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农学学报

农学学报 ›› 2026, Vol. 16 ›› Issue (5): 101-108.doi: 10.11923/j.issn.2095-4050.cjas2025-0081

• 农业信息 农业气象 • 上一篇    

作物模型WOFOST在许昌烟叶生产上的适用性研究

李文峰1(), 金淑媛2,3, 蒲团卫4()   

  1. 1 许昌市气象局， 河南许昌， 461113
    2 湖南省气象服务中心， 长沙 410118
    3 气象防灾减灾湖南省重点实验室， 长沙 410118
    4 河南省烟草公司许昌市公司， 河南许昌 461000
  • 收稿日期:2025-04-10 修回日期:2026-03-23 出版日期:2026-05-20 发布日期:2026-05-15
  • 通讯作者:
    蒲团卫，男，1975年出生，农艺师，主要从事烟草农业推广工作。通信地址：461000 许昌市湖滨路43号 河南省烟草公司许昌市公司，Tel：0374-2188075，E-mail：。
  • 作者简介:

    李文峰，男，1977年出生，河南许昌人，正研级高级工程师，硕士，主要从事农业气象服务技术方面的研究。通信地址：461113 河南省许昌市建安区花都大道与洪河南街交叉口 许昌市气象局，Tel：0374-2334788，E-mail：

  • 基金资助:
    河南省烟草公司许昌市公司科技项目“基于3S与作物模型结合的精细化烟草生产气象保障技术研究”(2024411000240027); 中国气象局/农业农村部烤烟气象服务中心开放式研究基金项目“基于WOFOST模型的豫中浓香型烟叶产量预测技术研究”(KYZX2023-05)

Study on Applicability of WOFOST Model in Xuchang Tobacco Production

LI Wenfeng1(), JIN Shuyuan2,3, PU Tuanwei4()   

  1. 1 Xuchang Meteorological Bureau, Xuchang, Henan 461113
    2 Hunan Provincial Meteorological Service Center, Changsha 410118
    3 Hunan Provincial Key Laboratories of Meteorological Disaster Prevention and Mitigation, Changsha 410118
    4 Henan Tobacco Company Xuchang City Company, Xuchang, Henan 461000
  • Received:2025-04-10 Revised:2026-03-23 Online:2026-05-20 Published:2026-05-15

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摘要：

针对豫中浓香型烤烟生产管理依赖经验、缺乏定量模拟工具的问题，为明确WOFOST模型在许昌烤烟产区的适用性，基于2021—2022年河南烤烟核心产区许昌建安区、襄城县田间观测与气象数据，采用OAT(one-at-a-time)法进行参数敏感性分析，结合“试错法”完成模型本地化校准与独立验证，以决定系数（R2）、拟合度指数（d）、归一化均方根误差（NRMSE）评估模型在叶干重、地上部生物量及叶面积指数的模拟精度。结果表明：（1）在叶干重WLV模拟校准中，WOFOST模型的模拟值与实测值呈显著线性关系，表明模型对叶干重的模拟精度较高；地上部生物量AGP的校准精度也较好；但叶面积指数LAI校准效果不如叶干重和地上部生物量，NRMSE为20%~30%；（2）利用2021年许昌、2022年许昌及襄城的数据对模型进行验证，对于最重要的生物量叶干重模拟效果较好。综合来看，WOFOST模型在验证中表现出较高的精度，90%(8/9)验证数据的R2和一致性指数d整体均高于0.8，近80%(7/9)高于0.9，NRMSE在10%~20%之间，模拟值与实测值的相关性和一致性较好。（3）经过校准与验证，WOFOST模型能够较好地模拟河南许昌烟叶的生长过程，为烟叶生产的定量化和数字化管理提供了基础。后续可耦合遥感数据开展长势监测与产量预报研究。

关键词: 烟草, WOFOST模型, 定量化, 参数本地化, 校准, 验证

Abstract:

To address the issue of relying on experience and lacking quantitative simulation tools in the production management of flue-cured tobacco in central Henan, in order to clarify the applicability of WOFOST model in Xuchang flue-cured tobacco production area, the parameter sensitivity analysis was carried out by OAT (one-at-a-time) method, and the localization calibration and independent verification of the model were completed by ' trial and error method '. The study was based on the field observation and meteorological data of Jian'an District and Xiangcheng County of Xuchang, Henan Province from 2021 to 2022, and the model's simulation accuracy for leaf dry weight (WLV), above-ground biomass (AGP), and leaf area index (LAI) was evaluated using the coefficient of determination (R2), consistency index (d), and normalized root mean square error (NRMSE). The main conclusions are as follows. (1) In the calibration of leaf dry weight (WLV), the simulation values from the WOFOST model showed a significant linear relationship with the observed values, indicating high accuracy in simulating leaf dry weight. The calibration accuracy for above-ground biomass (AGP) was also good. However, the calibration of the leaf area index (LAI) was less accurate, with NRMSE ranging from 20% to 30%. (2) The model was validated using data from Xuchang in 2021, Xuchang and Xiangcheng in 2022, and the simulation results were good for the most important biomass, leaf dry weight. Overall, the WOFOST model showed high accuracy in validation. The R2 and consistency index d of 90 % (8 / 9) validation data were higher than 0.8, nearly 80 % (7 / 9) were higher than 0.9, and NRMSE was between 10 % and 20 %. The correlation and consistency between simulated and measured values were good. (3) After calibration and verification, the WOFOST model could effectively simulate the growth process of tobacco in Xuchang, Henan, providing a foundation for quantitative and digital management of tobacco production. Subsequently, remote sensing data can be coupled to carry out research on crop growth monitoring and yield forecasting.

Key words: tobacco, WOFOST model, quantification, parameter localization, calibration, verification

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