Mine Water and the Environment

, Volume 31, Issue 4, pp 252–265 | Cite as

Quantitative Assessment of Mine Water Sources Based on the General Mixing Equation and Multivariate Statistics

  • Nad’a RapantováEmail author
  • Światosław Krzeszowski
  • Arnošt Grmela
  • Christian Wolkersdorfer
Technical Article


It is sometimes necessary to quantify the different sources of water entering a mine, based on the hydrochemical nature of the waters from individual aquifers that contribute to the mine water mixture. In order to solve the general mixing equation, a software tool, KYBL-7, was developed; its computational methodology is generally based on the balance of selected components of mine waters in steady state conditions, without considering chemical reactions. This approach was applied in the Sokolov Coal Basin, which is situated in the immediate vicinity of Carlsbad (Karlovy Vary), a worldwide renowned spa in the northern part of the Czech Republic. The technology and coal mining methods used in the Sokolov Coal Basin are limited due to its proximity to the Carlsbad thermal springs. Because of their social and economic significance, these springs are protected. Calculations proved that the Carlsbad waters contribute approximately 3 % to the mine water. The imbalance in the mine water mixture using known source waters was quantified by including an ‘unknown source’ in the mixture simulation. Geochemical modelling demonstrated that the water quality is a result of geochemical reactions of waters in contact with the atmosphere and the reverse dissolution of the accumulated precipitates in the open pit areas. Those results have been used to assess future technical measures that can be taken to protect the Carlsbad thermal waters.


Mine water sources proportions Open-pit coal mining Geochemical modelling Spring flow Water balance Carlsbad/Czech Republic 


Gelegentlich ist es notwendig, das mengenmäßige Verhältnis verschiedenen Quellen von Wässern zu bestimmen, die einem Bergwerk zufließen. Dies geschieht auf der Basis der hydrochemischen Eigenschaften der Wässer der unterschiedlichen Aquifere, die zur Zusammensetzung des Grubenwassers beitragen. Um die allgemeine Mischungsgleichung zu lösen, wurde die Software KYBL-7 entwickelt. Dessen numerische Methode basiert auf dem Gleichgewicht ausgewählter Parameter des Grubenwassers unter stationären Bedingungen ohne dabei chemische Reaktionen in Betracht zu ziehen. Vorgenannte Methode wurde im Sokolov Kohlebecken angewandt, das sich in unmittelbarer Nachbarschaft zu Karlsbad (Karlovy Vary) befindet; einem weltweit bekannten Thermalkurort im Norden der Tschechischen Republik. Die Thermalquellen selbst sind aufgrund ihrer gesellschaftlichen und wirtschaftlichen Bedeutung geschützt. Daher sind im Sokolov Kohlebecken aufgrund der Nähe zu diesen Thermalquellen manche Technologien und Methoden zum Kohlenabbau nur begrenzt einsetzbar. Berechnungen haben jedoch belegt, dass die Karlsbader Wässer etwa 3 % des Grubenwassers ausmachen. Dem Ungleichgewicht in der Grubenwasserzusammensetzung unter Verwendung der bekannten Wassertypen wurde dadurch Rechnung getragen, dass eine „unbekannte Quelle“in das Modell einbezogen wurde. Eine geochemische Modellierung hat gezeigt, dass die Wasserqualität ein Ergebnis geochemischen Reaktionen der Wässer mit der Atmosphäre einerseits und Rücklösung von Ausfällungsprodukten andererseits ist. Diese Ergebnisse wurden verwendet um potentielle technische Maßnahmen zu prüfen, mit denen die Karlsbader Thermalwässer künftig besser geschützt werden können.


En ocasiones es necesario cuantificar las diferentes fuentes de agua que entran a una mina, basado en la naturaleza hidroquímica de las aguas de acuíferos particulares que contribuyen al agua de mina. En función de resolver la ecuación general de mezclado, se desarrolló el software KYBL-7; su metodología computacional está basada en el balance de componentes seleccionados de aguas de mina en condiciones de estado estacionario, sin consideración de las reacciones químicas. Esta metodología fue aplicada en la cuenca de carbón Sokolov, situada en la vecindad de Carlsbad (Karlovy Vary), un spa reconocido a nivel mundial ubicado en la parte norte de la República Checa. La tecnología aplicada en la explotación del carbón usada en aquella Cuenca está limitada por su proximidad a los baños termales Carlsbad. Debido a su importancia social y económica, estos baños están protegidos. Los cálculos probaron que las aguas Carlsbad contribuyen aproximadamente con un 3 % del agua de mina. El desbalance en el agua de mina existente al compararlo con las fuentes de agua conocidas fue cuantificado incluyendo una “fuente desconocida” en la simulación de la mezcla. El modelo geoquímico demostró que la calidad del agua es un resultado de las reacciones geoquímicas de aguas en contacto con la atmósfera y la disolución de los precipitados acumulados en las áreas a cielo abierto. Aquellos resultados han sido usados para analizar las medidas técnicas futuras que pueden ser tomadas para proteger las aguas termales Carlsbad.


