Modeling Land Use and Climate Change Scenarios to Manage Water Quality in Integrated Agricultural-Urban Landscapes
PI: Whitney Pagan
The Chesapeake Bay, the largest estuary in the United States, faces significant water quality challenges due to non-point source pollution from urban and agricultural areas. Nutrient runoff, sediment, and other pollutants have degraded the bay’s ecosystem, prompting the U.S. Environmental Protection Agency (EPA) to establish the most extensive Total Maximum Daily Load (TMDL) in its history, targeting reductions in nitrogen, phosphorus, and sediment. As population growth and climate change intensify these pressures, innovative solutions are needed to manage competing land-use priorities sustainably.
This study leverages the Soil and Water Assessment Tool (SWAT) to simulate the impacts of land use and climate change scenarios on water quality in the Susquehanna River Basin, the largest tributary to the Chesapeake Bay watershed. Three scenarios—projected land use, projected climate, and their combined impacts—are modeled to evaluate the effectiveness of Best Management Practices (BMPs) in reducing runoff, sediment, nitrogen, and phosphorus loads. Agricultural BMPs include cover crops and buffer strips, while the urban BMPs include Low Impact Development (LID) strategies such as rain gardens and bioretention cells at a watershed scale.
Preliminary findings suggest that urban expansion will significantly increase phosphorus and sediment loads, while agricultural lands will continue to dominate nitrogen contributions. Climate change, with more frequent and intense storm events, poses additional challenges by reducing BMP effectiveness, particularly in urban areas. Despite these limitations, urban LID strategies show promise in mitigating pollution in highly developed areas, while agricultural BMPs remain critical for addressing watershed-scale nutrient loads.
This research provides actionable insights into BMP performance under future scenarios, highlighting the importance of integrating agricultural and urban management practices to achieve sustainable water quality improvements. Additionally, the study’s focus on the SRB serves as a model for understanding and managing water quality in integrated landscapes that balance the needs of agriculture, urban development, and ecosystem health.
A Comparative Study of Available Precipitation Products over Bangladesh
This project focuses on assessing the accuracy of popularly available open-source precipitation data products available for the Bangladesh region. The study aims to compare GPM, TRMM, CPC, ERA5, CHIRPS, IMDAA, and Aphrodite precipitation data against station observation data. My contributions to this study involve rainfall data processing and visualization and major contributions to the write-up, along with conceptual and technical support from Khan MD Golam Rabbani and Nazmul Ahasan at RIMES.