Filters: Types: Citation (X) > Types: OGC WFS Layer (X) > partyWithName: U.S. Geological Survey (X) > partyWithName: Office of Planning and Programming (X)
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In 2013, the U.S. Geological Survey and the U.S. Environmental Protection Agency characterized water-quality stressors and ecological conditions in 100 wadeable streams across the Midwestern United States. The goal of the study was to determine the relative effects of multiple ecological stressors – contaminants, nutrients, sediment, and habitat – on ecological communities in the streams. The Midwest is an intensely agricultural region where pesticides in streams pose risks to aquatic biota, but temporal variability in pesticide concentrations makes characterization of their exposure to organisms challenging. To compensate for the effects of temporal variability, we deployed polar organic chemical integrative samplers...
Categories: Data;
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Illinois,
Indiana,
Iowa,
Kansas,
Minnestoa,
Widespread nitrate contamination of groundwater in agricultural areas poses a major challenge to sustainable water resources. Efficient analysis of nitrate fluxes across large regions also remains difficult. This study introduces a method of characterizing nitrate transport processes continuously across regional unsaturated zones and groundwater based on surrogate, machine-learning metamodels of an N flux process-based model. The metamodels used boosted regression trees (BRTs) to relate mappable variables to parameters and outputs of a “vertical flux method” (VFM) applied in the Fox-Wolf-Peshtigo (FWP) area in Wisconsin. In this context, the metamodels are upscaling the VFM results throughout the region, and the...
The ascii grids represent regional probabilities that groundwater in a particular location will have dissolved oxygen (DO) concentrations less than selected threshold values representing anoxic groundwater conditions or will have dissolved manganese (Mn) concentrations greater than selected threshold values representing secondary drinking water-quality contaminant levels (SMCL) and health-based screening levels (HBSL) for water quality. The probability models were constrained by the alluvial boundary of the Central Valley to a depth of approximately 300 meters (m). We utilized prediction modeling methods, specifically boosted regression trees (BRT) with a Bernoulli error distribution within a statistical learning...
Categories: Publication;
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Boosted Regression Trees,
California,
Central Valley, California,
Domestic Well Water Use,
Drinking Water Use,
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