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Assessing the potential of soil wetness data for landslide early warning

 

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 difficulty to predict shallow landslides. Consequently, a dedicated research effort has been initiated to advance fundamentals and develop tools for the early warning of landslides at the regional scale.

 

While most studies focus on the use of precipitation information to assess thresholds for the initiation of landslides (e.g. by intensities and accumulations), 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 in regard to the representation of true soil conditions, and it is very challenging to run them in real-time.
 
The objective of this project is to assess the value of in-situ soil wetness measurements for its use in a landslide early warning system (LEWS). Until now, the study comprises following:

  • A comprehensive analysis of available soil wetness data from different research institutions and authorities at several sites all over Switzerland will be conducted and the results will be compared with a shallow landslide event data set. The aim is to assess statistical values of such time series anteceding observed landslide triggering events that can separate landslide events from non-events.
  • Different soil wetness measurement techniques will be compared at a common location in a landslide-prone region in the Swiss Prealps to identify advantages or disadvantages, respectively, of certain soil-wetness information.
  • 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 a precursor of landslides. The analysis of a large and complementary dataset of long-term soil wetness measurements in Switzerland is a unique opportunity to engage with the above research problems.

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.