Mitigating coastal flood risks in the Sundarbans: A combined InVEST and machine learning approach

Abstract

Adjacent marine, terrestrial, and climatic systems and their dynamic interactions impact the complex estuarine and coastal processes in the West Bengal portion of the Ganges, Brahmaputra, and Meghna (GBM), known as the Sundarbans delta. Human expansion has designed the coastal sea, ponds, marshes, and estuary islands in this region to withstand the negative effects of societal, economic, recreational, and residential activities. Environmental factors such as increasing sea levels and climate change are significant sources of concern in this sensitive area. In recent decades, coastal flooding has emerged as a worldwide issue. Consequently, communities must prioritize the mitigation of flood risks. We use the InVEST and coastal flood risk mitigation (CFRM) model for the Sundarban deltaic region to analyze flood conditions caused by successive rainfalls of varying intensities and identify potential mitigating solutions. Increasing sea levels and global warming are endangering coastal regions to an escalating degree. Ongoing erosion and cyclones, which often deliver substantial rainfall, endanger human life and property, especially along low-lying deltaic coastlines. The Sundarbans and its mangrove ecosystems along India's east coast are vulnerable to tropical super-cyclones, and their resistance has diminished in recent decades owing to several adverse environmental stresses, including changing climate conditions. This study used the InVEST-CFRM model to evaluate the vulnerability of the Sundarbans' mangrove-fringed coastline in relation to flood volume and runoff attenuation index. We used the InVEST-CFRM model to assess the vulnerability of the intricate Indian Sundarbans. The study used machine learning (ML) methods to validate and predict the model, achieving a high accuracy value ranging from 0.76 to 0.99. The results demonstrate a steady increase in flooding along the deltaic coast of the Sundarbans in recent decades. The central regions of the Sundarbans are least vulnerable to flooding, but human settlements in these areas are most at risk. This research will provide effective mitigation techniques for restoring a sustainable environment and assist in identifying locations that are vulnerable to flooding and associated socioeconomic impacts.