Long-Term Time-Series Analysis to Understand Groundwater Flow in Abandoned Subsurface Mines with Application to a Coalfield in Liège, Belgium

Complex underground flow processes can occur in flooded mine workings. As the groundwater rebounds, outbreaks, flooding, and slope stability problems can occur where hydraulic pressures build up in less drained areas. A time-series statistical analysis was conducted to understand how exploited areas...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Mine water and the environment 2018-09, Vol.37 (3), p.470-481
Hauptverfasser: Ronchi, B., Stassen, F., Drevet, J.-P., Frippiat, C. C., Berger, J.-L., Dingelstadt, C., Veschkens, M.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 481
container_issue 3
container_start_page 470
container_title Mine water and the environment
container_volume 37
creator Ronchi, B.
Stassen, F.
Drevet, J.-P.
Frippiat, C. C.
Berger, J.-L.
Dingelstadt, C.
Veschkens, M.
description Complex underground flow processes can occur in flooded mine workings. As the groundwater rebounds, outbreaks, flooding, and slope stability problems can occur where hydraulic pressures build up in less drained areas. A time-series statistical analysis was conducted to understand how exploited areas in an abandoned coalfield were connected and to calculate groundwater response times to rain events by spatially and temporally correlating piezometric levels and discharge rates. Ten years of flow rate and water level data were statistically analyzed for an abandoned coalfield in Liège (Belgium). Then, the results were compared to results from physically-based simulations (a 3D groundwater flow model) based on data from the first 2 years of monitoring. The statistical approach gives qualitative indications on the interconnections between the different areas of the coalfield, as well as on the storage capacity/transmissivity of the aquifer. Improved understanding of this hydrogeological behavior can be used to prevent post-mining accidents and assess the associated risks.
doi_str_mv 10.1007/s10230-018-0528-y
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2918164477</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2015633056</sourcerecordid><originalsourceid>FETCH-LOGICAL-c259y-a4239b812aba737b38ba8365dd5b63654c0fad1e312682dda00e2554e0b7d7883</originalsourceid><addsrcrecordid>eNp9kUGOEzEQRS0EEkPgAOwsscVQZbfdzjJEzIAUxGIya8vddgePOnawuxX1JTgH9-BiOAoSK9jUL6n-f1LpE_Ia4R0CtO8LAhfAADUDyTVbnpAbVKgYgtJP6w5csjUif05elPIIgK3i8ob82KV4YHufj3Qfjp7d-xx8oZtox6WEQqdEH6LzuUw2OnqX0xzd2U4-09sxnWmIdNPVS4re0fu5K3MebO_plxAr5Rymb3RzOo2ht1NI8UKzdJvsOAQ_ukt6F379PPi39IMfD2E-viTPBjsW_-qPrsjD7cf99hPbfb37vN3sWM_lemG24WLdaeS2s61oO6E7q4WSzslOVW16GKxDL5ArzZ2zAJ5L2XjoWtdqLVbkzZV7yun77MtkHtOc69PF8DVqVE3Ttv91AUolBNSxInh19TmVkv1gTjkcbV4MgrmUY67lmFqOuZRjlprh10yp3njw-S_536HfuKiS4g</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2015633056</pqid></control><display><type>article</type><title>Long-Term Time-Series Analysis to Understand Groundwater Flow in Abandoned Subsurface Mines with Application to a Coalfield in Liège, Belgium</title><source>SpringerNature Journals</source><creator>Ronchi, B. ; Stassen, F. ; Drevet, J.-P. ; Frippiat, C. C. ; Berger, J.-L. ; Dingelstadt, C. ; Veschkens, M.</creator><creatorcontrib>Ronchi, B. ; Stassen, F. ; Drevet, J.-P. ; Frippiat, C. C. ; Berger, J.-L. ; Dingelstadt, C. ; Veschkens, M.</creatorcontrib><description>Complex underground flow processes can occur in flooded mine workings. As the groundwater rebounds, outbreaks, flooding, and slope stability problems can occur where hydraulic pressures build up in less drained areas. A time-series statistical analysis was conducted to understand how exploited areas in an abandoned coalfield were connected and to calculate groundwater response times to rain events by spatially and temporally correlating piezometric levels and discharge rates. Ten years of flow rate and water level data were statistically analyzed for an abandoned coalfield in Liège (Belgium). Then, the results were compared to results from physically-based simulations (a 3D groundwater flow model) based on data from the first 2 years of monitoring. The statistical approach gives qualitative indications on the interconnections between the different areas of the coalfield, as well as on the storage capacity/transmissivity of the aquifer. Improved understanding of this hydrogeological behavior can be used to prevent post-mining accidents and assess the associated risks.