Skip to main content

Advertisement

Log in

A quantitative composition calculation model of mine water source based on “emblematic ions”

Un modèle de calcul quantitatif de la composition d’une eau minière basé sur les “ions emblématiques”

Un modelo cuantitativo de cálculo de la composición del agua de minas basado en los “iones emblemáticos”

基于“标志性离子”的矿井水源组成定量计算模型

Um modelo de cálculo de composição quantitativa de fonte de água de mina baseado em “íons emblemáticos”

  • Technical Note
  • Published:
Hydrogeology Journal Aims and scope Submit manuscript

Abstract

Preventing water inrush disasters in mines is crucial for ensuring safe coal production; therefore, it is necessary to adopt a simple and effective method to determine the source and composition of mine water for effective water control in coal mines. The major ions content of groundwater in mining areas is easy to monitor, but the selection of appropriate parameters and calculation methods is key to being able to accurately discriminate between the water sources. In this study, the major ions content of 18 water samples was analyzed by cluster analysis, and a set of mean reference values was constructed for these ions in the mine-impacted groundwater of the saturated aquifers. The coefficient of variation was used to screen the parameters suitable for calculating the composition of mine water, and an innovative concept of characteristic ions, hereby defined as “emblematic” ions, was put forward. These were identified in this study as K+ + Na+, Ca2+, Mg2+ and HCO3. The quantitative calculation model of the mine water source is established by using the fuzzy comprehensive evaluation method with the emblematic ions as the evaluation factor. Finally, the accuracy of the mathematical model is verified by comparing the calculated data with the actual observation data.

Résumé

Il est essentiel de prévenir les catastrophes liées à l’infiltration d’eau dans les mines pour garantir la sécurité de la production de charbon. Il est donc nécessaire d’adopter une méthode simple et efficace pour déterminer la source et la composition de l’eau de mine afin d’assurer un contrôle efficace de l’eau dans les mines de charbon. La teneur en ions majeurs des eaux souterraines dans les zones minières est facile à contrôler, mais la sélection de paramètres et de méthodes de calcul appropriés est essentielle pour pouvoir distinguer avec précision les différentes origines d’eau. Dans cette étude, la teneur en ions majeurs de 18 échantillons d’eau a été analysée par regroupement, et un ensemble de valeurs de référence moyennes a été construit pour ces ions dans les eaux souterraines impactées par les mines dans les aquifères saturés. Le coefficient de variation a été utilisé pour sélectionner les paramètres adaptés au calcul de la composition de l’eau de mine, et un concept innovant d’ions caractéristiques, définis ici comme des ions “emblématiques”, a été proposé. Ces derniers sont les suivants K+ + Na+,Ca2+, Mg2+ et HCO3 pour cette étude. Le modèle de calcul quantitatif de la source d’eau de mine est établi en utilisant la méthode d’évaluation globale floue avec les ions emblématiques comme facteur d’évaluation. Enfin, la précision du modèle mathématique est vérifiée en comparant les données calculées avec les données d’observation réelles.

Resumen

La prevención de los desastres provocados por la entrada de agua en las minas es fundamental para garantizar la seguridad de la producción de carbón. Por lo tanto, es necesario adoptar un método sencillo y eficaz para determinar el origen y la composición del agua de mina para un control eficaz del agua en las minas de carbón. El contenido en iones principales de las aguas subterráneas de las zonas mineras es fácil de controlar, pero la selección de los parámetros y métodos de cálculo adecuados es clave para poder discriminar con precisión las fuentes de agua. En este estudio, el contenido de iones principales de 18 muestras de agua se analizó mediante análisis de clusters, y se construyó un conjunto de valores medios de referencia para estos iones en las aguas subterráneas impactadas por minas de los acuíferos saturados. Se utilizó el coeficiente de variación para seleccionar los parámetros adecuados para calcular la composición del agua de mina, y se propuso un concepto innovador de iones característicos, definidos aquí como iones “emblemáticos”. En este estudio se identificaron como K+ + Na+, Ca2+, Mg2+ y HCO3. El modelo de cálculo cuantitativo de la fuente de agua de mina se establece utilizando el método de evaluación integral difusa con los iones emblemáticos como factor de evaluación. Por último, se verifica la precisión del modelo matemático comparando los datos calculados con los datos reales de observación.

