Bayesian multi-model projection of irrigation requirement and water use efficiency in three typical rice plantation region of China based on CMIP5

Abstract

Rice growth is significantly influenced by the ongoing climatic change and subjected to water shortages. Projection on the changes of rice productivity growth and water resources utilization under future climates is of great importance for food security and water resources sustainable management. Climate model outputs in combination with physical-based crop model is an effective way to modeling the crop productivity and water consumption response, but uncertainties associated with climate models remain a major challenge. In this study, we introduce a Bayesian model averaging (BMA) method to provide the multi-model ensemble projections by merging 4 climate models under four emissions scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) from phase five of the Coupled Model Intercomparsion Project (CMIP5). The comprehensive investigation on how the rice yield, water consumption (ET), irrigation water requirement (IR), water use efficiency (WUE) and irrigation water use efficiency (IWUE) response to future climate scenarios with taking account of CO2 concentration enrichment in three typical sites (Kunshan and Nanjing in the Yangtze River Basin, and Kaifeng in the Yellow River Basin) in rice plantation region of China was conducted by driving a well-validated rice crop model ORYAZ2000 with merging multi-model ensemble projected climate outputs. There are some obvious uncertainties for climate models projections in climatic variables with wide model spread, especially for solar radiation and wind speed. The BMA method is most competent to produce the ensemble with the lowest bias in comparison with simple model averaging (SA) method and individual climate model. In despite of the distinct response of the growth duration to future climate change for the three stations, the rice yield would be reduced significantly under the climate warming. IR would present more remarkable increase compared with the ET, especially for Nanjing and Kunshan stations, due to the decrease in precipitation during the rice growth period. The significant reduction in rice production together with enlargement in ET and IR, resulted in the generally depressed the WUE and IWUE. In addition, despite that the CO2 fertilization effect cannot compensate the negative effect of temperature increase, the increase of CO2 concentration can promote the overall level of yield and consequently improve the water use efficiencies of rice.