摘要
基于CMORPH、CMIP6等数据,采用非线性回归降尺度模型和修正系数法预测了气候变化下大湾区2015—2045年的降水演变;基于土地利用及驱动因子数据等,采用FLUS模型预测了2015—2045年的土地利用变化,最后基于风险评价指标体系对洪涝灾害风险进行预估。结果表明:较高及高洪涝灾害危险性地区主要分布于江门、广州及惠州等地,不同的发展情景(SSP126、SSP245、SSP370、SSP585)和年份下危险性差异较小;较高及高脆弱性地区主要分布在佛山、广州、东莞、深圳,2015—2045年间大湾区脆弱性将显著增加;较高及高敏感性地区主要分布于佛山、广州、东莞、深圳、中山,2015—2045年间大湾区敏感性变化不大;较高及高风险区主要分布于江门、佛山、广州、惠州、东莞,2015—2045年间大湾区洪涝灾害风险将显著增加,不同发展情景下大湾区洪涝灾害风险差别较小。
Based on CMORPH,CMIP6 datasets,etc.,this study used the nonlinear regression downscaling model and correction coefficient method to predict the precipitation changes in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)from 2015 to 2045 under climate change.Based on land use data and other driving factors,the FLUS model was then used to predict the land use change in GBA from 2015 to 2045.Finally,the flood disaster risk from 2015 to 2045 was predicted based on the risk evaluation index scheme.The results show that:(a)Slightly high and high hazard areas are distributed in Jiangmen,Guangzhou and Huizhou,and the risk difference is small under different development scenarios and years;(b)Slightly high and high vulnerabilities are seen in Foshan,Guangzhou,Dongguan and Shenzhen,and the vulnerability of GBA increased significantly from 2015 to 2045;(c)Slightly high and high sensitivities are mainly distributed in Foshan,Guangzhou,Dongguan,Shenzhen and Zhongshan,and the sensitivity of the GBA area exhibits marginal change from 2015 to 2045;(d)Slightly high and high risk are distributed in Jiangmen,Foshan,Guangzhou,Huizhou and Dongguan,and the risk of flood disaster in GBA increased significantly from 2015 to 2045.Under different development scenarios,the risk of flood disaster in GBA exhibits marginal changes.
作者
宋金帛
罗明
张强
SONG Jinbo;LUO Ming;ZHANG Qiang(School of geographic sciences, East China Normal University, Shanghai 200241, China;School of Geographical Science and Planning, Sun Yat-sen University, Guangdong Key Laboratory of Spatial Simulation of Urbanization and Geographical Environment, Guangdong Public Safety and Disaster Engineering Technology Research Center, Guangzhou, Guangdong 510275, China;State Key Laboratory of Earth Surface Processes and Resource Ecology,Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)
出处
《灾害学》
CSCD
北大核心
2022年第2期197-203,211,共8页
Journal of Catastrophology
基金
国家自然科学基金(41771536)
国家重点研发计划项目(2019YFA0606900、2019YFC1510400)。