在某些条件下,基于水化学特征定量评价矿井水中各充水水源的比例是非常重要的。文章利用KYBL-7软件求解矿井水混合方程。该软件的求解原理是在不考虑矿井水组份化学反应的前提下,进行矿井水选定组份的物质平衡计算,建立和求解矿井水混合方程。该方法被用于捷克共和国北部著名的温泉城市卡罗维发利(Karlovy Vary,在德语中被称为Carlsbad)附近的Sokolov煤田。Carlsbad温泉具有重要的社会和经济价值而受到保护。Sokolov煤田因为毗邻Carlsbad温泉而煤炭开采技术与方法受到限制。计算表明,Carlsbad温泉水仅占Sokolov矿区矿井水的3%左右。采用在矿井水混合模拟中加入“未知水源”的方法,文章实现矿井水不平衡组分的定量分析,从而达到计算各已知水源混合比例的目的。地球化学模拟结果表明,矿井水水质是水与大气接触发生地球化学反应以及露天煤矿区沉淀物质溶解反应的结果。该研成果已经用于评估Carlsbad温泉未来保护技术措施的可行和有效性。



This research was financially supported by the Czech Science Foundation (research project No. 105/09/0808) and by the Ministry of Education, Youth and Sports of the Czech Republic in the framework of the National research program 1M—the research centres (Research Centre for Integrated System Development Concerning Utilization of By-Products of Energy Resource Mining and Processing). Thanks to our anonymous reviewers who helped to improve this paper.