摘要

防止矿井突水灾害对于确保煤炭安全生产至关重要。因此, 采用一种简单有效的方法来确定矿井水的来源和组成, 对于煤矿有效的水控制是必要的。矿区地下水的主要离子含量易于监测, 但选择合适的参数和计算方法是准确区分不同水源的关键。本研究通过聚类分析对18个水样的主要离子含量进行了分析, 并为这些离子在受矿山影响的饱和含水层地下水中构建了一组平均的参考值。利用变异系数筛选适合计算矿井水组成的参数, 并提出了一种创新的特征离子概念, 将其定义为“标志性”离子。本研究中确定的这些离子为K+ + Na+、Ca2+、Mg2+和HCO3。通过以标志性离子为评价因素使用模糊综合评价方法建立了矿井水源的定量计算模型。最后, 通过将计算数据与实际观测数据进行比较, 验证了数学模型的准确性。

Resumo

A prevenção de desastres com inundação de água nas minas é crucial para garantir a produção segura de carvão. Portanto, é necessário adotar um método simples e eficaz para determinar a fonte e a composição da água da mina para um controle eficaz da água nas minas de carvão. O principal conteúdo de íons das águas subterrâneas em áreas de mineração é fácil de monitorar, mas a seleção de parâmetros e métodos de cálculo apropriados é fundamental para poder discriminar com precisão entre as fontes de água. Neste estudo, o conteúdo dos principais íons de 18 amostras de água foi analisado por análise de agrupamento, e um conjunto de valores médios de referência foi construído para esses íons nas águas subterrâneas impactadas pelas minas dos aquíferos saturados. O coeficiente de variação foi utilizado para selecionar os parâmetros adequados para o cálculo da composição da água de mina, e foi apresentado um conceito inovador de íons característicos, aqui definidos como íons “emblemáticos”. Estes foram identificados como K+ + Na+, Ca2+, Mg2+ e HCO3 neste estudo. O modelo de cálculo quantitativo da fonte de água da mina é estabelecido usando o método de avaliação abrangente fuzzy com os íons emblemáticos como fator de avaliação. Finalmente, a precisão do modelo matemático é verificada comparando os dados calculados com os dados de observação reais.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Bi Y, Wu J, Zhai X, Wang G, Shen S, Qing X (2021) Discriminant analysis of mine water inrush sources with multi-aquifer based on multivariate statistical analysis. Environ Earth Sci 80. https://doi.org/10.1007/s12665-021-09450-8

  • China State Bureau of Coal Industry (2000) Determination of potassium ions and sodium ions in coal mine water. MT/T252-2000, China State Bureau of Coal Industry, Beijing

  • China State Bureau of Coal Industry (2008a) Determination of chlorine ion in coal mine water. MT/T201-2008, China State Bureau of Coal Industry, Beijing

  • China State Bureau of Coal Industry (2008b) Determination of calcium ion and magnesium ion in coal mine water. MT/T202-2008, China State Bureau of Coal Industry, Beijing

  • China State Bureau of Coal Industry (2011) Determination of sulphate radical hydronium in coal mine water. MT/T205-2011, China State Bureau of Coal Industry, Beijing

  • China State Bureau of Coal Industry (2021) Methods for analysis of groundwater quality, part 49: determination of carbonate, bicarbonate ions, hydroxy-titration. DZ/T 0064.49-2021, China State Bureau of Coal Industry, Beijing

  • Du M, Zhang M, Wang S, Meng H, Che C, Guo R (2019) Stable isotopes reveals tap water source under different water supply modes in the eastern margin of the Qinghai-Tibet Plateau. Water 11:2578

    Article  Google Scholar 

  • Gao X, Huang H (2018) Discrimination of water bursting source based on change of water quantity and water level and hydrochemical characteristics. Coal Tech 37:198–200

    CAS  Google Scholar 

  • Grbčić L, Kranjčević L, Družeta S (2021) Machine learning and simulation-optimization coupling for water distribution network contamination source detection. Sens-Basel 21:1157. https://doi.org/10.3390/s21041157

    Article  Google Scholar 

  • Guan Z, Jia Z, Zhao Z, You Q (2019) Identification of inrush water recharge sources using hydrochemistry and stable isotopes: a case study of Mindong no. 1 coal mine in north-east Inner Mongolia, China. J Earth Syst Sci 128. https://doi.org/10.1007/s12040-019-1232-4

  • Guo X, Feng Q, Si J, Wei Y, Bao T, Xi H, Li Z (2019) Identifying the origin of groundwater for water resources sustainable management in an arid oasis, China. Hydrol Sci J 64:1253–1264. https://doi.org/10.1080/02626667.2019.1619080

    Article  Google Scholar 

  • Hu W, Zhao C (2021) Evolution of water hazard control technology in China’s coal mines. Mine Water Environ 40:334–344. https://doi.org/10.1007/s10230-020-00744-0

