Time series data and rainfall pattern subjected to climate change using non-parametric tests over a vulnerable region of Karnataka, India

Abstract

Fluctuations in the precipitation pattern often tend to have an impact on the availability of water, making it necessary to explore spatiotemporal variations in rainfall. This study explores the time series analysis of the rainfall from 1952 to 2019. The trend was analyzed using the modified Mann–Kendall test (MMK), and innovative trend analysis (ITA). The analysis showed that the northern region received the least rainfall while the southern region received the maximum rainfall except that one of the stations had a positive kurtosis. The kurtosis of the rainfall histogram ranges from −0.69 to 24.13. The trend was very well defined by all the methods, though MMK z statistics showed more occurrences of significant changes in the rainfall. The northeast monsoon carried a significantly decreasing trend at Chikkanayakanahalli station where the z value of MMK and ITA_R test showed values of −1.33 and −2.23, respectively, while all of the significantly increasing trends were defined by the MMK test in the annual and southwest monsoon season. The homogeneity test showed the most correlation between Pettitt and Buishand tests in comparison to SNHT. Later, the ARIMA model was run for the precipitation to predict the rainfall value from 2019 to 2029. HIGHLIGHTS The semi-arid region in Karnataka is prone to drought conditions and lacks the presence of any major rivers.; There are hardly any studies in the area which can contribute to policy making and mitigations method.; MMK, Sen Slope and ITA methods visualize the historical trend.; Homogeneity tests determine the changepoint and the ARIMA model forecasts the rainfall for the next decade.;

Keywords

• homogeneity test
• innovative trend analysis
• modified mann–kendall
• rainfall forecast
• sen's slope
• tumakuru