  1. Adamczewski Z (2010) Rachunek Wyrównawczy w 15 wykładach [Adjustment Analysis in 15 lectures], 2nd edn. Oficyna Wydawnicza Politechniki Warszawskiej, WarszawaGoogle Scholar
  2. Adamovic J, Coubal M (1999) Intrusive geometries and Cenozoic stress history of the northern part of the Bohemian Massif. Geolines 9:5–14Google Scholar
  3. Brassington R (2006) Field hydrogeology. Wiley, ChichesterCrossRefGoogle Scholar
  4. Cajz V, Valecka J (2010) Tectonic setting of the Ohře/Eger Graben between the central part of the České středohoří Mts. and the Most Basin, a regional study. J Geosci 55(3):201–215CrossRefGoogle Scholar
  5. Cressie NAC (1993) Statistics for spatial data, Revised Edn. Wiley, New York, NYGoogle Scholar
  6. Dupalová T, Sracek O, Vencelides Z, Žák K (2012) The origin of thermal waters in the northeastern part of the Eger Rift, Czech Republic. Appl Geochem 27(3):689–702. doi: 10.1016/j.apgeochem.2011.11.016 CrossRefGoogle Scholar
  7. Fetter CW (2001) Applied Hydrogeology, 4th edn. Prentice-Hall, New JerseyGoogle Scholar
  8. Geller W, Schultze M, Kleinmann R, Wolkersdorfer Ch (eds) (2012) Acidic pit lakes – the legacy of coal and metal surface mines. Environmental Science and Engineering. Springer, Heidelberg. doi: 10.1007/978-3-642-29384-9_3
  9. Gille JC, Clique M (1986) Rachunek macierzowy i wprowadzenie do analizy funkcjonalnej [The matrix calculus and introduction to the functional analysis], 2nd edn. Silesian University of Technology, GliwiceGoogle Scholar
  10. Gómez JB, Auqué LF, Gimeno MJ (2008) Sensitivity and uncertainty analysis of mixing and mass balance calculations with standard PCA-based geochemical codes. Appl Geochem 23:1941–1956CrossRefGoogle Scholar
  11. Hokr Z (1961) Terciér sokolovské hnědouhelné pánve [Tertiary of Sokolov Coal Basin]. Sbor Ústř Úst Geol 26(2):119–174Google Scholar
  12. Homola V, Klír S (1975) Hydrogeologie ČSSR III [Hydrogeology CSSR III]. Akademia, PrahaGoogle Scholar
  13. Hynie O (1963) Hydrogeologie ČSSR II Minerální vody [Hydrogeology ČSSR II. Mineral waters]. Nakladatelství ČSAV, PrahaGoogle Scholar
  14. Jolliffe IT (1986) Principal component analysis. Springer, New York, NYGoogle Scholar
  15. Keqiang H, Wancheng Y, Wenfu J (2011) Analysis of groundwater inrush conditions and critical inspection parameters at the Baixiangshan Iron Mine, China. Mine Water Environ 30(4):274–283. doi: 10.1007/s10230-011-0158-0 CrossRefGoogle Scholar
  16. Kipko EY, Spichak YN, Polozov YA, Kipko AE, Hepnar P (1993) Grouting of old flooded workings at M. Mayerova Mine in Czechoslovakia. Mine Water Environ 12(1–4):21–26Google Scholar
  17. Kopecký L (1978) Neoidic taphrogenic evolution and young alkaline volcanism of the Bohemian Massif. Sbor Geol Ved Geol, pp 91–108Google Scholar
  18. Krešić N (1997) Quantitative solutions in hydrogeology and groundwater modelling. Lewis, New York, NYGoogle Scholar
  19. Krzanowski WJ (1988) Principles of multivariate analysis. Oxford Science, OxfordGoogle Scholar
  20. Krzeszowski S (2005) Obliczanie składu i udziału nieznanego strumienia w mieszaninie o znanym składzie przy pomocy programu komputerowego KYBL-4 [Evaluation of the composition and proportion of an unknown source in the mixture by the computer program KYBL-4]. Zeszyty Naukowe Politechniki Śląskiej, Górnictwo z. 267:137–146Google Scholar
  21. Krzeszowski S (2009) Badania nad określeniem składu i udziału nieznanego strumienia wody w układach wodnych na przykładzie wód kopalnianych [Research on the proportion and composition of unknown source in mine water mixture—case studies]. Disseration, Politechnika Śląska Wydz. Inżynierii Środowiska i Energetyki, Instytut Inżynierii Wody i Ścieków, Gliwice, PolandGoogle Scholar
  22. Krzeszowski S, Grmela A, Rapantová N, Labus K (2005) Preliminary comments on the method of estimating the composition, and portion of an unknown source in mine waters mixture. Proc, XII. National Hydrogeological Congress, Ceske Budejovice, Ceske Budejovice, Czech Republic, pp 81–86Google Scholar
  23. Laaksoharju M, Skårman Ch, Skårman E (1999) Multivariate mixing and mass balance (M3) calculations, a new tool for decoding hydrogeochemical information. Appl Geochem 14(7):861–872CrossRefGoogle Scholar
  24. Laaksoharju M, Gascoyne M, Gurban I (2008) Understanding groundwater chemistry using mixing models. Appl Geochem 23:1921–1940CrossRefGoogle Scholar
  25. Laboutka M, Vylita B (1983) Mineral and thermal waters of Western Bohemia. GeoJournal 7(5):403–411CrossRefGoogle Scholar
  26. Manly BFJ (1994) Multivariate Statistical Methods—a primer. Chapman & Hall, LondonGoogle Scholar
  27. Mísař Z, Dudek A, Havlena V, Weiss V (1983) Geologie ČSSR I, Český masív [Geology ČSSR I, Bohemian Massif]. Státní pedagog. nakl., PrahaGoogle Scholar
  28. Paces T (1988) Volcanic Origin of Mineral Springs in Central Europe and their Utilization in Spas. In: Proc, International Conf on Volcanoes, Kagoshima, Japan, pp 878–881Google Scholar