</description><identifier>ISSN: 1025-9112</identifier><identifier>EISSN: 1616-1068</identifier><identifier>DOI: 10.1007/s10230-018-0528-y</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Abandoned mines ; Aquifers ; Coal ; Computer simulation ; Data processing ; Drainage ; Earth and Environmental Science ; Earth Sciences ; Ecotoxicology ; Exploitation ; Flooding ; Floods ; Flow rates ; Flow velocity ; Geology ; Groundwater ; Groundwater flow ; Hydraulics ; Hydrogeology ; Industrial Pollution Prevention ; Mine flooding ; Mineral Resources ; Mines ; Mining ; Mining accidents &amp; safety ; Outbreaks ; Permeability ; Rain ; Slope stability ; Statistical analysis ; Statistical methods ; Statistics ; Storage capacity ; Storage conditions ; Technical Article ; Three dimensional flow ; Three dimensional models ; Time series ; Transmissivity ; Underground mines ; Water levels ; Water Quality/Water Pollution</subject><ispartof>Mine water and the environment, 2018-09, Vol.37 (3), p.470-481</ispartof><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2018</rights><rights>Mine Water and the Environment is a copyright of Springer, (2018). All Rights Reserved.</rights><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2018.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c259y-a4239b812aba737b38ba8365dd5b63654c0fad1e312682dda00e2554e0b7d7883</citedby><cites>FETCH-LOGICAL-c259y-a4239b812aba737b38ba8365dd5b63654c0fad1e312682dda00e2554e0b7d7883</cites><orcidid>0000-0002-1226-6389</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10230-018-0528-y$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10230-018-0528-y$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Ronchi, B.</creatorcontrib><creatorcontrib>Stassen, F.</creatorcontrib><creatorcontrib>Drevet, J.-P.</creatorcontrib><creatorcontrib>Frippiat, C. C.</creatorcontrib><creatorcontrib>Berger, J.-L.</creatorcontrib><creatorcontrib>Dingelstadt, C.</creatorcontrib><creatorcontrib>Veschkens, M.</creatorcontrib><title>Long-Term Time-Series Analysis to Understand Groundwater Flow in Abandoned Subsurface Mines with Application to a Coalfield in Liège, Belgium</title><title>Mine water and the environment</title><addtitle>Mine Water Environ</addtitle><description>Complex underground flow processes can occur in flooded mine workings. As the groundwater rebounds, outbreaks, flooding, and slope stability problems can occur where hydraulic pressures build up in less drained areas. A time-series statistical analysis was conducted to understand how exploited areas in an abandoned coalfield were connected and to calculate groundwater response times to rain events by spatially and temporally correlating piezometric levels and discharge rates. Ten years of flow rate and water level data were statistically analyzed for an abandoned coalfield in Liège (Belgium). Then, the results were compared to results from physically-based simulations (a 3D groundwater flow model) based on data from the first 2 years of monitoring. The statistical approach gives qualitative indications on the interconnections between the different areas of the coalfield, as well as on the storage capacity/transmissivity of the aquifer. Improved understanding of this hydrogeological behavior can be used to prevent post-mining accidents and assess the associated risks.