粤港澳大湾区复合灾害系统脆弱性评估

王伟; 宋月; 黄莉; 徐凤凰; 石雨欣

doi:10.3969/j.issn.0258-2724.20240208

粤港澳大湾区复合灾害系统脆弱性评估

doi: 10.3969/j.issn.0258-2724.20240208

王伟^1,,
宋月¹,
黄莉^2, ,,
徐凤凰¹,
石雨欣¹

1.
河海大学港口海岸与近海工程学院，江苏南京 210098
2.
河海大学公共管理学院，江苏南京 211100

基金项目: 国家重点研发计划（2021YFC3001002），国家自然科学基金项目（71974052），国家自然科学基金委员会-联合国环境规划署（NSFC-UNEP）可持续发展国际合作科学计划重点项目“全球变化背景下滨海湿地人海复合系统演变与可持续发展”（42361144873）

详细信息

作者简介:
王伟（1979—），男，博士，教授，研究方向为灾害应急，E-mail：13813826667@163.com

通讯作者:
黄莉（1982—），女，博士，副教授，研究方向为灾害应急，E-mail：lily8214@126.com

中图分类号: TU984
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- 被引次数: 0
出版历程
- 收稿日期: 2024-04-25
- 修回日期: 2024-08-29
- 网络出版日期: 2025-10-21

Vulnerability Assessment of Composite Disaster Systems in Guangdong−Hong Kong−Macao Greater Bay Area

WANG Wei^1
,,
SONG Yue¹,
HUANG Li^{2
, ,},
XU Fenghuang¹,
SHI Yuxin¹

1.
College of Harbour, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China
2.
College of Public Administration, Hohai University, Nanjing 211100, China

摘要

摘要:
自然灾害之间相互作用形成复杂灾害链，致使复合灾害引发的损失更为严重. 为量化复合链生灾害风险并评估区域面对复杂灾害链的脆弱性，有效推进灾害风险防范工作，本文考虑灾害链的触发和叠加（折减）效应，从承灾体暴露度、孕灾环境敏感性和适应性3个维度，构建复合灾害系统脆弱性评估指标体系，进而建立串联式复合灾害承灾体暴露度、孕灾环境敏感性和适应性评估模型，并加权得到串联式复合灾害系统脆弱性评估模型. 以粤港澳大湾区暴雨-滑坡灾害链为例，结合卷积神经网络（CNN）、参数最优地理探测器-层次分析法耦合模型（OPGD-AHP）、序关系法-TOPSIS （technique for order preference by similarity to ideal solution）、熵权-TOPSIS等方法，计算得出粤港澳大湾区暴雨、滑坡，以及暴雨-滑坡灾害链的脆弱性指数，采用ArcGIS工具进一步绘制了对应的脆弱性等级统计图. 研究结果表明：粤港澳大湾区暴雨-滑坡灾害链脆弱性呈现出西部地区多高和较高脆弱区，中西部、西南部和东北部多中脆弱区，中部、中南部和东部多低和较低脆弱区的分布特征；同一区域面对不同单灾种的脆弱性之间，除了叠加关系，还存在一定的触发和协同效应，尤其是在高脆弱区与高脆弱区之间，以及低脆弱区与低脆弱区之间. 成果可在复合灾害系统脆弱性评估工作中推广应用，为我国复合灾害系统风险评估与减灾防灾提供技术支撑.
- 脆弱性评估 /
- 理论模型 /
- 复合灾害 /
- 暴雨-滑坡灾害链 /
- 粤港澳大湾区
Abstract:
The interaction between natural disasters forms a complex disaster chain, making the losses caused by composite disasters more severe. To quantify the risk of disasters caused by complex disaster chains, explore the vulnerability level of regions to complex disaster chains, and effectively promote disaster risk prevention work, the triggering and superposition (reduction) effects of disaster chains were considered. A vulnerability assessment index system for composite disaster systems was constructed from three dimensions: exposure of disaster-bearing bodies, susceptibility, and adaptability of disaster-prone environments. A series of models for assessing the exposure degree of composite disaster-bearing bodies, disaster-prone environmental sensitivity, and adaptability was established through derivation. Subsequently, they were weighted to obtain a series of vulnerability assessment models for composite disaster systems. By taking the rainstorm-landslide disaster chain in the Guangdong−Hong Kong−Macao Greater Bay Area as an example, the vulnerability index of rainstorm, landslide, and rainstorm-landslide disaster chain in the Greater Bay Area was calculated by combining convolutional neural network （CNN）, coupling model of a parameter optimal geographical detector and analytic hierarchy process （OPGD-AHP）, sequence relation method–technique for order preference by similarity to ideal solution (TOPSIS), and entropy weight-TOPSIS, and the corresponding vulnerability level zoning map was further drawn by using ArcGIS tools. The research results indicate that the vulnerability of the rainstorm-landslide disaster chain is high and relatively high in the western region, medium in the central and western regions, as well as southwest and northeast regions, and low and relatively low in the central, central and southern regions, and eastern regions in the Greater Bay Area. There are not only overlapping relationships but also certain triggering and synergistic effects between the vulnerability of different single disaster types in the same region, especially between high vulnerability areas, as well as between low vulnerability areas. The results can be promoted and applied in the vulnerability assessment of composite disaster systems, providing technical support for risk assessment and disaster reduction and prevention of composite disaster systems in China.
- vulnerability assessment /
- theoretical model /
- composite disaster /
- rainstorm-landslide chain /
- Greater Bay Area

