Data

fishStan is an R package (R Core Team 2020) providing a collection of hierarchical Bayesian models written in the Stan language as called through RStan (Stan Development Team 2020). The package is a USGS software software release. The purpose of the package is to document these models for use in USGS projects and allow easy discrimination. The package assumes the user is familiar with R...

The Best Management Practices Statistical Estimator (BMPSE) was developed by the U.S. Geological Survey (USGS), in cooperation with the Federal Highway Administration (FHWA) Office of Project Delivery and Environmental Review to provide planning-level information about the performance of structural best management practices for decision makers, planners, and highway engineers to assess...

This data release documents statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM)(Granato, 2013). The U.S. Geological Survey (USGS) developed SELDM and the statistics documented in this report in cooperation with the Federal Highway Administration (FHWA) to indicate the risk for stormwater...

This digital dataset contains geochemical and other information for 1,209 samples of groundwater from 343 wells located within 3-miles of the Buena Vista, Elk Hills, Midway-Sunset, and North and South Coles Levee oil fields in the southwestern San Joaquin Valley of central California. Data were compiled by the U.S. Geological Survey (USGS) from preexisting datasets and transferred...

The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the...

Nitrogen, phosphorus, and suspended-sediment loads, and changes in loads, in major rivers across the Chesapeake Bay watershed have been calculated using monitoring data from the Chesapeake Bay River Input Monitoring (RIM) stations for the period 1985 through 2019. Nutrient and suspended-sediment loads and changes in loads were determined by applying a weighted regression approach called...