Cutting-edge applied geophysics and data science in the evaluation of hydrogeological risk in urban areas

The frequency of extreme rainfall events has significantly risen in recent years, compelling administrators of urban areas to develop and adopt innovative strategies to effectively manage precipitation overload. This climatic trend has heightened the complexity of addressing hydrogeological risks, requiring a deeper understanding of the mechanisms driving catastrophic events. Among these, landslides represent one of the most critical challenges, necessitating multidisciplinary approaches to improve prediction, prevention, and mitigation strategies. Several studies have demonstrated how the spatial-temporal variation of moisture content in soil is crucial in the triggering and reactivation of landslide phenomena. Hydrogeophysics plays a pivotal role in understanding these processes at multiscale spatial-temporal resolutions. Its effectiveness is significantly enhanced when combined with detailed hydrological and environmental analyses. Multiparametric strategy, leveraging continuous multisensory monitoring systems, has proven to be one of the most effective methods for modeling soil moisture behavior. Recent advancements have optimized the selection of components for such systems, incorporating time-lapse ERT systems alongside various hydrologic and environmental sensors. This synergy enables sophisticated 2D and 3D dynamic thermo-hydro-geomechanical modeling of the subsurface, offering unprecedented insights into soil moisture dynamics and landslide mechanisms. Our work focuses on a peri-urban landslide located a few hundred meters from the centre of a small town in the southern Apennines of Italy, characterized by slow-moving displacements. We are establishing an open-air laboratory equipped with a monitoring station that integrates time-lapse ERT system with an array of several hydrological (tensiometers, soil moisture sensors, piezometers) and meteorological (thermometers, hygrometers, anemometers, pyranometers) sensors. The large quantity of data generated by this monitoring station will be managed through the development of innovative data processing methods, also leveraging advanced machine learning techniques. These approaches will enable efficient analysis and integration of geophysical, hydrogeological, and environmental datasets across laboratory and site scales, enhancing our ability to model and understand landslide behaviour with greater accuracy and precision.  This work is one of the activities carried out within the WP7-7.4 task of the ITINERIS "Italian Integrated Environmental Research Infrastructures System" project (PNRR M4C2 Inv.3.1 IR), funded by the EU's Next Generation program, an integrated geophysical approach for the assessment of geohazards in urban areas.