Applicability and performance of deterministic and probabilistic physically based landslide modeling in a data-scarce environment of the Colombian Andes. (June 2021)

• Record Type: Journal Article
• Authors: Marin, Roberto J.; Velásquez, María Fernanda; Sánchez, Oscar
• Is Part Of: Journal of South American earth sciences. Volume 108(2021)
• Publication Date: 2021-06
• Subjects: Shallow landslides -- Iverson -- SLIP -- Intensity -- Duration -- TRIGRS; Geology -- Latin America -- Periodicals; Earth sciences -- Latin America -- Periodicals; Geology -- Antarctica -- Periodicals; Earth sciences -- Antarctica -- Periodicals; Geology -- Caribbean Area -- Periodicals; Earth sciences -- Caribbean Area -- Periodicals; Géologie -- Amérique latine -- Périodiques; Sciences de la terre -- Amérique latine -- Périodiques; Géologie -- Antarctique -- Périodiques; Sciences de la terre -- Antarctique -- Périodiques; Géologie -- Caraïbes (Région) -- Périodiques; Sciences de la terre -- Caraïbes (Région) -- Périodiques; Earth sciences; Geology; Antarctica; Caribbean Area; Latin America; Periodicals; 550.5
• DOI: 10.1016/j.jsames.2021.103175
• Languages: English
• ISSNs: 0895-9811

Abstract

Abstract: Physically based models have been widely used around the world to study landslide occurrence. The accuracy in a physically based landslide susceptibility/hazard assessment depends mostly on the input parameters. In this research study, three physically based models' applicability and performance were assessed using deterministic and probabilistic approaches. It was carried out in a data-scarce environment: a tropical mountain basin of the Colombian Andes. TRIGRS, SLIP and Iverson models were applied with back analysis of the landslide events in the La Liboriana basin on May 18, 2015. The performance of the models was evaluated using ROC (receiver operating characteristic) analysis and %LRclass index. The results showed that the back analysis using landslide events could be a good alternative to define the input parameters for physically based models in data-scarce tropical mountain areas. The ROC analysis and %LRclass are considered useful techniques for assessing landslide modeling performance. The metric indices calculated should be seen as complementary information, and the drawbacks of these indices should be identified, as elucidated in this paper. Highlights: Landslide simulations of the May 18, 2015 La Liboriana landslide events were done. Assessing landslides with back analysis is a valuable tool in data-scarce environments. ROC analysis and %LRclass were used to evaluate the modeling predictability. Iverson, SLIP and TRIGRS models had a good performance in a tropical mountain basin.