A human-centered modeling approach to simulate best management practices and behaviors under uncertainty to meet water quality guidelines

When people interact with their environment, they often induce harm to the water. Total Maximum Daily Load (TMDL) is a vital method for undertaking water quality issues. It sets limits on how much pollution a water body, like a river, can handle each day. Water quality best management practices (BMPs) are a popular method to prevent pollutants from entering the water bodies and to achieve the goals set by TMDL. This action usually requires cooperation among different experts, data sharing, and engaged stakeholder involvement. This NSF project aims to improve our understanding of how to manage water quality better at different spatial scales. Three theories regarding human-environment interactions will lay the groundwork for our analyses. This project combines modeling, data analysis, and surveys to study farmers’ BMP implementation decisions at different spatial scales. The project is structured around three research tasks (RTs). RT1 engages stakeholders and experts in the project advisory board via regular meetings. The research team interviews and surveys local farmers to evaluate factors influencing the implementation of BMPs in the study area. RT2 involves the development of a two-way coupled agent-based water quality model, in which farmers are agents. The model simulates the agents’ decisions and implementation of BMP using the Bayesian inference method based on socio-psychological theories. RT3 uses numerical experiments to evaluate the effect of future climate and socioeconomic scenarios and human behavior uncertainty on TMDL targets. These scenarios are co-developed with the project advisory board and disseminated in the project wrap-up workshop. This collaborative project with real-world practitioners in the Chesapeake Bay produces and shares results to inform the Scientific and Technical Advisory Committee of the Chesapeake Bay Program. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.