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The accuracy prediction for the crop yield is conducive to the food security in regions and/or nations. To some extent, the prediction model for crop yields combining the crop mechanism model with statistical regression model (SRM) can improve the timeliness and robustness of the final yield prediction. In this study, the accumulated biomass (AB) simulated by the Agricultural Production Systems sIMulator (APSIM) model and multiple climate indices (e.g., climate suitability indices and extreme climate indices) were incorporated into SRM to predict the wheat yield in the North China Plain (NCP). The results showed that the prediction model based on the random forest (RF) algorithm outperformed the prediction models using other regression algorithms. The prediction for the wheat yield at SM (the period from the start of grain filling to the milky stage) based on RF can obtain a higher accuracy (r = 0.86, RMSE = 683 kg ha−1 and MAE = 498 kg ha−1). With the progression of wheat growth, the performances of yield prediction models improved gradually. The prediction of yield at FS (the period from flowering to the start of grain filling) can achieve higher precision and a longer lead time, which can be viewed as the optimum period providing the decent performance of the yield prediction and about one month's lead time. In addition, the precision of the predicted yield for the irrigated sites was higher than that for the rainfed sites. The APSIM-simulated AB had an importance of above 30% for the last three prediction events, including FIF event (the period from floral initiation to flowering), FS event (the period from flowering to the start of grain filling) and SM event (the period from the start of grain filling to the milky stage), which ranked first in the prediction model. The climate suitability indices, with a higher rank for every prediction event, played an important role in the prediction model. The winter wheat yield in the NCP was seriously affected by the low temperature events before flowering, the high temperature events after flowering and water stress. We hope that the prediction model can be used to develop adaptation strategies to mitigate the negative effects of climate change on crop productivity and provide the data support for food security. [ABSTRACT FROM AUTHOR]

• Future climate warming led to advance in wheat and maize phenology. • Future climate change had negative impact on maize but positive impact on wheat. • Crop water consumption was largely decreased under future climate scenarios. • Future climate change could mitigate groundwater overdraft across NCP. Climate change has already and will continue to exert a vital impact on crop yield and water use in the North China Plain (NCP). Currently, this plain is facing a dilemma between groundwater depletion and grain production demand. It is urgent to identify the impact of future climate change on crop yield and water consumption and then develop efficient adaptation strategies in the region. In this study, we used statistically downscaled daily climate data from 33 global climate models (GCMs) and two Representative Concentration Pathways (RCP4.5 and RCP8.5) for 61 stations distributed across the NCP and drove the well-validated APSIM model to simulate crop yield and water use for two future periods of 2031–2060 (2040s) and 2071–2100 (2080s). Data from all 33 GCMs show an increase in annual mean temperature and almost all the GCMs also show increases in annual mean solar radiation and annual total precipitation across the NCP. Future climate warming led to an advance in phenology for both winter wheat and summer maize, two typical crops in the NCP. However, the length of the reproductive growth period (RGP) of winter wheat was prolonged while that of summer maize was shortened under future climate scenarios across the NCP. Our simulated results show that future climate change had negative impacts on maize yield but positive impacts on wheat yield across the NCP. Mainly due to the shortening of the whole growth period, crop water consumption was largely decreased under future climate scenarios. The amount of irrigation required was also reduced mainly due to increased precipitation and decreased ET. Although future climate change would likely mitigate groundwater overdraft in most part of NCP, some areas in the northern NCP still had groundwater over-pumping in the future. Therefore, we suggest that it might be a good choice to change cropping system for reducing planting area of water-consuming crop (e.g. winter wheat) in those over-pumping areas to balance groundwater use and crop yield. [ABSTRACT FROM AUTHOR]