GNGTS 2022 - Atti del 40° Convegno Nazionale

442 GNGTS 2022 Sessione 3.2 CHARACTERISATION OF ANTHROPOGENIC CAVITIES THROUGH INTEGRATED NON-INVASIVE GEOPHYSICAL SURVEYS IN THE MEDIEVAL TOWN OF CAMPOROTONDO DI FIASTRONE, CENTRAL ITALY A. Zaragoza 1 , R. Teloni 2 , M. Zambrano 1 1 School of Science and Technology - Geology Division, University of Camerino, Italy 2 GeoMORE s.r.l., spinoff of Geology Division, University of Camerino, Camerino, Italy Introduction. The detection and characterisation of underground cavities and critical areas in urban cities has garnered significant interest from both engineering and historical perspectives. The increasing concern for underground structures is related to the proven correlation between the presence of cavities and the seismic amplification phenomena during strong earthquakes (Lancioni et al. , 2014). On the other hand, underground structures in urban areas can represent significant historical and cultural heritage to be preserved and promoted for tourism. However, securing and enhancing this patrimony can be particularly challenging (Argentieri et al. , 2018). In fact, direct detection of underground cavities is not often possible due to different issues like filling, blocked access, and refurbishing older urban pavements. In this regard, indirect identification of cavities through integrated geophysical methods may represent a valid solution. The Ground Penetrating Radar (GPR) is perhaps the most adapted tool for the detection of cavities in urban environments for its simple logistic and high resolution. However, this technique is sensible to the presence of underground services, tubes, and metallic meshes characteristic of the first meters of urban subsurface. Other method of popular use for the detection of cavities is the Electrical Resistivity Tomography (ERT). In the case of urban environments, flat electrodes are highly recommended since positioning classic vertical electrodes (drilling the pavement) is not always possible because of the historical and architectonic value of the urban pavements (Park et al. , 2017). In this work, we implement both techniques for the detection of known underground cavities with the intention of extrapolated its signature to other sites where cavities are presumably located. To do this, we have selected as study case the medieval village of Camporotondo di Fiastrone (MC), located in Central Italy. The town is characterised by a series of hypogenous structures in gravelled alluvial terraces, likely excavated for storage, cooling, and defensive purposes. Only some cavities are known and accessible, whereas the location of most of them remains unknown, representing a potential risk for the human activities. In this regard, buildings with nearby cavities were largely damaged by the 2016-17 seismic sequence in the central Apennines, Italy (Mw = 6.5, 30/10/2016) highlighting the seismic hazard connected to the presence of cavities. Through the methodology proposed in this work, we were able to detect and characterise the shallow cavities (depth < 6 m) present within the village of Camporotondo di Fiastrone, useful for the urban development planning of the post-seismic reconstruction phase. Methods. In this study, in order to create a catalogue of the existing underground cavities, we have combined the generation of geological models (sections at large and detailed scale), reviewof historical data andwitnesses’ interview, visiting of accessible cavities, and geophysical surveys (forward modelling, electrical tomography, and ground penetrating radar survey). The geological models were carried out through the integration of geological map, seismic microzonation data and direct observations. All the wells coming from the microzonation were revised and the gravel base was determined, a very important marker when defining the geological context of the cavities. To document the distribution of cavities the first step was searching for historical ones (cavities that are in the memory of citizens and mentioned in historical sources). In general, the location and geometry of these features are partially known, and their remembrance is handed down from person to person. During this operational phase