The influence of land use/land cover variability and rainfall intensity in triggering landslides: a back-analysis study via physically based models

• Published in: Natural hazards (Dordrecht) Vol. 105; no. 1; pp. 1139 - 1161
• Main Authors: Ávila, Frederico F., Alvalá, Regina C., Mendes, Rodolfo M., Amore, Diogo J.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 2021; Springer Nature B.V
• Subjects: Analysis; Civil Engineering; Comparative analysis; Earth and Environmental Science; Earth Sciences; Environmental Management; Geophysics/Geodesy; Geotechnical Engineering & Applied Earth Sciences; Hydrogeology; Hydrologic models; Hydrology; Infiltration rate; Land cover; Land use; Landslides; Landslides & mudslides; Model accuracy; Model testing; Natural Hazards; Pore pressure; Pore water pressure; Rain; Rainfall; Rainfall intensity; Review Article; Slope stability; Stability analysis; Static models; Variability; Landslides; TRIGRS; Hillslope stability; Land use and land cover
• DOI: 10.1007/s11069-020-04324-x
• EISSN: 1573-0840
• ISSN: 0921-030X

The objective of this study was to use physically based models to carry out a back-analysis of the set of factors that may have influenced slope instability and the consequent development of 65 landslides in the Bengalar Stream basin, located in the Northern Region of São José dos Campos, São Paulo State, Brazil, associated with rainfall between March 7 and 8, 2016. Unlike other models, the FS FIORI model used in this study allowed extra variables to be added to the model that can influence hillslope stability and is associated with land use and land cover (LULC) variability. Analysis of intense short-term and accumulated long-term rainfall influence on slope instability was possible via a TRIGRS model. A comparative analysis was also carried out between a static model (FS FIORI) and a transient model (TRIGRS) which considered the factor of safety and pore pressure to be a function of precipitation and infiltration rates. Despite the differences in their hydrological components, both models were shown to present relatively similar and demonstrated stability rates coherence, according to the characteristics of each model. The FS FIORI model only classified 1.3% of the entire basin as unstable (FS ≤ 1), whereas the TRIGRS model classified 4.5% and 2.9% of the entire basin as unstable in scenarios 1 and 2, respectively. The validity and the accuracy of each model were tested via a receiver operating characteristic (ROC) curve and an area under the curve (AUC). AUC values were: 0.6552 for the FS FIORI model, and 0.7238 and 0.7186 for scenarios 1 and 2 of the TRIGRS model, respectively. The models performed well, with values considered to be acceptable. These results demonstrate an advancement in slope stability modeling studies, including conditioning factors associated with LULC for slope stability calculations.