Bairu Chen, Zhiguo He, Li Li, Qian Chen, Junyu He, Feixiang Li, Dongdong Chu, Zeng Cao, Xuchao Yang
{"title":"利用开放数据全面评估风暴潮灾害的经济损失:中国舟山案例研究","authors":"Bairu Chen, Zhiguo He, Li Li, Qian Chen, Junyu He, Feixiang Li, Dongdong Chu, Zeng Cao, Xuchao Yang","doi":"10.2166/wcc.2024.731","DOIUrl":null,"url":null,"abstract":"\n \n As climate change continues to worsen, coastal areas are increasingly vulnerable to more frequent and severe storm surges. This poses a significant risk to economic entities, particularly in areas that have undergone rapid development. However, quantitative assessment of economic losses from storm surge disasters in China has been challenging due to limited exposure and vulnerability data. This study proposes a framework for comprehensive economic losses assessment of storm surge disasters using open data, focusing on Zhoushan City as an example. The study quantifies economic loss ratios caused by storm surges by identifying essential urban land use/cover (EULUC) and considering the water depth of different EULUC types for quantitative vulnerability assessment. The study then calculates direct economic losses using the loss ratio maps and gridded gross domestic product data and quantifies indirect economic losses (IEL) using an input–output model to account for inter-industry correlation. Results show that under the scenario of a super typhoon intensity (915 hPa), the total economic loss can reach 131 million CNY, with IEL accounting for 60% of the total. The construction and industrial sectors experience higher IEL due to excessive dependence on upstream and downstream industries, with IEL accounting for approximately 70%.","PeriodicalId":506949,"journal":{"name":"Journal of Water and Climate Change","volume":"45 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comprehensive economic losses assessment of storm surge disasters using open data: a case study of Zhoushan, China\",\"authors\":\"Bairu Chen, Zhiguo He, Li Li, Qian Chen, Junyu He, Feixiang Li, Dongdong Chu, Zeng Cao, Xuchao Yang\",\"doi\":\"10.2166/wcc.2024.731\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n \\n As climate change continues to worsen, coastal areas are increasingly vulnerable to more frequent and severe storm surges. This poses a significant risk to economic entities, particularly in areas that have undergone rapid development. However, quantitative assessment of economic losses from storm surge disasters in China has been challenging due to limited exposure and vulnerability data. This study proposes a framework for comprehensive economic losses assessment of storm surge disasters using open data, focusing on Zhoushan City as an example. The study quantifies economic loss ratios caused by storm surges by identifying essential urban land use/cover (EULUC) and considering the water depth of different EULUC types for quantitative vulnerability assessment. The study then calculates direct economic losses using the loss ratio maps and gridded gross domestic product data and quantifies indirect economic losses (IEL) using an input–output model to account for inter-industry correlation. Results show that under the scenario of a super typhoon intensity (915 hPa), the total economic loss can reach 131 million CNY, with IEL accounting for 60% of the total. The construction and industrial sectors experience higher IEL due to excessive dependence on upstream and downstream industries, with IEL accounting for approximately 70%.\",\"PeriodicalId\":506949,\"journal\":{\"name\":\"Journal of Water and Climate Change\",\"volume\":\"45 2\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Water and Climate Change\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2166/wcc.2024.731\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Water and Climate Change","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/wcc.2024.731","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comprehensive economic losses assessment of storm surge disasters using open data: a case study of Zhoushan, China
As climate change continues to worsen, coastal areas are increasingly vulnerable to more frequent and severe storm surges. This poses a significant risk to economic entities, particularly in areas that have undergone rapid development. However, quantitative assessment of economic losses from storm surge disasters in China has been challenging due to limited exposure and vulnerability data. This study proposes a framework for comprehensive economic losses assessment of storm surge disasters using open data, focusing on Zhoushan City as an example. The study quantifies economic loss ratios caused by storm surges by identifying essential urban land use/cover (EULUC) and considering the water depth of different EULUC types for quantitative vulnerability assessment. The study then calculates direct economic losses using the loss ratio maps and gridded gross domestic product data and quantifies indirect economic losses (IEL) using an input–output model to account for inter-industry correlation. Results show that under the scenario of a super typhoon intensity (915 hPa), the total economic loss can reach 131 million CNY, with IEL accounting for 60% of the total. The construction and industrial sectors experience higher IEL due to excessive dependence on upstream and downstream industries, with IEL accounting for approximately 70%.