Remote Sensing Approach to Upstream Slope Inspection
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 145, Issue 11
Abstract
Many conventional inspection practices for dams and levees place heavy demands on limited human resources. Furthermore, traditional inspections of riprap slope protection material rely on qualitative evaluations that involve a degree of subjectivity. The combination of these factors can result in incomplete and inaccurate assessments of the riprap condition over time. This paper presents a novel method for inspecting riprap slope protection material using three-dimensional (3D) point cloud data captured by lidar or photogrammetry. The method has been validated using two full-scale studies, a laboratory-scale study using gravels, and extensive two-dimensional (2D) numerical simulations. The validation shows that the small-scale topography of the slope face, known as roughness, is correlated to the median size of the riprap. Thus, as the riprap weathers and breaks into smaller pieces, the roughness of the slope will decrease. The roughness is a quantitative parameter that enables spatial analysis of the riprap condition over time. The studies performed to date indicate that this method can be used on slopes having an approximately planar face, clear of significant vegetation and debris, and armored using end-dumped riprap with a coefficient of uniformity not exceeding 2.5. The slopes of many operational dams and levees meet these criteria, making this a practical inspection tool that can target limited inspection resources to where they are most needed. The basics of the method are demonstrated using a field trial conducted at a reservoir in the northeastern United States.
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Acknowledgments
The authors appreciate the assistance with code development and field work provided by the following current and former Lafayette College students: Michael Yust, Michael Bennett, and Nouman Naveed. The authors also appreciate the feedback provided by Mr. Robert Kirby of Terra Engineers. The lidar equipment used for this research was funded by the National Science Foundation (NSF) (MRI Grant No. 1428322). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.
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©2019 American Society of Civil Engineers.
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Received: Jan 16, 2019
Accepted: Jun 13, 2019
Published online: Sep 13, 2019
Published in print: Nov 1, 2019
Discussion open until: Feb 13, 2020
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