Abstract
The predominance of floods that have been seen over the Indian subcontinent over the last few decades has restrained the growth of the economy than any other natural disaster. The primary objective of this study is to unwind the structure of various extreme precipitation events over India with the focus on hydrometeorological features of the four past catastrophic floods. Five precipitation indices; R-day, Rx-1 day, E1 (10–20 mm/day), E2 (20–30 mm/day), and E3 (30–50 mm/day) has been utilized along with Man-Kendall trend and linear trend (LT) methods to reveal the structure of extreme precipitation over the study region. Pearson’s correlation analysis has been carried to see the relationship between precipitation and integrated water vapor transport (IVT) over the flooded areas. We found that the west coast, central India, and eastern areas of the study region are quantified as flood vulnerable regions in contrast to western regions (Rajasthan and Gujarat) as drought-prone areas where daily rainfall of less than 10 mm is usually observed. The relationship between the yearly precipitation and IVT over the study region is showing an opposing (increasing/decreasing) trend in comparison with the extracted IVT and precipitation over the flood years which have shown a high correlation revealing that high IVT anomalies over the study region are responsible for creating extreme precipitation and flooding. Also, we found that enhanced SST anomalies over the Pacific and Indian oceans enhance the moisture supply to the Indian sub-continent leading to favorable conditions for extreme precipitation. This study finds its applications in predicting extreme events to reduce catastrophe.
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Junaid Dar has worked on the Idea and carried all the analysis and made the first draft. Abdul Qayoom dar has rechecked all the analyses and set the paper for submission.
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dar, J., dar, A.Q. The Structure of extreme precipitation and flood events over India in association with integrated water vapor transport from 1980 to 2015. Arab J Geosci 16, 162 (2023). https://doi.org/10.1007/s12517-023-11265-9
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DOI: https://doi.org/10.1007/s12517-023-11265-9