Application of Geophysical Methods to the Safety Analysis of an Earth Dam

Kim, J.H.; Yi, M.-J.; Song, Y.; Seol, Soon Jee; Chung, S.-H.; Kim, K.-S.

doi:10.3997/2214-4609-pdb.15.m-04

Cited by 7 publications

(8 citation statements)

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“…; Kim et al . ). More specifically, self potential methods have become increasingly popular for assessing dam‐related seepage flows (Al‐Saigh et al .…”

Section: Dam Geophysical Investigationsmentioning

confidence: 97%

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The geophysical investigation of lake water seepage in the regulated environment of the Bosherston Lily Ponds, South Wales, UK. Part 2: historical, dam‐related pathways

Husband

Cassidy

Stimpson

2009

Near Surface Geophysics

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The detection, characterization and assessment of water loss through hydrological pathways is an important aspect of civil, hydrological and environmental engineering. At any site, variations in the form and hydrological integrity of both natural and man-made features can play a critical role in fluid transportation through the presence of enhanced hydraulic conductivity. Traditional hydrological and invasive engineering investigation methods are often unsuitable for ecologically sensitive environments and in this paper, we report the results of a non-invasive hydro-geophysical study at the Bosheston Lily Ponds in Pembroke, South Wales, UK, an area classified a Special Area of Conservation (SAC). For over 30 years, the lake system has experienced unexplained water loss and the geophysical surveys focused on identifying hydraulic conduits/pathways in the underlying carboniferous limestone and assessing the integrity of the man-made dam structure at the outlet of the lake system. The site is managed under tight regulatory regime that limits the scope and extent of any hydrological/geophysical investigations. The main objectives were to determine whether bedrock fracturing is promoting natural water loss and, more pertinently, if structural failures in the modern (and original) dam structures were responsible for significant loss of water at the outlet of the lakes. Ground-penetrating radar (GPR), electrical resistance tomography (ERT) and self-potential (SP) surveys were collected at targeted sites and the information gained used to ascertain the nature of the observed/predicted lake water loss. The results show that both the modern and original dam appear to be intact, structurally sound and show no evidence for significant water flow through its structures. Instead, localized zones of natural, high-density fracturing in the limestone bedrock appear to be the predominant cause of lake water loss. seasonal average. However, the summer level of the lake has systematically decreased over the last 30 years and hydrological investigations, which studied the hydrological sinks and sources of the lily ponds, concluded that a staggering 250 000 m 3 of water is lost per month through seepage and evaporation. Various explanations have been proposed for the seepage pathways with the most compelling arising from observations of water flowing into the lakeside shoreline (i.e., outward flow through natural bedrock fracture zones) and the up-welling of freshwater in front of the man-made modern dam at the seaward end of the lake. Previous hydrological investigations, including dye tracer experiments and hydrological modelling, have all been unable to identify the key hydraulic pathways and determine the major causes of lake water seepage. It has been suspected for some time that, along with natural loss (through fractures in the limestone bedrock), structural weakness in the dam at the far end of the lily pond system was responsible for a major component of the seepage. As a European Special Area of Conservation, the FIGURE 1 Lo...

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“…; Kim et al . ). More specifically, self potential methods have become increasingly popular for assessing dam‐related seepage flows (Al‐Saigh et al .…”

Section: Dam Geophysical Investigationsmentioning

confidence: 97%

“…; Kim et al . ; Zhou et al . ) whilst resistivity techniques have been used to map zones of water/fluid seepage in both concrete and earth dams (Karastathis et al .…”

Section: Dam Geophysical Investigationsmentioning

confidence: 99%

The geophysical investigation of lake water seepage in the regulated environment of the Bosherston Lily Ponds, South Wales, UK. Part 2: historical, dam‐related pathways

Husband

Cassidy

Stimpson

2009

Near Surface Geophysics

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“…A good way to reduce this uncertainty, except by drilling, is the implementation of more than one geophysical method in the same area. There are several case studies showing that the integration of different geophysical methods, in general, is very useful (Ezersky et al 2006;Debeglia et al 2006;Kim et al 2007;Orfanos et al 2008;Torrese et al 2008). More specifically, the combination of resistivity tomography and microgravity is a powerful tool for the detection of underground cavities and also the ability to dis- The archaeological site of Bertseko.…”

