NATURAL DISASTER LOSSES, RECOVERY AND RESILIENCE

Geotehnički aspekti građevinarstva i zemljotresno inženjerstvo 2025, Vrnjačka Banja, 15 – 17. oktobar 2025. (pp. 7-9) 

 

АУТОР(И) / AUTHOR(S): Božidar Stojadinović

 

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DOI: 10.46793/GEOAG25.007S

САЖЕТАК / ABSTRACT:

 Earthquake disaster resilience of communities involves a complex interplay between social and technical factors, making it essential to account for their interdependencies when simulating recovery processes. This paper presents an agent-based model that simulates the long-term household recovery, capturing how earthquakes impact households and how households restore their well-being alongside the recovery of technical systems. Building on the Capabilities-based Interface for Socio-Technical Resilience (CI-STR) framework [1], the agent-based model (ABM) adopts human capabilities as primary drivers of household decision-making to cope with disaster impacts. The ABM uses household well-being deprivations as motivators, and postulates attainment of human capabilities as drivers for households to adapt and recover after earthquake disasters. A dynamic feedback loop in the simulation links household agents with the community’s technical systems: the community services act as inputs to support various capabilities, while outputs from households, including well-being assessments and coping actions, affect service demand and workforce availability. Modeling the damage and recovery of community’s technical systems is done using the pyrecodes resilience modeling and quantification framework [2].

The integrated CI-STR-pyrecodes model (Figure 1) is demonstrated in a semi-virtual case study by simulating a post-earthquake recovery scenario in the city of Alameda, California (Figure 2). By focusing on residential mobility as the main coping strategy, this case study examines the initial household displacement patterns driven by changes in capability attainment and well-being states, shows how these shifts subsequently influence the operation and recovery of technical systems, and extends the modeling timeline to capture the return of the households after their residences (houses) and the infrastructure systems that serve them have been repaired and restored to their functions.

The integrate CI-STR-pyrecodes model can be linked to the Swiss Earthquake Risk model [3] to enable studies of possible population displacement demands after a strong earthquake in Switzerland, as well as to anticipate the actions needed and the timelines required to facilitate a successful return of the displaced households to the earthquake-affected communities. The same resilience assessment can be done for Serbia, building on the work on seismic exposure [4}, fast risk assessment [5] and recovery (rebuilding) cost and time estimation [6].

КЉУЧНЕ РЕЧИ / KEYWORDS:

ПРОЈЕКАТ / ACKNOWLEDGEMENT:              

REFERENCES / ЛИТЕРАТУРА:

  • Tseng, T.-H., and Stojadinović, B., 2024. CI-STR: A capabilities-based interface to model socio-technical systems in disaster resilience assessment. International Journal of Disaster Risk Reduction, 111, 104763. https://doi.org/10.1016/j.ijdrr.2024.104763
  • Blagojević, N. and Stojadinović, B., 2022. A demand-supply framework for evaluating the effect of resource and service constraints on community disaster resilience. Resilient Cities and Structures, 1(1), 13–32. https://doi.org/10.1016/j.rcns.2022.03.001
  • Blagojević, N. A. Papadopoulo, L. Danciu and B. Stojadinović, Extending Naitonal Seismic Risk Models to Assess Regional Recovery Capabilities and Community Resilience: Case Study – Basel, Switzerland, Proceedings of the 18th World Conference on Earthquake Engineering (WCEE2024), June 30 – July 5, 2024, Milan, Italy.
  • Blagojevic, N. S. Brzev, M. Petrovic, J. Borozan, B. Bulajic, M. Markovic, M. Hadzima-Nyarko, V. Kokovic and B. Stojadinovic, “Residential Building Stock in Serbia: Classification and Vulnerability for Seismic Risk Studies”, Bulletin of Earthquake Engineering, vol. 21, pp. 4315-4383, on-line 10.04.2023, https://doi.org/10.1007/s10518-023-01676-0
  • Stojadinovic, Z., M. Kovacevic, D. Markovic and B. Stojadinovic, “Rapid Earthquake Loss Assessment Based on Machine Learning and Representative Sampling”, Earthquake Spectra, vol. 38, no. 1, pp. 152-177, February 2022, on-line September 6, 2021. https://doi.org/10.1177/87552930211042393
  • Stojadinovic, Z., M. Kovacevic, D. Marinkovic, B. Stojadinovic, “Data-Driven Housing Damage and Repair Cost Prediction Framework Based on the 2010 Kraljevo Earthquake Data”, Proceedings of the 16th World Conference on Earthquake Engineering (16WCEE), Paper #4987, January 9-13 2017, Santiago, Chile.