基于精细化空间格局的城市承灾体脆弱性评估OA北大核心CSTPCD
Assessment on the vulnerability of urban hazard bearing body based on refined spatial patterns
针对目前流域内部跨行政区单元空间精细化模拟并用于评估城市洪涝灾害工作的空白,本文着重聚焦精细化经济指标空间分布并将多源数据融合,构建了基于精细化空间格局的城市承灾体脆弱性评估体系,量化了深圳河流域脆弱性等级.研究结果表明:单一数据不足以准确模拟流域GDP密度,结合多源数据是进行GDP空间精细化更加有效的办法;深圳河流域GDP密度与第二、三产业空间化结果显示出高度一致性,产值密度最高达617 214万元/km2;流域两岸脆弱性等级存在显著差异和区域特征,深圳侧脆弱性明显高于香港侧,高脆弱性地区约占流域面积的8.8%.研究结果有助于识别灾害危险性大小和损失程度,提高城市洪涝灾害评估的精确性.
This study addressed current deficiencies in spatially refined simulation of economic units across administrative regions in a river basin for assessment of the urban flood hazard.Focusing on the spatial distribution of refined economic indicators,and incorporating multiple data sources,an urban flood risk assessment system was constructed for the quantification of the level of flood risk vulnerabilityin the Shenzhen River basin(China).Analysis based on the proposed system revealed the following.① A single datum was found insufficient for accurate simulation of the GDP density of the basin,and combining multisource data representsa more efficient approach for performing spatial refinement of GDP.② A high degree of consistency was evident in termsof the spatialization of GDP density and secondary and tertiary industries in the Shenzhen River basin,with the highest density of production values reaching 6 172.14 million yuan/km2.③ The level of vulnerability was found to vary oneither side of the Shenzhen River basin.The vulnerability to flooding/waterlogging on the Shenzhen side of the river is substantially higher than that on the Hong Kong side,and the area of high vulnerability comprises approximately 8.8%of the total basin area.The results of this study could help both identify the hazard intensity and degree of damage and improve accuracy in urban flooding/waterlogging risk assessment.
徐宗学;唐清竹;陈浩;杨芳
城市水循环与海绵城市技术北京市重点实验室,北京 100875||北京师范大学水科学研究院,北京 100875珠江水利委员会珠江水利科学研究院,广东广州 510611
水利科学
城市洪涝承灾体脆弱性空间精细化深圳河
urban flooding/waterlogginghazard bearing bodyvulnerabilityspatializationrefinementShenzhen River
《水科学进展》 2024 (001)
38-47 / 10
国家自然科学基金资助项目(52079005;52239003)The study is financially supported by the National Natural Science Foundation of China(No.52079005;No.52239003).
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