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CASE STUDY

Overhauling Seismic Risk Frameworks via Advanced Probabilistic Hazus Earthquake Modeling

Replaced an outdated, single-scenario planning model with advanced probabilistic earthquake simulations across multiple return periods to accurately quantify risk and justify future seismic retrofit programs. 

01. Challenge

Advanced Probabilistic and Mitigation Modeling 

A large city’s legacy seismic risk planning relied on a single, deterministic scenario. This model failed to reflect the true geographic diversity of the city or account for the statistical likelihood of varying low-to-extreme seismic intensities. Without detailed, granular risk metrics, emergency managers could not accurately assess potential physical or financial impacts to the city’s complex, multibillion-dollar building stock.

02. Solution

Executing Advanced Probabilistic Intensity and Mitigation Engineering

Our analytics team deployed sophisticated, state-of-the-art Hazus software modeling to execute a series of probabilistic earthquake simulations across low, moderate, and extreme intensities, ranging from 100-year up to extreme 2,500-year return periods. In parallel, we engineered highly customized structural mitigation models to simulate physical interventions, such as retrofitting unreinforced masonry, explicitly calculating the real-world return on investment for resilience options.

03. Impact

Formulating a Definitive Financial Case for Urban Resilience

The resulting risk portfolio provided the agency with its first highly accurate, baseline visualization of multi-hazard seismic vulnerabilities. By converting raw physical stress parameters into defensive financial models, we equipped the agency with the definitive data assets required to justify, prioritize, and capture funding for future seismic retrofit programs, fundamentally protecting critical public infrastructure from future tail-risk events.

100%

Geographic Risk Captured

14

Critical Infrastructure Types Modelled

$21B

Infrastructure Losses Modelled

2500

Maximum Return Period Modeled in Years

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