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Published on: October 16, 2018
Remote sensing-based drought hazard monitoring and assessment in a coastal plain: A principal component approach
Colins Johnny Jesudhas1, Jeswin Titus C2, Tirthankar Roy3
1Department of Civil Engineering, University College of Engineering, Nagercoil, Tamil Nadu, India.
Abstract:
Accurate drought information is essential for preventing agricultural and societal losses. The indicators of how severe a drought is the deficiency in precipitation, soil moisture, and vegetation stress. The indicators were evaluated using the Precipitation Condition Index (PCI), Vegetation Condition Index (VCI), and Temperature Condition Index (TCI).The indices were combined using Principal Component Analysis to create the Synthetic Drought Index (SDI) for the evaluation of drought severity. The indices were estimated using multi-source remote sensing data from the Tropical Rainfall Measuring Mission (TRMM) and Operational Land Imager (OLI) of various years. Temporal analysis showed that the district is drought-prone and deficiency of 65% of precipitation in northeast monsoon of 2016 and below average non-monsoon rainfall in 2017, caused drought and affected 223.5 Km2 in 2017. Below average precipitation in northeast monsoon of 2018 and below average non-monsoon rainfall in 2019, caused drought and affected 423 Km2 in 2019. The northeast coastal regions of Ottapidaram, Thoothukudi, and Vilathikulam taluks of the district were more severely prone to drought. Failure of monsoon is the root cause of water deficit in water bodies. The semi-arid coastal climate accelerates the evaporation of water in water bodies and causes soil moisture deficit that leads to drought in the coastal district. A sequential evaluation of this index can be used to identify the onset of drought and mitigate the effect of drought.
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