Analysis of Rainfall Trends in India, Incorporating Non-Parametric Tests and Wavelet Synopsis over the Last 117 Years

Abstract

Rainfall trend analysis is very important in the economic and sociocultural context of the country, like the development of irrigation and water resource management practices. In this paper, Mann-Kendall (M-K), Sen’s slope estimator, and wavelet analysis were used to analyze long-term (1901 ~ 2017) annual and seasonal rainfall trends in India. The sequential Mann-Kendall (SQMK) test is used to estimate the temporal variation of rainfall. The analysis shows monsoon precipitation in “Jammu and Kashmir, Himachal Pradesh, Uttarakhand, Uttar Pradesh, Chhattisgarh, Sikkim, Arunachal Pradesh, Mizoram, Assam, Karnataka, Nagaland, Kerala, Meghalaya, and Goa” have significant trends. The above-mentioned states were subjected to a discrete wavelet transform (DWT) analysis using Daubechies (db5-db10) and Symlet (sym5-sym10) mother wavelet families. The analysis revealed that the trends of subdivisions had a short-term periodicity of less than a decade. Therefore, the present study indicates significant changes over time. By utilizing wavelet techniques, it is possible to gain insight into both short- and long-term tendencies, making it simpler to spot patterns and sudden changes. Therefore, the present study by combining non-parametric tests with wavelet synopsis, offers a thorough comprehension of rainfall trends in India. The collaborative use of these techniques improves the precision of trend identification, offering valuable insights to make well-informed decisions for water resource management and climate adaptation strategies.

Keywords: rainfall trend, Mann-Kendall, SQMK, discrete wavelet transforms, daubechies, symlet, changepoint, India, 117 years