Rainfall Variability and Crop Planning of Dahod: A Case study from Tribal District in Gujarat, India

Abstract

India is an agrarian economy mostly depends on monsoon for its crop success. The onset and cessation of monsoon along with unpredictability in weather conditions, reflects the statistics in foodgrain production in this region. Planning of crop requires details on period of dry and wet spell of an area. The present study takes into account Markov chain model for rainfall probability analysis. The mean annual rainfall of Dahod district is 1073 mm with 59 rainy days. Only 41% shows rainfall above normal. 95% of annual rainfall is contributed by South-west monsoon whereas only 4% was contributed by North-east monsoon followed by 0.9% and 0.2% in summer and winter season. Analyzed data (1998-2019) reveals that monsoon start effectively from 25th SMW and cease on 40th SMW. The average monsoon period is of 16 weeks, i.e., 112 days. Initial, conditional and consecutive probability of dry and wet week indicates a shift in weather pattern around 20th SMW, transition of dry to wet weeks. More than 75% of wet probability can be observed from 27th to 35th SMW. Onwards 40th SMW, likelihood of P(D/D) keeps increasing up to 52 SMW. P(W/W) probability more than 75% can be observed from 27th to 32nd SMW. The district’s priority lies in poultry farming and vegetable cultivation along with sustaining soybean and chickpea. The cropping pattern of majority of district falls in maize-maize, maize-chickpea, maize-wheat-green gram, soybean-wheat-green gram and pigeon pea- groundnut, respectively. The area frequently experiences extended dry spells between monsoon. To address these challenges, crop diversification and efficient irrigation practices are prioritized.