Advancing SWAT modeling with rainfall risk-based fertilizer timing to improve nutrient management and crop yields

In 2016, the United States and Canada agreed to reduce phosphorus inputs to Lake Erie by 40 % to reduce the severity of Harmful Algal Blooms (HABs). These blooms have become more severe, with record events occurring in 2011 and 2015, and have compromised public safety, leading to do-not-drink advisories and negatively impacting the economy of the Western Lake Erie basin. To determine the potential benefits of avoiding nutrient application during high rainfall events compared to dry periods, we analyzed scenarios using three Soil and Water Assessment Tool (SWAT) hydrological models developed for the Maumee River Watershed. These SWAT models were developed by three different institutes and calibrated for flow and nutrient loadings at the watershed outlet. The scenarios varied the timing of nutrient (fertilizer as well as manure) applications at the hydrological response unit (HRU; smallest unit of a model) level based on the risk of rainfall events and included a (1) worst-condition scenario, in which nutrients were applied just before rain events having a high-risk of runoff and a (2) best-condition scenario, in which nutrients were applied during periods carrying a low-risk of runoff. The results demonstrate that applying nutrients during low-risk rainfall events reduced nitrate runoff by 10.9 %, total phosphorus by 1.2 %, and dissolved reactive phosphorus by 3.8 % during the spring season compared to high-risk rainfall events. While, the nitrate, total phosphorus and dissolved reactive phosphorus reductions were 6 % 0.7 % and 2.6 %, respectively on the annual scale. Additionally, nutrient application during high-risk rainfall events led to a reduction in crop yields, with soybean yields decreasing by 4.4 %, corn and rye by 3 %, and winter wheat by up to 5.5 %. These findings underscore the importance of optimizing nutrient application timing to minimize nutrient runoff and enhance crop productivity, contributing to improved water quality in the Great Lakes region. • Novel framework to trigger fertilizer application timings using rainfall risk in SWAT. • Multi-model approach to assess nutrient runoff reductions in different risk scenarios. • Optimized fertilizer timing reduces nutrient loss, boosts crop yields across models.