中国农业气象 ›› 2013, Vol. 34 ›› Issue (04): 447-454.doi: 10.3969/j.issn.1000-6362.2013.04.011

• 论文 • 上一篇    下一篇

CERES Rice模型在江汉平原的验证与适应性评价

曹秀霞,安开忠,蔡伟,苏荣瑞,姚凤梅   

  1. 1中国气象局荆州农业气象试验站,荆州434025;2湖北省监利县气象局,监利433300;3中国科学院计算地球动力学重点实验室,北京100049
  • 收稿日期:2012-11-26 出版日期:2013-08-20 发布日期:2014-01-03
  • 作者简介:曹秀霞(1986-),女,河南商丘人,硕士,助理工程师,主要从事农业气象灾害影响评估研究。Email:caoxxsynx@126.com
  • 基金资助:

    全球变化研究国家重大科学研究计划课题“全球变化影响下主要作物的脆弱性及评价指标”(2010CB951302);湖北省气象局重点项目“湖北水稻籼改粳农业气候资源分析及利用”

Validation and Adaptability Evaluation of CERESRice Model in the Jianghan Plain

CAO Xiu xia, AN Kai zhong, CAI Wei, SU Rong rui, YAO Feng mei   

  1. 1Jingzhou Agriculture Meteorological Experiment Station of China Meteorological Administration, Jingzhou 434025, China; 2Jianli Meteorological Bureau of Hubei Province, Jianli 433300; 3Key Laboratory of Computational Geodynamics, Chinese Academy of Sciences, Beijing 100049
  • Received:2012-11-26 Online:2013-08-20 Published:2014-01-03

摘要: 基于江汉平原武汉、荆州农业气象试验站双季早、晚稻及单季中稻多年田间试验数据和同期逐日气象数据,在利用GLUE参数估计模块结合“试错法”对模型参数标定基础上,对CERESRice模型叶面积指数及生物量动态、发育期、成熟时地上部生物量、产量等的模拟能力进行了验证。结果表明,模型对水稻发育期模拟较好,开花期和成熟期的模拟误差在3d以内,其中对感光性较弱的早稻模拟最好,感光性较强的晚稻模拟最差;生育期内叶面积指数和生物量动态模拟良好,一致性指数分别达0.98和1.0;模拟产量和地上部总生物量的相对均方根误差分别为8.72%和5.91%,总体效果较好,其中生殖关键期遭遇寒露风的晚稻产量NRMSE为11.16%,模拟效果偏差。说明CERES Rice模型在无明显异常天气条件下对江汉平原地区水稻模拟具有较好的适应性,CERES Rice模型可为江汉平原水稻生育期预测提供技术支撑,在考虑极端天气条件胁迫产量形成过程的基础上,可应用于该地区气象影响评价及产量预报业务。

关键词: 水稻, CERES Rice模型, 适应性评价, 江汉平原

Abstract: Daily weather records and observations from paddy rice field experiments at two sites in Jianghan plain (Wuhan and Jingzhou) were used to calibrate and validate the recently released version 4.5 of CERESRice model.The experiments included singleseason rice and doubleseason early rice and late rice.The model was firstly calibrated using the GLUE parameter estimation calculator and trial and error method as a complement, then validated through comparing the observed dynamic leaf area index (LAI) and biomass, development stage (flowering and maturity), total above ground biomass and grain yield with that of simulated. The results showed that the model performed well in development stage simulation, the errors between simulated and measured flowering and maturity date was no more than 3 days, with early rice the most accurate and late rice the least accurate, owing to the differences in photoperiod sensitivity. The simulated and observed of dynamic LAI and biomass during the growing stage showed a consensus trend, with the Index of Agreement(D) of 0.98 and 1.0 respectively, although slight difference existed in specific data. The predicted and observed grain yields and total aboveground biomass were also very close on the whole, with the relative Root Mean Square Error (RMSE) of 8.72% and 5.91% respectively, but a relative large RMSE of 11.6% for late rice for the chilling injury during the flowering stage. The results suggested that the CERES Rice model was able to simulate rice production with good performance in the Jianghan plain under a normal weather condition. This research supports the model application in the Jianghan plain for operational use, such as crop phenology prediction, as well as meteorological effect assessment and yield forecasting provided that effect of extreme weather condition on yield formation was taken into consideration.

Key words: Paddy rice, CERESRice model, Adaptability evaluation, Jianghan plain