Filters: partyWithName: William H Farmer (X) > partyWithName: Water Resources (X) > Types: OGC WMS Service (X)

Filters Date Range Past year (0) Past month (0) Past week (0) Past day (0) Custom range... To   Search Types Citation (2) Map Service (2) OGC WFS Layer (2) OGC WMS Layer (2) Contacts Jennifer C Murphy Scott C Worland Lower Mississippi-Gulf Water Science Center Julie E Kiang Lower Mississippi-Gulf Water Science Center More... Categories Data (2) Tag Types Place (2) Theme (2) Harvest Set (2) USGS Scientific Topic Keyword (1) Tag Schemes None (1) USGS Thesaurus (2) Geographic Names Information System (GNIS) (1) Common geographic areas (1) ISO 19115 Topic Category (1) View Results as: JSON ATOM CSV

Water-quality trends and trend component estimates for the Nation's rivers and streams using Weighted Regressions on Time, Discharge, and Season (WRTDS) models and generalized flow normalization, 1972-2012 Nonstationary streamflow due to environmental and human-induced causes can affect water quality over time, yet these effects are poorly accounted for in water-quality trend models. This data release provides instream water-quality trends and estimates of two components of change, for sites across the Nation previously presented in Oelsner et al. (2017). We used previously calibrated Weighted Regressions on Time, Discharge, and Season (WRTDS) models published in De Cicco et al. (2017) to estimate instream water-quality trends and associated uncertainties with the generalized flow normalization procedure available in EGRET version 3.0 (Hirsch et al., 2018a) and EGRETci version 2.0 (Hirsch et al., 2018b). The procedure... Categories: Data; Types: Citation, Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Contiguous United States and Puerto Rico, USGS Science Data Catalog (SDC), United States, biota, carbon, All tags... concentration, loads (fluxes), major ions, nutrients, rivers, salinity, sediment, streams, surface water quality, water-quality trends, Fewer tags 7Q10 records and basin characteristics for 224 basins in South Carolina, Georgia, and Alabama (2015) This data release provides the data and R scripts used for the 2018 publication titled "Improving predictions of hydrological low-flow indices in ungaged basins using machine learning", Environmental Modeling and Software, https://doi.org/10.1016/j.envsoft.2017.12.021.. There are two .csv files and 14 R-scripts included below. The lowflow_sc_ga_al_gagesII_2015.csv datafile contains the annual minimum seven-day mean streamflow with an annual exceedance probability of 90% (7Q10) for 224 basins in South Carolina, Georgia, and Alabama. The datafile also contains 231 basin characteristics from the Gages II dataset (https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011). The "all_preds.csv" file contains the leave-one-out... Categories: Data; Types: Citation, Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Alabama, Georgia, Hydrogeology, South Carolina, USGS Science Data Catalog (SDC), All tags... Water Resources, low-flow, machine learning, regionalization, statistical modeling, streamflow, Fewer tags