Strategies to improve the explanatory power of a dynamic slope stability model by enhancing land cover parameterisation and model complexity

Elmar M. Schmaltz*, L. P.H. Van Beek, Thom A. Bogaard, Sabine Kraushaar, Stefan Steger, Thomas Glade

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

6 Citations (Scopus)
106 Downloads (Pure)

Abstract

Despite the importance of land cover on landscape hydrology and slope stability, the representation of land cover dynamics in physically based models and their associated ecohydrological effects on slope stability is rather scarce. In this study, we assess the impact of different levels of complexity in land cover parameterisation on the explanatory power of a dynamic and process-based spatial slope stability model. Firstly, we present available and collected data sets and account for the stepwise parameterisation of the model. Secondly, we present approaches to simulate land cover: 1) a grassland landscape without forest coverage; 2) spatially static forest conditions, in which we assume limited knowledge about forest composition; 3) more detailed information of forested areas based on the computation of leaf area development and the implementation of vegetation-related processes; 4) similar to the third approach but with the additional consideration of the spatial expansion and vertical growth of vegetation. Lastly, the model is calibrated based on meteorological data sets and groundwater measurements. The model results are quantitatively validated for two landslide-triggering events that occurred in Western Austria. Predictive performances are estimated using the Area Under the receiver operating characteristic Curve (AUC). Our findings indicate that the performance of the slope stability model was strongly determined by model complexity and land cover parameterisation. The implementation of leaf area development and land cover dynamics further yield an acceptable predictive performance (AUC ~0.71-0.75) and a better conservativeness of the predicted unstable areas (FoC ~0.71). The consideration of dynamic land cover expansion provided better performances than the solely consideration of leaf area development. The results of this study highlight that an increase of effort in the land cover parameterisation of a dynamic slope stability model can increase the explanatory power of the model.
Original languageEnglish
Pages (from-to)1259-1273
Number of pages15
JournalEarth Surface Processes and Landforms
Volume44
Issue number6
DOIs
Publication statusPublished - 2019

Keywords

  • land cover dynamics
  • parameterisation
  • physically based slope stability modelling
  • predictive performance
  • Shallow translational landslides
  • STARWARS/PROBSTAB

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