Analysing Urban Flooding Risk with CMIP5 and CMIP6 Climate Projections
2024
Rafiu Oyelakin | Wenyu Yang | Peter Krebs
Fitting probability distribution functions to observed data is the standard way to compute future design floods, but may not accurately reflect the projected future pattern of extreme events related to climate change. In applying the latest coupled model intercomparison project (CMIP5 and CMIP6), this research investigates how likely it is that precipitation changes in CMIP5 and CMIP6 will affect both the magnitude and frequency of flood analysis. GCM output from four modelling institutes in CMIP5, with representative pathway concentration (RCP8.5) and the corresponding CMIP6 shared socioeconomic pathways (SSP585), were selected for historical and future periods, before the project precipitation was statistically downscaled for selected cities by using delta, quantile mapping (QM), and empirical quantile mapping (EQM). On the basis of performance evaluation, a rainfall-runoff hydrological model was developed by using the stormwater management model (SWMM) for CMIPs (CMIP5 and CMIP6) in historical and future horizons. The results reveal an unprecedented increase in extreme events, for both CMIP5 (historical) and CMIP6 (future) projections. The years 2070&ndash:2080 were identified by both CMIP5 and CMIP6 as experiencing the most severe flooding.
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