Entropy-based assessment of climate dynamics with varying elevations for hilly areas of Uttarakhand, India

Water is important to the planet's long-term sustainability since it affects where and how inhabitants may survive. Rainfall is the main element of the hydrological cycle and directly impacts agriculture sectors; a regular pattern of rainfall results in healthy crop production, extreme events such as floods and drought, and industrial and domestic sectors, among others. The present study tried to explore the variability in rainfall patterns and the effect of altitudinal differences on rainfall patterns using different measures of entropy indices based on a monthly, seasonal, and annual scale. The study was carried out for the southern part of Uttarakhand, namely Almora, Kashipur, Lansdowne, and Mukteshwar stations, using 116 years of rainfall data from 1901 to 2016. Considering seasonal analysis, the post-monsoon season had a high MMDI (0.345) for Lansdowne station, followed by Mukteshwar (0.309) and Almora (0.304). However, the highest MMDI (0.340) was recorded for Kashipur during the pre-monsoon season. Pre-monsoon season had the lowest MMDI for Mukteshwar station, followed by Almora and Lansdowne stations. However, the lowest MMDI was recorded during the winter season at Kashipur station. The results revealed that Kashipur and Lansdowne's stations had a high variation. In contrast, Almora and Mukteshwar stations had less variation in rainfall amounts. In adition, altitudinal assessment based on the entropy approach, a unique aspect of the study, can demonstrate an inverse relationship between elevation, rainfall patterns, and rainy days, suggesting that rainy days and rainfall patterns vary less frequently at higher elevations. The results of this study can also be used to make recommendations for future development in rainfall models, local agricultural policies, and management of extreme events such as droughts and floods, among others.