Prediction analysis model for groundwater potential based on set pair analysis of a confined aquifer overlying a mining area

Abstract

One important prerequisite for mine water inrush prevention and water inflow control in a coal mine is groundwater potential mapping. In this study, a synthetical method was developed to evaluate the groundwater potential of a confined aquifer overlying a mining area using the improved set pair analysis (ISPA) theory. Considering the influence of the hydrogeological and geological conditions, the characteristics of rock stratum and geological tectonics were used as the two major aspects to evaluate groundwater potential. The degree of connection was determined by the relationship between the total number of element characteristics and the number of identical, contradictory, and discrepant terms. The weight of evaluation indices was calculated based on information entropy, and the grade of groundwater potential was determined by the improved evaluation criterion of set pair analysis. To validate the practicality of the method, a case study at Hongliu coal mine was carried out. An entropy-set pair analysis-cosine model was constructed and five evaluation indices were selected: sandstone thickness, flushing fluid consumption, core recovery, fault fractal dimension, and fold fractal dimension. The groundwater potential of the study area was classified into four levels. The quantitative results were validated with data from field observations and compared with the results of geographic information systems (GIS), which were found to be in very good agreement.

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References

  1. Agarwal R, Garg PK (2016) Remote sensing and GIS based groundwater potential & recharge zones mapping using multi-criteria decision making technique. Water Resour Manag 30:243–260. https://doi.org/10.1007/s11269-015-1159-8

    Article  Google Scholar 

  2. Chenini I, Mammou AB (2010) Groundwater recharge study in arid region: an approach using GIS techniques and numerical modeling. Comput Geosci 36:801–817. https://doi.org/10.1016/j.cageo.2009.06.014

    Article  Google Scholar 

  3. Chowdhury A, Jha MK, Chowdary VM, Mal BC (2009) Integrated remote sensing and GIS-based approach for assessing groundwater potential in West Medinipur district, West Bengal, India. Int J Remote Sens 30:231–250. https://doi.org/10.1080/01431160802270131

    Article  Google Scholar 

  4. Corsini A, Cervi F, Ronchetti F (2009) Weight of evidence and artificial neural networks for potential groundwater spring mapping: an application to the Mt. Modino area (Northern Apennines, Italy). Geomorphology 111:79–87. https://doi.org/10.1016/j.geomorph.2008.03.015

    Article  Google Scholar 

  5. Cui XL, Li WP (2015) Forecasting and assessment of water abundance of sandstone roof by multivariate information. Coal Geol Explor 43(1):43–47 (in Chinese)

    Google Scholar 

  6. Dar IA, Sankar K, Dar MA (2010) Remote sensing technology and geographic information system modeling: an integrated approach towards the mapping of groundwater potential zones in Hardrock terrain, Mamundiyar basin. J Hydrol 394:285–295. https://doi.org/10.1016/j.jhydrol.2010.08.022

    Article  Google Scholar 

  7. Elewa HH, Qaddah AA (2011) Groundwater potentiality mapping in the Sinai peninsula, Egypt, using remote sensing and GIS-watershed-based modeling. Hydrogeol J 19:613–628. https://doi.org/10.1007/s10040-011-0703-8

    Article  Google Scholar 

  8. Feng ZG, Sun XQ (2014) Box-counting dimensions of fractal interpolation surfaces derived from fractal interpolation functions. J Math Anal Appl 412:416–425. https://doi.org/10.1016/j.jmaa.2013.10.032

    Article  Google Scholar 

  9. Feng LH, Sang GS, Hong WH (2014) Statistical prediction of changes in water resources trends based on set pair analysis. Water Resour Manag 28:1703–1711. https://doi.org/10.1007/s11269-014-0581-7

    Article  Google Scholar 

  10. Fernandez-Martinez M, Sanchez-Granero MA (2014) Fractal dimension for fractal structures. Topol Appl 163:93–111. https://doi.org/10.1016/j.topol.2013.10.010

