基于情景模拟的洪涝灾害经济损失动态评估

苏鑫; 邵薇薇; 刘家宏; 蒋云钟; 邵蕊; 王开博

doi:10.16511/j.cnki.qhdxxb.2022.22.040

清华大学学报（自然科学版） >

2022 , Vol. 62 >Issue 10: 1606 - 1617

DOI: https://doi.org/10.16511/j.cnki.qhdxxb.2022.22.040

防灾减灾

基于情景模拟的洪涝灾害经济损失动态评估

苏鑫 ,
邵薇薇 ,
刘家宏 ,
蒋云钟 ,
邵蕊 ,
王开博

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1. 中国水利水电科学研究院流域水循环模拟与调控国家重点实验室, 北京 100038;
2. 清华大学水利水电工程系, 水沙科学与水利水电工程国家重点实验室, 北京 100084;
3. 国家开发银行四川分行, 成都 610041

收稿日期: 2022-02-22

网络出版日期: 2022-09-03

基金资助

邵薇薇,正高级工程师,E-mail:shaoww@iwhr.com

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Dynamic assessment of economic losses from flood disasters based on scenario simulations

SU Xin ,
SHAO Weiwei ,
LIU Jiahong ,
JIANG Yunzhong ,
SHAO Rui ,
WANG Kaibo

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1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China;
2. State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China;
3. Sichuan Branch, China Development Bank, Chengdu 610041, China

Received date: 2022-02-22

Online published: 2022-09-03

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摘要

洪涝灾害损失评估是进行洪涝灾害管理的重要手段,对于防灾减灾具有重要意义。鉴于当前研究存在多以静态评估为主、缺少高分辨率的国民生产总值(GDP)空间分布数据、产业关联损失评估对象较为单一等问题,该文模拟了设计暴雨情景下的城市洪涝过程,基于土地利用数据、兴趣点数据(POI)和随机森林回归模型得到了高分辨率的GDP空间分布数据。在Python环境下利用Arcpy库将城市洪涝演进过程与社会经济数据进行空间拓扑叠加,获取了洪涝灾害直接经济损失的发展过程,再利用投入产出模型量化了由于产业间关联造成的间接经济损失。以位于广东省中山市和珠海市交界处的前山河流域为研究区,对50 a一遇设计暴雨情景下洪涝灾害造成的直接经济损失进行了动态评估,并量化了相应的产业关联经济损失。结果表明:洪涝灾害经济损失在不同行业的发展规律存在差异,积水量与积水深度最大的时刻并不一定是经济损失最大的时刻,间接经济损失在洪涝灾害损失中所占比例约为47%,部分行业间接经济损失甚至超过了直接经济损失,应该引起足够的重视。该研究可以丰富洪涝灾害损失评估方法,为防灾减灾的决策部署和灾后产业结构的调整提供技术支持。

关键词： 洪涝灾害; 直接经济损失; 间接经济损失; 动态评估

本文引用格式

苏鑫 , 邵薇薇 , 刘家宏 , 蒋云钟 , 邵蕊 , 王开博 . 基于情景模拟的洪涝灾害经济损失动态评估[J]. 清华大学学报（自然科学版）, 2022 , 62(10) : 1606 -1617 . DOI: 10.16511/j.cnki.qhdxxb.2022.22.040

Abstract

Flood loss assessments are an important part of flood management for disaster prevention and mitigation.Most previous research on flood losses has been based on static assessments without high-resolution GDP spatial distribution data with only single industry-related loss assessment objectives.This study simulated urban flooding for a design storm scenario to obtain high-resolution spatial distribution GDP based on land use data,point of interest (POI) data and a random forest regression model.The Arcpy library in Python was used to superimpose the urban flood areas on spatial topology social economic data to predict the direct economic losses due to the flood.An input-output model was used to quantify the indirect economic losses caused by inter-industry linkages.The Qianshan River Basin between Zhongshan and Zhuhai cities in Guangdong Province,China was used as an example to predict the direct economic losses caused by a 50 year design rainstorm and the corresponding industry-related economic losses.The results show differences in the flood economic losses for different industries.The time with greatest flood volume and inundation depth do not necessarily correspond to the time with greatest economic losses.The indirect economic losses account for about 47% of the flood losses and the indirect economic losses of some industries even exceed the direct economic losses,which should receive more attention.This study improves flood loss assessment methods and provides technical support for disaster prevention and mitigation decision-making and industrial structural changes after flooding.

Key words： flood disaster; direct economic loss; indirect economic loss; dynamic assessment

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