Abstract

Worldwide, cities with mountainous areas struggle with an increasing landslide risk as a consequence of global warming and population growth, especially in low-income informal settlements. Landslide Early Warning Systems (LEWS) are an effective measure to quickly reduce these risks until long-term risk mitigation measures can be realized. To date however, LEWS have only rarely been implemented in informal settlements due to their high costs and complex operation. Based on modern Internet of Things (IoT) technologies such as micro-electro-mechanical systems (MEMS) sensors and the LoRa (Long Range) communication protocol, the Inform@Risk research project is developing a cost-effective geosensor network specifically designed for use in a LEWS for informal settlements. It is currently being implemented in an informal settlement in the outskirts of Medellin, Colombia for the first time. The system, whose hardware and firmware is open source and can be replicated freely, consists of versatile LoRa sensor nodes which have a set of MEMS sensors (e.g., tilt sensor) on board and can be connected to various different sensors including a newly developed low cost subsurface sensor probe for the detection of ground movements and groundwater level measurements. Complemented with further innovative measurement systems such as the Continuous Shear Monitor (CSM) and a flexible data management and analysis system, the newly developed LEWS offers a good benefit-cost ratio and in the future can hopefully find application in other parts of the world.

Highlights

  • Worldwide, cities with mountainous areas struggle with an increasing landslide risk as a consequence of global warming and population growth, especially in low-income informal settlements

  • The Colombian team is comprised of representatives from the center of urban studies (EAFIT university, Medellin) and several municipal agencies responsible for risk management in the city of Medellín (e.g., SIATA, DAGRD) as well as two local NGOs and the Colombian Geological Society

  • The sensor network consists of three different sensor nodes, which allow to monitor movement/deformation of the subsurface (SN, Low-Cost Chain Inclinometer (LCI)) or existing infrastructure (IN) as well as the groundwater conditions in near surface soil layers

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Summary

Project Background and Goals

Landslide hazard is increasing year by year due to more intense and frequent rainfall as a consequence of climate change [1]. The poorest residents are often the most vulnerable to landslides because in many cases they live in the most dangerous areas [3,4,5,6] This is especially true in the Andes, where more than 10 million people are exposed to natural hazards and a high degree of inequality is prevalent [7,8]. Since long term risk reduction solutions, as, e.g., the relocation of the endangered inhabitants or the implementation of physical mitigation measures, are currently not feasible due to the high social, political and monetary efforts required and their potential to harm the landscape and ecosystem [13], the Inform@Risk project is designing and implementing a Landslide Early Warning System (LEWS) as a short- to medium-term risk reduction solution. The implementation of the system has been delayed due to the COVID-19 crisis and is currently scheduled for summer/fall 2021

Project Area
Geology and Landslide Processes
Landslide Early Warning Systems
LEWS in Medellín and Colombia
The Internet of Things and Landslide Monitoring
Monitoring System Layout
Measurement Concept for the LoRa Sensor Nodes
LoRa Sensor Nodes
Installation
Data Transmission and Storage
Data Management
Data Analysis
Short- to Medium Term Hazard Level
Early Warning and Alarms
Summary and Outlook
Resources
Full Text
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