    Article  Google Scholar 

  • Huang M, Mao A, Lu S, Wang Y (2022) Principal component analysis chaotic sparrow search RF model for identification of mine water inrush source. J Safety Environ 1–12. https://doi.org/10.13637/j.issn.1009-6094.2022.0623

  • Li B, Wu Q, Liu Z (2020) Identification of mine water inrush source based on PCA-FDA: Xiandewang Coal Mine case. Geofluids 2020:1–8. https://doi.org/10.1155/2020/2584094

    Article  CAS  Google Scholar 

  • Ma L, Qian J, Zhao W (2014) An approach for quickly identifying water-inrush source of mine based on GIS and groundwater chemistry and temperature. Coal Geol Explor 42:49–53

    CAS  Google Scholar 

  • Nikiema J, Gläßer W, Krieg R, Schirmer M (2013) Trace elements and their correlations in hand-dug wells in a laterite environment in a semi-arid region: case study of Tikaré, northern Burkina Faso. Environ Earth Sci 69:2393–2414. https://doi.org/10.1007/s12665-012-2068-2

    Article  CAS  Google Scholar 

  • Wang X, Yang G, Wang Q, Wang J, Zhang B, Wang J (2019) Research on water-filled source identification technology of coal seam floor based on multiple index factors. Geofluids 2019:1–9. https://doi.org/10.1155/2019/5485731

    Article  CAS  Google Scholar 

  • Wu J, Xu S, Zhou R, Qin Y (2016) Scenario analysis of mine water inrush hazard using Bayesian networks. Safety Sci 89:231–239. https://doi.org/10.1016/j.ssci.2016.06.013

    Article  Google Scholar 

  • Wu Q, Mu W, Xing Y, Qian C, Shen J, Wang Y, Zhao D (2019) Source discrimination of mine water inrush using multiple methods: a case study from the Beiyangzhuang Mine, northern China. B Eng Geol Environ 78:469–482. https://doi.org/10.1007/s10064-017-1194-1

    Article  CAS  Google Scholar 

  • Xu Z, Sun Y, Gao S, Zhao X, Duan R, Yao M, Liu Q (2018) Groundwater source discrimination and proportion determination of mine inflow using ion analyses: a case study from the Longmen Coal Mine, Henan Province, China. Mine Water Environ 37:385–392. https://doi.org/10.1007/s10230-018-0512-6

    Article  CAS  Google Scholar 

  • Yan B, Ren F, Cai M, Qiao C (2020) Bayesian model based on Markov chain Monte Carlo for identifying mine water sources in submarine gold mining. J Clean Prod 253:120008. https://doi.org/10.1016/j.jclepro.2020.120008

    Article  CAS  Google Scholar 

  • Yang Z, Lv H, Xu Z, Wang X (2022) Source discrimination of mine water based on the random forest method. Sci Rep-Uk 12. https://doi.org/10.1038/s41598-022-24037-4

  • Yin H, Zhou W, LaMoreaux JW (2018) Water inrush conceptual site models for coal mines of China. Environ Earth Sci 77. https://doi.org/10.1007/s12665-018-7920-6

  • Zhang H, Xing H, Yao D, Liu L, Xue D, Guo F (2019) The multiple logistic regression recognition model for mine water inrush source based on cluster analysis. Environ Earth Sci 78. https://doi.org/10.1007/s12665-019-8624-2

  • Zhao X, Xu Z, Sun Y (2022) Identification of mine water source based on AHP-entropy and set pair analysis. Geofluids 2022:1–10. https://doi.org/10.1155/2022/3862746

    Article  CAS  Google Scholar 

  • Zhong C, Yang Q, Ma H, Bian J, Zhang S, Lu X (2019) Application of environmental isotopes to identify recharge source, age, and renewability of phreatic water in Yinchuan Basin. Hydrol Process. https://doi.org/10.1002/hyp.13468

    Article  Google Scholar 

Download references

Funding

This research was supported by the National Natural Science Foundation of China (42172272), the National Key Research and Development Program of China (2019YFC1805400), the Graduate Innovation Program of China University of Mining and Technology (2022WLKXJ039) and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX22_2606).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhimin Xu.

Ethics declarations

Conflicts of interest

There is no conflict of interest regarding the publication of this paper.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yuan, H., Xu, Z., Sun, Y. et al. A quantitative composition calculation model of mine water source based on “emblematic ions”. Hydrogeol J 32, 913–923 (2024). https://doi.org/10.1007/s10040-024-02774-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10040-024-02774-2

Keywords

Navigation