SPATIOTEMPORAL RAINFALL VARIABILITY AND TRENDS IN TRIPURA, INDIA: IMPLICATIONS FOR WATER RESOURCE MANAGEMENT

Abstract

This article aims to understand how patterns of rainfall change over time and across different areas very important for managing water resources, especially for the regions that are influenced by the monsoon. The study explores the long-term trends and patterns of 22 weather stations across Tripura, India. To analyse these trends, we follow the Modified Mann-Kendall test with Sen’s slope estimator, both of which are well-used for environmental data analysis without assuming any specific distribution. The outcomes show noticeable differences in rainfall trends from one location to another. We also apply K-means clustering for grouping the stations based on their monthly rainfall pattern behaviour. The analysis shows clear clusters and gives diverse rainfall regimes all over the state. These results are very useful for supporting agricultural decisions, infrastructure planning, and strategy development to adapt to changing climate conditions.