They might be triggered by extreme rainfall events, snow melt, or a combination of rainfall and snow melt. Water-induced landslides are one of the major hazards in Norway due to their high frequency on hillsides and capacity to turn into a high-speed destructive debris flow. Among different triggering factors, water is mainly involved in the majority of slope destabilizations (Michoud et al. Landslides can be triggered by a wide range of factors including rainfall, snow melt, earthquakes, human activities, erosion, or a combination of different phenomena. According to the database, the overall value of damages and economic losses, directly or indirectly related to landslides, was estimated to be over US$ 310 billion since 2000. According to the statistics of the Centre for Research on the Epidemiology of Disasters (CRED 2021), the Emergency Events Database, retrieved in November 2021, roughly 488,000 deaths happened since 2000 due to natural hazards associated with landslides, which also includes ground movement due to earthquakes. The adverse consequences of landslides such as fatalities, injuries to people, economic losses, and environmental damages are well known and documented in the literature (Froude and Petley 2018 Haque et al. The current study also made an attempt to integrate the collected data into a physical-based landslide susceptibility model to obtain a more consistent and reliable hazard assessment.Ī landslide is defined as the downslope movement of soil, rock, and organic materials under the effects of gravity. The effects of rainfall, snow melting, ground freezing, and thawing were captured. During monitored period, the IoT-based hydrological monitoring system provided novel and valuable insights into the hydrological response of slopes to seasonally cold climates in terms of VWC and matric suction. The monitoring system was deployed in a case study area in central Norway at two locations of high susceptible geological units. Volumetric water content (VWC) sensors, suction sensors, and piezometers were used in the hydrological monitoring system to monitor the hydrological activities. Therefore, this study aims to demonstrate a case study on an automated hydrological monitoring system supported by the IoT-based state-of-the-art technologies employing public mobile networks. These monitoring systems can be significantly enhanced, and wider deployments can be achieved through the recent developments within the domain of the Internet of Things (IoT). Hydrological monitoring systems can provide relevant information that can be utilized in landslide early warning systems to mitigate the risk by issuing early warnings. Hydrological monitoring is a widely employed method to understand the initiation mechanism of water-induced landslides under various climate conditions. Water-induced landslides pose a great risk to the society in Norway due to their high frequency and capacity to evolve in destructive debris flows.
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