A structured approach to the use of near-surface geophysics in long-term monitoring

Versteeg, Roelof; Ankeny, M.; Harbour, Jerry L.; Heath, Gail; Kostelnik, K.M.; Mattson, Earl D.; Moor, Ken; Richardson, Alex; Wangerud, Ken

doi:10.1190/1.1776745

Cited by 19 publications

(9 citation statements)

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“…Continuous ERT measurements over pre-defined but limited time periods have been reported previously in the literature (Aaltonen and Olofsson, 2002;French and Binley, 2004;LaBrecque et al, 2004;Versteeg et al, 2004;Sjödahl et al, 2008;Kuras et al, 2009;Ogilvy et al, 2009), but no ERT system for automated and continuous long-term measurements in alpine or polar terrain has been available. The new A-ERT system was developed in close collaboration with the company Geolog (Germany) for cost-effective applications in polar and high-mountain terrain (robust and water-proof design, lightning protected, remotely controlled).…”

Section: A-ert Systemmentioning

confidence: 99%

Automated Time‐lapse ERT for Improved Process Analysis and Monitoring of Frozen Ground

Hilbich

Fuss

Hauck

2011

Permafrost & Periglacial

103

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A new automated electrical resistivity tomography (A-ERT) system is described that allows continuous measurements of the electrical resistivity distribution in high-mountain or polar terrain. The advantages of continuous resistivity monitoring, as opposed to single measurements at irregular time intervals, are illustrated using the permafrost monitoring station at the Schilthorn, Swiss Alps. Data processing was adjusted to permit automated time-effective handling and quality assessment of the large number of 2D electrical resistivity profiles generated. Results from a one-year dataset show small temporal changes during periods with snow cover, and the largest changes during snowmelt in early summer and during freezing in autumn, which are in phase with changes in either near-surface soil moisture or subsurface temperature. During the snowmelt period, spatially variable infiltration processes were observed, leading to a rapid increase in soil moisture and corresponding decrease in electrical resistivity over a period of a few days. This infiltration led to the onset of active-layer thawing long before the seasonal snow cover vanished. Statistical analyses showed that both spatial and temporal variability over the course of one year are similar, indicating the significance of spatial heterogeneity regarding active-layer dynamics. As a result of its cost-effective ability to monitor freezing and thawing processes even at greater depths, the new A-ERT system can be widely applied in permafrost regions, especially in the context of long-term degradation processes.

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Section: A-ert Systemmentioning

confidence: 99%

Automated Time‐lapse ERT for Improved Process Analysis and Monitoring of Frozen Ground

Hilbich

Fuss

Hauck

2011

Permafrost & Periglacial

103

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“…Outline of web-based workflow environment for environmental site monitoring. The example shown is for the Ruby Gulch Repository monitoring system (Versteeg, Heath et al 2003;Versteeg, Ankeny et al 2004) Our implementation has a number of elements that differentiate it from traditional workflow systems. For instance, instead of using a dedicated workflow language we use PHP.…”

Section: A Workflow System For Performance Monitoringmentioning

confidence: 99%

Managing a Capped Acid Rock Drainage (Ard) Repository Using Semi-Autonomous Monitoring and Modeling

Versteeg¹,

Wangerud²,

Richardson³

et al. 2006

JASMR

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Effective ARD repository management requires ongoing assessment of remedial integrity and operational performance in such a manner that short and long term risks and cost are balanced and optimized. Such management requires actionable information on the behavior of the repository. This information will typically be derived from diverse data (physical, chemical and hydrological), forward and inverse hydrological, geochemical and geophysical models and cost/benefit models. With the increase in volumes of data and complexity of analysis, end users face increasing challenges in obtaining information in a timely and cost effective manner. A web accessible workflow environment for performance monitoring, designed at the Idaho National Laboratory (INL), was implemented for a capped ARD repository (the Ruby Gulch Repository) and is part of the Gilt Edge Superfund site in South Dakota. This repository is instrumented with a geophysical, hydrological and environmental sensor network. Data from this network are transmitted automatically every two hours to a server. At the server, the data are automatically parsed in a relational database and analyzed using automatically executing scripts. The resulting information is both transmitted through automated reports and accessible by users through a web application. The combination of near real time reporting and analysis and integration with analysis tools provides for actionable information on short and long term repository behavior. The structure of a web accessible workflow system for performance monitoring is well suited for both managing data, creating information and providing access to information for diverse users.

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“…Volumetric imaging of the electrical properties of the subsurface by electrical resistivity tomography (ERT) has been intensively developed for over a decade. Permanently installed electrode arrays can now be used with automated multichannel data acquisition systems and rapid inversion algorithms to enable 2‐D or 3‐D time‐lapse imaging of dynamic processes (LaBreque et al 2004; Versteeg et al 2004; Ogilvy et al 2007). As the capabilities of such systems increase, more electrodes can be used thereby potentially increasing the spatial resolution of the resulting images.…”

Section: Introductionmentioning

confidence: 99%

Extreme sensitivity of crosshole electrical resistivity tomography measurements to geometric errors

Wilkinson¹,

Chambers²,

Lelliott³

et al. 2008

Geophysical Journal International

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S U M M A R YThe effects of geometric errors on crosshole resistivity data are investigated using analytical methods. Geometric errors are systematic and can occur due to uncertainties in the individual electrode positions, the vertical spacing between electrodes in the same borehole, or the vertical offset between electrodes in opposite boreholes. An estimate of the sensitivity to geometric error is calculated for each of two generic types of four-electrode crosshole configuration: current flow and potential difference crosshole (XH) and in-hole (IH). It is found that XH configurations are not particularly sensitive to geometric error unless the boreholes are closely spaced on the scale of the vertical separation of the current and potential electrodes. However, extremely sensitive IH configurations are shown to exist for any borehole separation. Therefore, it is recommended that XH configurations be used in preference to IH schemes. The effects of geometric error are demonstrated using real XH data from a closely spaced line of boreholes designed to monitor bioremediation of chlorinated solvents at an industrial site. A small fraction of the data had physically unrealistic apparent resistivities, which were either negative or unexpectedly large. However by filtering out configurations with high sensitivities to geometric error, all of the suspect data were removed. This filtering also significantly improved the convergence between the predicted and the measured resistivities when the data were inverted. In addition to systematic geometric errors, the measured data also exhibit a high level of random noise. Despite this, the resulting inverted images correspond reasonably closely with the known geology and nearby cone penetrometer resistivity profiles.

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A structured approach to the use of near-surface geophysics in long-term monitoring

Cited by 19 publications

References 0 publications

Automated Time‐lapse ERT for Improved Process Analysis and Monitoring of Frozen Ground

Automated Time‐lapse ERT for Improved Process Analysis and Monitoring of Frozen Ground

Managing a Capped Acid Rock Drainage (Ard) Repository Using Semi-Autonomous Monitoring and Modeling

Extreme sensitivity of crosshole electrical resistivity tomography measurements to geometric errors

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