    Article  Google Scholar 

  11. Ganapuram S, Vijaya Kumar GT, Murali Krishna IV, Kahya E, Demirel MC (2009) Mapping of groundwater potential zones in the Musi basin using remote sensing data and GIS. Adv Eng Softw 40:506–518. https://doi.org/10.1016/j.advengsoft.2008.10.001

    Article  Google Scholar 

  12. Han C, Pan XH, Li GL, Tu JN (2012) The fuzzy analytic hierarchy process of water abundance of an aquifer based on GIS and multi-source information fusion techniques. Hydrogeol Eng Geol 39(4):19–25 (in Chinese)

    Google Scholar 

  13. Hou ZY, Lu WX, Xue HB, Lin J (2017) A comparative research of different ensemble surrogate models based on set pair analysis for the DNAPL-contaminated aquifer remediation strategy optimization. J Contam Hydrol 203:28–37. https://doi.org/10.1016/j.jconhyd.2017.06.003

    Article  Google Scholar 

  14. Huang Z, Jiang ZQ, Zhu SY, Qian ZW, Cao DT (2014) Characterizing the hydraulic conductivity of rock formations between deep coal and aquifers using injection tests. Int J Rock Mech Min Sci 71:12–18. https://doi.org/10.1016/j.ijrmms.2014.06.017

    Article  Google Scholar 

  15. Jha MK, Chowdhury A, Chowdary VM, Peiffer S (2007) Groundwater management and development by integrated remote sensing and geographic information systems: prospects and constraints. Water Resour Manag 21:427–467. https://doi.org/10.1007/s11269-006-9024-4

    Article  Google Scholar 

  16. Kaliraj NS, Chandrasekar N, Magesh NS (2014) Identification of potential groundwater recharge zones in Vaigai upper basin, Tamil Nadu, using GIS-based analytical hierarchical process (AHP) technique. Arab J Geosci 7:1385–1401. https://doi.org/10.1007/s12517-013-0849-x

    Article  Google Scholar 

  17. Ku CY, Hsu SM, Chiou LB, Lin GF (2009) An empirical model for estimating hydraulic conductivity of highly disturbed clastic sedimentary rocks in Taiwan. Eng Geol 109:213–223. https://doi.org/10.1016/j.enggeo.2009.08.008

    Article  Google Scholar 

  18. Lee S, Kim YS, Oh HJ (2012) Application of a weights-of-evidence method and GIS to regional groundwater productivity potential mapping. J Environ Manag 96(1):91–105. https://doi.org/10.1016/j.jenvman.2011.09.016

    Article  Google Scholar 

  19. Li GY, Mou L, Zhou WF (2015) Paleokarst crust of ordovician limestone and its utilization in evaluating water inrushes in coalmines of North China. Carbonates Evaporites 30(4):365–371. https://doi.org/10.1007/s13146-015-0231-z

    Article  Google Scholar 

  20. Li CH, Sun L, Jia JX, Cai YP, Wang X (2016) Risk assessment of water pollution sources based on an integrated k-means clustering and set pair analysis method in the region of Shiyan, China. Sci Total Environ 557–558:307–316. https://doi.org/10.1016/j.scitotenv.2016.03.069

    Article  Google Scholar 

  21. Liu DM, Lian HQ, Han Y, Li F (2014) Study on water enrichment prediction of coal roof sandstone aquifer based on PNN. Coal Technol 33(9):336–338 (in Chinese)

    Google Scholar 

  22. Madrucci V, Taioli F, Araujo CCD (2008) Groundwater favourability map using GIS multicriteria data analysis on crystalline terrain, Sao Paulo state, Brazil. J Hydrol 357:153–173. https://doi.org/10.1016/j.jhydrol.2008.03.026

    Article  Google Scholar 

  23. Magesh NS, Chandrasekar N, Soundranayagam JP (2012) Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques. Geosci Front 3(2):189–196. https://doi.org/10.1016/j.gsf.2011.10.007

    Article  Google Scholar 

  24. Mahmoud SH, Alazba AA (2016) Integrated remote sensing and GIS-based approach for deciphering groundwater potential zones in the central region of Saudi Arabia. Environ Earth Sci 75:1–28. https://doi.org/10.1007/s12665-015-5156-2

