Abstract
The Sundarbans coastal delta, spread across the international boundary between Bangladesh and India, is a globally recognized priority for conserving biodiversity. This region is particularly vulnerable to frequent fooding and the degradation of its fragile wetland environment, with an average elevation of just 2 m above sea level. The extent of this potential loss can be predicted with acceptable confdence since the average sea level is expected to increase 2 m globally by 2100, compared to the baseline period (2022). We investigated the possible impacts of three sea-level rise (SLR) scenarios on the Sundarbans using feld and remote measurements, simulation modelling, and geographic information systems. Hindcast’s modelling eforts using the Sea Level Afecting Marshes Model (SLAMM) and machine learning (ML) algorithms accurate predictions of reported area declines during the 1990–2022 period. The input characteristics applied were the National Wetland Inventory (NWI) classifcations, the slope of each cell, and the Digital Elevation Map (DEM). Next, using ML approaches, NWI categories were developed. We examined the efects of varying sea levels at 0.49 m in 2022, 0.79 m in 2050, 1.52 m in 2075, and 2 m in 2100, considering diferent wetland types, marsh accretion, wave erosion, and changes in surface elevation. According to estimates, the mangrove wetland area will decrease by~46 km2 between 2022 and 2050 under the 1.5-m and 1-m SLR scenarios. The decline in mangrove area by 2100 is estimated to be 81 km2 , 111 km2 , and 583 km2 under the 1-m, 1.5-m, and 2-m SLR scenarios, respectively. Our results suggest that in a 1-m inundation scenario, approximately 325.36 km2 of land may be submerged, whereas, for a 2-m inundation, this area increases substantially to 874.49 km2 , more than 2.5 times the area impacted by the 1-m scenario. Both scenarios resulted in signifcant land loss in the Sundarbans. Severe adverse efects from erosion and foods are expected in the coastal zone, including decreased capacity to sequester carbon gases. This study will help coastal management organizations estimate the impacts of SLR and pinpoint places that need signifcant mitigating eforts.
