基于APSIM模型的新疆北疆冬小麦灌溉制度优化研究

Optimization of irrigation scheduling for spring wheat in Northern Xinjiang based on APSIM model

  • 摘要:
    目的 为探究新疆北疆冬小麦不同灌水下限对生理指标和产量的影响,进而优化其灌溉制度。
    方法 以新疆昌吉市2023~2025年旱地冬小麦大田试验数据为参考,采用基于贝叶斯的蒙特卡洛马尔科夫链法改进后的APSIM模型,模拟了6种不同灌溉制度下冬小麦生长指标和产量的变化,并构建12种灌溉情景,优选出适宜当地冬小麦的灌溉制度。
    结果 小麦生长指标和产量均随着灌溉定额的增加呈现先增加后减少趋势,其中W3处理生长指标和产量与其他处理相比较优。表现较差的W6处理株高增长18.11%~19.29%、LAI增加18.73%~30.22%、产量提高38.77%~44.82%;对比改进前后的APSIM模型模拟结果,改进前的决定系数(R2)为0.768和0.666、一致性指标(D)为0.885和0.918、相对均方根误差(NRMSE)为0.09和0.10、均方根误差(RMSE)为821.07和889.55 kg/hm2,改进后R2为0.955和0.974、D为0.961和0.995、NRMSE为0.05和0.04、RMSE为454.83和319.45 kg/hm2,改进后模型模拟结果较优,可以适用于该地区冬小麦模拟研究;分析APSIM模型综合模拟的12种灌溉制度,结果表明P6处理(灌溉定额为440.14 mm)作物产量较优。
    结论 新疆昌吉市冬小麦较优灌溉制度:在出苗-越冬期灌70 mm,返青期灌32.76 mm,拔节期灌65.52 mm,抽穗期灌102.32 mm,开花期灌74.24 mm,灌浆期灌46.16 mm,成熟期灌49.14 mm,其作物产量2年产量分别为10707.4210404.76 kg/hm2,该研究结果可为APSIM模型在新疆北疆冬小麦灌溉制度的优化提供理论依据。

     

    Abstract:
    Objective To explore the effects of different irrigation limits on physiological indicators and yield of winter wheat in northern Xinjiang, and to optimize its irrigation scheduling.
    Methods Taking the field experiment data of dryland winter wheat in Changji City, Xinjiang from 2023 to 2025 as a reference, an improved APSIM model based on Bayesian Monte Carlo Markov chain method was used to simulate the changes in winter wheat growth indicators and yield under six different irrigation scheduling. Twelve irrigation scenarios were constructed to select the appropriate irrigation scheduling for local winter wheat.
    Results The growth indicators and yield of wheat showed a trend of first increasing and then decreasing with the increase of irrigation quota, among which W3 treatment had better growth indicators and yield compared to other treatments. The W6 treatment, which is relatively poor, increased plant height by 18.11% to 19.29%, LAI by 18.73% to 30.22%, and yield by 38.77% to 44.82%; Comparing the simulation results of the APSIM model before and after improvement, the coefficient of determination (R2) before improvement was 0.768 and 0.666, the consistency index (D) was 0.885 and 0.918, the relative root mean square error (NRMSE) was 0.09 and 0.10, and the root mean square error (RMSE) was 821.07 and 889.55 kg/hm2. After improvement, the R2 was 0.955 and 0.974, D was 0.961 and 0.995, NRMSE was 0.05 and 0.04, and RMSE was 454.83 and 319.45 kg/hm2. The simulation results of the improved model were good and can be applied to winter wheat simulation research in this region; Analyzing the 12 irrigation scheduling simulated by the APSIM model, the results showed that the P6 treatment (irrigation quota of 440.14 mm) had better crop yield.
    Conclusion The optimal irrigation scheduling for winter wheat in Changji City, Xinjiang is as follows: 70 mm irrigation during the emergence to overwintering period, 32.76 mm irrigation during the greening period, 65.52 mm irrigation during the jointing period, 102.32 mm irrigation during the heading period, 74.24 mm irrigation during the flowering period, 46.16 mm irrigation during the grain filling period, and 49.14 mm irrigation during the maturity period. The crop yield is 10707.42 and 10404.76 kg/hm2, respectively. This study provides a theoretical basis for optimizing the irrigation scheduling of winter wheat in Northern Xinjiang using the APSIM model.

     

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