Morphostructure of Landslides: Characterization Through Electrical Resistivity Tomography (ERT)
Abstract
Rotational landslide has generally been characterized through shallow geophysics methods and satellite analysis to study potential hazards to the population. At present, the recognition of landslides by their morpho-structure considers the combination of multiple sources of information and precision levels acquired through geomorphological, geophysical, and geotechnical methods. Our landslide case study is in San José de Maipo, Central Chile. We present a methodology for morphostructural characterization through electrical resistivity tomography. The validation of this methodology considers data acquisition through the ARES II resistivity system, data processing using RES2DINV inversion software, and the electric profile interpretation. The Wenner-Schlumberger geometric arrangement was used for the ERT data acquisition, with two contrasts in the resistivity values. Therefore, we interpret that the morphostructures are limited by sharp contrasts in resistivity values between horizontal and vertical layers (resistivity values) along the unstable slope. These values show high resistivity values in the upper zone of the landslide and low values in the lower zone. We delimited the rupture surface at 20 m in the middle of the profile. The depth decreases laterally, reaching 5 m. Finally, the proposed morphostructural model allowed the sliding to be characterized geometrically as a concave upward recognizable rupture surface of known depth and extension. We presented the mosphostructural model to determine the landslide geometrically to obtain data on the rotational landslide's depth, extension, and morphology. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Más información
| Título según SCOPUS: | Morphostructure of Landslides: Characterization Through Electrical Resistivity Tomography (ERT) |
| Título de la Revista: | Advances in Science, Technology and Innovation |
| Editorial: | Springer Nature |
| Fecha de publicación: | 2023 |
| Página de inicio: | 155 |
| Página final: | 158 |
| Idioma: | English |
| DOI: |
10.1007/978-3-031-42917-0_35 |
| Notas: | SCOPUS |