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自然资源学报 >

2018 , Vol. 33 >Issue 4: 684 - 695

DOI: https://doi.org/10.11849/zrzyxb.20170392

资源研究方法

基于自助法与云模型的区域旱灾风险评估及区划研究

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  • 1.合肥工业大学 a. 土木与水利工程学院, b. 水资源与环境系统工程研究所,合肥 230009;
    2.蚌埠学院机械与车辆工程学院,安徽 蚌埠 233030;
    3.安徽省水利部淮河水利委员会水利科学研究院,水利水资源安徽省重点实验室,安徽 蚌埠 233000
吴成国（1982- ）,男,甘肃民乐人,讲师,研究方向为水资源系统工程。E-mail: wule9825@163.com

收稿日期: 2017-04-27

  修回日期: 2017-11-07

  网络出版日期: 2018-04-10

基金资助

国家重点研发计划项目（2017YFC1502405）;国家自然科学基金项目（51579059,51579060,51709071）;山东省重点研发计划项目（2017GSF20101）;安徽省高校自然科学研究项目（113052015KJ04）

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Risk Assessment and Division Model for Regional Drought Disaster Based on Cloud Model and Bootstrap Method

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  • 1.a. School of Civil and Hydraulic Engineering, b. Institute of Water Resources and Environmental Systems Engineering, Hefei University of Technology, Hefei 230009, China;
    2. School of Mechanical and Vehicle Engineering, Bengbu College, Bengbu 233030, China;
    3. Water Resources Research Institute of Anhui Province and Huaihe River Commission, MWR, Bengbu 230088, China

Received date: 2017-04-27

  Revised date: 2017-11-07

  Online published: 2018-04-10

Supported by

National Key Research and Development Program of China, No. 2017YFC1502405;National Natural Science Foundation of China, No. 51579059, 51579060 and 51709071;Key Research and Development Program of Shandong Province, No. 2017GSF20101;Natural Science Research Project of Universities in Anhui Province, No. 113052015KJ04.

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摘要

区域旱灾风险评估与区划是科学揭示旱灾风险系统要素相互作用与演变机制的基础性工作,可为制定区域旱灾风险防控措施、实现旱灾风险管理提供合理有效的决策依据。为系统描述区域旱灾风险系统包含的随机性、模糊性及未确知性等复杂不确定性信息,论文基于随机抽样Bootstrap方法在合理构建区域旱灾风险系统样本方案集的基础上,将传统的确定性旱灾等级标准进行云化处理,采用正向正态云算法对区域因旱受灾风险系统Bootstrap样本集进行风险估计,并借助ArcGIS自然间断点分级法对区域旱灾风险分布状况进行区划研究,最终建立了基于自助法与云模型的区域旱灾风险评估及区划模型。该模型在安徽省的应用结果表明：1）云模型方法能较好地描述旱灾风险系统的不确定性,计算所得的旱灾风险率区间估计结果能进一步反映风险内涵;2）淮北平原（阜阳市、宿州市、亳州市、滁州市）、江淮丘陵地区（六安市）及皖东南山区（黄山市、池州市）未来发生旱灾风险事件的总体概率较大,是安徽省旱灾风险管理的重点区域。可见,采用云模型方法进行旱灾风险评估能进一步降低旱灾风险系统不确定性对评估结果的误差影响,对区域旱灾风险评估及区划的理论与实践研究具有参考应用价值。

关键词： 安徽省; 风险率; 旱灾风险评估; 正向正态云算法; 自助法

本文引用格式

吴成国, 白露, 白夏, 金菊良, 蒋尚明 . 基于自助法与云模型的区域旱灾风险评估及区划研究[J]. 自然资源学报, 2018 , 33(4) : 684 -695 . DOI: 10.11849/zrzyxb.20170392

Abstract

Regional drought disaster risk assessment and division is a basic work for scientifically revealing the element mutual interaction and evolution mechanism of drought disaster risk system and can provide reasonable decision-making basis for developing drought disaster risk prevention and control measures and realizing drought disaster risk management. In order to effectively describe the uncertainties, including randomness, fuzziness and unascertained characteristics of regional drought disaster risk system, firstly, the Bootstrap sample set of regional drought disaster risk system was established using the random sampling method. Then, after fuzzily processing the traditional drought disaster grade standard using the Cloud Theory, the forward and normal cloud algorithm was proposed for interval estimation analysis of the Bootstrap sample set. Besides, the natural breaks classification method in ArcGIS was used to analyze the regional drought disaster risk distribution. Finally, the risk assessment and division model for regional drought disaster based on Cloud Model and Bootstrap Method (CMBM) was proposed in this paper. The results of applying the model in Anhui Province indicate that: 1) The Cloud Model theory can describe the uncertainties of drought disaster system better, and the interval assessing results of drought disaster risk can further reveal the nature of risk. 2) The overall risk probability of drought disaster in Huaibei Plain (Fuyan, Suzhou, Bozhou and Chuzhou), Jianghuai Hilly Region (Lu’an) and southeast area of Anhui Province (Huangshan, Chizhou) is relatively high in the future, so more attention should be paid in these areas to prevent drought disaster. This study proposed a scientific and effective drought disaster risk assessment and division model based on Cloud Model and Bootstrap Method, and the model can further decrease the influence of the uncertainties of drought disaster risk system on assessment results. The paper has a great theoretical significance in guiding regional drought disaster risk assessment and division.

Key words： Anhui Province; Bootstrap Method; drought disaster risk assessment; forward and normal cloud algorithm; risk rate

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