Multi-Model Optimization of Field and In-Channel Management Actions in Agricultural Watersheds to Reduce Nitrate, Phosphorus, and Sediment Loads

Intensive agricultural practices in the Midwestern United States have enhanced crop production at the expense of water quality. Efforts to reduce adverse impacts of agriculture appear to have achieved some success at the field scale, but have not improved water quality at the outlet of many watersheds. Conventional approaches focus on managing primary inputs (nitrogen and phosphorus) to the landscape yet often neglect secondary processes of downstream processes of removal, transformation, or amplification that are indirectly impacted by land use. In this study, we evaluate the effectiveness of suites of field and channel management actions to reduce nitrate, phosphorus and sediment loads while minimizing cost. Aquatic and terrestrial biophysical processes were captured by integrating three watershed scale models including, a Soil and Water Assessment Tool watershed model, a data-driven sediment storage and delivery model, and a process-based nitrogen routing network model. The integrated multi-model allows us to account for key biophysical network processes (e.g. near-channel sediment generation, aquatic nitrate removal via denitrification) and features (e.g. bluffs, floodplains, fluvial wetlands) that can modify fluxes between the field and watershed outlet scales. Our analyses reveal which management options were most efficient for improving water quality and identify cost and configurations that meet the regional water quality target of 45% reduction in nitrate and phosphorus while considering effects on sediment. Despite distributed nutrient sources and complex hydrological drivers, our analyses identify locations within the watershed where concentrated management interventions are most effective. We summarize generalizable insights and emphasize the importance of considering channel network processes to effectively guide management of key pollutants in similar agricultural watersheds.