Inventory models for regional scale natural hazards risk assessment
Authors: Ploeger S K , Nollet M -J , Sawada M , Abo El Ezz A 
Published: June 2018

This document presents the results of research efforts aimed to develop inventory models of the demography and general building stock for urban centers and rural communities across eastern Canada. The inventory models are intended for use in the rapid seismic
risk assessment tool ER2 (for Rapid Risk Evaluation). Research and development of the inventory models were carried out jointly by the University of Ottawa and École de technologie supérieure (ETS) Montréal. These were part of the larger Prompt Evaluation of Seismic Risk project (PESR
CSSP-2016-CP-2283), led by National Resources Canada (NRCan) for the Canadian Safety and Security Program (CSSP) managed by Defence Research and Development Canada (DRDC) Centre for Security Science (CSS) and Public Safety Canada. The ER2 tool informs the public safety community and emergency
management decision makers with information on various aspects of seismic risk. It consists of two software components for two distinct types of use. The first focusses on near real-time risk analyses following a major earthquake event, while the second component supports various risk assessment
initiatives for scenario-based risk analyses.
The inventory models were developed across a study area extending from the Greater Toronto Area (Ontario) to Quebec City (Quebec). The study boundary encompasses approximately 123,455 km2, 6,398 census units (census tracts and dissemination areas) and over 4.2 million buildings. Detailed inventories
for building types and occupancy classes were conducted for 12 municipalities ranging from rural communities to large urban centres in both Ontario and Quebec. Since these inventories cover only about 0.6% of the study area (km2) or 4.8% of the total number of buildings, a procedure had to
be developed to extrapolate representative building information from the detailed inventories to be applied across the remaining census units in the study area. First, the procedure started with an estimation on the number of buildings for each census unit based on available geospatial datasets;
demographic information was also collected. Second, each census unit was identified by an IoX class code that accounts its population (by size and as populated or non-populated), land use (as residential or commercial, and related densification) and average age (before or after 1960). All census
units within the study area was represented in total by 45 different IoX classes. Third, the distribution of building characteristics within the detailed inventory were summarized by IoX code which provide a reasonable representation of the actual construction practices. Within the inventoried
buildings, around 94% are residential buildings, 93% are wood constructions and around 74% were build after 1960. Distribution of building characteristics differ depending on the size of the community, its main land use and the average year of construction.
In order to estimate the potential economic losses from earthquake scenarios, average square footage, and replacement and content values in dollar terms were associated for various occupancy classes in each default IoX class. To further estimate potential social losses (injuries, fatalities, shelter
needs), demography distribution models were built considering three common times of the day: 2am (nighttime), 2pm (daytime) and 5pm (commuting time), accompanied with respective residential, working and commuting population estimations. A two-tiered approach was used to address population
distributions. These tiers represent a 'rural' model where it is assumed that the 'workers' work within their census unit and the 'urban' model where it is assumed that most of the 'workers' commute to another census unit.