Mapping Susceptibility to Debris Flows Triggered by Tropical Storms: A Case Study of the San Vicente Volcano Area (El Salvador, CA)

In this study, an inventory of storm-triggered debris flows performed in the area of the San Vicente volcano (El Salvador, CA) was used to calibrate predictive models and prepare a landslide susceptibility map. The storm event struck the area in November 2009 as the result of the simultaneous action...

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Bibliographic Details
Published in:Earth (Basel, Switzerland) Switzerland), 2021-03, Vol.2 (1), p.66-85
Main Authors: Mercurio, Claudio, Martinello, Chiara, Rotigliano, Edoardo, Argueta-Platero, Abel Alexei, Reyes-Martínez, Mario Ernesto, Rivera-Ayala, Jacqueline Yamileth, Conoscenti, Christian
Format: Article
Language:English
Subjects:
Debris flow
Detritus
Discriminant analysis
Flow mapping
Geomorphology
Hurricanes
Landslides
Landslides & mudslides
Low pressure
Mapping
Pixels
Prediction models
Risk reduction
Spline functions
Statistical analysis
Storm damage
Storms
Tropical storms
Volcanoes
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Summary:In this study, an inventory of storm-triggered debris flows performed in the area of the San Vicente volcano (El Salvador, CA) was used to calibrate predictive models and prepare a landslide susceptibility map. The storm event struck the area in November 2009 as the result of the simultaneous action of low-pressure system 96E and Hurricane Ida. Multivariate Adaptive Regression Splines (MARS) was employed to model the relationships between a set of environmental variables and the locations of the debris flows. Validation of the models was performed by splitting 100 random samples of event and non-event 10 m pixels into training and test subsets. The validation results revealed an excellent (area under the receiver operating characteristic (ROC) curve (AUC) = 0.80) and stable (AUC std. dev. = 0.01) ability of MARS to predict the locations of the debris flows which occurred in the study area. However, when using the Youden’s index as probability threshold to discriminate between pixels predicted as positives and negatives, MARS exhibits a moderate ability to identify stable cells (specificity = 0.66). The final debris flow susceptibility map, which was prepared by averaging for each pixel the score of the 100 MARS repetitions, shows where future debris flows are more likely to occur, and thus may help in mitigating the risk associated with these landslides.
ISSN:2673-4834
2673-4834
DOI:10.3390/earth2010005