The economic impacts of Climate Change to flood risk across the Central Asia Regional Economic Cooperation (CAREC)

This case study documents the application of multi-RCM derived Intensity-Duration-Frequency (IDF) curves to assess the changing nature of probabilistic flood risk in the CAREC region at future time horizons.

In this study, multi-model precipitation extremes under RCP4.5 and RCP8.5 at future climate horizons (e.g. 2040s and 2070s) are used to derive alternative views of flood risk and damage potential across the eleven countries (Afghanistan, Azerbaijan, China (Inner Mongolia Autonomous Region; Xinjiang Uyghur Autonomous Region), Georgia, Kazakhstan, Kyrgyz Republic, Mongolia, Pakistan, Tajikistan, Turkmenistan and Uzbekistan) within the Central Asia Regional Economic Cooperation (CAREC).

Multiple regional climate model (RCM) daily precipitation data from the Coordinated Regional Climate Downscaling Experiment (CORDEX) are first bias corrected through non-parametric quantile mapping. Quantile mapping is an approach used to reduce systematic biases in RCM precipitation, particularly extremes, by adjusting the historical modeled precipitation distributions against observations and carrying the transformation forward to adjust future projections. The bias-corrected projections are used to derive sub-country level Intensity-Duration-Frequency (IDF) curves before being combined with a 10,000 year stochastic simulation of river and surface water flood event set to derive change factors in baseline hydrology for river gauges and gridded precipitation points across Central Asia. These change factors have been used to create a series of alternative stochastic flood event sets for the various time horizons and emission scenarios, which in turn, are then analysed against the GED4ALL economic exposure data and a detailed taxonomy of fragility curves to assess the economic impact of climate change in all CAREC countries. The study captures the complex and non-linear relationship between climate change and flood risk across a diverse continent. In turn, focus is given to how these findings may affect key global planning horizons with regard to disaster risk financing and sustainable development.