Abstract

In recent years, the measurement of dam displacements has benefited from a great improvement of existing technology, which has allowed a higher degree of automation. This has led to data collection with an improved temporal and spatial resolution. Robotic total stations and GNSS (Global Navigation Satellite System) techniques, often in an integrated manner, may provide efficient solutions for measuring 3D displacements on precise locations on the outer surfaces of dams. On the other hand, remote-sensing techniques, such as terrestrial laser scanning, ground-based SAR (synthetic aperture radar) and satellite differential interferometric SAR offer the chance to extend the observed region to a large portion of a structure and its surrounding areas, integrating the information that is usually provided in a limited number of in-situ control points. The design and implementation of integrated monitoring systems have been revealed as a strategic solution to analyze different situations in a spatial and temporal context. Research devoted to the optimization of data processing tools has evolved with the aim of improving the accuracy and reliability of the measured deformations. The analysis of the observed data for the interpretation and prediction of dam deformations under external loads has been largely investigated on the basis of purely statistical or deterministic methods. The latter may integrate observation from geodetic, remote-sensing and geotechnical/structural sensors with mechanical models of the dam structure. In this paper, a review of the available technologies for dam deformation monitoring is provided, including those sensors that are already applied in routinary operations and some experimental solutions. The aim was to support people who are working in this field to have a complete view of existing solutions, as well as to understand future directions and trends.

Highlights

  • Monitoring the health of dam infrastructures has a key role in ensuring their safety conditions and maintaining their operational functions

  • They allow for the measurement of horizontal deviations with respect to the optical line-of-sight (LoS) established between a stand-point located at one side of the dam and a portable target that may be deployed along the upper crown of the structure

  • A further step forward in this research direction was made by Corsetti [23], who recently presented the application of an A-DInSAR technique to generate deformation time series at a full spatial resolution and from multi-sensor synthetic aperture radar (SAR) data

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Summary

Introduction

Monitoring the health of dam infrastructures has a key role in ensuring their safety conditions and maintaining their operational functions. In parallel, during the last decades, dam monitoring has benefited from the development of remote-sensing techniques from ground-based and satellite platforms These have offered unprecedented opportunities for improving the structural analysis, since they extended the monitoring to a large portion of a structure, instead of a limited number of few CPs [13]. Since the first experimental applications of these methods, many improvements have been made and the current state-of-the-art features a much greater potential for field operations, including the capability of building up long time-series of observations (i.e., displacements in range direction between the sensor and the illuminated point) Such data sets can be used for retrospective analyses using archives of SAR data (see, e.g., Milillo [18]). Precedes the final discussion on the monitoring techniques and on the future perspectives in dam deformation monitoring (Section 6)

Which Are the Types of Deformations to be Measured in Dams?
Optical Collimators
Geodetic Networks
Global Navigation Satellite Systems
Terrestrial-Based Radio Frequency Ranging
Terrestrial Laser Scanning
Ground-Based InSAR
Spaceborne Advanced DInSAR
Integrated Monitoring Systems
Conventional Deformation Analysis
Time-Series Analysis for Investigation of Deformations’ Causative Reasons
Statistical Methods
Deterministic Methods
Conclusions
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