Tracking the Yield Sensitivity of Rice–Wheat System to Weather Anomalies

Abstract

Climate change impacts agriculture, food production and security in view of a region’s geography, monsoon dependency and weather extremities. Yield sensitivity to the anomalies of weather is an emerging issue in the perspective of climate smart farming. The present study develops an approach to assess the yield sensitivity of rice–wheat cropping system using a non-parametric Mann–Kendall’s test for examining the long-run weather anomalies between 1981 and 2013, followed by regressing yield (stepwise) on weekly weather variables. This approach confirms the long-run weather anomalies and then proceeds to identify the sensitive weeks for climate smart practices, and adaptation strategies for drawing policies. A significant long-run trend has been noticed in the weather variables barring rainfall in rice growing season and evapotranspiration in wheat growing season. Stepwise regression indicated that rice yields are positively influenced by minimum temperature during its growth week 13, evapotranspiration in week 15 and wind speed in week 10; and wheat yields are sensitive to the maximum temperature and evapotranspiration in week 1, as well as sunshine hours in week 6. Volatility in weather variables during ripening in rice and crown root initiation and late tillering in wheat reduces the yield. The interactive effect of significant weather variables on rice and wheat yield indicated its sensitivity due to the weather anomalies in varying magnitudes. This approach is ideal to measure the sensitivity in crop yield owing to anomalies in disaggregated weather variables. Further, it warrants suitable and relevant policy recommendations. In our case, the future research should focus on developing agro-climatic region specific rice and wheat genotypes resilient to climate change, identifying climate smart farming practices as well as adaptation strategies.