Quantitative evaluation of flood damage methodologies under a portfolio of adaptation scenarios

Flood risk is anticipated to increase, driven by climate change and socioeconomic development. Flood impact assessments rely heavily on models, and understanding the effects of uncertainties encompassed in the modelling chain is critical to adequately interpret flood risk and the development of effective flood adaptation measures. Previous research has focused on the effects of processes embedded in models, and flood frequency analysis of flood risk. However, no study has yet evaluated the cascading effects of flood damage assessment methodologies on uncertainty in the estimation of expected annual damage (EAD), optimal flood protection, and residual flood damage (RFD). Here, using an updated global river and inundation model forced by the latest climate data and employing a standard flood methodology, we found that global EAD will increase by $16.2 (USD throughout) and $44.5 billion yr−1 during 2020–2100 under low- and high-emissions scenarios, respectively. During the same period, despite the adoption of optimal levels of flood protections, global total RFD remained high under both low- and high-emissions scenarios, at $25.8 and $36.2 billion yr−1, respectively. Our results demonstrate that, under current levels of flood protection, EAD will approximately double with a switch in methodology. Aggregating data at the regional scale revealed conflicting trends between methodologies for developing and high-income countries, driven by existing levels of flood protection as well as the intensity, evolution, and distribution of gross domestic product at the administrative unit scale. Flood damage methodology is the dominant source of uncertainty, followed by unit construction cost and discount rate.