Field hydrological monitoring with IoT-based low-cost sensor network on slopes subjected to rainfall-induced landslides
- Dipartimento di Ingegneria, Università degli Studi della Campania “Luigi Vanvitelli”, Aversa, Italy (pasquale.marino1@unicampania.it)
Many mountainous areas of Campania, Southern Italy, are characterized by steep slopes covered by layered granular unsaturated pyroclastic deposits, mainly consisting of ashes and pumices, laying upon fractured limestone bedrock. The total thickness of the soil is quite variable with a few meters (1.0 m–1.5 m) in the steepest part of the slopes, and larger at the foot. Shallow landslides are often triggered after large and intense precipitations, turning into destructive debris flows that cause heavy damage and victims. The slope of Cervinara, located around 40 km Northeast of Naples (Campania, Italy), was involved in a catastrophic debris flow between 15-16 December 1999, triggered by a rainfall event of 325 mm in about 48 h. Since 2001, hydrological monitoring activities have been carried out at the slope, by measuring precipitation depth, soil volumetric water content and capillary tension. Moreover, in December 2017 an automatic hydro-meteorological station has been installed at the elevation of 575 m a.s.l., near the scarp of the 1999 landslide. It allows the assessment of slope hydrological balance, by identifying the major hydrological processes involving the cover and the perched aquifer, which develops in the upper part of the fractured bedrock during the rainy season. Lately, since 1 December 2022, new monitoring activities started. A remotely accessible low-cost network has been installed moving away from the landslide scarp of 1999, for expanding the area interested by soil moisture monitoring. The tested prototype network is based on the use of capacitive sensors placed at nodes located 20 m apart from each other with a communication system within the domain of Internet of Things (IoT) technology. Specifically, the low-cost sensors network allowed measurements of soil water content, communicating through short-range wireless IoT system (i.e., Wi-Fi) thanks to ESP32 boards. The field data can be visualized remotely on ThingSpeakTM IoT platform on laptops and smartphones.
The tested IoT-based low-cost network shows the potential to enhance the amount of monitored hydrological data at affordable cost, so to improve risk management in landslide-prone areas. The same IoT network architecture with diffuse measurements can be replicated with long-distance radio communication between nodes, which allows extending the mutual distance up to few kilometers.
How to cite: Marino, P., Roman-Quintero, D. C., Santonastaso, G. F., and Greco, R.: Field hydrological monitoring with IoT-based low-cost sensor network on slopes subjected to rainfall-induced landslides, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-2708, https://doi.org/10.5194/egusphere-egu23-2708, 2023.