Analyzing the Impact of Rainfall Patterns on Agriculture, Economy and Tourism in India: A Statistical Approach

Abstract

The current study examines rainfall trends in India, encompassing its effect on various economic aspects and forecasting for 2023-2030. The Mann-Kendall test and Sen’s slope estimator are utilized to analyze annual and seasonal rainfall patterns. Results reveal a pronounced winter decline (2001-2022) alongside significant pre- monsoon, monsoon, and post-monsoon increases. Annual rainfall consistently de- creases, contrasting with rising pre-monsoon, monsoon, and post-monsoon trends. Annual rainfall exhibits the steepest decline (-1.0891 mm/year), while the monsoon season displays the highest increase (3.2538 mm/year). Further, the present study explores relationships between rainfall and economic growth, tourism, and agriculture. A statistically insignificant yet positive correlation is found between annual rainfall and per-capita GDP, indicating other economic drivers. Tourism shows a weak, statistically insignificant link with annual rainfall. In contrast, a robust statistically significant correlation emerges between annual rainfall and food- grain production, highlighting its role in agriculture. Finally, the present research forecasts annual rainfall (2023-2030) using the ARIMA (1,0,0) model, predicting a continued decline. This has profound implications for water resources, agriculture, and the economy, necessitating proactive measures such as water conservation, drought-resistant farming, and alternative energy investments.