Articles | Volume 23, issue 1
https://doi.org/10.5194/nhess-23-279-2023
https://doi.org/10.5194/nhess-23-279-2023
Research article
 | 
25 Jan 2023
Research article |  | 25 Jan 2023

Using principal component analysis to incorporate multi-layer soil moisture information in hydrometeorological thresholds for landslide prediction: an investigation based on ERA5-Land reanalysis data

Nunziarita Palazzolo, David J. Peres, Enrico Creaco, and Antonino Cancelliere

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Latest update: 29 Jun 2024
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Short summary
We propose an approach exploiting PCA to derive hydrometeorological landslide-triggering thresholds using multi-layered soil moisture data from ERA5-Land reanalysis. Comparison of thresholds based on single- and multi-layered soil moisture information provides a means to identify the significance of multi-layered data for landslide triggering in a region. In Sicily, the proposed approach yields thresholds with a higher performance than traditional precipitation-based ones (TSS = 0.71 vs. 0.50).
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