Abstract: Floods are the most common and costliest natural hazard in the United States (USA) and world. As climate change progresses, the rising frequency and intensity of storms raise concerns about their negative impact on surface water quality dynamics. However, the complex relationships between flooding, watershed characteristics, and surface water quality are not fully understood. To enhance our understanding of flood dynamics and floodwater contamination, this study investigated spatiotemporal patterns of flood extent and pathogen presence, and identified the watershed characteristics that best explain water quality signatures in floodwaters.

Bio: Dr. Fidan is an Assistant Professor of Ecological Systems Engineering at the University of Tennessee exploring the complex dynamics of our environment using data analytics and modeling approaches. In recent years, data-driven methods, such as machine learning, have gained momentum in the life sciences due to their ability to capture non-linear environmental dynamics with low computational cost. Dr. Fidan will present different projects that leverage data-driven modeling to answer questions regarding how human actions influence ecosystem health and downstream water resources, and future research ideas in collaboration with UTK colleagues.