This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1007/s10346-021-01728-z. This is version 1 of this Preprint.
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Abstract
When an active landslide is first identified in an artificial reservoir, a comprehensive study has to be quickly conducted to analyse the possible hazard that it may represent to such a critical infrastructure. This paper presents the case of the El Arrecife Landslide, located in a slope of the Rules Reservoir (Southern Spain), as an example of geological and motion data integration for elaborating a preliminary hazard assessment. For this purpose, a field survey was carried out to define the kinematics of the landslide: translational in favour of a specific foliation set, and rotational at the foot of the landslide. A possible failure surface has been proposed, as well as an estimation of the volume of the landslide: 14.7 million m3. At the same time, remote sensing and geophysical techniques were applied to obtain historical displacement rates. A mean subsidence rate of up to 2 cm/yr was obtained by means of Synthetic Aperture Radar Interferometry (InSAR) and Ground Penetrating Radar (GPR) data, during the last 5 and 22 years, respectively. The Structure-from-Motion (SfM) technique provided a higher rate, up to 26 cm/yr during the last 14 years, due to compaction of a slag heap located within the foot of the landslide. All of this collected information will be valuable to optimise the planning of future monitoring surveys (i.e. Differential Global Positioning Systems, inclinometers, ground drilling and InSAR) that should be applied in order to prevent further damage on the reservoir and related infrastructures.
DOI
https://doi.org/10.31223/X50D0J
Subjects
Earth Sciences, Environmental Monitoring, Environmental Sciences, Geology, Geomorphology, Geophysics and Seismology
Keywords
InSAR, Landslide, reservoir, GPR, Reservoir, Quick hazard assessment, Geological data, Multi-technique monitoring, InSAR, SfM, GPR, quick characterisation, geological data, multi-technique monitoring, SfM
Dates
Published: 2021-10-01 14:55
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