Remote analysis of an open-pit slope failure: Las Cruces case study, Spain

Juan López-Vinielles,Joaquín Mulas,Marta Béjar-Pizarro,Antón Filatov,Oriol Monserrat,Pablo Blanco,Pablo Ezquerro,Gerardo Herrera,Juan C García-Davalillo,José A Fernández-Merodo,Rosa M Mateos,Roberto Sarro,Anna Barra,Javier García-Robles,José M Azañón,Jorge P Galve

doi:10.1007/s10346-020-01413-7

Abstract

Slope failures occur in open-pit mining areas worldwide, producing considerable damage in addition to economic loss. Identifying the triggering factors and detecting unstable slopes and precursory displacements —which can be achieved by exploiting remote sensing data— are critical for reducing their impact. Here we present a methodology that combines digital photogrammetry, satellite radar interferometry, and geo-mechanical modeling, to perform remote analyses of slope instabilities in open-pit mining areas. We illustrate this approach through the back analysis of a massive landslide that occurred in an active open-pit mine in southwest Spain in January 2019. Based on pre- and post-event high-resolution digital elevation models derived from digital photogrammetry, we estimate an entire sliding mass volume of around 14 million m3. Radar interferometry reveals that during the year preceding the landslide, the line of sight accumulated displacement in the slope reached − 5.7 and 4.6 cm in ascending and descending geometry, respectively, showing two acceleration events clearly correlated with rainfall in descending geometry. By means of 3D and 2D stability analyses we located the slope instability, and remote sensing monitoring led us to identify the likely triggers of failure. Las Cruces event can be attributed to delayed and progressive failure mechanisms triggered by two factors: (i) the loss of historical suction due to a pore-water pressure increase driven by rainfall and (ii) the strain-softening behavior of the sliding material. Finally, we discuss the potential of this methodological approach either to remotely perform post-event analyses of mining-related landslides and evaluate potential triggering factors or to remotely identify critical slopes in mining areas and provide pre-alert warning.

Highlights

Mass movements and surface deformations, caused by ground subsidence or slope instability processes, are very frequent phenomena in both abandoned and active mining areas (Bell and Donnelly 2006)
We classify the slope failure as a complex movement (Varnes 1978) with a well-defined exposed shear plane clearly present in the post-failure DEM (Fig. 4a), which suggests that a primary failure initiated somewhere near the north dump barrier berm, triggering subsequent failures towards the dump
This study, focused on the January 2019 landslide triggered at Las Cruces open-pit mine, highlights the potential of conducting remote analyses of slope instabilities in open-pit mining areas combining Structure from motion (SfM) photogrammetry, satellite InSAR, and finite element (FE) modeling

Summary

Introduction

Mass movements and surface deformations, caused by ground subsidence or slope instability processes, are very frequent phenomena in both abandoned and active mining areas (Bell and Donnelly 2006). In open-pit mining, ground movements potentially lead to slope failures entailing risks for personnel, equipment, and infrastructures, in addition to disrupting mine scheduling and increasing production costs (Paradella et al 2015). The literature describes large-scale landslides in open-pit mines whose mobilized mass volumes range from 200,000 m3 to 65 million m3. These studies focus on slope monitoring (Brawner and Stacey 1979; Pankow et al 2014; Carlà et al 2018), slope modeling (Voight and Kennedy 1979; Tutluoglu et al 2011; Ozbay and Cabalar 2014), and slope stabilization (Seegmiller 1979)

Methods

Results

Conclusion