Assessment of inundation extent due to super cyclones Amphan and Yaas using Sentinel-1 SAR imagery in Google Earth Engine

• Published in: Theoretical and applied climatology 2024-06, Vol.155 (6), p.5659-5675
• Main Authors: Mondal, Momsona, Nanda, Manoj Kumar, Peña-Arancibia, Jorge Luis, Sarkar, Debolina, Ghosh, Argha, Goswami, Rupak, Mukherjee, Asis, Saha, Abhijit, Brahmachari, Koushik, Sarkar, Sukamal, Mainuddin, Mohammed
• Format: Article
• Language: English
• Subjects: Agricultural land; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Atmospheric Sciences; Backscatter; Backscattering; C band; Climatology; Cloud computing; Coastal flooding; Coastal management; Coastal plains; Coastal zone; Cyclones; Data analysis; Digital Elevation Models; Digital mapping; Earth and Environmental Science; Earth Sciences; Engines; Environmental degradation; Environmental hazards; Flood control; Flood management; Flooding; Floods; Human settlements; Hurricanes; Infrared analysis; Mapping; Precipitation; Rainfall; SAR (radar); Satellite data; Satellites; Surface water; Synthetic aperture radar; Tropical cyclones; Urban areas; Waste Water Technology; Water Management; Water Pollution Control
• ISSN: 0177-798X; 1434-4483
• DOI: 10.1007/s00704-024-04948-0

The coastal region of West Bengal, India, is vulnerable to the tropical cyclones from the Bay of Bengal often causing loss of life, infrastructure damage, agricultural devastation, and environmental degradation exemplified by the devastating impacts of Amphan in May 2020 and Yaas in May 2021. Considering the importance of accurately mapping flood extent, a study was conducted to evaluate the inundation caused by Amphan and Yaas in three coastal districts of West Bengal: East Medinipur, North 24 Parganas, and South 24 Parganas, by using satellite-derived data products and Google Earth Engine (GEE). The changes in backscattering signal of dual-polar Sentinel-1-C-band Synthetic Aperture Radar (SAR) due to flooding were analyzed to detect the inundation extent. The Copernicus Digital Elevation Model (GLO30) and JRC Global Surface Water Mapping Layers were used for terrain correction, masking of high slope areas and seasonal water bodies. The Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) revealed rainfall increases of 47–135% above the long-term average in these districts. Amphan caused widespread flooding in East Medinipur (17.56% of total area and 35% of croplands) affecting 349,097 people while the other districts were moderately affected. The impact of Yaas was comparatively lower. The study provides detailed Block-wise (third-level administrative unit) inundation map due to Amphan and Yaas of the study region. The methodological framework outlined herein, presents a scientifically rigorous method involving open-source satellite data and cloud computing platform to make informed decisions for flood management in the coastal plains. Highlights • Sentinel-1 SAR imageries of pre and post cyclonic inundation extents are analyzed for VH backscatter thresholding to estimate the inundation caused by cyclones Amphan and Yaas in West Bengal. • Significant rainfall deviation was observed during both the cyclones calculated from past 30 years data (1991-2020). • Impact on cropland, urban areas and population estimated from Google Dynamic World and JRC Human Settlement layer database. • Maximum flooding of 17.56% area occurred in East Medinipur district affecting 349,097 people during Amphan, while impact of Yaas was comparatively less. About 35% of cultivable land was inundated. • South 24 Parganas district suffered more than other coastal districts during Yaas.