A data-driven approach to evaluate and inform the effectiveness of agricultural Best Management Practices (BMPs)
Abstract
Agricultural runoff continues to be a leading cause of water quality degradation in the Susquehanna River Basin, the largest contributor of nutrients and sediment to the Chesapeake Bay. Despite widespread promotion of Best Management Practices (BMPs), decision-makers lack field-based data to evaluate their real-world effectiveness.
This project addresses that critical gap by conducting a field-and model-based evaluation of BMP performance in small agricultural watersheds in Centre County, Pennsylvania. By grounding our study at this scale, we aim to capture site-level variability and generate empirical insights that can be scaled to support regional conservation strategies. The project will monitor water quality before and after implementation of few selected farm BMPs using weekly stream sampling and high-frequency sensors deployed at selected farm sites.
The collected data—including nutrient and sediment concentrations and flow estimates—will be used to quantify contaminant load reductions and calibrate an ecohydrological model. This model will simulate BMP impacts across various implementation scenarios to support conservation planning and targeted watershed management.
Concurrently, interviews and focus groups with landowners and conservation professionals will assess BMP adoption barriers, communication needs, and data feedback preferences.
We will apply an existing pay-for performance (P4P) incentive framework to estimate potential farmer compensation based on observed environmental benefits of BMPs. Results will be shared through individualized landowner reports, field demonstrations, stakeholder workshops, and Extension-led webinars. An anonymized, curated dataset will be made publicly available to inform broader Chesapeake Bay watershed goals.
By integrating empirical monitoring, stakeholder engagement, and incentive modeling, this project will provide actionable insights to improve BMP targeting, strengthen trust in science-driven watershed management, and advance Sea Grant’s mission to support water resources management.
