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Exploring the impact of spatial correlations and uncertainties for portfolio analysis in probabilistic seismic loss estimation

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Weatherill,  Graeme
0 Pre-GFZ, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Silva,  V.
External Organizations;

Crowley,  H.
External Organizations;

Bazzurro,  P.
External Organizations;

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Zitation

Weatherill, G., Silva, V., Crowley, H., Bazzurro, P. (2015): Exploring the impact of spatial correlations and uncertainties for portfolio analysis in probabilistic seismic loss estimation. - Bulletin of Earthquake Engineering, 13, 957-981.
https://doi.org/10.1007/s10518-015-9730-5


Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5018792
Zusammenfassung
The significant potential for human and economic losses arising from earthquakes affecting urban infrastructure has been demonstrated by many recent events such as, for example, L’Aquila (2009), Christchurch (2011) and Tohoku (2012). Within the current practice of seismic loss estimation in both academic and industry models, the modelling of spatial variability of the earthquake ground motion input across a region, and its corresponding influence upon portfolios of heterogeneous building types, may be oversimplified. In particular, the correlation properties that are well-known in observations of ground motion intensity measures (IMs) may not always be fully represented within the probabilistic modelling of seismic loss. Using a case study based on the Tuscany region of Italy, the impacts of including spatially cross-correlated random fields of different ground motion IMs are appraised at varying spatial resolutions. This case study illustrates the impact on the resulting seismic loss when considering synthetic aggregated portfolios over different spatial scales. Inclusion of spatial cross-correlation of IMs into the seismic risk analysis may often result in the likelihood of observing larger (and in certain cases smaller) losses for a portfolio distributed over a typical city scale, when compared against simulations in which the cross-correlation is neglected. It can also be seen that the degree to which the spatial correlations and cross-correlations can impact upon the loss estimates is sensitive to the conditions of the portfolio, particularly with respect to the spatial scale, the engineering properties of the different building types within the portfolio and the heterogeneity of the portfolio with respect to the types.