Impact of extreme weather events on cropland inundation over Indian subcontinent

被引:0
|
作者
A Jaya Prakash
Shubham Kumar
Mukunda Dev Behera
Pulakesh Das
Amit Kumar
Prashant Kumar Srivastava
机构
[1] Indian Institute of Technology Kharagpur,Centre for Oceans, Rivers, Atmosphere and Land Sciences
[2] World Resources Institute,Department of Geoinformatics
[3] Central University of Jharkhand,Institute of Environment and Sustainable Development
[4] Banaras Hindu University,undefined
来源
Environmental Monitoring and Assessment | 2023年 / 195卷
关键词
IMERG-GPM; SPI; Water inundation; Sentinel-1; Thresholding; Croplands;
D O I
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中图分类号
学科分类号
摘要
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 24th of September 2021 in the Bay of Bengal (BoB), hit the eastern Indian coasts on the 26th 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 km2), followed by Telangana (~2040 km2) and Odisha (~1132 km2), and the least in Chhattisgarh (~93.75 km2). 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.
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