Volume 31 Issue 6
Jun.  2023
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Article Contents
WANG K Y, YANG Y M, YANG Y H, LIU D L, CHEN L. Evaluation of the effect of future climatic change on Hebei cotton production and water consumption using multiple GCMs[J]. Chinese Journal of Eco-Agriculture, 2023, 31(6): 845−857 doi: 10.12357/cjea.20230016
Citation: WANG K Y, YANG Y M, YANG Y H, LIU D L, CHEN L. Evaluation of the effect of future climatic change on Hebei cotton production and water consumption using multiple GCMs[J]. Chinese Journal of Eco-Agriculture, 2023, 31(6): 845−857 doi: 10.12357/cjea.20230016

Evaluation of the effect of future climatic change on Hebei cotton production and water consumption using multiple GCMs

doi: 10.12357/cjea.20230016
Funds:  This study was supported by the National Natural Science Foundation of China (31871518), the Natural Science Foundation of Hebei Province (C2022503008) and the International Cooperation Program of Ministry of Science and Technology of China (2022YFE0119500).
More Information
  • Corresponding author: E-mail: ymyang@sjziam.ac.cn
  • Received Date: 2023-01-06
  • Accepted Date: 2023-02-14
  • Rev Recd Date: 2023-02-13
  • Available Online: 2023-02-14
  • Publish Date: 2023-06-10
  • Climatic models are the primary source of uncertainty in climate change impact assessments. Uncertainty can be significantly decreased by using multiple climate models during an assessment. In this study, the crop model APSIM-COTTON was carefully calibrated based on two years of field experiments, and 22 GCM (Global Climate Models) models (AR6) were used to drive crop models to evaluate the effects of climate change on cotton production and water consumption in Hebei Province. The leaf area index, plant height, squares number, bolls number, and dry matter weight of each plant were used to correct various APSIM-COTTON parameters. The coefficient of determination was greater than 0.8, indicating that the simulated and observed values fit well. The trend of climate change at this site was that the solar radiation intensity under SSP1-2.6, SSP2-4.5, and SSP5-8.5 was higher than the baseline (from 1980 to 2010) and increased with time, but it was lower than the baseline under SSP3-7.0. Temperature tended to increase in all scenarios, and the amplitude increased with the increase in radiative forcing and time. In most scenarios, the minimum temperature increased more than the maximum temperature, and annual rainfall increased over time. The responses of cotton production and water consumption to future climate change are the comprehensive effects of CO2 concentration, solar radiation, temperature, rainfall, and other climatic factors. The crop model simulation results showed that the sowing date was advanced under all climate scenarios and future time periods, and all development stages (emergence, squaring, flowering, and harvesting) were shorter than those of the baseline period. In the 2090s, under scenarios SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, the boll opening stage advanced 9.3, 12.0, 14.7, and 16.0 days, respectively, whereas the harvest stage advanced 15.3, 21.0, 30.3, and 35.2 days, respectively. The annual evapotranspiration (ET) under all scenarios, except SSP3-7.0, showed an increasing trend, whereas the irrigation amount decreased. Under the SSP5-8.5 scenario, the annual ET in the 2030s, 2050s, 2070s, and 2090s increased by 6.5, 7.8, 14.3, and 32.7 mm compared with the baseline, whereas the irrigation amount decreased by 25.7, 23.8, 30.5, and 29.0 mm, respectively. In the future, changes in cotton yield will not be large in scenarios of lower radiation focusing (SSP1-2.6), and there will be a decreasing trend with age under high radiation forcing (SSP5-8.5 and SSP3-7.0). Under SSP1-2.6 and SSP2-4.5 scenarios, lint yield decreased by approximately 61.5 and 46.6 kg∙hm2, respectively, in the 2090s. However, under SSP3-7.0 and SSP5-8.5 scenarios, the reduction by 2090s reached 407.1 and 432.5 kg∙hm2, respectively. In this study, 22 GCM models were used to simulate the response of cotton growth and water consumption to climate change over 100 years in the 21st century, and the changing trends in different scenarios and time periods were compared to provide technical support for developing adaptation strategies to climate change. However, the uncertainty of evaluating the climatic effect on cotton production still exists in this study. More site data should be considered in the calibration process, and more crop simulation models with different mechanisms should be compared in future research.
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