Geotechnical site investigation may obtain the data of multiple soil parameters. These data for different soil parameters are cross-correlated and spatially correlated in the three-dimensional space. How to effectively use these site investigation data to quantify the uncertainties of soil parameters remains a challenging issue. To address this issue

this paper proposes a joint probability density function (PDF) estimation method of geotechnical parameters based on multi-source site investigation data with consideration of the three-dimensional spatial variability of these geotechnical parameters. The paper first briefly reviews the PDF estimation method based on multi-source investigation data at a single sounding that only considers the spatial variability in the vertical direction. The Gibbs sampler-based method is then proposed to estimate the joint PDF of geotechnical parameters based on multi-source site investigation data at multiple soundings by taking the three-dimensional spatial variability of these soil parameters into consideration. A simulated virtual site and a practical site at Texas USA are employed to demonstrate the performance of the proposed method. It is shown that the proposed method can provide an effective tool for uncertainty quantification with multi-source investigation data. Compared with the single sounding method

the proposed method can effectively reduce the statistical uncertainty.