Rock scour evaluation procedures consider both the erosion capacity of flowing water and the resistance offered by the rock mass. The Block Scour Spectrum (BSS) provides a framework for assessing the rock mass resistance according to details of the discontinuity structure. This study introduces a procedure for identifying and extracting rock block structural elements directly from LiDAR point clouds using open source algorithms to support BSS analyses. The approach offers a road map for tackling the details of discrete fracture network generation and block mould computations. As a case study, spillway scour at the Ricobayo Dam in Zamora, Spain is evaluated.

1. Introduction

The assessment of scour potential needs to consider both the erosion capacity of flowing water (demand) and the resistance offered by the rock mass. Widely applied methods for evaluating rock scour include the semi-empirical Erosion Index Method (EIM) [1-2] and the Comprehensive Scour Model (CSM) [3]. EIM adopts principles of rock mass rating systems and assigns penalties based on general considerations of dominant rock mass discontinuity patterns. The scour resistance offered by the rock mass is then compared to the demand which is represented by stream power. The ratio of resistance to demand is then the basis for scour potential. The CSM approach considers scour potential for water jets impinging plunge pools, and the rock mass structure is idealized as a regular system of rectangular blocks. Recent developments concerning rock scour have examined the problem in the context of block theory, wherein details of the discontinuity structure are evaluated with the Block Scour Spectrum (BSS) [7]. In order to apply the BSS approach, it is necessary to identify the individual discontinuities that intersect to form kinematically removable blocks. Apart from the information pertaining to the magnitude and direction of the applied hydraulic loads, the block geometry parameters such as shape and volume are also required to complete the BSS analysis. The remote collection of the spatial data using geomatics techniques such as LiDAR and digital photogrammetry has expanded rapidly in recent years However, quickly identifying and extracting the scour-significant rock blocks from the point clouds is a challenge. In this paper, we illustrate an approach for processing and estimating three-dimensional rock structure parameters directly from LiDAR point clouds.

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