HTML全文

图 1 暴雨-滑坡灾害链脆弱性评估流程

Figure 1. Flow chart of vulnerability assessment of rainstorm-landslide disaster chain

下载: 全尺寸图片幻灯片

图 2 粤港澳大湾区暴雨-滑坡灾害链各维度与脆弱性分布

Figure 2. Distribution of dimensions and vulnerability of rainstorm-landslide disaster chain in Greater Bay Area

下载: 全尺寸图片幻灯片

图 3 单灾种与灾害链脆弱性等级分布

Figure 3. Distribution of single disaster type and vulnerability level of disaster chain

下载: 全尺寸图片幻灯片

表 1 暴雨-滑坡灾害链脆弱性评价指标体系

Table 1. Vulnerability assessment index system of rainstorm-landslide disaster chain

维度层	准则层	指标层	涉及灾种
暴露度	社会	居住用地	暴雨、滑坡
		工业用地	暴雨、滑坡
		道路密度	暴雨、滑坡
	人口	人口密度	暴雨、滑坡
	经济	耕地	暴雨、滑坡
	经济	地均 GDP	暴雨、滑坡
敏感性	水文	河网密度	暴雨
	地质	地层岩性	滑坡
	地质	地表温度	暴雨
	地形	高程	暴雨、滑坡
		地形起伏度	暴雨、滑坡
		海岸线距离	暴雨
		坡向	滑坡
		坡度	暴雨、滑坡
	植被	NDVI	暴雨、滑坡
	土地利用	土地利用类型	暴雨、滑坡
	土地利用	土地利用程度	滑坡
适应性	防灾能力	居民人均可支配收入	暴雨、滑坡
		每 10 万常住人口中大学程度人口数	暴雨、滑坡
		堤防长度	暴雨
		地质隐患点防治能力	滑坡
		地质灾害防治资金投入	滑坡
		地质灾害监测预警能力	滑坡
	应灾能力	15 岁以下及 65 岁以上人口比例	暴雨、滑坡
		女性占比	暴雨、滑坡
		每万人拥有医疗机构床位数	暴雨、滑坡
		每万人拥有避灾点数量	暴雨、滑坡
		排水管网密度	暴雨
		水库库容占比	暴雨
		政府应急救援能力	暴雨、滑坡
		应急物资储备能力	暴雨、滑坡

下载: 导出CSV

表 2 粤港澳大湾区暴雨-滑坡灾害链脆弱性评估方法

Table 2. Vulnerability assessment methods of rainstorm-landslide disaster chain in Greater Bay Area

维度	权重确定方法	指标计算方法
暴露度	序关系分析法	TOPSIS 法
敏感性	OPGD-AHP 耦合模型 CNN 模型	ArcGIS 平台空间加权叠加
适应性	熵权法	TOPSIS 法

下载: 导出CSV

表 3 暴雨、滑坡灾害暴露度评估指标对应权重

Table 3. Weight of assessment indexes for rainstorm and landslide exposure degrees

指标	暴雨	滑坡
地均 GDP	0.22	0.18
耕地占比	0.1	0.12
居住用地占比	0.16	0.17
工业用地占比	0.1	0.14
道路密度	0.19	0.14
人口密度	0.23	0.25

下载: 导出CSV

表 4 暴雨-滑坡转化阈值与转化概率

Table 4. Threshold and probability of rainstorm-landslide transformation

降雨量区段/ mm	占降雨总样本比例/%	该降雨区段滑坡样本数占全部位移点数比例/%
0～83.45	95.17	34.81
83.45～312.60	4.83	37.50
312.60 以上	0	0

下载: 导出CSV

表 5 暴雨灾害适应性评估指标对应权重

Table 5. Index weight of rainstorm adaptability assessment

指标	权重
堤防长度	0.24
居民人均可支配收入	0.14
每 10 万常住人口中大学程度人口数	0.09
每万人拥有医疗机构床位数	0.10
每万人拥有避灾点数量	0.06
应急物资储备能力	0.14
排水管道密度	0.03
水库库容占比	0.04
政府应急救援能力	0.08
15 岁以下及 65 岁以上人口比例	0.05
女性占比	0.03

下载: 导出CSV

表 6 滑坡灾害适应性评估指标对应权重

Table 6. Index weight of landslide adaptability assessment

指标	权重
地质隐患点防治能力	0.14
地质灾害防治资金投入	0.11
地质灾害监测预警能力	0.15
居民人均可支配收入	0.16
每 10 万常住人口中大学程度人口数	0.06
每万人拥有医疗机构床位数	0.04
每万人拥有避灾点数量	0.03
应急物资储备能力	0.08
政府应急救援能力	0.06
女性占比	0.08
15 岁以下及 65 岁以上人口比例	0.09

下载: 导出CSV

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