Data Releases

This data release is the update of the U.S. Geological Survey - ScienceBase data release Bera (2020b), with the processed data for the period October 1, 2018, through September 30, 2019. This data release describes the watershed data management (WDM) database SC19.WDM. The precipitation data are collected from a tipping-bucket rain-gage network and the hydrologic data (stage and discharge) are col

This data release is the update of the U.S. Geological Survey (USGS) - ScienceBase data release Bera (2020b), with the processed data for the period October 1, 2018, through September 30, 2019. This data release describes the watershed data management (WDM) database file WBDR19.WDM. The WDM database file WBDR18.WDM (Bera, 2020b) is updated with the quality-assured and quality-controlled meteorolog

In August 2020, the U.S. Geologic Survey acquired high-precision survey data of first-floor doorway threshold elevations at buildings in the Lake Champlain floodplain in Vermont. For a representative sample of buildings within the 106 feet (National Geodetic Vertical Datum of 1929) stage boundary of the regional flood-inundation map (Flynn and Hayes, 2019), 153 buildings, or nearly 12 percent of t

Using previously published (Robinson and others, 2019) no-flow fractions and L-moments of nonzero streamflow from decadal streamflow flow-duration analysis (daily mean streamflow), probability distributions were fit to provide 27 estimated quantiles of decadal flow-duration curves, and hence the probability distributions are a form of parametric modeling that ensures monotonicity of the quantiles

Field data for fishes sampled using mid-water trawls, otter trawls, and the SmeltCam during day and night in San Pablo Bay, CA. This data release includes all measured environmental parameters and fish taxa included in the analysis.

Citation Note: These data were collected as part of a research study published in Marine and Petroleum Geology. Please reference the following paper when citing these data: Botterell, P.J., Houseknecht, D.W., Lillis, P.G, Barbanti, S.M., Dahl, J.E, and Moldowan, J.M., 2021. Geochemical advances in Arctic Alaska oil typing ? North Slope oil correlation and charge history. Marine and Petroleum Geo

Data were collected in August, 2020 to support development of a bathymetric map for Larimore Dam in Grand Forks County, North Dakota. Global Navigation Satellite System (GNSS) surveying equipment was used in static and real-time kinematic (RTK) mode to establish a local reference mark and check-in/check-out point, to collect water surface elevations, and to collect topographic points along establi

This data release includes four sets of gridded annual net infiltration (groundwater recharge) and irrigation water use data sets for the Mississippi Embayment Regional Aquifer System (MERAS).Also included are gridded water balance component data sets of precipitation, runoff, actual evapotranspiration, and soil-water storage for 2000 to 2018. The net infiltration, irrigation, runoff, actual evapo

Groundwater samples were collected from a South Florida Water Management District (SFWMD) monitoring well at the discharge point of the Kissimmee River into Lake Okeechobee between 2018 and 2019. The groundwater source was the Upper Floridan Aquifer at approximately 1,000 feet below land surface (fbls). Samples were dosed with nitrogen, phosphorus, and carbon, then sampled over a period of time to

This data set provides NCBI accession numbers for nucleotide sequence data derived from a mitochondrial DNA locus (control region) and double digest restriction-site associated DNA (ddRAD).

This dataset was used as part of a continent-wide analysis of tree fecundity and its association with climate and tree size. This dataset consists of: plotinfo.csv, which contains basic attribute information for the field plots where the data were collected; seeddata.csv, which contains the data for seeds collected (how many, what type, etc.); trapxycoord.csv, which contains location and identific

Ensemble-tree machine learning (ML) regression models can be prone to systematic bias: small values are overestimated and large values are underestimated. Additional bias can be introduced if the dependent variable is a transform of the original data. Six methods were evaluated for their ability to correct systematic and introduced bias: (1) empirical distribution matching (EDM); (2) regression of