Impact of extreme weather events on cropland inundation over Indian subcontinent

• Published in: Environmental monitoring and assessment 2023-01, Vol.195 (1), p.50-50, Article 50
• Main Authors: Prakash, A Jaya, Kumar, Shubham, Behera, Mukunda Dev, Das, Pulakesh, Kumar, Amit, Srivastava, Prashant Kumar
• Format: Article
• Language: English
• Subjects: Agricultural land; Assessments; Atmospheric Protection/Air Quality Control/Air Pollution; Climatology; Crop damage; Crop insurance; Crop production; Crops; Cyclones; Cyclonic storms; Disaster management; Earth and Environmental Science; Ecology; Ecotoxicology; Emergency preparedness; Emergency response; Environment; Environmental Management; Environmental monitoring; Environmental science; Extreme weather; Flooding; Hydrologic data; Land cover; Land use; Meteorological satellites; Mitigation; Monitoring/Environmental Analysis; Precipitation; Precipitation data; Satellite data; Satellites; Spatiotemporal data; Standardized precipitation index; Storms; Water damage; Weather
• ISSN: 0167-6369; 1573-2959
• DOI: 10.1007/s10661-022-10553-3

Cyclonic storms and extreme precipitation lead to loss of lives and significant damage to land and property, crop productivity, etc. The “Gulab” cyclonic storm formed on the 24 th of September 2021 in the Bay of Bengal (BoB), hit the eastern Indian coasts on the 26 th of September and caused massive damage and water inundation. This study used Integrated Multi-satellite Retrievals for GPM (IMERG) satellite precipitation data for daily to monthly scale assessments focusing on the “Gulab” cyclonic event. The Otsu’s thresholding approach was applied to Sentinel-1 data to map water inundation. Standardized Precipitation Index (SPI) was employed to analyze the precipitation deviation compared to the 20 years mean climatology across India from June to November 2021 on a monthly scale. The water-inundated areas were overlaid on a recent publicly available high-resolution land use land cover (LULC) map to demarcate crop area damage in four eastern Indian states such as Andhra Pradesh, Chhattisgarh, Odisha, and Telangana. The maximum water inundation and crop area damages were observed in Andhra Pradesh (~2700 km 2 ), followed by Telangana (~2040 km 2 ) and Odisha (~1132 km 2 ), and the least in Chhattisgarh (~93.75 km 2 ). This study has potential implications for an emergency response to extreme weather events, such as cyclones, extreme precipitation, and flood. The spatio-temporal data layers and rapid assessment methodology can be helpful to various users such as disaster management authorities, mitigation and response teams, and crop insurance scheme development. The relevant satellite data, products, and cloud-computing facility could operationalize systematic disaster monitoring under the rising threats of extreme weather events in the coming years.