|Reference:||Computers & Geosciences 36 (2010): 257–269|
|ISBN / DOI:||doi: 10.1016/j.cageo.2009.07.006|
The era of earthquake risk and loss estimation basically began with the seminal paper on hazard by Allin Cornell in the year 1968. Following the 1971 San Fernando earthquake, the first studies placed strong emphasis on the prediction of human losses (number of casualties and injured used to estimate the needs in terms of health care and shelters in the immediate aftermath of a strong event). In contrast to these early risk modeling efforts, later studies have focused on the disruption of the serviceability of roads, telecommunications and other important lifeline systems. In the 1990’s the National Institute of Building Sciences (NIBS) developed a tool (HAZUS®99) for the Federal Emergency Management Agency (FEMA), where the goal was to incorporate the best quantitative methodology in earthquake loss estimates.
Herein, the current version of the open-source risk and loss estimation software SELENA v4.1 is presented. While using the spectral displacement-based approach (capacity spectrum method), this fully self-contained tool analytically computes the degree of damage on specific building typologies as well as the associated economic losses and number of casualties. The earthquake ground shaking estimates for SELENA v4.1 can be calculated or provided in three different ways: deterministic, probabilistic or based on near-real-time data. The main distinguishing feature of SELENA compared to other risk estimation software tools is that it is implemented in a ‘logic tree’ computation scheme which accounts for uncertainties of any input (e.g., scenario earthquake parameters, ground-motion prediction equations, soil models) or inventory data (e.g., building typology, capacity curves and fragility functions). The data used in the analysis is assigned with a decimal weighting factor defining the weight of the respective branch of the logic tree. The weighting of the input parameters accounts for the epistemic and aleatoric uncertainties that will always follow the necessary parameterization of the different types of input data.
Like previous SELENA versions, SELENA v4.1 is coded in MATLAB which allows for easy dissemination among the scientific-technical community. Furthermore, any user has access to the source code in order to adapt, improve or refine the tool according to his or her particular needs. The handling of SELENA’s current version and the provision of input data is customized for an academic environment but which can then support decision-makers of local, state and regional governmental agencies in estimating possible losses from future earthquakes.