Influence of local versus national datasets on seismic loss estimates: A case study for residential buildings in the metropolitan area of Montreal, Canada

Abstract

Assessing seismic losses requires information on ground shaking levels, a comprehensive inventory of elements at risk and their asset values to evaluate repair/reconstruction costs. The uncertainties associated with these parameters are often significant and the available data are often incomplete. This study aims to assess the value and utility of detailed data in refining seismic risk estimates. Over several years, detailed site conditions and residential exposure datasets were compiled for Greater Montreal. These models were used to estimate building damage and associated losses for various seismic scenarios. Recently, Natural Resources Canada developed a national exposure model to provide a National Earthquake Risk Profile using data derived from existing sources such as topographic maps and census data. This paper compares seismic loss projections for residential buildings using the local dataset as a baseline with those from the national model using OpenQuake and the latest Seismic Hazard Model. The local site model is based on in situ data and site measurements, while the global, proxy-based model relies on USGS correlations between slope topography and site classification. Results show that the global model overestimates seismic hazards, resulting in 30% higher residential losses than the local model. Absolute losses are increased by a factor of 3.6–5.6 depending on the building classification when using the national exposure model compared to the local inventory while relative losses are increased by a factor of 1.1–1.5. These results emphasize the need to develop detailed seismic risk assessment databases for accurate risk assessments, and for selecting appropriate risk reduction measures.