Assessing agricultural vulnerability to climate extremes in Rayalaseema and KBKK regions of India: a panel ARDL approach

The regions of Rayalaseema and KBKK (Kalahandi-Bolangir-Koraput-Kandhamal) face significant agricultural challenges against frequently occurring meteorological abnormalities like floods, droughts, and erratic rainfall. Therefore, this paper investigates the impact of weather extremes on crop yields in the above two distinct regions of India belonging to Andhra Pradesh and Odisha, respectively, by applying the Panel Autoregressive Distributed Lag (ARDL) model. The analysis spans eight districts in two regions, utilizing a 50-year panel dataset (1966–2015) to study six key crops: rice, maize, chickpea, pigeon pea, groundnut, and cotton. The ARDL model analyzes the long-term and short-term relationships between agricultural yields and meteorological variables, incorporating essential weather factors such as evapotranspiration, water deficit, temperature, rainfall variation, and technology variables like fertilizer usage and irrigation.Across the various regions and crops, the results show the heterogeneous influence of weather variables on crop yields. In the long run, minimum temperature (β = 12.70, p < 0.05) and rainfall variation (β = 0.024, p < 0.01) considerably enhanced chickpea and rice yields, respectively. However, maximum temperaturehas showna significant negative impact on yield of pigeon pea (β = − 18.96, p < 0.01) and Chickpea (β = − 30.15, p < 0.01). Short-run results indicate dynamic adjustments for rice and cotton. Rice yield is significantly affected by evapotranspiration (short-run β = − 1.17, p < 0.01) and minimum temperature (short-run β = − 5.29, p < 0.01). On the other hand, the cotton yield suffered a significant reduction due to fluctuations in maximum temperature (short-run β = − 28.33, p < 0.05).Looking at the extent of vulnerabilities of these two regions against climatic variability, the findings underscore the requirement for region-specific agricultural policies to mitigate the risks. These insights can guide policymakers in developing adaptive strategies to enhance climate resilience in agriculture, specifically in semi-arid and rain-fed regions like Rayalaseema and KBKK.