Vulnerability assessment of the Deepor Beel, a Ramsar wetland in Northeast India, to changing climate

Wetlands are complex ecosystems that sustain livelihoods and provide diverse ecological services, making them exceptionally susceptible to climate change. This study evaluates the vulnerability of Deepor Beel, a Ramsar site in Northeast India, and identifies key assets for conservation. Five target assets were selected based on their representation of the wetland, significance for ecological processes, potential threat to Ramsar status, and sensitivity to change. These assets are the catchment and its hydrological regime, migratory birds, aquatic vegetation, fisheries, and tourism. The vulnerability assessment was based on climate data, obtained from CMIP6 GCMs. Twelve GCM models were downscaled and bias-corrected using the Inverse Distance Weighting method and linear scaling for Deepor Beel's most degraded watershed. A Multicriteria Decision-Making (MCDM) approach and rating metric determined the overall rank of each GCM. Multi-model ensembles, employing the random forest algorithm, were used for climate projections from the top five GCMs. The projections indicated a relative increase in rainfall during the monsoon (June-September) and a decrease during winter (October-January). Additionally, a decrease in temperature was observed during the monsoon and pre-monsoon (February-May) periods, while an increase was noted during winters. A comprehensive questionnaire survey was conducted to assess the sensitivity and exposure of assets to climate threats, allowing impact calculations using an impact scoring matrix. The adaptive capacity was similarly assessed to determine vulnerability using a vulnerability scoring matrix. Migratory birds were found highly vulnerable during future monsoon and winter periods. These findings will help decision-makers preserve assets critical to maintaining Deepor Beel's Ramsar status.

Keywords: Ramsar Wetland, vulnerability, Multicriteria Decision-Making, CMIP6 Global Circulation Model (GCM)