</description><subject>Abandoned mines</subject><subject>Aquifers</subject><subject>Coal</subject><subject>Computer simulation</subject><subject>Data processing</subject><subject>Drainage</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Ecotoxicology</subject><subject>Exploitation</subject><subject>Flooding</subject><subject>Floods</subject><subject>Flow rates</subject><subject>Flow velocity</subject><subject>Geology</subject><subject>Groundwater</subject><subject>Groundwater flow</subject><subject>Hydraulics</subject><subject>Hydrogeology</subject><subject>Industrial Pollution Prevention</subject><subject>Mine flooding</subject><subject>Mineral Resources</subject><subject>Mines</subject><subject>Mining</subject><subject>Mining accidents &amp; safety</subject><subject>Outbreaks</subject><subject>Permeability</subject><subject>Rain</subject><subject>Slope stability</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>Statistics</subject><subject>Storage capacity</subject><subject>Storage conditions</subject><subject>Technical Article</subject><subject>Three dimensional flow</subject><subject>Three dimensional models</subject><subject>Time series</subject><subject>Transmissivity</subject><subject>Underground mines</subject><subject>Water levels</subject><subject>Water Quality/Water Pollution</subject><issn>1025-9112</issn><issn>1616-1068</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kUGOEzEQRS0EEkPgAOwsscVQZbfdzjJEzIAUxGIya8vddgePOnawuxX1JTgH9-BiOAoSK9jUL6n-f1LpE_Ia4R0CtO8LAhfAADUDyTVbnpAbVKgYgtJP6w5csjUif05elPIIgK3i8ob82KV4YHufj3Qfjp7d-xx8oZtox6WEQqdEH6LzuUw2OnqX0xzd2U4-09sxnWmIdNPVS4re0fu5K3MebO_plxAr5Rymb3RzOo2ht1NI8UKzdJvsOAQ_ukt6F379PPi39IMfD2E-viTPBjsW_-qPrsjD7cf99hPbfb37vN3sWM_lemG24WLdaeS2s61oO6E7q4WSzslOVW16GKxDL5ArzZ2zAJ5L2XjoWtdqLVbkzZV7yun77MtkHtOc69PF8DVqVE3Ttv91AUolBNSxInh19TmVkv1gTjkcbV4MgrmUY67lmFqOuZRjlprh10yp3njw-S_536HfuKiS4g</recordid><startdate>20180901</startdate><enddate>20180901</enddate><creator>Ronchi, B.</creator><creator>Stassen, F.</creator><creator>Drevet, J.-P.</creator><creator>Frippiat, C. C.</creator><creator>Berger, J.-L.</creator><creator>Dingelstadt, C.</creator><creator>Veschkens, M.</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QH</scope><scope>7ST</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8C1</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H97</scope><scope>HCIFZ</scope><scope>L.G</scope><scope>M2P</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0002-1226-6389</orcidid></search><sort><creationdate>20180901</creationdate><title>Long-Term Time-Series Analysis to Understand Groundwater Flow in Abandoned Subsurface Mines with Application to a Coalfield in Liège, Belgium</title><author>Ronchi, B. ; Stassen, F. ; Drevet, J.-P. ; Frippiat, C. C. ; Berger, J.-L. ; Dingelstadt, C. ; Veschkens, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c259y-a4239b812aba737b38ba8365dd5b63654c0fad1e312682dda00e2554e0b7d7883</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Abandoned mines</topic><topic>Aquifers</topic><topic>Coal</topic><topic>Computer simulation</topic><topic>Data processing</topic><topic>Drainage</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Ecotoxicology</topic><topic>Exploitation</topic><topic>Flooding</topic><topic>Floods</topic><topic>Flow rates</topic><topic>Flow velocity</topic><topic>Geology</topic><topic>Groundwater</topic><topic>Groundwater flow</topic><topic>Hydraulics</topic><topic>Hydrogeology</topic><topic>Industrial Pollution Prevention</topic><topic>Mine flooding</topic><topic>Mineral Resources</topic><topic>Mines</topic><topic>Mining</topic><topic>Mining accidents &amp; safety</topic><topic>Outbreaks</topic><topic>Permeability</topic><topic>Rain</topic><topic>Slope stability</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><topic>Statistics</topic><topic>Storage capacity</topic><topic>Storage conditions</topic><topic>Technical Article</topic><topic>Three dimensional flow</topic><topic>Three dimensional models</topic><topic>Time series</topic><topic>Transmissivity</topic><topic>Underground mines</topic><topic>Water levels</topic><topic>Water Quality/Water Pollution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ronchi, B.</creatorcontrib><creatorcontrib>Stassen, F.</creatorcontrib><creatorcontrib>Drevet, J.-P.</creatorcontrib><creatorcontrib>Frippiat, C. C.</creatorcontrib><creatorcontrib>Berger, J.-L.</creatorcontrib><creatorcontrib>Dingelstadt, C.</creatorcontrib><creatorcontrib>Veschkens, M.