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Assessing the potential of soil wetness data for landslide early warning

English title Assessing the potential of soil wetness data for landslide early warning
Applicant Stähli Manfred
Number 175785
Funding scheme Project funding (Div. I-III)
Research institution Swiss Federal Research Inst. WSL Direktion
Institution of higher education Swiss Federal Institute for Forest, Snow and Landscape Research - WSL
Main discipline Pedology
Start/End 01.04.2018 - 30.09.2021
Approved amount 224'952.00
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All Disciplines (2)


Keywords (6)

early warning systems; landslides; soil wetness; precursors; electrical resistivity tomography; Time Domain Reflectometry

Lay Summary (German)

Für die Frühwarnung von möglichen Hangrutschungen werden heute meistens Niederschlags-Messungen verwendet. Hier in dieser Forschungsarbeit soll untersucht werden, ob auch Bodenfeuchte-Messungen nützlich sind, um bevorstehende Hangrutschungen zu erkennen.
Lay summary
Mit diesem Forschungsprojekt soll abgeklärt werden, inwieweit sich klassische Bodenfeuchtemessungen für die regionale Warnung von Hangrutschungen eignen. Zu diesem Zweck nutzen wir langjährige Bodenfeuchte-Messreihen und vergleichen sie mit beobachteten Hangrutschungen. Insbesondere interessieren uns typische Bodenfeuchte-Muster kurz vor dem Eintreffen solcher Ereignisse. Ausserdem werden an einem Standort, wo in der Vergangenheit Hangrutschungen aufgetreten sind, zahlreiche Bodenfeuchte-Messgeräte installiert, um kritische Bodensättigung zu analysieren. Und schliesslich soll ein kürzlich entwickeltes numerisches Modell verwendet werden, um die Bodenfeuchte bei der Auslösung von Hangrutschungen zu simulieren. Uns interessiert, ob die Messungen gegenüber dem Modell einen Mehrwert generieren.
Diese Forschungsarbeit ist Teil einer längerfristigen Forschungsstrategie im Hinblick auf ein nationales Hangrutsch-Frühwarnsystem für die Schweiz. Neben der Eidg. Forschungsanstalt WSL sind die ETH Zürich (Bodenphysik) und die Uni Fribourg (Geographie) an dieser Arbeit beteiligt.
Direct link to Lay Summary Last update: 29.09.2017

Responsible applicant and co-applicants


Name Institute

Project partner


Assessing the potential of soil moisture measurements for regional landslide early warning
Wicki Adrian, Lehmann Peter, Hauck Christian, Seneviratne Sonia I., Waldner Peter, Stähli Manfred (2020), Assessing the potential of soil moisture measurements for regional landslide early warning, in Landslides.


Group / person Country
Types of collaboration
Universität Fribourg, Department of Geosciences Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
ETH Zürich, Soil and Terrestrial Physics Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
European Geophysical Union (EGU) Annual Meeting 2020 Poster Performance analysis of regional landslide early warning based on soil moisture simulations 04.05.2020 Wien, Austria Wicki Adrian; Stähli Manfred;
Swiss Geoscience Meeting 2019 Poster Soil hydrological monitoring for regional landslide early warning 23.11.2019 Fribourg, Switzerland Stähli Manfred; Wicki Adrian;
European Geophysical Union (EGU) Annual Meeting 2019 Talk given at a conference Assessing the potential of soil wetness data for landslide early warning 08.04.2019 Wien, Austria Wicki Adrian; Stähli Manfred;
Swiss Geoscience Meeting 2018 Poster Soil wetness data for landslide early warning 01.12.2018 Bern, Switzerland Wicki Adrian; Stähli Manfred;

Knowledge transfer events


Title Date Place
LEWS2020 - Workshop on Regional Landslide Early Warning Systems – experiences, progresses and needs 28.01.2020 Perugia, Italy

Associated projects

Number Title Start Funding scheme
122299 Local and regional hydrologic and geomorphic factors determining landslide patterns 01.01.2009 Project funding (Div. I-III)
117407 Hydro-mechanical monitoring of landslide triggering in steep terrain 01.07.2007 R'EQUIP


In mountainous areas, landslides triggered by heavy rain present a serious risk to people and infrastructure. Recent major events in central Switzerland have demonstrated the numerousness, abruptness and seemingly unpredictability of landslides based on weather information only. As a consequence of these events, a dedicated research effort has been initiated in Switzerland (and worldwide) to advance fundamentals and develop tools for the early warning of landslides at the regional scale. While most studies focused on the use of precipitation information, e.g. intensities and accumulations, to assess thresholds for the initiation of landslides, less work has been put into the utilization of soil wetness information to anticipate the imminent occurrence of landslides. In this respect, most attempts were made to estimate (spatial or local) soil saturation with numerical hydrological models to assess the criticality of the antecedent soil wetness in terms of slope stability. Such numerical models, however, have limitations with regard to the representation of true soil conditions, and it is very challenging to run them in real-time. Here, in this proposed SNF project, the overarching objective is instead to assess the value of in-situ soil wetness measurements in advertising imminent occurrence of landslides for potential use in future Landslide Early Warning Systems (LEWS). To this end, a comprehensive analysis of available soil wetness data from several pre-alpine and alpine sites in Switzerland will be conducted with the aim to assess statistical values of such time series anteceding observed landslide triggering events that can separate landslide events from non-events. In a second step, a unique dataset of a recent field experiment (artificial irrigation of a hillslope until failure) will be revisited and analyzed in this respect. Then, a comparison of four different soil wetness measurement techniques at one common location in a landslide-prone region (Emmental) will be made with the aim of identifying advantages or disadvantages, respectively, of certain soil-wetness information. And finally, a state-of-the-art numerical model for the spatial simulation of landslide triggering will be applied to serve as a benchmark for the soil-wetness-measurement derived indicators.The project will pursue particular innovations in the analysis of soil-wetness time series by identifying characteristic patterns of soil moisture behavior (e.g. variability-mean relationships) that could be used as precursors of landslides. To this end, the large and complementary dataset of longterm and event-based soil wetness measurements, which is immediately available for this project, is a unique treasure trove to answer the overarching question.As an expected outcome of this project, decision-makers and experts responsible for the warning of natural hazards will receive a better knowledge base for the design of a national soil moisture observatory and to issue regional to national warnings regarding imminent landslide hazard.