modification (please see the Supplemental Element for citations or please refer to the cross-r

Benthic diatom assemblages are known to be indicative of water quality but have yet to be widely adopted in biological assessments in the United States due to several limitations. Our goal was to address some of these limitations by developing regional multi-metric indices (MMIs) that are robust to inter-laboratory taxonomic inconsistency, adjusted for natural covariates, and sensitive to a wide r

The hydrologic modeling approach used to predict functional flows relies on daily streamflow data from gages operated by the U.S. Geological Survey (USGS) in California. This dataset contains, for each of 219 gages, a collection of metrics computed on each water year for the period of record to and including Water Year 2016.

This dataset is a collection of 12 rasters depicting geochemical and geophysical characteristics of surface or near surface geology. These rasters were created to quantify the influence of geology on surface and critical zone processes like stream water chemistry, soil formation, ecologic processes, and species distributions by providing estimates of spatial variability in current geochemical and