Hygric pore network modelling and simulation, employing the pore network (PN) extracted from pore structure images, is a powerful tool for obtaining the hygric properties of porous materials. However, reliable PN acquisition of porous building materials remains elusive, because of the continuous size distributions of pore elements across several length scales. The extracted single-scale PN from an individual pore structure image can only unveil a partial reality, while the multi-scale PN, that combines several single-scale PNs, is neither directly applicable since there often is no distinct separation of scales in such continuous pore element size distributions. This paper, therefore, introduces an indirect method to generate full-scale PNs of porous building materials. Several single-scale PNs of a real building material, ceramic brick, are extracted from its X-ray Computed Tomography (XCT) and X-ray Microscopy (XRM) images, each with varying spatial resolutions. Statistical data of these extracted PNs is subsequently integrated to facilitate stochastic full-scale PN generation. The generated full-scale PN maintains the PN parameter distributions, along with the parameter correlations. Furthermore, the hygric properties of the generated full-scale PN are obtained through simulation and compared with measured data for validation. The results indicate a strong agreement across the majority of the moisture retention and permeability curves, and the potential explanations for the disparity are discussed for future improvement.