Investigation of rainfall variability of the southern part of Uttarakhand using entropy theory

Abstract

Rainfall is a natural phenomenon with high probability of randomness. The extent of rainfall variability may be an indicator of wet season or dry season. The information on rainfall variability can be used to understand the dynamics of seasonal or annual weather pattern, which can further be adopted to study the extent of climatic variability of a region. The rainfall variability in the present study has been studied using entropy theory. Entropy theory gives transitory information about the uncertainty in rainfall patterns on behalf of the stochastic approach. In this study, three rain gauge stations, situated in southern part of Uttarakhand, were selected. The rain gauge stations were situated at Almora, Nainital and Pauri. The temporal data of rainfall from 1901 to 2016 has been taken from India Meteorological Department (IMD). Disorder index (DI), estimated using entropy equations, has been derived for winter, pre−monsoon, monsoon, and post−monsoon seasons for the study period. The study suggested that DI and mean marginal disorder index (MMDI) were observed high (i.e. 0.351) for the post− monsoon season at Nainital station, followed by Pauri, and Almora stations. In terms of total seasonal variation in rainy days at the selected stations, Almora station has relatively high degree of DI and MMDI. The highest and lowest MMDIs value were 0.235 and 0.122 observed for pre−monsoon and post−monsoon season respectively. It indicated that rainy day's variation was high in post−monsoon and low in pre− monsoon season for the study period. This variation in the distribution of rainfall over the area may lead to inconsistency in the rainfall pattern.