Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Selection of optimal escape routes in a flood-prone area based on 2D hydrodynamic modelling

Guo, Peng, Xia, Junqiang, Zhou, Meirong, Falconer, Roger A. ORCID: https://orcid.org/0000-0001-5960-2864, Chen, Qian and Zhang, Xiaolei 2018. Selection of optimal escape routes in a flood-prone area based on 2D hydrodynamic modelling. Journal of Hydroinformatics 20 (6) , pp. 1310-1322. 10.2166/hydro.2018.161

[thumbnail of 20180705-Final selection of optimal escape routes in flood-prone area(ver.5)_RAF.pdf]
Preview
PDF - Accepted Post-Print Version
Download (3MB) | Preview

Abstract

Optimizing escape routes during an extreme flood event is an effective way to mitigate casualties. In this study, a model for selecting optimal escape routes in a flood-prone area has been proposed, which includes a module for predicting the two-dimensional hydrodynamics and modules for assessing the hazard degree for evacuees, calculation of evacuation times and determination of different escape routes. In the module for determining escape routes, two evacuation schemes were used: Scheme A to find optimal escape routes based on established road networks, and Scheme B to design a new optimal evacuation route. Extreme overbank floods occurred in the Lower Yellow River (LYR) in July 1958 (‘58.7’) and August 1982 (‘82.8’) and the proposed model was applied to select the optimal escape routes on a typical floodplain area of the LYR for these two floods. Model predictions indicated that: (i) the optimal escape routes for these two floods were the same for all three starting locations, and the optimized routes provided 3 h more time for evacuees to escape; and (ii) the time of evacuation would need to be earlier for the ‘58.7’ flood because of its larger amount of water volume and higher peak discharge.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Advanced Research Computing @ Cardiff (ARCCA)
Publisher: IWA Publishing
ISSN: 1464-7141
Funders: Global Challenges Research Fund
Date of First Compliant Deposit: 8 October 2018
Date of Acceptance: 23 July 2018
Last Modified: 20 Nov 2023 00:02
URI: https://orca.cardiff.ac.uk/id/eprint/115622

Citation Data

Cited 4 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics