Regional scale evaluation of slope exposure to co-seismic failures: a tool for optimizing land use planning and emergency management

Identifying slopes most prone to earthquake-induced failure on a regional scale is fundamental for guiding effective damage mitigation strategies in long-term land use planning and for optimizing emergency response during seismic events. Two decades ago, Del Gaudio et al. (2003) proposed an approach for reconnaissance-level assessments of earthquake-induced landslide hazards. This approach relates the slope’s critical acceleration a_c, a threshold needed to mobilize co-seismic failures, to the resistance demand imposed by regional seismicity. Based on the simplified Newmark (1965) model of landslide initiation under seismic forcing, this approach estimates the critical acceleration (A_c)_x required to limit the probability of Newmark's displacement D_N exceeding a predetermined threshold x, which is critical for landslide activation.

With the increasing data availability  through civil protection initiatives, such as seismic microzonation studies, involving joint efforts by professionals and researchers and improved data analysis tools, there is an opportunity to refine this approach. This study tested some of these refinements on the landslide-prone Daunia Mountains (southeastern Italy). First, new empirical D_N predictive equations specific for the study area were calibrated using over 200 real and synthetic accelerograms representative of seismic scenarios relevant to the Daunia seismic hazard. The results showed that this region-specific model considerably improved the accuracy of D_N predictions compared with equations calibrated using data from other regions, although the effect on slope resistance estimates was minor.

Secondly, significant advancements were made in incorporating site response effects on (A_c)_x using site-specific, probabilistic estimates of Arias intensity amplification factors. These amplification factors were estimated via site response analyses exploiting seismic microzonation data to i) generate 1D shear-wave velocity models from advanced ambient noise data analyses and ii) simulate  site response using sets of relevant accelerograms. Tests demonstrated that incorporating these amplification factors leads to considerably higher resistance demand values compared to those derived using generic assumed amplification factors.  

The refined approach proposed here allows the creation of maps showing (A_c)_x values that, when compared with GIS-based estimates of actual slope a_c values, can pinpoint slopes more likely to experience co-seismic failure. These maps can be used where long-term mitigation measures or emergency rescue operations should be prioritized, thereby enhancing societal resilience to seismic events.

 

References

Del Gaudio, V., Pierri, P., Wasowski, J., 2003. An Approach to Time-Probabilistic Evaluation of Seismically Induced Landslide Hazard. Bull Seismol Soc Am 93(2):557–569. https://doi.org/10.1785/0120020016.

Newmark, N.M., 1965. Effects of earthquakes on dams and embankments. Geotechnique 15 (2), 139–159.