Spatio-temporal analysis of rainfall along with trend analysis: A case study of Chhattisgarh State of East Central India

In the present study, long-term daily gridded rainfall data was obtained from IMD (Indian Meteorological Department) for the period of 1971–2021. Initially, the consistency of rainfall data was checked using the scatter plots between station observed data and IMD gridded data of three stations. Stations are selected on the basis of observed rainfall data availability in the agro-climatic zones (ACZs) of Chhattisgarh. The current analysis has been carried out for the three ACZs, having 27 districts in Chhattisgarh State. The study is intended to emphasize spatiotemporal variation in Chhattisgarh state in terms of monthly, seasonal, and yearly basis. Mann-Kendall (MK), Modified Mann-Kendall (MMK), and Theil-Sen slope estimator have been used for possible trend detection and magnitude quantification respectively. The entire analysis has been performed using MATLAB and Python codes. Annual average rainfall of the state was found to be 1279 mm during 1971-2021. It was also found that about 80-85% of rainfall received in the monsoon period (June-Sep). As per ACZs of Chhattisgarh, Bastar Plateau and Chhattisgarh Plain received the highest (1490 mm) and lowest (1203 mm) rainfall respectively. The Northern Hills have shown the highest coefficient of variability. 14 districts are showing positive trends, remaining 13 districts have shown negative trends also annual and monsoon rainfall time series have shown significantly similar results in MK and MMK trend analysis. Finally, spatio-temporal analysis has been carried out using the Inverse Distance Weighted (IDW) approach of Arc-GIS 10.5. The annual magnitude of the slope varies from -4.910 mm/year (Jashpur) to 5.405 mm/year (Sukma). Further, the final map has been prepared for coefficient of variation (%), and trend results. These results will be useful for the understanding of the climatic behavior and its uncertainty towards agricultural, drought, water surplus, and deficit zone identification along with water resources planning and mitigation over the east-central India.