A study on siting of emergency shelters for dam failure floods considering population distribution and weather effects

Journal Article (2024)
Author(s)

Yutie Jiao (Zhengzhou University)

Zongkun Li (Zhengzhou University)

Wei Ge (Yellow River Engineering Consulting Co, Zhengzhou University)

Laihong Jing (Yellow River Engineering Consulting Co)

Meimei Wu (Henan University of Technology, Zhengzhou )

Te Wang (Zhengzhou University)

Heqiang Sun (Zhengzhou University)

Jianyou Wang (Zhengzhou University)

Xiangyang Zhang (Zhengzhou University)

Pieter van Gelder (TU Delft - Technology, Policy and Management)

Research Group
Safety and Security Science
DOI related publication
https://doi.org/10.1016/j.scitotenv.2024.169901 Final published version
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Publication Year
2024
Language
English
Research Group
Safety and Security Science
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Journal title
Science of the Total Environment
Volume number
914
Article number
169901
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Institutional Repository

Abstract

In recent years, dam failures have occurred frequently because of extreme weather, posing a significant threat to downstream residents. The establishment of emergency shelters is crucial for reducing casualties. The selection of suitable shelters depends on key information such as the number and distribution of affected people, and the effective capacity and accessibility of the shelters. However, previous studies on siting shelters did not fully consider population distribution differences at a finer scale. This limitation hinders the accuracy of estimating the number of affected people. In addition, most studies ignored the impact of extreme rainfall on the effective capacity and accessibility of shelters, leading to a low applicability of the shelter selection results. Therefore, in this study, land-use and land-cover change (LUCC) and nighttime lighting data were used to simulate population distribution and determine the number and distribution of affected people. Qualified candidate shelters were obtained based on screening criteria, and their effective capacity and accessibility information under different weather conditions were quantified. Considering factors such as population transfer efficiency, construction cost and shelter capacity constraints, a multi-objective siting model was established and solved using the non-dominated sorting genetic algorithm II (NSGA- II) to obtain the final siting scheme. The method was applied to the Dafangying Reservoir, and the results showed the following: (1) The overall mean relative error (MRE) of the population in the 35 downstream streets was 11.16 %, with good fitting accuracy. The simulation results truly reflect the population distribution. (2) Normal weather screening generated 352 qualified candidate shelters, whereas extreme rainfall weather screening generated 266 candidate shelters. (3) Based on the population distribution and weather factors, four scenarios were set up, with 63, 106, 73, and 131 shelters selected. These two factors have a significant impact on the selection of shelters and the allocation of evacuees, and should be considered in the event of a dam-failure floods.