Effect of Crop Sowing Date on Water Balance in Tropical Regions of India for Kharif-Season

In this study, an attempt is made to maximize the availability of the rain water in a crop period by altering the date of sowing (DOS) of crop such that crop period requires the least amount of irrigation. The study is focussed on Rice farming in Tropical regions of India, for Kharif-season. The seasonally aggregated values of precipitation (PA), evapotranspiration (ETA) and crop water balance (CWBA) are used to determine optimal sowing dates, which are varied in a range of 40 days from the existing DOS (− 10 to + 30 days). The hydro-meteorological data (HMD: P, T_max and T_min) are made available by IMD, Pune for a span of 7 decades (year 1951–2020) at daily resolution. Three Koppen climate zones in India are considered in this study: Tropical Dry (As), Tropical Savannah (Aw) and Tropical monsoon (Am). The results show that for the As region, PA initially increases till 4th of the June starts falling afterwards for all DOS, but ETA decreasing continuously, eventually CWBA increases continuously till mid-June thus sowing dates are ideal. For Aw, PA initially rises (for early DOS) and thereafter it falls slightly (for late DOS), whereas ETA decreases continuously for all progressing DOS. CWBA is increasing initially till the mid-June and falls afterwards till June end, therefore results reveal that the best time to sow crops in this climate zone is around 13 days after monsoon starts. For Am, PA initially rises (for early DOS) and thereafter it falls continuously (for late DOS), whereas ETA stays same for all progressing DOS. CWBA initially rises till 5th June after that it falls till end of June, so results reveal to sow in early days of monsoon. This study shows that combining PA, ETA, and CWBA data efficiently analyses patterns and optimizes DOS. The CWBA could be improved by modifying DOS in response to the ET. Using this, a decision support system may be developed to help farmers make well-informed decisions that will increase agricultural productivity.