基于Mixed-MRIO模型的湖北省洪涝灾害脆弱性区域产业识别

Identifying Vulnerable Regions and Sectors to Flood Disaster Using Mixed-MRIO Model in Hubei Province

随着区域经济一体化发展,某地区遭受洪涝灾害会通过产业关联对灾区外造成波及影响,准确预估其影响大小有助于城市产业的规划建设。构建直接、波及损失集成评估框架,利用功能脆弱性曲线估算不同超大规模淹没情景下受灾区各产业部门的直接损失,将其设置为外生冲击变量,输入混合多区域投入产出模型(Mixed-MRIO Model),评估灾区外的波及损失,识别湖北省内洪涝灾害脆弱性区域及产业部门。主要结论如下:(1)武汉市中度淹没情景下造成的波及损失是直接损失的36.61%;(2)从区域关联角度分析,荆门市和荆州市与省内其他区域的产业后向关联较为紧密且更加脆弱,在超大规模洪涝灾害冲击数值模拟中所遭受的损失始终位于前列,二者平均损失值约为损失值最小的天门神农架地区的4.8和4.2倍;(3)从产业关联角度分析,省内发生洪涝灾害造成的波及影响主要集中在农业、生活相关制造业以及居民服务业与交通运输、仓储和邮政业等生产性服务业,其中损失值最大的生活相关制造业是损失最小的科学研究和技术服务业的百倍之多。研究结果可为政府制定防灾减灾政策、灾后重建决策等提供参考。

Under the background of climate change and regional economic integration,flood disasters occurred in a certain place will have serious ripple effects on external regions through industrial correlation,although these regions are far apart in space.Accurate estimation of the ripple effect is helpful for policy-makers to formulate industrial layout plan and improve the efficiency of flood management.The purpose of this research is to construct an integrated framework for estimating the direct and ripple losses at the same time.The specific steps to build the framework are as follows.First,using functional fragility curves to estimate the direct losses of various sectors in the stricken area under simulate scenarios of different massive inundation.Then,based on the mixed multiregional input-output model,this study uses the direct losses data as exogenous variables to evaluate the ripple losses outside the stricken area under different inundation depths.Vulnerable regions and industrial sectors in Hubei Province can be identified by aggregating data from simulations across different regions.The main findings are as follows:(1)The ripple losses caused by Wuhan City under the moderate inundation scenario is 36.61%of the direct losses.(2)From the perspective of regional correlation,Jingmen City and Jingzhou City are more vulnerable,which are closely linked with other regions in Hubei Province.Because these two cities have always suffered huge losses in the numerical simulation of massive flood disaster.The average ripple loss of these two cities is about 4.8 times and 4.2 times that of Tianmen and Shennongjia area,which has the smallest ripple loss.(3)From the perspective of industrial sectors correlation,the ripple economic impact of flood disasters is mainly concentrated in agriculture,livelihood-related manufacturing,residential services,as well as transport,storage and postal services.Among them,the livelihood-related manufacturing with the largest loss is even a hundred times more than the scientific research and technical service.The results can provide reference for the government to formulate disaster prevention and mitigation policies and make post-disaster reconstruction decisions.