Abstract
Wetlands are essential for preserving numerous natural cycles and providing habitat for a wide variety of wildlife. They are essential to maintaining the appropriate balance of the ecosystem. The Ramsar Convention categorises wetlands as Ramsar Wetlands based on certain parameters (botanical, geological, and hydrological features) and national importance. There could be multiple threats to the wetland ecosystem such as habitat loss, pollution, invasive species, climate change, overexploitation, hydrological modifications, etc. This study delves into assessing the climate vulnerability of 15 newly designated Ramsar sites in India in 2022. Historical analysis of the inundation area of these sites from 1991 to 2022 was performed using pre-processed Landsat imageries in Google Earth Engine. The accuracy of mapping inundation was evaluated by creating error matrix and analyzing user’s accuracy, producer’s accuracy and overall accuracy. Future climate vulnerability was assessed using recent climate projections of shared socioeconomic pathway (SSP 245) from Coupled Model Intercomparison Project-Phase 6 (CMIP6). Machine learning regression algorithms were employed to understand the relationship between wetland inundation and climate variables, paving the way for predictive analysis. Some Ramsar sites showed significantly decreasing trends in past inundation patterns, highlighting their potential vulnerability to climate changes. This analysis underscores the importance of proactive measures to protect these Ramsar sites in the face of evolving climatic conditions, emphasizing the critical role of conservation efforts in preserving these essential ecosystems.
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Data Availability
To delineate the historical inundation patterns of Ramsar wetland sites in India, we used preprocessed remote sensing data by the United States Geological Survey (USGS) from three Landsat sensors: Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI. This dataset, spanning a 30-year period from 1991 to 2020 and is conveniently accessible through the Google Earth Engine data catalog for academic purposes (https://developers.google.com/earth-engine/datasets/catalog/?filter=Landsat%205%20TM). Additionally, historical temperature and precipitation data were sourced from the Indian Meteorological Department (https://www.imdpune.gov.in/cmpg/Griddata/Rainfall_25_Bin.html). For future projections, we utilized bias-corrected precipitation and temperature (maximum and minimum) data from thirteen Global Climate Models (GCMs) on a daily scale, as provided by Mishra et al. (2020) (https://zenodo.org/record/3987736#.ZEYfY3ZByUk). Notably, all data and software employed for this study are available via open access.
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All authors contributed to the study conceptualization and design. The first draft of the manuscript was written by Erumalla Saikumar and Shivam Singh jointly under the supervision of Manish Kumar Goyal. The review was carried out by Shivam Singh and Manish Kumar Goyal. All authors read and approved the final manuscript.
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Singh, S., Goyal, M.K. & Saikumar, E. Assessing Climate Vulnerability of Ramsar Wetlands through CMIP6 Projections. Water Resour Manage 38, 1381–1395 (2024). https://doi.org/10.1007/s11269-023-03726-3
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DOI: https://doi.org/10.1007/s11269-023-03726-3