The use of robotized inclinometric system in Early Warning System. The case study of a large landslide monitoring.

Geohazard monitoring is a key component in an early warning system (EWS). The implementation of monitoring actions provides data for the acquisition of variables related to the landslide, its triggering and kinematic; additionally, it can provide insights of its evolution in time in order to plan mitigation actions, including alarms and warnings. The use of high-frequency systems can also provide such data in the shortest time thus optimizing the aforementioned actions. In the last decades, numerous surface monitoring systems were developed, with various features, providing punctual information, like GNSS or Robotized Total Stations, at high frequency or large-scale data, i.e. Remote Sensing, at lower temporal resolution. The choice of the best one is related to the goals to be fulfilled but, independently from the selected method, surface techniques monitor only a displacement resulting from the sum of all the deep-seated ground deformations. To properly detect the subsoil behavior of a landslide, the use of subsurface sensors is necessary. To couple the subsoil survey with high frequency monitoring a robotic inclinometric system was developed, and patented, by the Geohazard Monitoring Group (GMG) of CNR-IRPI. The instrumentation features the operational characteristics of the manual inclinometric measures (reliability, double readings 0/180˚…) but integrates the advantages of the robotization (accuracy, measurement frequency…), too. The robotized instrumentation also called “Automated Inclinometer System” (AIS) allows the automatic exploration of all the borehole length (up to 120 meters in the standard configuration) with a single probe. The AIS is remotely connected by a 4G modem so it is possible to define the acquisition parameters, download measured data and check the device functioning parameters. The instrumentation was deployed, at the beginning of December 2021, in a borehole located in Passiria Valley (northeastern Italy) to monitor a large and slow-moving landslide involving the whole mountain face; thanks to instrumentation modularity, the AIS is ready to measure after only 4÷5 hours of installation time. Concurrently with the main installation, a GNSS benchmark was positioned and surveyed to provide, with the next measurement campaigns, a crosscheck with the AIS results. After 10÷15 days of monitoring at 1 measurement/day the landslide’s sliding surface, its depth and deformation rate, were clearly identified, thus confirming the capability of the AIS to perform early detection of the landslide kinematic. This result is key information in the risk reduction chain as it shortens the time necessary to achieve the numerical parameters describing the landslide and, consequently, plain the following, mitigating, actions.