The actual effective reliability of a high-alpine real-time monitoring system

Landslide early warning depends on the availability of reliable real-time monitoring data. In this context, high reliability means optimal data continuity (minimal data loss), sufficient redundancy of sensors observing a variety of parameters, and a high accuracy of monitoring techniques. Nowadays, most manufacturers can provide nearly perfect reliability for modern IoT monitoring devices under laboratory or calibration conditions. However, under challenging high alpine conditions, the actual effective reliability of a monitoring system remains unknown as long as the system is not fully operational or is even kept confidential from the public.

Here, we analyse the effective reliability of the real-time monitoring system at the Hochvogel summit (2,592 m a.s.l.) where conditions combine limited access throughout the year especially in winter, inaccessible steep areas, no permanent power supply, high snow loads, high probability of lightning strikes, and highly jointed and weathered rock mass. The monitoring system is operational since October 2019 transmitting data every 10 min via wireless LoRa technology from 10-12 geotechnical sensors (crack meters, laser distance meters, inclinometers, rain gauge). Many sensors operate at the edge of radio range (2,800 m horizontal and 1,500 m vertical distance to the gateway, mostly without direct line of sight). We analyse the probability of data loss in three categories: (i) daily average, i.e. days on which at least one measured value was transmitted are valid; (ii) hourly average; and (iii) all 10-minute data. Generally, the probability of missing data increases with higher temporal resolution, as suboptimal conditions and transmission problems are often short-lived. Due to its magnitude and failure process, we expect the Hochvogel instability to accelerate several hours to few days before failure. Therefore, hourly and daily datasets are most important. The daily transmission reliability for most sensors is 97.3–100 %. From the laser distance gauges, less data can be used for early warning, as they are covered by snow for several months per year. On an hourly basis, the transmission reliability is 96.7–99.4 % for crack meters, and 56-65 % for the laser distance sensors.

This analysis of more than 5 years of data allows us to quantify the effective reliability of the Hochvogel monitoring system and to identify the most important reasons for data loss and particularly critical periods in which several sensors fail simultaneously. This will help decision-makers and responsible parties to plan or adapt their systems and give guidance on how much financial means they must spend to reach the desired level of resilience, reliability, or redundancy.