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 San Vicente volcano (El Salvador, CA) was used to calibrate predictive models and prepare a landslide susceptibility map. The storm event struck November 2009 as result simultaneous action low-pressure system 96E Hurricane Ida. Multivariate Adaptive Regression Splines (MARS) employed model relationships between set environmental variables locations flows. Validation by splitting 100 random samples non-event 10 m pixels into training test subsets. validation results revealed excellent (area under receiver operating characteristic (ROC) curve (AUC) = 0.80) stable (AUC std. dev. 0.01) ability MARS predict which occurred study area. However, when using Youden’s index probability threshold discriminate predicted positives negatives, exhibits moderate identify cells (specificity 0.66). final flow map, prepared averaging for each pixel score repetitions, shows where future are more likely occur, thus may help mitigating risk associated with these landslides.