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Regression tree datasets used to identify trophic states in Tennessee reservoirs

December 22, 2021

This dataset was developed in partnership with the Tennessee Department of Environmental Conservation to determine the susceptibility of selected Tennessee reservoirs to eutrophication and potential harmful algal blooms. A R script, based on recursive partitioning and the model-based boosting routine, was used to generate regression trees that grouped Tennessee reservoirs into five endpoints along individual low-to-high gradients of Secchi depth and chlorophyll a concentrations (Green, et al, 2021; Heal and Green, 2021). Input data for these reservoirs were obtained from SPAtially Referenced Regression On Watershed (SPARROW) attributes models that estimate total phosphorus and total nitrogen loads in Tennessee water bodies (Roland II, 2019).

References:

Green, W. Reed, Hoos, Anne B., Wilson, Alan E., and Heal, Elizabeth N., 2021, Development of a screening tool to examine lake and reservoir susceptibility to eutrophication in selected watersheds of the eastern and southeastern United States: U.S. Geological Survey Scientific Investigations Report, https://doi.org/...

Heal, E.N., and Green, W.R., 2021, Nutrient loading, flushing rate, and lake morphometry data used to identify trophic states in selected watersheds of the eastern and southeastern United States: U.S. Geological Survey data release, https://doi.org/10.5066/P9K7EOH0.

Roland II, V.L., 2019, Data used in the creation of total phosphorus and total nitrogen SPARROW models for the state of Tennessee (ver. 1.1, February 2020): U.S. Geological Survey data release, https://doi.org/10.5066/P96RWGU0.

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