Temporal Distribution of Rainfall in Northern Hilly Region of Chhattisgarh, India: A Crop Planning Approach

Abstract

Understanding the temporal distribution and probability of rainfall is crucial for optimizing cropping patterns and ensuring sustainable agriculture. This study analyses 33 years (1990–2022) of daily rainfall data and employs Markov chain analysis to assess the weekly rainfall distribution, probability of rainfall occurrence and its implications for crop planning. Results indicate that the 30th standard meteorological week (23–29 July) recorded the highest mean weekly rainfall (103.2 mm) with a coefficient of variation (CV) of 90.2%, while a stable rainfall period was observed between the 27th and 38th standard weeks (2 July–23 September). The probability of receiving 10 mm or more rainfall in a week exceeded 50% for 17 weeks (24th–40th week), ensuring adequate moisture for ploughing, land preparation and weeding. Additionally, the probability of receiving 20 mm and 50 mm of rainfall in a week exceeded 50% for 15 and 8 weeks, respectively, supporting optimal crop growth and groundwater recharge. The study highlights the 12-week window as the most suitable growing season for rainfed agriculture in Surguja district.