@Article{ĮvilaAlvaMendAmor:2021:BaStVi,
author = "{\'A}vila, Frederico Fernandes de and Alval{\'a}, Regina
C{\'e}lia dos Santos and Mendes, Rodolfo M. and Amore, Diogo J.",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Centro
Nacional de Monitoramento e Alertas de Desastres Naturais
(CEMADEN)} and {Centro Nacional de Monitoramento e Alertas de
Desastres Naturais (CEMADEN)} and {Centro Nacional de
Monitoramento e Alertas de Desastres Naturais (CEMADEN)}",
title = "The influence of land use/land cover variability and rainfall
intensity in triggering landslides: a back-analysis study via
physically based models",
journal = "Natural Hazards",
year = "2021",
volume = "105",
number = "1",
pages = "1139--1161",
month = "Jan.",
keywords = "Landslides · Hillslope stability · Land use and land cover ·
TRIGRS.",
abstract = "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
infuenced slope instability and the consequent development of 65
landslides in the Bengalar Stream basin, located in the Northern
Region of S{\~a}o Jos{\'e} dos Campos, S{\~a}o 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 infuence
hillslope stability and is associated with land use and land cover
(LULC) variability. Analysis of intense short-term and accumulated
long-term rainfall infuence 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 infltration rates. Despite the
diferences 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 classifed 1.3% of the entire basin as
unstable (FS\≤1), whereas the TRIGRS model classifed 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.",
doi = "10.1007/s11069-020-04324-x",
url = "http://dx.doi.org/10.1007/s11069-020-04324-x",
issn = "0921-030X",
language = "en",
targetfile = "avila_influence.pdf",
urlaccessdate = "20 maio 2024"
}