SPATIOTEMPORAL ANALYSIS OF ANNUAL AND SEASONAL PRECIPITATION OVER EASTERN RAJASTHAN

Abstract

Precipitation is one of the most important variables in the hydrological cycle which affects floods, droughts, water resources and ecosystem services. Information regarding precipitation trends in the water sector to identify climate change consequences and understanding the hydrology of an area both need knowledge of water availability over time and space. Because of increasing/decreasing tendencies in hydrometeorological time series, such as droughts, floods, and so on, climate change is projected to have a significant effect on rainfall and runoff. While using trend approach, various models have been proposed to tackle these issues. Many researchers have recently employed several parametric and non-parametric statistical methods to analyze trends in hydrometeorological time series in India and around the globe. For trend analysis of rainfall, both parametric and non-parametric approaches are generally used where non-parametric approaches include the Mann-Kendall Test, Spearman's rho Test, and Sen's Slope Test, and parametric approaches include methods like linear regression methods. In this study, non-parametric approaches Mann-Kendall and Sen's slope estimation test are used to analyse trends in 12 districts in Eastern Rajasthan. The box-whisker and Ljung box tests are employed to screen for outliers and serial correlations, and autocorrelations are eliminated using the pre-whitening procedure. Although the Mann-Kendall test is unaffected by outliers, it produces inaccurate results for serial correlations. Because the innovative trend analysis approach has no constraints, it is a more dependable and advanced tool for detecting hidden trends than non-parametric approaches. A scatter graph between the test statistics is used to compare trend indicators for all three procedures. The ITA test statistic, the MK test statistic, and Sen's slope estimator test statistic all have a high level of agreement in these plots.