Adopting the margin of stability for space–time landslide prediction – A data-driven approach for generating spatial dynamic thresholds

Abstract

Shallow landslide initiation typically results from an interplay of dynamic triggering and preparatory conditions along with static predisposition factors. While data-driven methods for assessing landslide susceptibility or for establishing rainfall-triggering thresholds are prevalent, integrating spatio-temporal information for dynamic large-area landslide prediction remains a challenge. The main aim of this research is to generate a dynamic spatial landslide initiation model that operates at a daily scale and explicitly counteracts potential errors in the available landslide data. Unlike previous studies focusing on space–time landslide modelling, it places a strong emphasis on reducing the propagation of landslide data errors into the modelling results, while ensuring interpretable outcomes. It introduces also other noteworthy innovations, such as visualizing the final predictions as dynamic spatial thresholds linked to true positive rates and false alarm rates and by using animations for highlighting its application potential for hindcasting and scenario-building.

Keywords

Early warning / Space-time model / Rainfall thresholds / Landslide susceptibility, Generalized Additive Mixed Model / Forecasting

CRediT authorship contribution statement

Stefan Steger: Conceptualization, Methodology, Modelling, Validation, Visualization, Writing – original draft. Mateo Moreno: Conceptualization, Methodology, Data collection, Visualization, Writing – review & editing. Alice Crespi: Conceptualization, Methodology, Data collection, Visualization, Writing – review & editing. Stefano Luigi Gariano: Methodology, Writing – review & editing. Maria Teresa Brunetti: Methodology, Writing – review & editing. Massimo Melillo: Methodology, Writing – review & editing. Silvia Peruccacci: Methodology, Writing – review & editing. Francesco Marra: Methodology, Writing – review & editing. Lotte de Vugt: Conceptualization, Data collection, Writing – review & editing. Thomas Zieher: Conceptualization, Data collection, Writing – review & editing. Martin Rutzinger: Conceptualization, Data collection, Writing – review & editing. Volkmar Mair: Conceptualization, Writing – review & editing. Massimiliano Pittore: Conceptualization, Writing – review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The research leading to these results is related to the PROSLIDE project that received funding from the research program Research Südtirol/Alto Adige 2019 of the Autonomous Province of Bozen/Bolzano – Südtirol/Alto Adige. We also thank the four reviewers for their valuable comments that helped to increase the quality of the manuscript.

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