地理学报 ›› 2011, Vol. 66 ›› Issue (5): 643-652.doi: 10.11821/xb201105007

• 生态评价 • 上一篇    下一篇

基于EPIC模型的黄淮海夏玉米旱灾风险评价

贾慧聪1,2, 王静爱1,3,4, 潘东华5, 曹春香2   

  1. 1. 北京师范大学地理学与遥感科学学院, 北京 100875;
    2. 遥感科学国家重点实验室(中国科学院遥感应用研究所), 北京 100101;
    3. 区域地理研究重点实验室(北京师范大学), 北京 100875;
    4. 地表过程与资源生态国家重点实验室(北京师范大学), 北京 100875;
    5. 民政部国家减灾中心, 北京 100022
  • 收稿日期:2011-01-06 修回日期:2011-02-20 出版日期:2011-05-20 发布日期:2011-05-20
  • 通讯作者: 王静爱(1955-), 女, 满族, 河北定州人, 教授, 主要从事自然灾害与区域地理研究。E-mail: sqq@bnu.edu.cn
  • 作者简介:贾慧聪(1981-), 女, 山东聊城人, 助理研究员, 主要从事自然灾害风险评估研究。E-mail: jiahc@irsa.ac.cn
  • 基金资助:

    国家科技支撑计划项目(2006BAD20B03)

Maize Drought Disaster Risk Assessment Based on EPIC Model: A Case Study of Maize Region in Northern China

JIA Huicong1,2, WANG Jing'ai1,3,4, PAN Donghua5, CAO Chunxiang2   

  1. 1. School of Geography, Beijing Normal University, Beijing 100875, China;
    2. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of CAS and Beijing Normal University, Beijing 100101, China;
    3. Key Laboratory of Regional Geography, Beijing Normal University, Beijing 100875, China;
    4. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China;
    5. National Disaster Reduction Center of China, Ministry of Civil Affairs of the People's Republic of China, Beijing 100022, China
  • Received:2011-01-06 Revised:2011-02-20 Online:2011-05-20 Published:2011-05-20
  • Supported by:

    National Key Technologies R&D Program of China, No.2006BAD20B03

摘要: 玉米是中国最主要的粮食作物之一,因其较高的需水量,受气候影响,极易遭受旱灾。因此,以黄淮海夏播玉米区为例,从风险的角度进行玉米旱灾评价,对于农业旱灾预警和保障国家粮食安全具有重要的现实和指导意义。在全面收集研究区气象、土壤、土地利用、农气观测等资料的基础上,基于农业旱灾风险评价的概念框架“致灾因子危险性H评价(Hazard)—承灾体脆弱性曲线Vc 评价(Vulnerability Curve)—作物减产风险性R评价(Risk)”,引入基于物理过程的作物模型EPIC (Erosion Productivity Impact Calulator),采用作物模型模拟和数字制图等技术,分别从全生育期和分生育期角度,对黄淮海夏播玉米区玉米旱灾风险的时空分布进行了定量评价。结果表明:在2、5、10 和20 年一遇致灾水平下,黄淮海夏播玉米区玉米旱灾减产风险总体呈现出从西北向东南方向递减的趋势,这主要由气候环境和下垫面的地形地貌条件所决定。20 年一遇水平时,产量损失风险的高值区(R ≥ 0.5) 集中分布在冀北高原山地和山东省中南部地区,占黄淮海夏播玉米区玉米总面积的7.63%。黄淮海夏播玉米区成灾风险较高的生育期:拔节期—抽雄期、抽雄期—乳熟期、乳熟期—成熟期应加强防范。研究可为高风险区和高风险时段的玉米旱灾风险防范提供理论依据和科技支撑。

关键词: 脆弱性曲线, 风险评价, 旱灾, 玉米产量, EPIC模型, 黄淮海夏播玉米区

Abstract: As the global climate change and food security became an increasingly important issue, agriculture drought comes to the focus of attention. China is a typical monsoon climate country as well as an agricultural country with the world's largest population. The East Asian monsoon has had a tremendous impact on agricultural production. Therefore, a maize drought disaster risk assessment, in line with the requirements of sustainable development of agriculture, is important to drought disaster reduction and food security. This study collected information on meteorology, soil, land use and agro-meteorological observation of the research area, and quantitative assessment was done to present spatio-temporal distribution of maize drought in maize region of northern China based on the concept framework of "Hazard-inducing factors assessment (Hazard)-Vulnerability assessment of hazard-affected body (Vulnerability Curve)-Risk assessment (Risk)", importing crop model EPIC (Erosion Productivity Impact Calculator), and using crop model simulation and digital mapping techniques, from the point of view of whole growth period and sub-growth period. The results showed that in terms of 2-, 5-, 10- and 20-year return periods, the overall maize drought risk decreased gradually from northwest to southeast in the maize planting areas. In the 20-year return period, high risk value regions (maize risk level ≥ 0.5) are concentrated in northern Hebei plateau and central and southern parts of Shandong Province, accounting for 7.63% of the total maize area. The high risk maize growing periods of maize region in northern China were heading - tasseling period, tasseling - milking period and milking - mature period, which should be paid more attention. This paper may provide theoretical basis and technological support for maize drought risk prevention and mitigation of high-risk areas and high-risk periods.

Key words: physical vulnerability curve, risk assessment, agriculture drought, maize production, EPIC model, maize region of northern China