Optimization of municipal bridge retrofitting based on nationwide spatial clustering integrating seismic risk and fiscal capacity in Japan

Enhancing seismic resilience in municipalities remains a critical challenge for earthquake-prone countries. Seismic retrofitting of bridges is essential since damage to bridges can significantly delay the post-earthquake recovery process. This study presents a nationwide analytical framework for prioritizing seismic retrofitting of municipally managed bridges. The proposed framework integrates seismic risk, municipal fiscal capacity, spatial interdependence and economic effectiveness. Expected economic loss is estimated as seismic risk for individual bridges using hazard and fragility curves. Municipal recovery capacity is quantified as a resilience indicator by combining the seismic risk with the fiscal reserves available for post-earthquake response. Spatial autocorrelation analysis is applied to examine spatially clustered patterns of recovery capacity beyond administrative boundaries. For municipalities within spatial clusters with low recovery capacity, a budget-constrained optimization problem is formulated to identify candidate bridges for seismic retrofitting. A genetic algorithm is employed to maximize net economic benefits while incorporating the remaining service life of individual bridges. The proposed framework is applied to a nationwide illustrative example in Japan. The results reveal spatial variability in both recovery capacity and the effectiveness of bridge seismic retrofitting. Municipalities exhibiting comparable recovery capacity can obtain different economic benefits from bridge seismic retrofitting. These differences reflect variations in bridge characteristics, such as structural vulnerability, spatial configuration and potential seismic intensity of individual bridges. The framework supports the efficient allocation of limited budgets and identifies municipalities and bridges with high economic benefits from seismic retrofitting. Consequently, practical decision-making that enhances resilience at the municipal scale can be achieved. The framework supports the appropriate allocation of limited budgets and the identification of municipalities and bridges with high economic effectiveness of seismic retrofitting, offering practical decision-making for enhancing resilience at the municipal scale. • The proposed approach supports rational budget allocation for earthquake mitigation. • Municipal recovery capacity is quantified based on seismic risk and fiscal capacity. • Municipal recovery capacity exhibits spatial autocorrelation across Japan. • Spatial clusters of low recovery capacity are observed in several regions of Japan. • Similar recovery capacity can yield different economic benefit from bridge retrofits.

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Publication Details

Journal
International Journal of Disaster Risk Reduction
Published
2026-03-21
DOI
https://doi.org/10.1016/j.ijdrr.2026.106111
Primary Topic
Seismic Performance and Analysis
Type
article
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article

Optimization of municipal bridge retrofitting based on nationwide spatial clustering integrating seismic risk and fiscal capacity in Japan

Hiroki Ishibashi
International Journal of Disaster Risk Reduction
Seismic Performance and Analysis
article

Optimization of municipal bridge retrofitting based on nationwide spatial clustering integrating seismic risk and fiscal capacity in Japan

Hiroki Ishibashi
article en

Abstract

Enhancing seismic resilience in municipalities remains a critical challenge for earthquake-prone countries. Seismic retrofitting of bridges is essential since damage to bridges can significantly delay the post-earthquake recovery process. This study presents a nationwide analytical framework for prioritizing seismic retrofitting of municipally managed bridges. The proposed framework integrates seismic risk, municipal fiscal capacity, spatial interdependence and economic effectiveness. Expected economic loss is estimated as seismic risk for individual bridges using hazard and fragility curves. Municipal recovery capacity is quantified as a resilience indicator by combining the seismic risk with the fiscal reserves available for post-earthquake response. Spatial autocorrelation analysis is applied to examine spatially clustered patterns of recovery capacity beyond administrative boundaries. For municipalities within spatial clusters with low recovery capacity, a budget-constrained optimization problem is formulated to identify candidate bridges for seismic retrofitting. A genetic algorithm is employed to maximize net economic benefits while incorporating the remaining service life of individual bridges. The proposed framework is applied to a nationwide illustrative example in Japan. The results reveal spatial variability in both recovery capacity and the effectiveness of bridge seismic retrofitting. Municipalities exhibiting comparable recovery capacity can obtain different economic benefits from bridge seismic retrofitting. These differences reflect variations in bridge characteristics, such as structural vulnerability, spatial configuration and potential seismic intensity of individual bridges. The framework supports the efficient allocation of limited budgets and identifies municipalities and bridges with high economic benefits from seismic retrofitting. Consequently, practical decision-making that enhances resilience at the municipal scale can be achieved. The framework supports the appropriate allocation of limited budgets and the identification of municipalities and bridges with high economic effectiveness of seismic retrofitting, offering practical decision-making for enhancing resilience at the municipal scale. • The proposed approach supports rational budget allocation for earthquake mitigation. • Municipal recovery capacity is quantified based on seismic risk and fiscal capacity. • Municipal recovery capacity exhibits spatial autocorrelation across Japan. • Spatial clusters of low recovery capacity are observed in several regions of Japan. • Similar recovery capacity can yield different economic benefit from bridge retrofits.

International Journal of Disaster Risk ReductionVol. 138
Nihon University (JP)
Openalex Percentile: Top 13%
Seismic Performance and Analysis
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