https://doi.org/10.1029/2021EF002571

Basu, N.B., Dony, J., Van Meter, K.J., Johnston, S.J., Layton, A.T. (2023). A Random Forest in the Great Lakes: Stream Nutrient Concentrations across the Transboundary Great Lakes Basin. Earth's Future, 11(4), e2021EF002571 https://doi.org/10.1029/2021EF002571

Excess nutrient inputs from agricultural and urban sources have accelerated eutrophication and increased the incidence of algal blooms in the Great Lakes Basin (GLB). Lake basin management to address these threats relies on understanding the key drivers of pollution. Here, we use a random forest machine learning model to leverage information from 202 monitored streams in the GLB to predict seasonal and annual flow-weighted concentrations of nitrogen and phosphorus, as well as nutrient ratios across the GLB. Land use (agricultural and urban land) and land management (tile drainage and wetland density) emerge as the two most important predictors for dissolved inorganic nitrogen (DIN; NO3− + NO2−) and soluble reactive phosphorus (SRP; PO43), while soil type and wetland density are more important for particulate P (PP). Partial dependence plots demonstrate increasing nutrient concentrations with increasing tile density and decreasing wetland density. In addition, increasing tile and livestock densities and decreasing forest cover correspond to higher SRP:Total Phosphorus (TP) ratios. Seasonally, the highest proportions of SRP occur in summer and fall. Higher livestock densities are also correlated with increasing N:P (DIN:TP) ratios. Livestock operations can contribute to the buildup of soil nutrients from excess manure application, while increasing subsurface drainage can provide transport pathways for dissolved nutrients. Given that both SRP:TP and the N:P ratios are strong predictors of harmful algal blooms, our study highlights the importance of livestock management, drainage management, and wetland restoration in efforts to address eutrophication in intensively managed landscapes. Key Points -Random forest model, developed using data from 202 streams, identifies various land use and management controls on nutrients -High livestock densities correspond with greater proportions of bioavailable P and higher N:P ratios, and thus greater risk of blooms -The highest proportions of bioavailable P occur seasonally in summer and fall, and in the Lake Erie Basin

While attempts have been made to improve water quality and reduce algal blooms in the Great Lakes Basin, we still have a limited understanding of where the greatest inputs of nutrients to the lakes are coming come from and why. In the current study, we have used nitrogen and phosphorus concentration data from over 200 monitoring stations around the Great Lakes to model daily, seasonal, and annual concentrations and to link these concentration magnitudes to a variety of watershed characteristics. Our results show that land use and land management are important predictors of nitrogen and phosphorus concentrations, with tile drainage emerging as a key driver of higher nitrate and soluble phosphorus concentrations. For particulate phosphorus, however, our results show that soil type and wetland density are more important predictors. Higher tile drainage densities and livestock densities were found to be associated with higher N:P ratios and higher ratios of soluble to total phosphorus. We also found that concentrations of soluble reactive phosphorus are highest during the summer and fall months in watersheds dominated by agriculture, which is in contrast to seasonal patterns observed in less-impacted watersheds. Understanding watershed drivers of nutrient concentrations is critical for managing and improving water quality.

Lake Futures, Other

https://doi.org/10.1029/2021EF002571 The compiled data set used in this research is available through the CUAHSI Hydroshare site at https://doi.org/10.4211/hs.b94e2da3b5094cdfa679ad31fe7fb09d (N. B. Basu et al., 2021).