    Article  Google Scholar 

  25. Manap MA, Nampak H, Pradhan B, Lee S, Sulaiman WNA, Ramli MF (2014) Application of probabilistic-based frequency ratio model in groundwater potential mapping using remote sensing data and GIS. Arab J Geosci 7:711–724. https://doi.org/10.1007/s12517-012-0795-z

    Article  Google Scholar 

  26. Moghaddam DD, Rezaei M, Pourghasemi HR, Pourtaghie ZS, Pradhan B (2015) Groundwater spring potential mapping using bivariate statistical model and GIS in the Taleghan watershed, Iran. Arab J Geosci 8(2):913–929. https://doi.org/10.1007/s12517-013-1161-5

    Article  Google Scholar 

  27. Naghibi SA, Dashtpagerdi MM (2017) Evaluation of four supervised learning methods for groundwater spring potential mapping in Khalkhal region (Iran) using GIS-based features. Hydrogeol J 25:169–189. https://doi.org/10.1007/s10040-016-1466-z

    Article  Google Scholar 

  28. Naghibi SA, Moghaddam DD, Kalantar B, Pradhan B, Kisi O (2017) A comparative assessment of GIS-based data mining models and a novel ensemble model in groundwater well potential mapping. J Hydrol 548:471–483. https://doi.org/10.1016/j.jhydrol.2017.03.020

    Article  Google Scholar 

  29. Nampak H, Pradhan B, Manap MA (2014) Application of GIS based data driven evidential belief function model to predict groundwater potential zonation. J Hydrol 513(6):283–300. https://doi.org/10.1016/j.jhydrol.2014.02.053

    Article  Google Scholar 

  30. Nobre RCM, Filho OCR, Mansur WJ, Nobre MMM, Cosenza CAN (2007) Groundwater vulnerability and risk mapping using GIS, modeling and a fuzzy logic tool. J Contam Hydrol 94:277–292. https://doi.org/10.1016/j.jconhyd.2007.07.008

    Article  Google Scholar 

  31. Oh HJ, Kim YS, Choi JK, Park E, Lee S (2011) GIS mapping of regional probabilistic groundwater potential in the area of Pohang City, Korea. J Hydrol 399:158–172. https://doi.org/10.1016/j.jhydrol.2010.12.027

    Article  Google Scholar 

  32. Prasad RK, Mondal NC, Banerjee P, Nandakumar MV, Singh VS (2008) Deciphering potential groundwater zone in hard rock through the application of GIS. Environ Geol 55:467–475. https://doi.org/10.1007/s00254-007-0992-3

    Article  Google Scholar 

  33. Qiu M, Shi LQ, Teng C, Han J (2016) Water-richness evaluation of ordovician limestone based on grey correlation analysis, FDAHP and geophysical exploration. Chin J Rock Mech Eng s1:3203–3213 (in Chinese)

    Google Scholar 

  34. Rahmati O, Samani AN, Mahdavi M, Pourghasemi HR, Zeinivand H (2015) Groundwater potential mapping at Kurdistan region of Iran using analytic hierarchy process and GIS. Arab J Geosci 8(9):7059–7071. https://doi.org/10.1007/s12517-014-1668-4

    Article  Google Scholar 

  35. Razandi Y, Pourghasemi HR, Neisani NS, Rahmati O (2015) Application of analytical hierarchy process, frequency ratio, and certainty factor models for groundwater potential mapping using GIS. Earth Sci Inf 8(4):867–883. https://doi.org/10.1007/s12145-015-0220-8

    Article  Google Scholar 

  36. Shao YH, Yao DX, Lu HF, Wang K (2014) Evaluation of water abundance of loose bed bottom aquifer. Saf Coal Mines 45(7):127–130 (in Chinese)

    Google Scholar 

  37. Shekhar S, Pandey AC (2015) Delineation of groundwater potential zone in hard rock terrain of India using remote sensing, geographical information system (GIS) and analytic hierarchy process (AHP) techniques. Geocarto Int 30(4):402–421. https://doi.org/10.1080/10106049.2014.894584

