黄淮海地区夏玉米干旱风险评估与区划

干旱具有发生频率大、持续时间长、发生范围 广、灾害损失重等特点 [12], 其频繁发生和长期持续 给国民经济特别是农业生产带来巨大损失 , 已成为 危害世界包括我国农业在内的最主要的自然灾害之 一 [34], 也是造成玉米减产的主要气象灾害 [5]。 国内外关于农业干旱灾害风险评估的研究已有 很多 , 目前其研究方法主要有两种 : 一是采用单一 指标进行风险评估或区划。 如王积全等 [1,4,69]利用干 旱成灾面积指数或受灾面积指数对甘肃省民勤县、 辽宁省等地区进行了风险评估 ; 陈晓楠等 [10] 将实际 产量资料分离成趋势产量和气象产量 , 利用相对减 产率作为指标 , 针对西安市小麦进行了干旱风险分 析。二是利用自然灾害风险评估原理 [11], 从致灾因 子危险性、孕灾环境敏感性、承载体易损性等多个 方面 , 综合多因素对自然灾害发生及影响风险进行 区划和评估。此类研究成果很多 [1216], 也是近年来 应用较为广泛的方法。 黄淮海地区不仅是我国最大的粮食产区 [17], 也 是我国夏玉米的主产区 [18], 更是干旱灾害易发区和 重灾区。因此加强黄淮海地区夏玉米干旱灾害风险 评估与区划有着重要的现实意义和战略意义。李树 岩等 [19]运用统计学方法分析了黄淮地区降水和夏玉 米产量之间的关系 , 得到降水距平百分率能够反映 干旱对夏玉米产量的影响并可用于损失评估的结论 ; 赵林等 [20] 选用标准降雨指数 (SPI) 分析了黄淮海地 区的干旱时空动态格局 ; 郁凌华 [18] 从气象角度出发 对黄淮海地区涝渍灾损情况进行评估。笔者基于自 然灾害风险评估原理对该地区夏玉米干旱灾害进行 了风险评估和区划。 在基于自然灾害风险原理的灾害综合风险评估 中 , 危险性的评估是重中之重 , 所以危险性指标的 选择显得至关重要。危险性指标多选用降水、标准 降雨指数 (SPI)、降水距平等指数 [2122]按照特定的标 准划分等级 , 评价干旱灾害严重程度 , 然而这些方 法都无法计算出每个干旱等级出现的概率。笔者选 择信息扩散法将降水距平百分率作为灾害致灾因子 危险性的基本指标 , 计算各降水百分率的出现概率 ,
北京
乔赛男 1
哈尔滨
张晓慧 1
150025;
(1. 黑龙江省普通高等学校地理环境遥感监测重点实验室 /哈尔滨师范大学 2. 中国气象科学研究院 100081)
摘
要
黄淮海地区是我国最大的粮食产区和夏玉米的主产区 , 同时也是干旱灾害的频发区 , 因此加强黄淮
海地区夏玉米干旱灾害风险评估与区划有着重要的现实和战略意义。利用黄淮海地区气象数据以及地形、土 地利用类型等数据 , 基于自然灾害风险评估原理 , 运用信息扩散法、加权综合评价法和层次分析法 , 结合 GIS 技术对黄淮海地区夏玉米干旱灾害进行风险性评估与区划。结果表明 : 黄淮海地区夏玉米干旱危险性整体偏 高 , 干旱频率均在 64.36% 以上 , 高危险性等级主要分布在河北省北部和安徽省北部 ; 敏感性偏高 , 高敏感性 等级占总面积的 20.80%, 集中分布于山东省沿海等地 ; 易损性偏低 , 高、中易损性地区占总面积的 22.4%, 各 省均有少量分布 ; 干旱综合风险偏高 , 高、 中综合风险地区占总面积的 68.43%, 整个黄淮海地区除安徽省东南 部外其他地区风险性均较高。 关键词 夏玉米 干旱灾害 风险评估与区划 黄淮海地区 信息扩散法 层次分析法 灾害风险评估原理 中图分类号 : S166 文献标识码 : A 文章编号 : 1671-3990(2015)01-0110-09
* 公益性行业 (气象 )科研专项 (GYHY201306038)资助 ** 通讯作者 : 张丽娟 , 主要从事气象灾害与生态研究。 E-mail: zlj19650205@163.com 杨平 , 主要从事生态系统模拟研究。 E-mail: 250833396@qq.com 收稿日期 : 20140604 接受日期 : 20141112
(1. Key Laboratory of Geographical Environment Remote Sensing Monitoring, Colleges and Universities of Heilongjiang Province/ Harbin Normal University, Harbin 150025, China; 2. Chinese Academy of Meteorological Sciences, Beijing 100081, China)
Risk assessment and zoning of drought for summer maize in the Huang-Huai-Hai Region
YANG Ping1, ZHANG Lijuan1, ZHAO Yanxia2, JIANG Lanqi1, QIAO Sainan1, ZHANG Xiaohui1
中国生态Βιβλιοθήκη Baidu业学报
2015 年 1 月
第 23 卷
第1期
Chinese Journal of Eco-Agriculture, Jan. 2015, 23(1): 110 118
DOI: 10.13930/j.cnki.cjea.140667
黄淮海地区夏玉米干旱风险评估与区划*
杨 平1 张丽娟 1** 赵艳霞 2 姜蓝齐 1
第1期
杨
平等 : 黄淮海地区夏玉米干旱风险评估与区划
111
