3D models from geological maps: strengths and weaknesses from the Pasubio Massif (Southern Alps)

Abstract

3D geological models provide digital representations of subsurface architecture and are increasingly applied in both academic research and industry. Their construction can follow implicit or explicit approaches, depending on data availability and final modelling applications. While 3D models based on subsurface data are traditionally employed in several fields of study, models derived from outcrop data are increasingly being developed. In this study, newly acquired geological mapping data from the Pasubio Massif (Southern Alps, northern Italy), covering an area of ~36 km² within the geographic extent of the CARG sheet 081 “Rovereto”, were used to develop and test an iterative explicit workflow for 3D geological modelling using Move software. The workflow is based on the construction of a structured grid of geological cross-sections, followed by the interpolation of stratigraphic horizons and fault surfaces through Ordinary Kriging. Field observations indicate that the lithostratigraphic units cropping out in the study area form a gently NW-dipping monoclinal structure, exhibit overall constant thicknesses and are affected by the Schio-Vicenza fault system. Model validation first involved a qualitative comparison between mapped geological boundaries and faults with those obtained from the intersection of the modelled surfaces with the topography (DEM), followed by thickness maps evaluation as an internal consistency check. Where inconsistencies emerged, cross-sections were refined and the model was iteratively updated until geological geometries and thickness trends became consistent with field-mapped evidence. A final quantitative assessment was then performed by analysing thickness deviations from mean unit thicknesses and by measuring the spatial overlap between mapped and model-interpolated geological boundaries and fault traces. Comparison between the preliminary and validated models, supported by thickness deviation statistics, indicates that most residual discrepancies are constrained within ±10–20% of expected thickness values. The results highlight the critical role of iterative validation in ensuring geologically robust 3D models, emphasising common sources of uncertainty in explicit geomodelling workflows. This study provides a methodological framework for producing reliable 3D geological models in data-poor regions, complementing the recently published ISPRA guidelines for the organisation and standardisation of model datasets and supporting future applications in academic research and regional or national geological surveys.