Civil Engineering Reference
In-Depth Information
Earthquakes in the past have repeatedly illustrated the extent of undesir-
able consequences (in terms of loss of human life and property) whenever
they have struck vulnerable areas of populations. Historically, earthquakes
have caused gravely disproportionate losses in certain countries. Except for
a few developed nations, such as the United States, New Zealand, and Japan,
most fatality or casualty-related losses have occurred in countries from the
developing world, where vulnerable building stock caused huge death tolls.
Spence (2007a) summarized some of the specifi c achievements and failures
of earthquake risk reduction in the last 40 years for countries from both
the developed and developing world.
The dominant commonalities shared by vulnerable countries, are low per
capita income, rapid population growth followed by urbanization, develop-
ment with little attention to safety, poor earthquake-resistant building
design codes, and/or lack of enforcement of existing building codes. Despite
some dedicated efforts within a number of countries to develop new build-
ing codes, the existing residential building stock is hardly affected by these
changes. Bird and Bommer (2004) observed that unreinforced masonry and
reinforced concrete buildings are the most vulnerable to collapse. Building
collapses do remain the dominant cause of deaths and injuries in earth-
quakes (Coburn and Spence, 2002). It appears that a broad level of under-
standing of regional building stock and its vulnerability during past
earthquakes could provide an opportunity to attempt a fi rst order estima-
tion of likely earthquake-related casualties from earthquakes.
As discussed in the previous section, the empirical vulnerability models
rely directly upon the relationship between population exposure and earth-
quake fatality rates at each level of shaking intensity in order to estimate
total fatalities. What is added in the semi-empirical model is detailed data
on building types, their collapse vulnerability, and the fatality rate associ-
ated with structural collapses. In the current implementation, we focus
primarily on estimating structural collapse, which usually is the dominant
cause of earthquake fatalities.
The quantitative model incorporates shaking hazard on a latitude/longi-
tude grid from the ShakeMap system, population exposure by building type
within a given country, fragility of building type expressed in terms of prob-
ability of collapse at each intensity, and fatality rate given building collapse.
Building inventory and vulnerability data have been compiled at the country
level. For each country, the inventory database provides the population
distribution according to different structure types for two occupancy types
(residential and non-residential) and two population density types (urban
and rural). Details about inventory database development are discussed in
Jaiswal and Wald (2008).
At each grid cell (approx. 1 km by 1 km), we have the total population,
urban/rural categorization of that cell based on Global Rural-Urban
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