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

Expand
  • 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 date: 2011-01-06

  Revised date: 2011-02-20

  Online published: 2011-05-20

Supported by

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

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.

Cite this article

JIA Huicong, WANG Jing'ai, PAN Donghua, CAO Chunxiang . Maize Drought Disaster Risk Assessment Based on EPIC Model: A Case Study of Maize Region in Northern China[J]. Acta Geographica Sinica, 2011 , 66(5) : 643 -652 . DOI: 10.11821/xb201105007

References

[1] National Grain & Oils Information Center, http://www.grain.gov.cn/BigClass.asp?BName=玉米频道. [国家粮油信息中心.http://www.grain.gov.cn/BigClass.asp?BName=玉米频道.]



[2] The Editorial Committee of China Agricultural Statistical Yearbook. China Agriculture Yearbook (2006). Beijing: ChinaAgriculture Press, 2006. [中国农业年鉴编辑委员会. 中国农业年鉴(2006). 北京: 中国农业出版社, 2006.]



[3] Zheng Yuanchang. Review on global natural catastrophes. Natural Disaster Reduction in China, 2000, 10(1): 14-19. [郑远长. 全球自然灾害概述. 中国减灾, 2000, 10(1): 14-19.]



[4] Yue Guidong. Cloning and analyses of genes involved in response to drought stress in maize [D]. Jinan: ShandongUniversity, 2004. [岳桂东. 玉米干旱胁迫相关基因的克隆与分析[D]. 济南: 山东大学, 2004.]



[5] Smith K. Environmental Hazards. London: Routledge, 1996: 389.



[6] BenWisner. At Risk: Natural Hazards, People's Vulnerability and Disasters. London: Routledge, 2000.



[7] IPCC. Climate Change 2001: Impacts, Adaptation and Vulnerability, Summary for Policymakers. WMO, 2001.



[8] Downing T E, Butterfield R, Cohen S et al. Vulnerability Indices: Climate Change Impacts and Adaptation. UNEP PolicySeries, UNEP, Nairobi, 2001.



[9] United Nations. Risk awareness and assessment//Living with Risk. ISDR, UN, WMO and Asian Disaster Reduction Centre,Geneva, 2002: 39-78.



[10] Carreno et al. (Inter-American Development Bank, Colombia University). Indicators of disaster risk and risk managementprogram for Latin America and the Caribbean, 2000.



[11] Perles Roselló M J, Vías Martinez J M, Andreo Navarro B. Vulnerability of human environment to risk: Case ofgroundwater contamination risk. Environment International, 2009, 35(2): 325-335.



[12] Zhang Jiquan, Li Ning. Quantitative Methods and Applications of Risk Assessment and Management on MainMeteorological Disasters. Beijing: Beijing Normal University Press, 2007. [张继权, 李宁. 主要气象灾害风险评价与管理的数量化方法及其应用. 北京: 北京师范大学出版社, 2007.]



[13] UN/ISDR (United Nations International Strategy for Disaster Reduction). Living with Risk: A Global Review of DisasterReduction Initiatives. Geneva: UN/ISDR, 2007.



[14] Liu Jiandong, Wang Shili, Yu Qiang et al. Simulation of impacts of doubled CO2 on the climatic productivity inHuang-Huai-Hai Plain. Journal of Natural Disasters. 2001, 10(1): 17-23. [刘建栋, 王石立, 于强等. CO2倍增对黄淮海气候生产力影响的数值模拟. 自然灾害学报, 2001, 10(1): 17-23.]



[15] Yang Xiu, Sun Fang, Lin Erda et al. Study on the sensitivity and vulnerability of maize to climate change in China. ActaEcologica Sinica, 2005, 24(4): 54-57. [杨修, 孙芳, 林而达等. 我国玉米对气候变化的敏感性和脆弱性研究. 地域研究与开发, 2005, 24(4): 54-57.]



[16] Jia Jianying, Guo Jianping, Peng Ni. Effects of climate change on yield of maize in Northeast China. Journal of AnhuiAgri. Sci., 2010, 38(32): 18309-18312. [贾建英, 郭建平, 彭妮. 气候变化对东北地区玉米产量的影响. 安徽农业科学,2010, 38(32): 18309-18312.]



[17] Tong Pingya. Regionalization of Maize Growing Areas in China. Beijing: China Agricultural Scientech Press, 1992. [佟屏亚. 中国玉米种植区划. 北京: 中国农业科技出版社, 1992.]



[18] Liu Jiyuan, Zhang Zengxiang, Zhuang Dafang et al. A study on the spatial-temporal dynamic changes of land-use anddriving forces analyses of China in the 1990s. Geographical Research, 2003, 22(1): 1-12. [刘纪远, 张增祥, 庄大方等. 20世纪90 年代中国土地利用变化时空特征及其成因分析. 地理研究, 2003, 22(1): 1-12.]



[19] Williams J R, Jones C A, Kiniry J R et al. The EPIC crop growth model. Transactions of the ASAE, 1989, 32(2): 489-511.



[20] Williams J R. The EPIC model. Remple, TX: USDAARS Grassland, Soil andWater Research Laboratory, 1997.



[21] Cai Xitian, Xu Zongxue, Su Baolin et al. Distributed simulation for regional evapotranspiration and verification by usingremote sensing. Transactions of the Chinese Society of Agricultural Engineering, 2009, 25(10): 154-160. [蔡锡填, 徐宗学, 苏保林等. 区域蒸散发分布式模拟及其遥感验证. 农业工程学报, 2009, 25(10): 154-160.]



[22] Leopold C, Krideman P E. Growth and Development of Plant. Beijing: Science Press, 1975. [Leopold C, Krideman P E. 植物的生长和发育. 北京: 科学出版社, 1975.]
Outlines

/