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Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Northeastern United States (2019) Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Northeastern United States (2019)
Tables are presented listing parameters used in logistic regression equations describing drought streamflow probabilities in the Northeastern United States. Streamflow daily data, streamflow monthly mean data, maximum likelihood logistic regression (MLLR) equation explanatory parameters, equation goodness of fit parameters, and Receiver Operating Characteristic (ROC) AUC values...
Shenandoah River Accumulated Wastewater Ratio Shenandoah River Accumulated Wastewater Ratio
De facto wastewater reuse from Waste Water Treatment Facilities (WWTF) has the potential to be a significant contributor of Endocrine Disrupting Chemicals. An ArcGIS model of WWTFs, NHDPlus Version 2 stream networks (USGS and EPA 2012), and gage stations across the Shenandoah River watershed was created to calculate accumulated wastewater ratio. Virginia Pollutant Discharge Elimination...
Basin Characteristics Rasters for West Virginia StreamStats 2021 Basin Characteristics Rasters for West Virginia StreamStats 2021
The U.S. Geological Survey (USGS) has calculated over 25 different basin characteristics as part of preparing the West Virginia StreamStats 2021 application. These datasets are raster representations of various environmental, geological, and land use attributes within the West Virginia StreamStats 2021 study area and will be served in the West Virginia StreamStats 2021 application to...
Inputs and Selected Predictions of a Differential Spatially Referenced Regression Model for 20-year Changes in Total Nitrogen in the Chesapeake Bay Watershed Inputs and Selected Predictions of a Differential Spatially Referenced Regression Model for 20-year Changes in Total Nitrogen in the Chesapeake Bay Watershed
The core equations of the SPARROW model (Schwarz and others, 2006) were implemented in differential form using the R programming language (R Core Team, 2017), as the basis of a tool for empirically relating a regional pattern of changes in constituent flux, over a multi-year period, to spatially referenced changes in explanatory variables over the same period. A pilot implementation was...
Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Delaware River Basin (2020) Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Delaware River Basin (2020)
Tables are presented listing parameters and fit statistics for 25,453 maximum likelihood logistic regression (MLLR) models describing hydrological drought probabilities at 324 gaged locations on rivers and streams in the Delaware River Basin (DRB). Data from previous months are used to estimate chance of hydrological drought during future summer months. Models containing 1 explanatory...
Nitrogen, phosphorus, and suspended-sediment loads and trends measured at the Chesapeake Bay Nontidal Network stations: Water years 1985-2018 (ver. 2.0, May 2020) Nitrogen, phosphorus, and suspended-sediment loads and trends measured at the Chesapeake Bay Nontidal Network stations: Water years 1985-2018 (ver. 2.0, May 2020)
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 Nontidal Network (NTN) stations for the period 1985 through 2018. Nutrient and suspended-sediment loads and changes in loads were determined by applying a weighted regression approach called WRTDS...