PU Jinlin, WANG Jun, WANG Kefeng, et al. Response of winter wheat yield under straw mulching in dryland to precipitation and temperature using APSIM model[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2024, 40(21): 101-109. DOI: 10.11975/j.issn.1002-6819.202404221
    Citation: PU Jinlin, WANG Jun, WANG Kefeng, et al. Response of winter wheat yield under straw mulching in dryland to precipitation and temperature using APSIM model[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2024, 40(21): 101-109. DOI: 10.11975/j.issn.1002-6819.202404221

    Response of winter wheat yield under straw mulching in dryland to precipitation and temperature using APSIM model

    • Wheat production is controlled by precipitation and temperature as well as management practices. However, how wheat yield responds to straw mulching under different climate change scenarios are not well known. Crop models can effectively analyze the impact of different climate conditions and field management practices on crop growth and yield. In this study, based on the observation data from a long-term field experiment that conducted in the Loess Plateau and the on-site daily climatic records from 1999 to 2022, we explored the response of winter wheat to straw mulching under different climate scenarios using the APSIM(agricultural production systems simulator)model. Three treatments as wheat straw mulching at high rate of 9000 kg/hm2 (HSM), low rate of 4500 kg/hm2 (LSM), and no mulching control (CK) were included in the field experiment. Data from field observations of crop growth and soil properties were used to calibrate and validate the APSIM model, ensuring accurate simulation of the conditions. Five levels of precipitation changes (Daily precipitation ±20%, ±10%, and 0) and five levels of temperature changes (Daily temperature 0 ℃, +1 ℃, +2 ℃, +3 ℃, and +4 ℃) were interacted to established a set of climate change scenarios in APSIM model. The variation coefficient and sustainability index of winter wheat yield were also calculated with the modeling data. The simulation results showed that the APSIM model is powerful simulating the grain yield and aboveground biomass accurately with the determination coefficients varied between 0.75-0.92, the normalized root mean square errors varied between 11.07%-14.65%, and the consistency index D varied between 0.84-0.91, respectively. Both precipitation and temperature changes had significant effects on winter wheat yield, and precipitation was more dominant influence than air temperature. When the temperature was constant, winter wheat yield increased with increasing precipitation, with the yield enhancement effect ranked as HSM>LSM>CK among treatments. However, when the precipitation was constant, winter wheat yield decreased with increasing temperature, with the reduction effect ranked as LSM>HSM>CK. Wheat yield also decreased under the interacted scenarios of precipitation and temperature, with the yield reduction effect ranked as CK>LSM>HSM among treatments. Across all climate change scenarios, winter wheat yield was greater in HSM than in LSM and CK. The sustainability index of winter wheat yield was also higher and the variation coefficient of winter wheat yield was lower in HSM than in LSM and CK. Compared with those under other climate change scenarios, wheat yield had a larger variation coefficient and lower sustainability index under the scenario of 20% decrease in precipitation and 2-3 ℃ increase in temperature, indicating a high risk in wheat production. In conclusion, winter wheat production in the Loess Plateau region can be improved by adopting high straw mulching in the context of future climate change. The results of the study provide a theoretical basis for future production and management of winter wheat on the Loess Plateau. In future modeling study, more climate change factors should be included to reduce the uncertainties and provide more comprehensive predictions for wheat production.
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