Date of Award


Degree Name

Master of Science


Civil Engineering

First Advisor

Kalra, Ajay


Hydrological extremes associated with climate change are becoming an increasing concern all over the world. Frequent flooding, one of the extremes, needs to be analyzed while considering climate change to mitigate flood risk. This study forecasted streamflow and evaluated the risk of flooding in the Neuse River, North Carolina considering future climatic scenarios, and comparing them with an existing Federal Emergency Management Agency (FEMA) flood insurance study (FIS) report. The cumulative distribution function transformation (CDF-t) method was adopted for bias correction to reduce the uncertainty present in the Coupled Model Intercomparison Project Phase 6 (CMIP6) streamflow data. To calculate 100-year and 500-year flood discharges, the Generalized Extreme Value (GEV) (L-Moment) was utilized on bias-corrected multimodel ensemble data with different climate projections. The delta change method was applied for the quantification of flows, utilizing the future 100-year peak flow and FEMA 100-year peak flows. Out of all projections, shared socio-economic pathways (SSP)5-8.5 exhibited the maximum design streamflow, which was routed through a hydraulic model, the Hydrological Engineering Center’s River Analysis System (HEC-RAS), to generate flood inundation and risk maps. The result indicates an increase in flood inundation extent compared to the existing study, depicting a higher flood hazard and risk in the future. This study highlights the importance of forecasting future flood risk and utilizing the projected climate data to obtain essential information to determine effective strategic plans for future floodplain management.




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