Responses of spring wheat growth to climate change in different climatic regions of northwest China

Abstract

This study aimed to assess the impact of climate change on spring wheat production and to provide more accurate projections by directly investigating the effect of climate change on crop development and yield. Based on ground observation data from 1981 (1986 Dingxi) to 2020 in four case areas in northwest China, and the relationships among spring wheat growth, yield, and climate factors were analyzed and determined. The results showed that the extreme arid (Dunhuang) and semiarid regions (Dingxi) tend to be warmer and wetter, whereas arid regions (Wuwei) and semihumid regions (Linxia) tend to be warmer and drier. Correlation analysis indicated that yield of spring wheat in Wuwei, Dingxi, and Linxia Stations increased significantly. The decrease in the number of days (≥30 ˚C) during the growth period at Wuwei resulted in a significant yield increase in the past 40 years. At Dingxi, yield increased over the last 35 years due to the significant increases in precipitation during growth, the number of grains per panicle, and thousand-grain weight, and the decrease in infertile spikelets. Further increase in global temperature and changes in future precipitation patterns will likely affect spring wheat production in northwest China.

Optimization of Parameters Related to Grain Growth of Spring Wheat in Dryland Based on the Next-Generation APSIM

“…The simulated results were validated with the field measurements by the equations, which showed that the RMSE and the NRMSE of the model were significantly reduced, and the simulated values were better fitted to the measured values. This study not only improved the model performance but also the optimization results, which were within the reasonable range of the dryland spring wheat growth and development study in Gansu Province [34], which was consistent with the growth state of dryland spring wheat in the study area. The method improved the efficiency of parameter optimization, which not only provided more data references for future studies but also laid the foundation for the future evaluation model of parameter optimization adaptation of the yield formation process in dryland spring wheat.…”

Study on Ensemble Calibration of Flood Forecasting Based on Response curve of rainfall dynamic system and LSTM.

“…In recent years, flood disasters have posed a great threat to the social economy and the safety of residents' lives and property. Accurate flood prediction plays an important role in eliminating the threat and protecting the safety of residents' lives and property (Wang et al, 2011). As climate change and human activities have changed the underlying surface of the watershed, the runoff generation mechanism of the watershed has become complicated.…”