Province. The drought disaster sensitivity of summer maize in the Huang-Huai-Hai Region was higher, areas with high sensitivity grades accounted for 20.80% of the total area, which was mainly distributed in the coastal areas of Shandong Province. Overall, the region’s drought disaster vulnerability of summer maize was low. The highest and higher vulnerability areas accounted for 22.4% of the total area, and distributed in every province. The comprehensive drought risk index for the whole study area was high with the highest and higher risk areas accounting for 68.43% of the total area. The whole of Huang-Huai-Hai region was in high risk hazard zone, except for southeastern Anhui Province. Keywords Summer maize; Drought disaster; Risk assessment and zoning; Huang-Huai-Hai Region; Information diffusion theory; Analytic hierarchy process; Natural disaster risk assessment principle (Received Jun. 4, 2014; accepted Nov. 12, 2014)
Abstract
The Huang-Huai-Hai Region is one of China’s major grain producing areas, especially summer maize. Thus drought risk
assessment of summer maize in the Huang-Huai-Hai Region is critical in developing countermeasures to ensure grain security. This article assessed and zoned drought risk for summer maize cultivated in the Huang-Huai-Hai Region using the principles of natural disaster risk assessment along with meteorological data, terrain data, land use data and other relevant data in the Huang-Huai-Hai Region. The study also used spatial analysis techniques such as weighted comprehensive analysis (WCA), analytic hierarchy process (AHP) and Geographic Information System (GIS) as well as information diffusion theory. There has been extensive research involving the use of the principles of natural disaster risk assessment in recent years. This study calculated comprehensive drought risk index from three angles — disaster hazard, sensitivity and vulnerability. The selection of hazard index is critical and indicators such as precipitation and standard precipitation index (SPI) hardly precisely calculate the probability distribution of a specific drought index. This defect could be compensated for by using information diffusion theory. Firstly, percent precipitation anomaly was used as basic hazard index in calculating probability distribution based on information diffusion theory. The probability distribution of percent precipitation anomaly was divided by drought grade. Secondly, a weighted comprehensive analysis was conducted to determine hazard degree. The final results were calculated by selecting corresponding indicators for sensitivity and vulnerability. In this way, drought disaster risk for summer maize in the Huang-Huai-Hai Region was zoned based on a comprehensive hazard, sensitivity and vulnerability risk index. The results showed significant spatial differences in hazard sensitivity, vulnerability and comprehensive risk index for summer maize in the Huang-Huai-Hai Region. Drought hazard was relatively high and drought frequency exceeded 64.36%. The highest hazard areas were mainly distributed in the northern parts of Hebei Province and Anhui