Associate Professor Youngstown State University, Ohio, United States
Flooding due to extreme rain events has been a major concern across the world due to the significant loss of lives and property. Floodplain inundation mapping is crucial to quantify the impacts of such flood events. This study is conducted to generate flood inundation mapping for the existing and future climatic conditions using the Coupled Model Intercomparison Project Phase 5 (CMIP5) and Coupled Model Intercomparison Project Phase (CMIP6) climate models, for the Chagrin River and Grand River basin located in Northeast Ohio. The hydrological model (HEC-HMS) was calibrated over four years using Daymet gridded precipitation data referred to as Daily Surface Weather and Climatological Summaries and United States Geological Services (USGS) streamflow data. The hydraulic model (HEC-RAS) was developed with USGS LiDAR data, Federal Emergency Management Agency (FEMA) data, and field-verified cross-sections. Recorded streamflow data from a USGS station and gauge data from Hyfi stations were used as boundary conditions for the HEC-RAS model. The models performed consistently better both in the calibration and validation phases, which were evaluated using various statistical measures, such as Nash-Sutcliffe Efficiency (NSE) and Percent Bias (PBIAS). The values of NSE were greater than 0.67, and PBIAS values were less than 10% for HEC-HMS model. Similarly, NSE were greater than 0.70, and PBIAS values were less than 3% for both HEC-RAS 1D and 2D model. In the next step, the coupled HEC-HMS and HEC-RAS models were used to investigate flood inundation at various ranges of historical and future precipitation for both Grand and Chagrin River watersheds to analyze regional flooding patterns in Northeast Ohio. The preliminary results indicate an increase in flood inundation area of nearly 28% in the near future and approximately 40% in the far future compared to the baseline period for the River Basin.
