Urban flood risk differentiation under land use scenario simulation

被引：22
|
作者：
Zhao, Hongbo [1 ,2 ]
Gu, Tianshun [1 ,2 ]
Tang, Junqing [1 ,2 ]
Gong, Zhaoya [1 ,2 ]
Zhao, Pengjun [1 ,2 ,3 ]
机构：
[1] Henan Univ, Key Res Inst Yellow River Civilizat & Sustainable, Kaifeng 475001, Peoples R China
[2] Henan Univ, Collaborat Innovat Ctr Yellow River Civilizat Join, Minist Educ, Kaifeng 475001, Peoples R China
[3] Peking Univ, Sch Urban Planning & Design, Shenzhen Grad Sch, Shenzhen, Peoples R China
来源：
ISCIENCE | 2023年 / 26卷 / 04期
关键词：
BAYESIAN NETWORK; COVER CHANGE; POPULATION; MANAGEMENT; PATTERN; IMPACT; BASIN;
D O I：
10.1016/j.isci.2023.106479
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
The frequent urban floods have seriously affected the regional sustainable devel-opment in recent years. It is significant to understand the characteristics of urban flood risk and reasonably predict urban flood risk under different land use sce-narios. This study used the random forest and multi-criteria decision analysis models to assess the spatiotemporal characteristics of flood risk in Zhengzhou City, China, from 2005 to 2020, and proposed a robust method coupling Bayesian network and patch-generating land use simulation models to predict future flood risk probability. We found that the flood risk in Zhengzhou City presented an up-ward trend from 2005 to 2020, and its spatial pattern was "high in the middle and low in the surrounding areas". In addition, land use patterns under the sustainable development scenario would be more conducive to reducing flood risk. Our results can provide theoretical support for scientifically optimizing land use to improve urban flood risk management.
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页数：29
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