Ground characterization is instrumental to managing ground risks in the built environment. Several variables affect the appropriate characterization of the ground, including the early desk study, site investigation, and ground data management. During project planning and design stages, the quality, management, and interpretation of collected ground data are imperative to develop reliable ground models that accurately represent the subsurface conditions. Owners and asset managers are increasingly recognizing the benefits of collecting digital data, or digitizing existing data, and storing it into centralized data repositories. Creating an up-to-date and centralized library of project information increases efficiency by reducing the repetition of costly investigations and allows for changes to be tracked over the course of the project, from inception to decommissioning. The adoption of advanced digital technology and state-of-the-art tools such as three-dimensional (3D) ground modelling software in tandem with traditional methods of ground data management is required to streamline the current industry practice of ground modelling at local and national levels. This paper presents a digital workflow for efficient and reliable ground characterization that can optimize the planning, design, construction, and operations of ground-related projects. Best practices associated with ground data collection, management, processing, and interpretation are reviewed and documented. Data visualization tools are also critical to help users develop reliable ground models. Therefore, the benefits of using 3D ground modelling to effectively visualize variability in geological conditions and project locations, along with its challenges and limitations, are discussed. The ground industry is quickly evolving and recognizing the unparalleled benefits of fully integrated data management workflows. It is intended that the recommended workflow provided in this paper can be referred to in the development and design of future projects.
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Tran et al. (2024) studied this question.
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