Content area

Abstract

As a result of climate change, urban areas are increasingly vulnerable to flooding, which can cause devastating effects, both in terms of loss of life and property. Therefore, an accurate assessment of urban flood processes and improved pre-disaster mitigation strategies in threatened areas is essential. Urban flood modeling enables users to understand, assess, and forecast flood conditions as well as their impact. For effective flood modeling, especially in highly urbanized floodplains, model selection based on the contextual requirements is a challenge. This review provides a systematic overview of the application of urban flood modeling approaches from the perspective of urban flood strategy design sequences. In this review, recent research advances are presented as well as suggestions for future research topics that will improve the availability and reliability of urban flood modeling methods. The results of this review will help urban flood managers and potential users balancing model complexity and needs while undertaking effective flood modeling tasks.

Details

Title
A review on applications of urban flood models in flood mitigation strategies
Author
Qi Wenchao 1 ; Ma, Chao 1 ; Xu Hongshi 2 ; Chen Zifan 1 ; Zhao, Kai 1 ; Han, Hao 3 

 Tianjin University, State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin, China (GRID:grid.33763.32) (ISNI:0000 0004 1761 2484); Tianjin University, School of Civil Engineering, Tianjin, China (GRID:grid.33763.32) (ISNI:0000 0004 1761 2484) 
 Zhengzhou University, School of Water Conservancy Engineering, Zhengzhou, China (GRID:grid.207374.5) (ISNI:0000 0001 2189 3846) 
 Xi’an University of Technology, State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Xi’ an, China (GRID:grid.440722.7) (ISNI:0000 0000 9591 9677) 
Pages
31-62
Publication year
2021
Publication date
Aug 2021
Publisher
Springer Nature B.V.
ISSN
0921030X
e-ISSN
15730840
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2555785944
Copyright
© The Author(s), under exclusive licence to Springer Nature B.V. 2021.