ALBERT

Description: Understanding how different climate factors interact and impact rice yield is essential for effective agricultural management strategies and policies. However, the potential impacts are less clear at the regional scale. In this work, we used the latest version of the ORYZA crop model to evaluate the impacts of climate change and carbon dioxide (CO 2 ) on rice yields in the Sichuan Basin of China based on high-quality agricultural experimental, meteorological and soil data and the incorporation of future climate data generated by five general circulation models (GCMs) under three newly released representative concentration pathway (RCP) 2.6, 4.5 and 8.5 scenarios. Considering climate change alone, our modelling results indicated a continuing rice reduction for most stations by 2–17, 4–28 and 1–43% under the RCP2.6, 4.5 and 8.5 scenarios, respectively; when considering the CO 2 fertilizer effect, rice yields increased by 3–10, 4–13 and 5–20% under the RCP2.6, 4.5 and 8.5 scenarios, respectively. However, for most stations, the CO 2 fertilizer effect could not completely offset the negative impacts of climate change on rice yields. In addition, temperature and radiation were the main climate factors that cause yield variation by affecting the rice maturity periods (DAE), spikelet fertility factor (SPFERT) and spikelet number (NSP). The uncertainty arising from the climate models was less than 10% under the RCP2.6 scenario, 15% under the RCP4.5 scenario and 20% under the RCP8.5 scenario, indicating good consistency in rice yield simulations. These findings offer insight into the physiological mechanisms and the degree of climate change impacts on rice yields, thus informing appropriate adaptive strategies for rice planting in the Sichuan Basin, China. We use the ORYZA v3 model, coupled with climate data generated by five general circulation models (GCMs) under three representative concentration pathways (RCPs) (2.6, 4.5 and 8.5), to simulate climate change impacts on rice yields in the Sichuan Basin of China. We collect high-quality meteorological, soil and agricultural experimental data at the plot scale to calibrate, validate and evaluate the crop model. We identify the main factors that affect rice yields, explore the degree and the physiological mechanisms of climate change on rice yields and quantify the uncertainty arising from climate models.