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Abstract: In this paper all the phases for the realization of the early warning system for the rockslide of Torgiovannetto in Central Italy are described. The landslide consists in a 182,000m3 rock wedge threatening two roads which are important for local transportation. The present work encompasses all the components of an early warning system, including the geological knowledge, the risk scenarios, the kinematic characterization of the landslide, the choice and installation of the monitoring system, the setting of appropriate alarm levels and the definition of plans of civil protection. The focus is on practical and logistical issues met in all these phases and the counter-measures adopted. At present the system consists in 13 wire extensometers, 1 thermometer, 1 rain gauge and 3 cameras. Should a velocity threshold be exceeded by two or more sensors, the attention level would be entered, causing improved monitoring and surveillance. In case the behavior of the landslide changes and, by using expert judgment and forecasting methods, an imminent failure is hinted, then an alarm is issued and the upper road is closed. This paper can provide ideas and solutions for a landslide early warning system that aims to be simple, flexible, versatile and with a low probability of giving false alarms. [Copyright &y& Elsevier]

During recent years, the availability of innovative monitoring instrumentation has been a fundamental component in the development of efficient and reliable early warning systems (EWS). In fact, the potential to achieve high sampling frequencies, together with automatic data transmission and elaboration are key features for a near-real time approach. This paper presents a case study located in Central Italy, where the realization of an important state route required a series of preliminary surveys. The monitoring system installed on site included manual inclinometers, automatic modular underground monitoring system (MUMS) inclinometers, piezometers, and geognostic surveys. In particular, data recorded by innovative instrumentation allowed for the detection of major slope displacements that ultimately led to the landslide collapse. The implementation of advanced tools, featuring remote and automatic procedures for data sampling and elaboration, played a key role in the critical event identification and prediction. In fact, thanks to displacement data recorded by the MUMS inclinometer, it was possible to forecast the slope failure that was later confirmed during the following site inspection. Additionally, a numerical analysis was performed to better understand the mechanical behavior of the slope, back-analyze the monitored event, and to assess the stability conditions of the area of interest. [ABSTRACT FROM AUTHOR]