Alfred Kalyanapu is an assistant professor in the Civil and Environmental Engineering Department at Tennessee Technological University (TTU) since 2011. At TTU, he leads the Tennessee Tech Water Resources Modeling and Simulation (TechWARMS) research group focusing on understanding water and its interaction with urban areas through modeling & simulations. He holds Ph.D. and M.S in Civil Engineering degrees from the University of Utah and B.Tech degree from the National Institute of Technology, Warangal, India. He has previously held graduate research assistantship at the Los Alamos National Laboratory. His research interests include: computational hydrology/hydraulics, numerical modeling and high-performance computing, flood risk management applications, sustainability-focused decision making and GIS applications in Civil and Environmental Engineering.
On average 196 million people in more than 90 countries are exposed to flooding each year, while in the United States (US) by 2005, flood damages increased to USD 6 billion per year, causing managing these risks crucial for future growth. Addressing this flood risk needs modeling and simulating rainfall-runoff processes and floods, but it is a challenging task due to many sources of uncertainties. Computer models have been used to simulate floods for more than four decades, typically modeled in a one-dimensional (1D) fashion due to computational restrictions and ease of use for most modeling applications. However, 1D approach has significant limitations for simulating floods especially in urban areas. These limitations can be overcome by using a two-dimensional (2D) approach for modeling floods, but this comes with significant computational cost. In addition to these computational challenges, uncertainties associated in data and model inputs. This presentation focuses on addressing current challenges and limitations in hydraulic and hydrologic modeling applications. Specifically, a fast 2D flood model named, Flood2D-GPU will be introduced. Using this model, a Monte Carlo probabilistic flood risk-modeling framework will be presented to demonstrate its application towards population at risk estimations and flood loss studies. In addition, studies performed on reducing uncertainties in DEMs, relative comparison of model structures on their performance, impact of precipitation on design flood estimations will be presented. The presentation will conclude with future 2D modeling application potential towards design of resilient flood control infrastructure.