Including climate change projections in probabilistic flood risk assessment

This paper demonstrates a framework for producing probabilistic flood risk estimates, focusing on two sections of the Rhine River. We used an ensemble of six (bias-corrected) regional climate model (RCM) future simulations to create a 3000-year time-series through resampling. This was complemented with 12 global climate model (GCM)-based future time-series, constructed by resampling observed time-series of daily precipitation and temperature and modifying these to represent future climate conditions using an advanced delta change approach. We used the resampled time-series as input in the hydrological model Hydrologiska Byrans Vattenbalansavdelning (HBV)-96 to simulate daily discharge and extreme discharge quantiles for return periods up to 3000 years. To convert extreme discharges to estimates of flood damage and risk, we coupled a simple inundation model with a damage model. We then fitted probability density functions (PDFs) for the RCM, GCM, and combined ensembles. The framework allows for the assessment of the probability distribution of flood risk under future climate scenario conditions. Because this paper represents a demonstration of a methodological framework, the absolute figures should not be used in decision making at this time.