Spatio-temporal analysis of rainfall extremes in the flood-prone Nagavali and Vamsadhara Basins in eastern India

Abstract

Understanding the spatio-temporal distribution of rainfall characteristics has a major role in assessing the availability of water resources over a catchment. Therefore, it is necessary to understand the changes in rainfall characteristics using gridded precipitation data and robust statistical analysis for making decisions. In this study, the trends in rainfall and rainfall extremes over the Nagavali and Vamsadhara river basins are studied at three time steps (long-term-1901-2018, pre-1950, and post-1950) with four different Mann-Kendall (MK) tests using daily gridded rainfall data of 118 years (1901–2018). The spatial patterns of the trends are evaluated with the kriging interpolation method. Magnitude in rainfall and rainfall extremes (CDD, CWD, PRCPTOT, R10MM, R20MM, R40MM, R95PTOT, RX1DAY, and RX5DAY) are analyzed using the Sen’s slope method. Except in the monsoon season, a decreasing trend is observed in all the rainfall extremes in post-1950 compared to pre-1950 period. Whereas, in the monsoon an increasing trend is observed for the extremes in post-1950 period. Overall period (i.e, 1901–2018) an increasing trend is observed for rainfall and rainfall extremes in the pre-monsoon (March–May), monsoon (June–Sep) seasons and a decreasing trend in the winter season (Dec–Feb) for both the basins. No obvious trends are evident in the post-monsoon season (Oct–Nov). At the annual scale, rainfall and rainfall extremes exhibited an increasing trend. Overall, the Nagavali basin experienced more extreme rainfall events indicating the higher vulnerability of floods while the middle and lower portions of the Vamsadhara basin shown increase in extremes. When linked with hydrological analysis, insights gained from this study are useful for flood vulnerability mapping and risk assessment for both the basins.

Description
Keywords
Rainfall, Extremes, Mann-kendall test, Sen’s slope, Kriging interpolation
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