    Article  Google Scholar 

  38. Shi LQ, Niu C, Zhai PH, Wei JC, Zhu L, Gao WF (2013) Application of three-dimensional high density resistivity technique in detecting roof water. Prog Geophys 28(6):3276–3279 (in Chinese)

    Google Scholar 

  39. Su MR, Yang ZF, Chen B, Ulgiati S (2009) Urban ecosystem health assessment based on emergy and set pair analysis—a comparative study of typical Chinese cities. Ecol Model 220(18):2341–2348. https://doi.org/10.1016/j.ecolmodel.2009.06.010

    Article  Google Scholar 

  40. Sun LL, Wang ZH, Wang HJ, Wang YH, Sun YQ (2013) Detection research on water abundance of floor aquifers. Min Saf Environ Prot 40(1):61–64 (in Chinese)

    Google Scholar 

  41. Tan C, Song Y, Che H (2017) Application of set pair analysis method on occupational hazard of coal mining. Saf Sci 92:10–16. https://doi.org/10.1016/j.ssci.2016.09.005

    Article  Google Scholar 

  42. Turesson A (2006) Water content and porosity estimated from ground-penetrating radar and resistivity. J Appl Geophys 58(2):99–111. https://doi.org/10.1016/j.jappgeo.2005.04.004

    Article  Google Scholar 

  43. Tweed SO, Leblanc M, Webb JA, Lubczynski MW (2007) Remote sensing and GIS for mapping groundwater recharge and discharge areas in salinity prone catchments, southeastern Australia. Hydrogeol J 15(1):75–96. https://doi.org/10.1007/s10040-006-0129-x

    Article  Google Scholar 

  44. Wang WS, Jin JL, Ding J, Li YQ (2009) A new approach to water resources system assessment-set pair analysis method. Sci China Ser E-Tech Sci 52(10):3017–3023. https://doi.org/10.1007/s11431-009-0099-z

    Article  Google Scholar 

  45. Wang T, Chen JS, Wang T, Wang S (2015a) Entropy weight-set pair analysis based on tracer techniques for dam leakage investigation. Nat Hazards 76(2):747–767. https://doi.org/10.1007/s11069-014-1515-7

    Article  Google Scholar 

  46. Wang MW, Xu XY, Li J, Jin JL, Shen FQ (2015b) A novel model of set pair analysis coupled with extenics for evaluation of surrounding rock stability. Math Probl Eng 2015:1):1–1):9. https://doi.org/10.1155/2015/892549

    Article  Google Scholar 

  47. Wang YC, Jing HW, Yu LY, Su HJ, Luo N (2016a) Set pair analysis for risk assessment of water inrush in karst tunnels. Bull Eng Geol Environ 76:1–9. https://doi.org/10.1007/s10064-016-0918-y

    Article  Google Scholar 

  48. Wang XY, Wang TT, Wang Q, Liu XM, Li RZ, Liu BJ (2016b) Evaluation of floor water inrush based on fractal theory and an improved analytic hierarchy process. Mine Water Environ 36:1–9. https://doi.org/10.1007/s10230-016-0407-3

    Article  Google Scholar 

  49. Wei C, Dai XY, Ye SF, Guo ZY, Wu JP (2016) Prediction analysis model of integrated carrying capacity using set pair analysis. Ocean Coast Manag 120:39–48. https://doi.org/10.1016/j.ocecoaman.2015.11.011

    Article  Google Scholar 

  50. Wu Q, Fan ZL, Liu SQ, Zhang YW, Sun WJ (2011a) Water-richness evaluation method of water-filled aquifer based on the principle of information fusion with GIS: water-richness index method. J China Coal Soc 36(7):1124–1128 (in Chinese)

    Google Scholar 

  51. Wu XR, Wei JC, Yin HY, Zhang YQ (2011b) Study on water enrichment prediction of roof sandstone aquifer based on the fuzzy clustering method: a case study on Longgu coal mine. J Shandong Univ Sci Technol Nat Sci 30(2):14–18 (in Chinese)

    Google Scholar 

  52. Wu Q, Wang Y, Zhao DK, Shen JJ (2017) Water abundance assessment method and application of loose aquifer based on sedimentary characteristics. J China Univ Min Technol 46(3):460–466 (in Chinese)