  29. Parkhurst DL, Appelo CAJ (1999) User’s Guide to PHREEQC (Version 2) – A Computer Program for Speciation, Batch-Reaction, One-Dimensional Transport, and Inverse Geochemical Calculations. Water-Resources Investigations Report WRI 99-4259:312Google Scholar
  30. Perry EF, Evans RS (1999) Application of geochemical modelling and hydrologic techniques to interpret sources, mixing and evolution of mine drainage. Mining and Reclamation for the Next Millennium, vol 2. In: Proc, 16th Annual National Meeting of the American Soc for Surface Mining and Reclamation, pp 444–452Google Scholar
  31. PIRAMID Consortium (2003) Passive In situ Remediation of Acid Mine/Industrial Drainage (PIRAMID). A research project of the European Commission 5th Framework Programme, key action 1: Sustainable Management and Quality on Water, Final Report Contract EVK1-CT-1999—000021, Accessed 22 Jan 2012
  32. Plummer LN, Prestemon EC, Parkhurst DL (1994) An Interactive Code (NETPATH) for Modeling NET Geochemical Reactions along a Flow PATH. Version 2.0, USGS Water-Resources Investigations Report 94—4169,
  33. Rajchl M, Uličný D, Grygar R, Mach K (2009) Evolution of basin architecture in an incipient continental rift: the Cenozoic Most Basin, Eger Graben (Central Europe). Basin Res 21(3):269–294Google Scholar
  34. Rapantova N, Grmela A, Vojtek D, Halir J, Michalek B (2007) Groundwater flow modelling applications in mining hydrogeology. Mine Water Environ 26(4):264–271CrossRefGoogle Scholar
  35. Rojík P (2004) Tektonosedimentární vývoj sokolovské pánve a její interakce s územím Krušných hor [Tectono-sedimentary development of Sokolov Coal Basin and its interaction with Krušné Hory Mountaines]. Dissertation. Charles University, PragueGoogle Scholar
  36. Sena C, Molinero J (2009) Water resources assessment and hydrogeological modelling as a tool for the feasibility study of a closure plan for an open pit mine (La Respina Mine, Spain). Mine Water Environ 28(2):94–101CrossRefGoogle Scholar
  37. Singh RN (1986) Mine Inundations. Int J Mine Water 5(2):1–27CrossRefGoogle Scholar
  38. Singh RN, Atkins AS (1985) Analytical techniques for the estimation of mine water inflow. Int J Min Eng 3(1):65–77CrossRefGoogle Scholar
  39. Usher BH, Strachotta C, Strand R, Jackson J (2010) Linking fundamental geochemistry and empirical observations for water quality predictions using Goldsim. In: Wolkersdorfer Ch, Freund A, Proc, Mine Water and Innovative Thinking—International Mine Water Assoc Symp, Cape Breton Univ Press, Sydney, NS, Canada, pp 313–317Google Scholar
  40. Vrba J (1996) Thermal mineral water springs in Karlovy Vary. Environ Geol 27(2):120–125. doi: 10.1007/BF01061684 Google Scholar
  41. Vutukuri VS, Singh RN (1995) Mine inundation—case histories. Mine Water Environ 14(1–4):107–130Google Scholar
  42. Wardrop DR, Leake CC, Abra J (2001) Practical techniques that minimize the impact of quarries on the water environment. Transactions of the Institute of Mining and Metallurgy (Section B: Applied Earth Sciences) 110:B5–B13Google Scholar
  43. Wiencław E, Koda E (2008) Numerical modelling for dewatering system development in a lignite open pit mine [Wykorzystanie modelowania do rozbudowy systemu odwodnienia w odkrywkowej kopalni wegla brunatnego] Biuletyn—Panstwowego Instytutu Geologicznego 431:267–274Google Scholar
  44. Wolkersdorfer Ch (2008) Water management at abandoned flooded underground mines. Springer, BerlinGoogle Scholar
  45. Wolkersdorfer Ch, Bowell R (2005) Contemporary reviews of mine water studies in Europe, Part 3. Mine Water Environ 24(2):58–76, GermanyGoogle Scholar
  46. Xiaouhui G, Xiaoping M (2010) Mine water discharge prediction based on least square support vector machines. Min Sci Technol 20(5):738–742Google Scholar
  47. Younger PL (1993) Possible environmental impact of the closure of two collieries in county durham. Water Environ Manage 7(5):521–531Google Scholar
  48. Younger PL, Banwart SA, Hedin RS (2002) Mine water—hydrology, pollution, remediation. Kluwer, Dordrecht, The NetherlandsGoogle Scholar
  49. Younger PL, Wolkersdorfer C, ERMITE Consortium (2004) Mining impacts on the fresh water environment: technical and managerial guidelines for catchment scale management. Mine Water Environ 23(S-1):2–80Google Scholar
  50. Zhu QH, Feng MM, Mao XB (2008) Numerical analyses of water inrush from working face-floor during mining. J Chin Univ Min Technol 18(2):159–163CrossRefGoogle Scholar
  51. Ziegler PA (1992) European Cenozoic rift system. Tectonophysics 208:91–111CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Nad’a Rapantová
    • 1
    Email author
  • Światosław Krzeszowski
    • 2
  • Arnošt Grmela
    • 1
  • Christian Wolkersdorfer
    • 3
    • 4
  1. 1.Institute of Clean Technologies for Mining and Utilization of Raw Materials for Energy UseVSB - Technical University of OstravaOstravaCzech Republic
  2. 2.Silesian University of TechnologyGliwicePoland
  3. 3.Cape Breton UniversitySydneyCanada
  4. 4.International Mine Water AssociationWendelsteinGermany

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