1. Introduction

With recent developments and application of geographical information system (GIS) capabilities, geohazard assessments can benefit from detailed data integration. This facilitates the merging of different datasets, such as 3D exploration seismic; high-resolution seismic (e.g. HR2D, sub-bottom profiler); geotechnical (e.g. boreholes, cone penetration tests (CPT)); or environmental (e.g. sampling, visual inspection) data. The result of this integration is a conceptual geological model to be used as a support for the geohazard assessment, and which is provided to the engineering team in charge of a facility design. The engineering team, however, expects predictions (time, place, magnitude and probability of an event), while most geoscientists can only offer an improved forecast (general statement of future possibilities). To reduce this subjectivity, the interpreter should conduct an evaluation of the reliability of the model, taking into account the uncertainties related to each dataset (e.g. accuracy, resolution). The quantification of uncertainties may be carried out for each dataset, but that of the conceptual geological model as a whole is not easy to determine. This paper reviews best practice in terms of data integration by means of a GIS and details uncertainties that should be taken into account. It also addresses considerations related to geostatistics and probabilities, in order to provide a reliable conceptual geological model for geohazard assessment.

2. Geographical Information System: A Powerful Tool for Data Integration

At that time, geotechnical engineering was still regarded as part of civil engineering, relying upon the principles of mechanics and hydraulics. Today, geotechnical engineering is recognised as an obvious bridge between geology and civil engineering, and in many areas it requires an integrated and multidisciplinary approach. Such an approach linking geosciences and geotechnical engineering should be considered in terms of common concerns and requirements, such as obtaining, organising, validating, displaying and interpreting surface and subsurface data.

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