For the last 20+ years, slope stability modelling by practicing engineers and basic software users has mostly been limited to 2D cross-sections. Faster computers and improvements in the user interface of 3D software are now facilitating a shift towards the routine use of 3D stability modelling. Deformation monitoring technology has also been rapidly improving, with realtime interferometric radar now capable of providing updates every minute across an entire slope. This is a step-change in risk management compared with manual surveying of individual survey prisms going back as little as 15 years. Radars are also geo-referenced to the same coordinate system used in slope stability models. This paper presents case studies to illustrate the benefits of routinely adopting 3D modelling for slope stability as well as the added advantage of integrating the 3D models with interferometric radar data, thereby bringing together predictive models and live monitoring data.

1 Introduction

Slope stability modelling and slope hazard management using slope deformation monitoring until now have been separate, individual tasks, often undertaken by different geotechnical engineers or companies for a single project. For example, in a typical open pit mine, the slope could be designed (modelled) by an external consultant and the slope hazard management and deformation monitoring performed by the client or mining company. This usually results in a disconnect between the predicted and actual ground behavior.

In the last decade several efforts were made to reconcile or validate slope designs and models with excavation progression with varying degrees of success (Baczynski et al. 2008; Dixon et al. 2011; Bar, 2012). At the same time, slope stability modelling techniques have evolved and increased in complexity with improvements in computing capability and available software. As we approach the 2020's, three-dimensional (3D) limit equilibrium and finite element analysis software are readily available and offer a range of options to model complex failure mechanisms (McQuillan et al. 2018; Bar & McQuillan, 2018).

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