Water Quality and Estimated Changes in the Plum Creek Watershed 2010-2020 (Data Release and Model Archive)

The U.S. Geological Survey and the University of Wisconsin – Green Bay collected hydrologic and water-quality data to assess the effectiveness of agricultural conservation management practice (CMP) implementation at Mainstem Plum Creek and West Plum Creek in northeastern Wisconsin. Monitoring data from 2010–2020 at Mainstem Plum and 2013–2020 at West Plum were used to detect changes in hydrologic and water-quality responses during runoff events. Runoff events were defined by hydrographers and used to compute event loads and event flow-weighted mean concentrations of total phosphorus and total suspended solids – all of which are included in this data release. Additionally, changes in these parameters were assessed between two time periods (“initial” and “post-CMP implementation”) using the R scripts included in this model archive. Because event discharges, loads, and concentrations are influenced by factors such as weather and the conditions preceding events, random-forest and regression models were developed to control for these factors and to elucidate water-quality changes more directly associated with CMP implementation. Residuals from random-forest models were used to detect changes between the two time periods via Wilcoxon signed-rank tests, and multiple linear regression models were used to determine percent change in responses via time-period dummy variable coefficients. Results indicate statistically insignificant changes in most responses during runoff events. This parent page serves as a landing page for two child items associated with Water Quality and Estimated Changes in the Plum Creek Watershed 2010-2020. Data release child page: contains the event times, event loads, and flow-weighted mean concentrations used for modeling purposes. Model archive child page: contains the inputs, scripts, and outputs used and produced to evaluate changes in water quality associated with conservation management practice implementation.

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  "geospatial"
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