Abstract
Coastal regions face an escalating threat from global warming and rising sea levels. Many lives and properties, particularly in low-lying delta areas, are at risk due to ongoing erosion and frequent cyclones. The Sundarbans, located along India’s eastern coastline and known for its mangrove ecosystems, is highly vulnerable due to its dense population, coastal erosion, and frequent storm surges, and its resilience has declined under increasing environmental pressures, especially in the context of a changing climate. This study investigates the coastal vulnerability of the mangrove-fringed coastlines of the Sundarbans using the InVEST coastal vulnerability (CVI) model. The model validation was carried out using through four machine learning (ML) algorithms. The Analysis covers four years: 1990, 2000, 2010, and 2020, considering the influence of extreme climatic events, such as tropical cyclones, to assess their impact on the vulnerability of the Sundarbans. Results indicates that over the past few decades, the Sundarbans deltaic shoreline has become increasingly vulnerable. Central regions with high mangrove density exhibit the lowest vulnerability, while areas near human settlements are the most vulnerable. Although natural habitats like mangroves has a huge impact on coastal susceptibility, extreme climatic events causes significant damage to them, further exposing the region to hazards. A block-wise assessment identifies four of the most vulnerable areas of Sundarbans: Sagar, Patharpratima, Namkhana, and Kakdweeep. These findings helps to identify vulnerable zones, understand their social implications, and propose effective measures for restoring a sustainable ecosystem.
