Along-trace profiles of the Timpa San Lorenzo fault structure (Calabria, Italy)

 

 

   
Fig. 1. 3D view of the Timpa di San Lorenzo structure (center) with the Pollino range at the West (left). View from NE, Google Earth maps.

 

One quite spectacular geological structure in Southern Italy that can be visualized in 3D terrain browsers such as Google Earth is the Timpa di San Lorenzo (TSL) carbonatic structure, outcropping at the border between Basilicata and Calabria near San Lorenzo Bellizzi (Fig. 1).  

If you play for instance with Google Earth, you would note a well exposed, planar fault surface cutting through limestones in the footwall. This fault is dissected by other faults, the main one being a NW-SE high-angle fault. North of it the TSL fault has a WNW-ESE trend, while to the South it is NNW-SSE (Fig. 2).

 

   
Fig. 2. Geological sketch representing the Timpa di San Lorenzo structure (center), subdivided into two segments by a NW-SE trending fault. The Mt. Pollino range is at the West (left).

In Alberti (2019) the two main segments were analyzed with GIS tools, namely the qgSurf plugin for QGIS, in order to derive the best-fitting planes to the various fault segments.

For the northern segment the geological plane fitting the traces has an attitude of 072°/39° (dip direction/dip angle), i.e., a medium-angle fault dipping to the ENE.

In the southern segment the best-fitting plane attitude is 082°/40°, i.e. a 10° trend rotation in a clockwise manner with respect to the northern sector.

 

In order to help visualize these inferred geological planes directly within geological profiles, I am adding in the pygsf and gst Python modules a new GIS tool that uses line traces with attitudes, intersect them with profiles and plot the intersected attitude in the profiles. This tool is still in development.

 

To analyse the geological situation for the studied zone, I used the two previous geological attitudes in order to derive, using the ‘Plane-DEM intersections’ tool of the QGIS  qgSurf plugin, their expected topographic traces. These line traces were clipped to the appropriate spatial domain and then merged together into a single line shapefile.

Using pygsf, gst and spatdata modules in development mode within Jupyter Notebook, the Timpa di San Lorenzo data were imported from the spatdata module, maps with faults (both mapped and theoretical traces) and profiles traces were created (Fig. 3).

Fig. 3. Geological plane traces approximating the Timpa di San Lorenzo structure (yellow lines), with numbered traces of parallel profiles. Profiles from 1 to 7 are of the fault northern segment, from 8 to 13 from the southern one.

The final product is represented by the geological profiles (Fig. 4), always produced within Jupyter Notebook using the three mentioned modules. The produced profiles highlights the carbonatic structures, while the pelagic sediments and meta-sediments units are not mapped.

As you can see in the profiles, the theoretical planes approximate quite well the attitude of the outcropping TSL fault slickensides (profiles 1 to 8, with the exception of profile 3, where the TSL fault is masked by other  units).

In the southern segment, the slickenside is visible mainly in profile 8 and also profile 9.
Moving soutwards, both the fault slickenside and the footwall is more and more eroded, due to the deep incision of the Torrente Raganello (profiles 10-13).

Fig. 4. Parallel profiles of the Timpa di San Lorenzo structure (yellow lines), with fault intersections (red dots), geological outcrops of limestones (PL, green) and the profile trace of the best-fitting geological planes (yellow bars). Profiles from 1 to 7 are of the fault northern segment, from 8 to 13 from the southern one. Additional outcrops are of Quaternary sediments (Qt), Albidona Formation (Al) and Saraceno Formation (Sa).

 

The Jupyter Notebook document used to create these (and more) analyses is available here.

 

To replicate the analysis you have to clone the gsf, gst and spatdata repositories, install the modules (for instance in development mode) and then run the notebook.

References

 

Alberti M. 2019. GIS analysis of geological surfaces orientations: the qgSurf plugin for QGIS. PeerJ Preprints 7:e27694v1 https://doi.org/10.7287/peerj.preprints.27694v1