Evaluating the future risk of coastal Ramsar wetlands in India to extreme rainfalls using fuzzy logic

Abstract

Wetlands are often found in areas that undergo periodic flooding, such as coastal seas, lakes, and rivers. Coastal wetlands are particularly vulnerable to climate change effects, such as changes in precipitation patterns, risk of extreme rainfall, and cyclones/storms. This study assessed the uncertainties associated with extreme rainfalls in terms of return levels (RLs; 20 and 50 years) and quantified the potential risk level of these events in the future for coastal wetlands in India. The extreme precipitation indices (EPIs) were evaluated using a non-stationary approach, and the results showed that Thane Creek had the highest RLs, followed by Kolleru Lake. The risk level for each wetland was assessed using the fuzzy logic approach, which considered parameters such as exposure, vulnerability, and threat. The overall risk assessment showed that Thane Creek, Kolleru Lake, Pallikaranai Marsh Reserve Forest, and Tampara Lake are at a “High” risk level for both RLs of EPIs. Furthermore, the automated Shortwave Infrared (SWIR) thresholding technique was employed in Google Earth Engine to create inundation maps of wetlands. This study also indicated that Thane Creek is at risk of flooding based on the analysis of spatiotemporal changes. The impact evaluation of Thane Creek showed that rapid urbanization has encroached upon the creek's boundaries. Therefore, the variability of EPIs may be affected by climatic oscillations, leading to an upsurge in extreme rainfalls, causing the coastal wetlands to flood. Policymakers can use these findings to develop effective strategies for the proper management of coastal wetlands.