Study of Rainfall Variability Using Multi-Scale Entropy for Mandi and Shimla Regions of Himachal Pradesh, India

Global climate change can cause a shift in rainfall patterns. Shifts in rainfall patterns can impact agricultural practices and water management both in rural and urban societies. Information theory can be used to study the shift in rainfall patterns. In the present study, marginal entropy has been used to understand the randomness in rainfall data of the Mandi and Shimla districts of Himachal Pradesh, India. Marginal entropy quantifies the uncertainty or randomness associated with a single variable. In this study, the single variable was rainfall. Rainfall time series data from 1980 to 2021 have been used for both study locations. The results suggested that in both districts of Himachal Pradesh, marginal entropy (ME), at least in 50% of the total study period, exceeded average ME. The average ME was 0.129. It indicated that shifts in rainfall behavior were taking place, possibly due to climatic or anthropogenic influences in the region.