A Monitoring and Modeling Approach to Quantifying the Effectiveness of Best Management Practices in a Small Agricultural Watershed

Abstract

Conventional agricultural practices produce nonpoint source water pollution. The implementation of Best Management Practices (BMPs) in a watershed plays a vital role in improving water quality. Assessing the effectiveness of BMPs requires both monitoring and modelling. A nonpoint source management water policy change was introduced in Minnesota to monitor and model small watersheds for 16 years to determine the effectiveness of BMPs. Monitoring small watersheds alone has not shown water quality improvement; there has been a lack of observable improvement in water quality due to the fragmentation of landscape BMPs and lag time. Dobbins Creek was selected as a sentinel watershed to track water quality for a period longer than a few years to account for lag time. Dobbins Creek is a small agricultural watershed located in the headwaters of the Cedar River. This is an important large watershed that contributes to Gulf of Mexico hypoxia. A monitoring and modelling program were implemented in 2016 that included the analysis of sediment and nutrients at strategic locations in the watershed. We demonstrate how to show an exceedance of water quality standards primarily during stormflow before major BMP implementation. Over time we anticipate water quality changes with land use changes and financial incentives, but the proper approach must be designed and financially supported to be truly effective