A framework for assessing the impact of climate change on rainfall extremes and urban flooding using GIS based SCS-CN and HEC-RAS model

Due to global warming, the frequency of extreme rainfall events in Bangladesh has been increasing causing urban flooding, leading to loss of life and damage to living environment. To address these issues, this study proposed a comprehensive framework that integrated Global Climate Model (GCM), GIS-based SCS-CN approach, and HEC-RAS model. The Balu River catchment area was selected as the study area. Historical rainfall data from 1980 to 2023 were obtained from Bangladesh Meteorological Department (BMD). Frequency analysis of extreme rainfall was conducted using the Gumbel Extreme Value Type-I distribution. For future projections, outputs from 10 CMIP6 GCMs were utilized. Changes in annual maximum daily precipitation were assessed using the Multi-Model Ensemble (MME) mean under two Shared Socioeconomic Pathways (SSP2–4.5 and SSP5–8.5) for three future periods: near future (2015–2044), mid future (2045–2074), and far future (2075–2100). Runoff and peak discharge were estimated using GIS-based SCS-CN method alongside the HEC-HMS model. Results indicate that under SSP2–4.5 and SSP5–8.5, the extreme rainfall will be increased by 13.39% and 18.60% in near future, by 24.09% and 33.94% in mid future, and by 27.51% and 74.32% in far future. Correspondingly, peak discharge is expected to rise by 19.20% and 26.77% in near future, by 34.74% and 49.23% in mid future, and by 39.71% and 109.68% in the far future under the same scenarios. The HEC-RAS model will be used to estimate the spatial extent of increased flooding resulting from these projected changes.