Characterisation of the shallow subsurface has gained in importance as civil and geotechnical engineering and environmental applications have become more dependent on a precise definition of geomechanical and geohydrological properties.  A better understanding of the subsurface conditions offers wide-ranging benefits to governments, industry and individual citizens.Subsurface geological modelling became an economic and technologic reality in the late 1980's, when competing 3-D geoscientific information systems were the subject of considerable research and evaluation, especially by the petroleum exploration industry. Investigations in the shallow subsurface impose additional requirements that have only recently become technically and economically achievable. The very shallow urban underground environment, where many  infrastructure and utilities elements are located, presents the most difficult characterisation problems.Subsurface modelling techniques have matured, along with modern data base concepts. The evolution of the Internet and Web-browser technologies has expanded information transmission and dissemination capabilities. Subsurface models are being integrated with decision-support systems to provide predictions of technical and economic performance. Yet even the most sophisticated of these models leave some uncertainty in geologic interpretation. A variety of techniques for assessing uncertainty have been developed and are being evaluated.

Characterisation of the shallow subsurface has gained in importance as civil and geotechnical engineering and environmental applications have become more dependent on a precise definition of geomechanical and geohydrological properties.  A better understanding of the subsurface conditions offers wide-ranging benefits to governments, industry and individual citizens.Subsurface geological modelling became an economic and technologic reality in the late 1980's, when competing 3-D geoscientific information systems were the subject of considerable research and evaluation, especially by the petroleum exploration industry. Investigations in the shallow subsurface impose additional requirements that have only recently become technically and economically achievable. The very shallow urban underground environment, where many  infrastructure and utilities elements are located, presents the most difficult characterisation problems.Subsurface modelling techniques have matured, along with modern data base concepts. The evolution of the Internet and Web-browser technologies has expanded information transmission and dissemination capabilities. Subsurface models are being integrated with decision-support systems to provide predictions of technical and economic performance. Yet even the most sophisticated of these models leave some uncertainty in geologic interpretation. A variety of techniques for assessing uncertainty have been developed and are being evaluated.

Characterisation of the shallow subsurface has gained in importance as civil and geotechnical engineering and environmental applications have become more dependent on a precise definition of geomechanical and geohydrological properties.  A better understanding of the subsurface conditions offers wide-ranging benefits to governments, industry and individual citizens.Subsurface geological modelling became an economic and technologic reality in the late 1980's, when competing 3-D geoscientific information systems were the subject of considerable research and evaluation, especially by the petroleum exploration industry. Investigations in the shallow subsurface impose additional requirements that have only recently become technically and economically achievable. The very shallow urban underground environment, where many  infrastructure and utilities elements are located, presents the most difficult characterisation problems.Subsurface modelling techniques have matured, along with modern data base concepts. The evolution of the Internet and Web-browser technologies has expanded information transmission and dissemination capabilities. Subsurface models are being integrated with decision-support systems to provide predictions of technical and economic performance. Yet even the most sophisticated of these models leave some uncertainty in geologic interpretation. A variety of techniques for assessing uncertainty have been developed and are being evaluated.