The Cixerri Plain (SW Sardinia, Italy) is characterised by numerous sinkholes that pose a major hazard to farmland and strategic infrastructures. An engineering geological model was developed to detect subsiding areas and the possible presence of subsurface cavities that may evolve into sinkholes, by constraining predisposing factors and attempting to assign the well-known mechanisms controlling their evolution. The approach integrates single-station ambient noise measurements, nanoseismic monitoring, and multitemporal topographic surveys, including LiDAR and GNSS/UAV-derived digital elevation models (DEM). Resonance frequencies and directional effects reveal a fault-controlled “horst and graben” architecture, enabling the estimation of the depth to the buried limestone bedrock beneath the continental deposits, which ranges from approximately 80 to 120 m in the deepest sectors. The HVNSR function drops below unity (deamplification) at resonance frequencies higher than 5 Hz, clustering near already existing sinkholes, suggesting partially emptied, low-cohesion horizons at depth. Furthermore, nanoseismic measurements allow to cluster microevents consistent with bedrock microcracking and cavity growth, supporting an active subsurface evolution. DEM differencing highlights both widespread subsidence and specific lowered zones (≈ 50–100 m) hosting sinkholes up to 6–8 m in diameter. These observations support a depth-dependent framework in which cover-collapse processes prevail where the bedrock is shallow, collapse-piping becomes dominant where the cover thickens, and hybrid behaviours occur in transitional sectors. These outcomes provide a basis for sinkhole hazard zoning and to attribute rating to monitoring and mitigation actions.

Engineering geological model of the Cixerri Plain (Sardinia, Italy) based on integrated geophysical investigations for sinkhole hazard assessment

Fiorucci M.;
2026-01-01

Abstract

The Cixerri Plain (SW Sardinia, Italy) is characterised by numerous sinkholes that pose a major hazard to farmland and strategic infrastructures. An engineering geological model was developed to detect subsiding areas and the possible presence of subsurface cavities that may evolve into sinkholes, by constraining predisposing factors and attempting to assign the well-known mechanisms controlling their evolution. The approach integrates single-station ambient noise measurements, nanoseismic monitoring, and multitemporal topographic surveys, including LiDAR and GNSS/UAV-derived digital elevation models (DEM). Resonance frequencies and directional effects reveal a fault-controlled “horst and graben” architecture, enabling the estimation of the depth to the buried limestone bedrock beneath the continental deposits, which ranges from approximately 80 to 120 m in the deepest sectors. The HVNSR function drops below unity (deamplification) at resonance frequencies higher than 5 Hz, clustering near already existing sinkholes, suggesting partially emptied, low-cohesion horizons at depth. Furthermore, nanoseismic measurements allow to cluster microevents consistent with bedrock microcracking and cavity growth, supporting an active subsurface evolution. DEM differencing highlights both widespread subsidence and specific lowered zones (≈ 50–100 m) hosting sinkholes up to 6–8 m in diameter. These observations support a depth-dependent framework in which cover-collapse processes prevail where the bedrock is shallow, collapse-piping becomes dominant where the cover thickens, and hybrid behaviours occur in transitional sectors. These outcomes provide a basis for sinkhole hazard zoning and to attribute rating to monitoring and mitigation actions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11580/127183
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