Spatial monitoring of groundwater drawdown and rebound associated with quarry dewatering using automated time-lapse electrical resistivity tomography and distribution guided clustering

Dewatering systems used for mining and quarrying operations often result in highly artificial and complex groundwater conditions, which can be difficult to characterise and monitor using borehole point sampling approaches. Here automated time-lapse electrical resistivity tomography (ALERT) is consid...

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Main Authors: Chambers, Jon E., Meldrum, Philip I., Wilkinson, Paul B., Ward, Wil O.C., Jackson, Christopher R., Matthew, B., Joel, P., Kuras, Oliver, Bai, Li, Uhlemann, Sebastian, Gunn, David
Format: Article
Published: Elsevier 2015
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Online Access:https://eprints.nottingham.ac.uk/37748/
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author Chambers, Jon E.
Meldrum, Philip I.
Wilkinson, Paul B.
Ward, Wil O.C.
Jackson, Christopher R.
Matthew, B.
Joel, P.
Kuras, Oliver
Bai, Li
Uhlemann, Sebastian
Gunn, David
author_facet Chambers, Jon E.
Meldrum, Philip I.
Wilkinson, Paul B.
Ward, Wil O.C.
Jackson, Christopher R.
Matthew, B.
Joel, P.
Kuras, Oliver
Bai, Li
Uhlemann, Sebastian
Gunn, David
author_sort Chambers, Jon E.
building Nottingham Research Data Repository
collection Online Access
description Dewatering systems used for mining and quarrying operations often result in highly artificial and complex groundwater conditions, which can be difficult to characterise and monitor using borehole point sampling approaches. Here automated time-lapse electrical resistivity tomography (ALERT) is considered as a means of monitoring subsurface groundwater dynamics associated with changes in the dewatering regime in an operational sand and gravel quarry. We considered two scenarios: the first was unplanned interruption to dewatering due to a pump failure for a period of several days, which involved comparing ALERT monitoring results before and after groundwater rebound; the second involved a planned interruption to pumping over a period of 6 h, for which near-continuous ALERT monitoring of groundwater rebound and drawdown was undertaken. The results of the second test were analysed using distribution guided clustering (DGC) to provide a more quantitative and objective assessment of changes in the subsurface over time. ALERT successfully identified groundwater level changes during both monitoring scenarios. It provided a more useful indication of the rate of water level rise and maximum water levels than piezometer monitoring results. This was due to the piezometers rapidly responding to pressure changes at depth, whilst ALERT/DGC provided information of slower changes associated with the storage and delayed drainage of water within the sediment. By applying DGC we were able to automatically and quantitatively define changes in the resistivity sections, which correlated well with the direct observations of groundwater at site. For ERT monitoring applications that generate numerous time series, the use of DGC could significantly enhance the efficiency of data interpretation, and provide a means of automating groundwater monitoring through assigning alarm thresholds associated with rapid changes in groundwater conditions.
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spelling nottingham-377482020-05-04T17:13:45Z https://eprints.nottingham.ac.uk/37748/ Spatial monitoring of groundwater drawdown and rebound associated with quarry dewatering using automated time-lapse electrical resistivity tomography and distribution guided clustering Chambers, Jon E. Meldrum, Philip I. Wilkinson, Paul B. Ward, Wil O.C. Jackson, Christopher R. Matthew, B. Joel, P. Kuras, Oliver Bai, Li Uhlemann, Sebastian Gunn, David Dewatering systems used for mining and quarrying operations often result in highly artificial and complex groundwater conditions, which can be difficult to characterise and monitor using borehole point sampling approaches. Here automated time-lapse electrical resistivity tomography (ALERT) is considered as a means of monitoring subsurface groundwater dynamics associated with changes in the dewatering regime in an operational sand and gravel quarry. We considered two scenarios: the first was unplanned interruption to dewatering due to a pump failure for a period of several days, which involved comparing ALERT monitoring results before and after groundwater rebound; the second involved a planned interruption to pumping over a period of 6 h, for which near-continuous ALERT monitoring of groundwater rebound and drawdown was undertaken. The results of the second test were analysed using distribution guided clustering (DGC) to provide a more quantitative and objective assessment of changes in the subsurface over time. ALERT successfully identified groundwater level changes during both monitoring scenarios. It provided a more useful indication of the rate of water level rise and maximum water levels than piezometer monitoring results. This was due to the piezometers rapidly responding to pressure changes at depth, whilst ALERT/DGC provided information of slower changes associated with the storage and delayed drainage of water within the sediment. By applying DGC we were able to automatically and quantitatively define changes in the resistivity sections, which correlated well with the direct observations of groundwater at site. For ERT monitoring applications that generate numerous time series, the use of DGC could significantly enhance the efficiency of data interpretation, and provide a means of automating groundwater monitoring through assigning alarm thresholds associated with rapid changes in groundwater conditions. Elsevier 2015-07-02 Article PeerReviewed Chambers, Jon E., Meldrum, Philip I., Wilkinson, Paul B., Ward, Wil O.C., Jackson, Christopher R., Matthew, B., Joel, P., Kuras, Oliver, Bai, Li, Uhlemann, Sebastian and Gunn, David (2015) Spatial monitoring of groundwater drawdown and rebound associated with quarry dewatering using automated time-lapse electrical resistivity tomography and distribution guided clustering. Engineering Geology, 193 . pp. 412-420. ISSN 1872-6917 Electrical resistivity tomography (ERT); Mining; Dewatering; Groundwater monitoring; Clustering; Image analysis http://www.sciencedirect.com/science/article/pii/S0013795215001696 doi:10.1016/j.enggeo.2015.05.015 doi:10.1016/j.enggeo.2015.05.015
spellingShingle Electrical resistivity tomography (ERT); Mining; Dewatering; Groundwater monitoring; Clustering; Image analysis
Chambers, Jon E.
Meldrum, Philip I.
Wilkinson, Paul B.
Ward, Wil O.C.
Jackson, Christopher R.
Matthew, B.
Joel, P.
Kuras, Oliver
Bai, Li
Uhlemann, Sebastian
Gunn, David
Spatial monitoring of groundwater drawdown and rebound associated with quarry dewatering using automated time-lapse electrical resistivity tomography and distribution guided clustering
title Spatial monitoring of groundwater drawdown and rebound associated with quarry dewatering using automated time-lapse electrical resistivity tomography and distribution guided clustering
title_full Spatial monitoring of groundwater drawdown and rebound associated with quarry dewatering using automated time-lapse electrical resistivity tomography and distribution guided clustering
title_fullStr Spatial monitoring of groundwater drawdown and rebound associated with quarry dewatering using automated time-lapse electrical resistivity tomography and distribution guided clustering
title_full_unstemmed Spatial monitoring of groundwater drawdown and rebound associated with quarry dewatering using automated time-lapse electrical resistivity tomography and distribution guided clustering
title_short Spatial monitoring of groundwater drawdown and rebound associated with quarry dewatering using automated time-lapse electrical resistivity tomography and distribution guided clustering
title_sort spatial monitoring of groundwater drawdown and rebound associated with quarry dewatering using automated time-lapse electrical resistivity tomography and distribution guided clustering
topic Electrical resistivity tomography (ERT); Mining; Dewatering; Groundwater monitoring; Clustering; Image analysis
url https://eprints.nottingham.ac.uk/37748/
https://eprints.nottingham.ac.uk/37748/
https://eprints.nottingham.ac.uk/37748/