Flood Risk Projection Using a Hybrid Simulation Technique

Abstract. Future climate conditions project an increase in the frequency and severity of flooding in many regions of the world. Evaluation of candidate flood adaptation strategies must consider risk assessment methods that capture scenario-based loss and damage (L&D) for cost-benefit analysis. There is a need to develop tools that improve understanding of a region’s risk exposure while recognizing data and resource limitations available for this purpose. This study aims to address this gap by employing a novel approach that utilizes historic L&D data with an eye towards the current end-tail of extreme flood events as a prognosticator of what the future might hold. A hybrid Monte Carlo simulation technique is deployed to develop flood L&D projections under future climate change scenarios and used to estimate return periods of extreme flood events. Application of this methodology is illustrated in a case study using the Northeast region of the United States. The results show decreases in expected return periods of large flooding events, thereby expanding the geographic area of increased risk. These findings suggest this approach could function as a promising screening tool to help guide local flood adaptation planning, including the possibility of adopting this approach for other extreme weather events.