Early detection of climate change-induced shallow landslides with IoT-technology
Abstract Climate change in the Alps is increasing winter rainfall and raising the snowline, thereby elevating the risk of shallow landslides and threatening infrastructure. However, forecasting such events remains challenging due to their localized and unpredictable nature. Here we present an innova...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
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| Series: | Communications Earth & Environment |
| Online Access: | https://doi.org/10.1038/s43247-025-02668-5 |
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| Summary: | Abstract Climate change in the Alps is increasing winter rainfall and raising the snowline, thereby elevating the risk of shallow landslides and threatening infrastructure. However, forecasting such events remains challenging due to their localized and unpredictable nature. Here we present an innovative approach combining laboratory experiments, field measurements, and real-time autonomous monitoring to develop geotechnical-hydraulic hypotheses for early warning strategies. Subsurface conditions—such as topography, volumetric water content, matric suction, and soil temperature—are continuously monitored alongside key triggering factors including snow cover, precipitation intensity, and temperature fluctuations to improve the understanding of the shallow landslide initiation. Data were collected at an instrumented test site in the Alps, where a shallow landslide was triggered by heavy rainfall in December 2023. The monitoring system is based on a sensor network that includes Shallow Landslide Detectors. These results highlight the potential of low-cost, distributed monitoring systems to enhance early warning capabilities in alpine environments increasingly affected by climatic extremes. |
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| ISSN: | 2662-4435 |