    Google Scholar 

  53. Yan F, Xu KL, Li DS, Zhang XM (2016) Hazard assessment for biomass gasification station using general set pair analysis. BioResources 11(4):8307–8324. https://doi.org/10.15376/biores.11.4.8307-8324

    Article  Google Scholar 

  54. Yang FG, Liang Y, Singh VP, Wang WS, Zhou XQ, Liu XN, Cao SY, Huang E, Wu YH (2014) Debris flow hazard assessment using set pair analysis models: take Beichuan county as an example. J Mt Sci 11(4):1015–1022. https://doi.org/10.1007/s11629-013-2495-x

    Article  Google Scholar 

  55. Yang C, Liu SD, Liu L (2016) Water abundance of mine floor limestone by simulation experiment. Int J Min Sci Technol 26(3):495–500. https://doi.org/10.1016/j.ijmst.2016.02.019

    Article  Google Scholar 

  56. Yang C, Liu SD, Wu RX (2017a) Quantitative prediction of water volumes within a coal mine underlying limestone strata using geophysical methods. Mine Water Environ 36:51–58. https://doi.org/10.1007/s10230-016-0394-4

    Article  Google Scholar 

  57. Yang BB, Sui WH, Duan LH (2017b) Risk assessment of water inrush in an underground coal mine based on GIS and fuzzy set theory. Mine Water Environ 36:617–627. https://doi.org/10.1007/s10230-017-0457-1

    Article  Google Scholar 

  58. Yeh HF, Lin HI, Lee ST, Chang MH, Hsu KC, Lee CH (2014) GIS and SBF for estimating groundwater recharge of a mountainous basin in the Wu river watershed, Taiwan. J Earth Syst Sci 123(3):503–516. https://doi.org/10.1007/s12040-014-0420-5

    Article  Google Scholar 

  59. Yin HY, Wei JC, Lefticariu L, Guo JB, Xie DL, Li ZL, Zhao P (2016) Numerical simulation of water flow from the coal seam floor in a deep longwall mine in China. Mine Water Environ 35(2):1–10. https://doi.org/10.1007/s10230-016-0385-5

    Article  Google Scholar 

  60. Yin HY, Shi YL, Niu HG, Xie DL, Wei JC, Lefticariu L, Xu SX (2018) A GIS-based model of potential groundwater yield zonation for a sandstone aquifer in the Juye Coalfield, Shangdong, China. Hydrogeol J 557:434–447. https://doi.org/10.1016/j.jhydrol.2017.12.043

    Article  Google Scholar 

  61. Zhao KQ (1989) Theory and analysis of set pair e a new concept and system analysis method. In: Conference Thesis of System Theory and Regional Planning. pp 87–91

  62. Zhao KQ (1994) Set pair analysis and its preliminary application. Explor Nat 13(47):67–72 (in Chinese)

    Google Scholar 

  63. Zou Q, Zhou JZ, Zhou C, Song LX, Guo J (2013) Comprehensive flood risk assessment based on set pair analysis-variable fuzzy sets model and fuzzy AHP. Stoch Env Res Risk A 27(2):525–546. https://doi.org/10.1007/s00477-012-0598-5

    Article  Google Scholar 

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Funding

This research was financially supported by National Key R&D Program of China (Grant No. 2017YFC0804101) and National Natural Science Foundation of China (Grant Nos. 41402250 and 41372290) and Nature Science Foundation of Shandong Province (Grant No. ZR2015PD010) and Taishan Scholar Talent Team Support Plan for Advantaged & Unique Discipline Areas (Grant No. 0101006).

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Correspondence to Jiuchuan Wei or Daolei Xie.

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Shi, S., Wei, J., Xie, D. et al. Prediction analysis model for groundwater potential based on set pair analysis of a confined aquifer overlying a mining area. Arab J Geosci 12, 115 (2019). https://doi.org/10.1007/s12517-019-4267-6

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Keywords

  • Groundwater potential map
  • Set pair analysis (SPA)
  • Confined aquifer
  • Connection degree