中国农业气象

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利用风险预测方法甄选农业气象灾害指标初探

侯双双;姜会飞;廖树华;高静;肖静;霍治国;   

  1. 中国农业大学资源与环境学院;中国农业大学农学与生物技术学院;中国气象科学研究院;
  • 出版日期:2010-06-10 发布日期:2010-06-10
  • 基金资助:
    国家“十一五”科技支撑项目(2007BAC29B05;2008BAK50B02);; 教育部高等学校科技创新工程重大项目培育资金项目(708013)

Agro-meteorology Disaster Index Selection Based on Risk Prediction Method

HOU Shuang-shuang1,JIANG Hui-fei1,LIAO Shu-hua2,GAO Jing1, XIAO Jing1,HUO Zhi-guo3(1.College of Resources and Environment Science,China Agricultural University, Beijing 100193,China;2.College of Agriculture and Biotechnology,China Agricultural University,Beijing 100193;3.Chinese Academy of Meteorological Sciences,Beijing 100081)   

  • Online:2010-06-10 Published:2010-06-10

摘要: 农业气象灾害指标的确定是进行农业气象灾害预测预报和防灾减灾的基础,本文运用风险预测方法探索农业气象灾害指标的甄选。以农业旱涝指标K和降水距平百分率Pa为例,分别构建山西运城冬小麦1981-2000年、1981-2001年和1981-2002年播种-成熟、返青-拔节和拔节-成熟等3个生育阶段K指标和Pa的时间序列,运用马尔柯夫转移概率和农业气象灾害指标时间序列的概率密度函数对2001-2003年农业旱涝状态进行风险预测。结果表明,K指标预测状态与实际一致,而Pa效果较差,说明K指标在反映山西运城冬小麦旱涝指标上比Pa应用效果要好。同时研究也表明,运用风险预测方法甄选农业旱涝灾害指标是一种简单、快捷和有效的农业气象灾害指标挑选方法。

关键词: 旱涝指标, 马尔柯夫随机过程, 转移概率, 风险预测

Abstract: Index selection was basic for forecast and prediction,mitigation and prevention to agro-meteorology disasters.A case study on crop drought-flood index(K) and precipitation anomaly percentage(Pa) was conducted.A series of time sequences on K and Pa about three growth stage of winter wheat(sowing to mature,regreen to jointing,jointing to mature) during 1981-2000,1981-2001,1981-2002,was established in Yuncheng,Shanxi province.Drought and flood disasters during 2001-2003 were predicted by using Markov model and probability distribution function.The results showed that prediction based on K was consistent with the real situation from 2001 to 2003,as the relative veracity was only 55.5% based on Pa.It was indicated that the K as crop drought and flood index was more effective than Pa.The method of selection agro-meteorology disaster index based on risk prediction was simple and convenient,which could recommend to a new method for selecting agro-meteorology index.

Key words: Index of drought and flood, Index of drought and flood, Markov random process, Transfer probability, Risk prediction