Section: First Phase Of the Survey: Reconnaissance 2d Resistivity Tommentioning

confidence: 99%

2D‐3D resistivity and microgravity measurements for the detection of an ancient tunnel in the Lavrion area, Greece

Orfanos

Αποστολόπουλος

2011

Near Surface Geophysics

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At the archaeological site of Bertseko, Lavrion, Greece, the entrance of an ancient tunnel was found during archaeological excavations. Approximately 15 m from the entrance the tunnel remains inaccessible – blocked with filled material. The main aim of the geophysical survey was to verify if the tunnel is unblocked after that point and to delineate its direction. Another objective was to understand the purpose of its construction. As a first detection approach, eight 2D resistivity profiles were carried out with a pole‐pole array in a non rectangular grid, in order to image a wider area, a greater depth and to avoid several surface obstacles. Then the most promising area was outlined and selected for analysis with 3D resistivity tomography using parallel survey lines with a pole‐dipole array. Moreover, the microgravity method was used, for better resolution and verification of resistivity results. This study has shown that the influence of 3D effects in resistivity arrays, the choice of the 3D or 2D (pseudo‐3D) inversion approach, the position and the direction of the target in respect to the 2D profiles or 3D survey grid, are crucial factors that significantly affect the accuracy of the resistivity method in tunnel detection. Moreover, the design of the microgravity measurements, based on results of other geophysical methods, permits a flexible survey with a moderate acquisition time. If the geological environment is not complex, inversion of microgravity data is feasible and can be very useful, as it offers depth information about the target and can be directly comparative with resistivity models. The reconnaissance 2D resistivity survey was an important step for the optimized application of 3D resistivity and microgravity methods. The integrated results provided answers to archaeologist’s questions, delineating the direction of the tunnel with minimum ambiguity and showing that the ancient tunnel was not constructed to connect the two ancient tanks but is part of an ancient underground mine.

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“…E lectrical resistivity survey (ERS), as one of the most wellknown and commonly applied investigation technologies (Loke et al [1]), has been widely used in environmental investigations (LaBrecque et al [2], Hayley et al [3], Reynolds [4]), engineering prospecting (Kim et al [5], Wilkinson et al [6], Sjodahl et al [7]), hydrological surveys (Park [8]; Slater and Binley [9], Rucker [10], Cho et al [11]) and mining applications (Legault et al [12], Chambers et al [13], Liu et al [14]). Geological interpretations using observed data are usually far from revealing the complex characteristics of subsurface properties.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning Inversion of Electrical Resistivity Data

Liu

Guo

et al. 2020

IEEE Trans. Geosci. Remote Sensing

152

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The inverse problem of electrical resistivity surveys (ERS) is difficult because of its nonlinear and ill-posed nature. For this task, traditional linear inversion methods still face challenges such as sub-optimal approximation and initial model selection. Inspired by the remarkable non-linear mapping ability of deep learning approaches, in this paper we propose to build the mapping from apparent resistivity data (input) to resistivity model (output) directly by convolutional neural networks (CNNs). However, the vertically varying characteristic of patterns in the apparent resistivity data may cause ambiguity when using CNNs with the weight sharing and effective receptive field properties. To address the potential issue, we supply an additional tier feature map to CNNs to help it get aware of the relationship between input and output. Based on the prevalent U-Net architecture, we design our network (ERSInvNet) which can be trained endto-end and reach real-time inference during testing. We further introduce depth weighting function and smooth constraint into loss function to improve inversion accuracy for the deep region and suppress false anomalies. Four groups of experiments are considered to demonstrate the feasibility and efficiency of the proposed methods. According to the comprehensive qualitative analysis and quantitative comparison, ERSInvNet with tier feature map, smooth constraints and depth weighting function together achieve the best performance.

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Application of Geophysical Methods to the Safety Analysis of an Earth Dam

Cited by 7 publications

References 0 publications

The geophysical investigation of lake water seepage in the regulated environment of the Bosherston Lily Ponds, South Wales, UK. Part 2: historical, dam‐related pathways

The geophysical investigation of lake water seepage in the regulated environment of the Bosherston Lily Ponds, South Wales, UK. Part 2: historical, dam‐related pathways

2D‐3D resistivity and microgravity measurements for the detection of an ancient tunnel in the Lavrion area, Greece

Deep Learning Inversion of Electrical Resistivity Data

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