Evaluation of global gridded crop models (GGCMs) for the simulation of major grain crop yields in China

Multimodel ensembles are powerful tools for evaluating agricultural production. Multimodel simulation results provided by the Global Gridded Crop Model Intercomparison (GGCMI) facilitate the evaluation of grain production situation in China. With census crop yield data, the performance of nine global gridded crop models (GGCMs) in China was evaluated, and the yield gaps of four crops (maize, rice, soybean, and wheat) were estimated. The results showed that GGCMs better simulated maize yields than those of other crops in the northeast, north, northwest, east, and center. GEPIC (CLM-CROP) performed best in simulating maize (wheat) yield in the north, east, and northwest (southwest and south), due to reasonable parameter (cultivar and phenology parameters) settings. Because the rice phenology parameters were calibrated against phenological observation networks and a simple nitrogen limitation index was introduced, ORCHIDEE-CROP performed well in rice yield simulation and soybean yield simulation (center and southwest). Among four crops, wheat has the largest yield gap (7.3-14.1%), in which the poor soil of northwest (14.1%) exposes wheat to relatively high nutritional stress. Thus, in northwest China, optimizing nitrogen management in wheat production can effectively mitigate the negative impact of climate change on crop production.

Automated summary

Multimodel ensembles provide a powerful tool for evaluating agricultural production. This study evaluates the performance of nine global gridded crop models in simulating the yields of four major crops in China. The results show that the models better simulate maize yields compared to other crops in several regions. Wheat has the largest yield gap, mainly due to nutritional stress in the northwest region. Optimizing nitrogen management in wheat production can effectively mitigate the negative impact of climate change on crop production in northwest China.