Preprints
https://doi.org/10.5194/hess-2021-133
https://doi.org/10.5194/hess-2021-133

  15 Mar 2021

15 Mar 2021

Review status: this preprint is currently under review for the journal HESS.

Simulated or measured soil moisture: Which one is adding more value to regional landslide early warning?

Adrian Wicki1, Per-Erik Jansson2, Peter Lehmann3, Christian Hauck4, and Manfred Stähli1 Adrian Wicki et al.
  • 1Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
  • 2KTH Royal Institute of Technology, 100 44 Stockholm, Sweden
  • 3ETH Zurich, Institute of Terrestrial Ecosystems, Universitätstrasse 16, 8092 Zürich, Switzerland
  • 4University of Fribourg, Department of Geosciences, Chemin du Musée 4, 1700 Fribourg, Switzerland

Abstract. The inclusion of soil wetness information in empirical landslide prediction models was shown to improve the forecast goodness of regional landslide early warning systems (LEWS). However, it is still unclear which source of information – numerical models or in-situ measurements – are of higher value for this purpose. In this study, soil moisture dynamics at 133 grassland sites in Switzerland were simulated for the period of 1981 to 2019 using a physically-based 1D soil moisture transfer model (CoupModel). A common parametrization set was defined for all sites except for site-specific soil hydrological properties, and the model performance was assessed at a subset of 14 sites where in-situ soil moisture measurements were available on the same plot. A previously developed statistical framework was applied to fit an empirical landslide forecast model, and ROC analysis was used to assess the forecast goodness. To assess the sensitivity of the landslide forecasts, the statistical framework was applied to different CoupModel parametrizations, to various distances between simulation sites and landslides, and to measured soil moisture from a subset of 35 sites for comparison with a measurement-based forecast model. We found that (i) simulated soil moisture is a skilful predictor for regional landslide activity, (ii) that it is sensitive to the formulation of the upper and lower boundary conditions, and (iii) that the information content is strongly distance-dependent. Compared to a measurement-based landslide forecast model, the model-based forecast performs better as the homogenization of hydrological processes and the site representation can lead to a better representation of triggering event conditions. However, it is limited in reproducing critical antecedent saturation conditions due to an inadequate representation of the long-term water storage.

Adrian Wicki et al.

Status: open (until 10 May 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-133', Anonymous Referee #1, 21 Apr 2021 reply
  • RC2: 'Comment on "Simulated or measured soil moisture: Which one is adding more value to regional landslide early warning?" by Wicki et al.', Roberto Greco, 25 Apr 2021 reply

Adrian Wicki et al.

Adrian Wicki et al.

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Short summary
Soil moisture information was shown valuable for predicting landslides. Here, soil moisture was simulated at 133 sites in Switzerland and the temporal variability was compared to the regional occurrence of landslides. We found that simulated soil moisture is a good predictor for landslides and that the forecast goodness is similar to using in situ measurements. This encourages the use of models for complementing existing soil moisture monitoring networks for regional landslide early warning.