A multi-risk approach for projecting climate change-associated coastal flood, applied to India

This paper presents a methodology for estimating coastal flood and inundation risk using passive modeling in four coastal urban areas in India. The methodology has been developed by identifying the latest and publicly available datasets, open-source software, and easily adaptable methodology to estimate coastal flood risk: Mumbai, Chennai, Kochi, and Thiruvananthapuram. The highest projections of combined SLR, tide and surge levels from the GTSMip dataset was used for each of the study areas to model the flood risk for the period 2023–2027. The method has been successful in generating subsidence forecasts for regions where GNSS measurements are not available, resulting in better modeling of coastal flooding risk. Further, including land use as a dampening effect for flood water reduced the risk of overestimation while using bathtub models. The analysis showed that Mumbai had a significantly higher percentage of vulnerable regions than the other three cities. The method can be considered a first step in realistically estimating the coastal flood risks and providing valuable insights for policymakers.