Role of municipal database in constructing site-specific multivariate probability distribution

The purpose of this paper is to investigate whether the quasi-site-specific model established based on a municipal or regional database can be more effective in supporting site-specific predictions than one based on a global database. To do this, a Bayesian updating approach that combines site-specific data and a municipal database under realistic MUSIC (Multivariate, Uncertain and Unique, Sparse, and InComplete) attributes for the site data is adopted. This approach assumes that the site data and the municipal database follow the same distribution, which can be partially verified using standard correlation plots. The quasi-site-specific model can then be adopted to make site-specific predictions for the relevant design properties. Because real soil data follow MUSIC attributes, this Bayesian updating is only feasible in the presence of a probability distribution construction method that can handle such data. A real case study for Shanghai shows that a municipal database is more effective in supporting site-specific predictions than a global database. In contrast, another real case study shows that a regional database that covers multiple countries in the Scandinavian region is not necessarily more effective than a global database.