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Filters: Contacts: {oldPartyId:11375} (X) > partyWithName: U.S. Geological Survey - ScienceBase (X) > partyWithName: Susan Wherry (X)

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This data release contains the model inputs, outputs, and source code (written in R) for the boosted regression tree (BRT) and artificial neural network (ANN) models developed for four sites in Upper Klamath Lake which were used to simulate daily maximum pH and daily minimum dissolved oxygen (DO) from May 18th to October 4th in 2005-12 and 2015-19 at four sites, and to evaluate variable effects and their importance. Simulations were not developed for 2013 and 2014 due to a large amount of missing meteorological data. The sites included: 1) Williamson River (WMR), which was located in the northern portion of the lake near the mouth of the Williamson River and had a depth between 0.7 and 2.9 meters; 2) Rattlesnake...
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The tabular data sets and associated maps in this data release represent water-quality data that were collected between April and November of 2017 and between July and November of 2019 to describe baseline conditions prior to or sometimes following treatments using herbicides or other methods to reduce the biomass of non-native water primrose (Ludwigia) within off-channel water bodies of the Willamette River near Albany and Keizer, Oregon. The water-quality parameters measured in this study included water temperature, specific conductance, pH, dissolved oxygen, turbidity, total chlorophyll, phycocyanin (blue-green algae pigment), and fluorescing dissolved organic matter in surface water.
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This data release contains a boosted regression tree (BRT) model (written in the R programming language), and the input and output data from that model that were used to relate base flow nitrate concentrations in the Chesapeake Bay watershed to catchment characteristics. The input data consists of two types of information: 1) surface water nitrate concentrations collected by the USGS and partnering agencies in the Chesapeake Bay watershed between 1970 and 2013 and 2) potential predictor variables that included nitrogen sources, catchment characteristics, soil and groundwater chemistry, soil drainage and composition, and aquifer geology. The results from the BRT model were used to identify ten significant predictors...


    map background search result map search result map Water quality measurements in off-channel water bodies of the Willamette River near Albany and Keizer, OR (2017 and 2019) Input and results from a boosted regression tree (BRT) model relating base flow nitrate concentrations in the Chesapeake Bay watershed to catchment characteristics (1970-2013) Input and results from boosted regression tree and artificial neural network models that predict daily maximum pH and daily minimum dissolved oxygen in Upper Klamath Lake, 2005-2019 Water quality measurements in off-channel water bodies of the Willamette River near Albany and Keizer, OR (2017 and 2019) Input and results from boosted regression tree and artificial neural network models that predict daily maximum pH and daily minimum dissolved oxygen in Upper Klamath Lake, 2005-2019 Input and results from a boosted regression tree (BRT) model relating base flow nitrate concentrations in the Chesapeake Bay watershed to catchment characteristics (1970-2013)