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>Public Health Database</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural &amp; Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric &amp; Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 3: Aquatic Pollution &amp; Environmental Quality</collection><collection>SciTech Premium Collection</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><collection>Science Database</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric &amp; Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Environment Abstracts</collection><jtitle>Mine water and the environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ronchi, B.</au><au>Stassen, F.</au><au>Drevet, J.-P.</au><au>Frippiat, C. C.</au><au>Berger, J.-L.</au><au>Dingelstadt, C.</au><au>Veschkens, M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Long-Term Time-Series Analysis to Understand Groundwater Flow in Abandoned Subsurface Mines with Application to a Coalfield in Liège, Belgium</atitle><jtitle>Mine water and the environment</jtitle><stitle>Mine Water Environ</stitle><date>2018-09-01</date><risdate>2018</risdate><volume>37</volume><issue>3</issue><spage>470</spage><epage>481</epage><pages>470-481</pages><issn>1025-9112</issn><eissn>1616-1068</eissn><abstract>Complex underground flow processes can occur in flooded mine workings. As the groundwater rebounds, outbreaks, flooding, and slope stability problems can occur where hydraulic pressures build up in less drained areas. A time-series statistical analysis was conducted to understand how exploited areas in an abandoned coalfield were connected and to calculate groundwater response times to rain events by spatially and temporally correlating piezometric levels and discharge rates. Ten years of flow rate and water level data were statistically analyzed for an abandoned coalfield in Liège (Belgium). Then, the results were compared to results from physically-based simulations (a 3D groundwater flow model) based on data from the first 2 years of monitoring. The statistical approach gives qualitative indications on the interconnections between the different areas of the coalfield, as well as on the storage capacity/transmissivity of the aquifer. Improved understanding of this hydrogeological behavior can be used to prevent post-mining accidents and assess the associated risks.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s10230-018-0528-y</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-1226-6389</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 1025-9112
ispartof Mine water and the environment, 2018-09, Vol.37 (3), p.470-481
issn 1025-9112
1616-1068
language eng
recordid cdi_proquest_journals_2918164477
source SpringerNature Journals
subjects Abandoned mines
Aquifers
Coal
Computer simulation
Data processing
Drainage
Earth and Environmental Science
Earth Sciences
Ecotoxicology
Exploitation
Flooding
Floods
Flow rates
Flow velocity
Geology
Groundwater
Groundwater flow
Hydraulics
Hydrogeology
Industrial Pollution Prevention
Mine flooding
Mineral Resources
Mines
Mining
Mining accidents & safety
Outbreaks
Permeability
Rain
Slope stability
Statistical analysis
Statistical methods
Statistics
Storage capacity
Storage conditions
Technical Article
Three dimensional flow
Three dimensional models
Time series
Transmissivity
Underground mines
Water levels
Water Quality/Water Pollution
title Long-Term Time-Series Analysis to Understand Groundwater Flow in Abandoned Subsurface Mines with Application to a Coalfield in Liège, Belgium
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-22T08%3A53%3A32IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Long-Term%20Time-Series%20Analysis%20to%20Understand%20Groundwater%20Flow%20in%20Abandoned%20Subsurface%20Mines%20with%20Application%20to%20a%20Coalfield%20in%20Li%C3%A8ge,%20Belgium&rft.jtitle=Mine%20water%20and%20the%20environment&rft.au=Ronchi,%20B.&rft.date=2018-09-01&rft.volume=37&rft.issue=3&rft.spage=470&rft.epage=481&rft.pages=470-481&rft.issn=1025-9112&rft.eissn=1616-1068&rft_id=info:doi/10.1007/s10230-018-0528-y&rft_dat=%3Cproquest_cross%3E2015633056%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2015633056&rft_id=info:pmid/&rfr_iscdi=true