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中国农学通报 ›› 2025, Vol. 41 ›› Issue (20): 106-112.doi: 10.11924/j.issn.1000-6850.casb2024-0472

• 资源·环境·生态·土壤·气象 • 上一篇    下一篇

玉米生长发育模拟模型MaizeSM对土默特左旗玉米生长模拟适用性分析

张岚晶1(), 梁燕1, 高琪2, 苏利军1(), 孙尚瑜1, 云磊3, 王一鸣4   

  1. 1 呼和浩特市气象局,呼和浩特 010010
    2 土默特左旗气象局,呼和浩特 010100
    3 和林格尔县气象局,呼和浩特 011500
    4 托克托县气象局,呼和浩特 010200
  • 收稿日期:2024-07-16 修回日期:2025-01-20 出版日期:2025-07-15 发布日期:2025-07-21
  • 通讯作者:
    苏利军,男,1982年出生,内蒙古凉城人,正高级工程师,硕士研究生,研究方向:农业气象服务。通信地址:010010 呼和浩特市气象局, E-mail:
  • 作者简介:

    张岚晶,女,1989年出生,内蒙古呼和浩特人,工程师,硕士研究生,研究方向:气象防灾减灾服务。通信地址:010010 呼和浩特市气象局,E-mail:

  • 基金资助:
    2023年度呼和浩特市智慧农业气象科技特派员保障团队专项“玉米决策气象服务专项”(2023-00390)

Analysis of Applicability of MaizeSM Model for Maize Growth Simulation in Tumd Left Banner

ZHANG Lanjing1(), LIANG Yan1, GAO Qi2, SU Lijun1(), SUN Shangyu1, YUN Lei3, WANG Yiming4   

  1. 1 Hohhot Meteorological Bureau, Hohhot 010010
    2 Tumd Left Banner Meteorological Bureau, Hohhot 010100
    3 Hollinger County Meteorological Bureau, Hohhot 011500
    4 Tokoto County Weather Service, Hohhot 010200
  • Received:2024-07-16 Revised:2025-01-20 Published:2025-07-15 Online:2025-07-21

摘要:

为探究玉米生长发育模拟模型MaizeSM在土默特左旗地区的适用性,本研究采用全局敏感性分析方法确定该模型的敏感性参数。基于2010—2022年试验田玉米品种数据、气象观测站数据、土壤理化数据以及田间管理数据,对模型参数进行本地化调试,从而有效模拟与预测当地玉米不同生长阶段的生长过程和特征,运用实际产量、发育期日数指标对模拟结果进行精度验证。结果显示,该模型存在9个敏感参数,在出苗—拔节阶段,基本发育系数k1的敏感性最高,而开花前茎鞘存储物向籽粒的转运效率参数TR1的敏感性最低。各生育期天数与产量的模拟值和实际值均存在相关性,其中产量的实际值与模拟值相关性最高。此外,归一化均方根误差NRMSE均小于30%,均方根误差RMSE处于合理区间。综上所述,作物模型对当地玉米生长的模拟效果良好。本地化后的玉米生长发育模拟模型MaizeSM参数完善了农业气象服务基于站点尺度的精细化产量预报,进一步提升了农业模型在土默特左旗地区气候变化影响评估、业务及农业生产中的应用能力,有助于农业管理者制定最佳种植策略,实现最优生产效果。

关键词: 模型MaizeSM, 土默特左旗, 适用性, 敏感参数, 本地化调试, 精度验证

Abstract:

In order to assess the suitability of MaizeSM crop model in Tumd Left Banner, a global sensitivity analysis method was employed to identify sensitive parameters of the model. Subsequently, localized model parameters were calibrated using maize variety data from experimental fields, meteorological observations, soil physical and chemical data, and field management records spanning 2010 to 2022. This calibration enabled accurate simulation and prediction of local maize growth processes and characteristics across different stages. Accuracy of simulation results was verified using actual yield and growth period duration indicators. The results showed that findings revealed nine sensitive parameters within the model, with k1 (emerging-joining stage basic development coefficient) being identified as most sensitive while TR1 (stem sheath storage transport efficiency parameter before flowering) exhibited minimal sensitivity. Strong correlations between simulated values for each growth period and actual values were observed, with normalized root-mean-square error (NRMSE) below 30% and root-mean-square error (RMSE) falling within an acceptable range. The crop model can simulate the local maize growth well. The crop model demonstrates good simulation performance for local maize growth. The localized maize growth simulation model, MaizeSM, with improved parameters, has enhanced the refined yield prediction based on station-scale agricultural meteorological services. This further strengthens the application capabilities of agricultural models in climate change impact assessment, operational services, and agricultural production in the Tumd Left Banner region. These advancements assist agricultural managers in formulating optimal planting strategies to achieve maximum production efficiency.

Key words: MaizeSM crop model, Tumd Left Banner, applicability, sensitive parameter, localization debugging, accuracy verification