Climate change impact analysis using bias-corrected multiple global climate models on rice and wheat yield

Abstract

Rice and wheat, two staple food grain crops, play a key role in farmers' income and food security. The response of these crops towards climate change is heterogeneous and uncertain. Therefore, it becomes essential to analyse the impact of climate change on these crops. An investigation was performed to analyse the impact of climate change on rice and wheat yield and to quantify the uncertainties in the yield predictions in West Bengal, India. The climatic projections from eight global climate models were used to simulate the rice and wheat yields in all districts of West Bengal. A quantile mapping method was used to correct systematic biases of daily rainfall, solar radiation and temperature. The corrected data were then used for driving crop environment and resource synthesis models for yield simulations. Results reveal that rice yield is expected to reduce by 7–9% in the 2020s, 8–14% in the 2050s and 8–15% in the 2080s, whereas wheat yield is expected to go down by 18–20% in the 2020s, 20–28% in the 2050s and 18–33% in the 2080s. These reductions signify that rice and wheat yield is more likely to decline under the future climate change condition, which may affect the regional food sustainability. HIGHLIGHTS GCMs are used to assess the effect of climate change on rice and wheat yield.; Quantile mapping method is used to correct bias of GCMs outputs.; DSSAT-CERES for rice and wheat is used for yield prediction.; Rice and wheat yield is expected to reduce, respectively, up to 15 and 33% by the end of the 21st century in West Bengal.; Study prompts to develop adaptation for regional food sustainability.;

Keywords

• ceres
• global climate model
• quantile mapping method