Abstract
Investigations were undertaken in the riparian zone near Shangba village, an AMD area, in southern China to determine the effects that river–groundwater interactions and groundwater residence time have had on environmental quality and geochemical evolution of groundwater. Based on the Darcy’s law and ionic mass balances as well as the method of isotopic tracer, the results showed that there were active interactions between AMD-contaminated river water and groundwater in the riparian zone in the study area. River water was found to be the main source of groundwater recharge in the northwestern part of the study area, whereas groundwater was found to be discharging into the river in the southeastern part of the study area throughout the year. End-member mixing analysis quantified that the contributions of river water to groundwater decreased gradually from 35.9% to negligible levels along the flow path. The calculated mixing concentrations of major ions indicated that water–rock reactions were the most important influence on groundwater quality. The wide range of Ca2+ + Mg2+ and HCO3− ratios and the change of groundwater type from Ca2+–SO42− type to a chemical composition dominated by Ca2+–HCO3− type indicated a change of the major water–rock reaction process from the influence of H2SO4 (AMD) to that of CO2 (soil respiration) along a groundwater flow path. Furthermore, the kinetics interpretation of SO42− and HCO3− concentrations suggested that the overlapping time of their kinetics triggered the hydrochemical evolution and the change of major weathering agent. This process might take approximately 8 years and this kinetic time will be continued when a steady source of contamination enter the aquifer.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Explore related subjects
Discover the latest articles and news from researchers in related subjects, suggested using machine learning.References
Amalfitano S, Del Bon A, Zoppini A, Ghergo S, Fazi S, Parrone D, Casella P, Stano F, Preziosi E (2014) Groundwater geochemistry and microbial community structure in the aquifer transition from volcanic to alluvial areas. Water Res 65:384–394. https://doi.org/10.1016/j.watres.2014.08.004
Brakensiek DL, Rawls WJ, Stephenson GR (1986) A note on determining soil properties for soils containing rock fragments. J Range Manag Arch 50(3):408–409
Brodie R, Sundaram B, Tottenham R, Hostetler S, Ransley T (2007) An overview of tools for assessing groundwater-surface water connectivity. Bureau of Rural Sciences, Canberra
Caraballo MA, Macías F, Nieto JM, Ayora C (2016) Long term fluctuations of groundwater mine pollution in a sulfide mining district with dry Mediterranean climate: implications for water resources management and remediation. Sci Total Environ 539:427–435. https://doi.org/10.1016/j.scitotenv.2015.08.156
Chen A, Lin C, Lu W, Wu Y, Ma Y, Li J, Zhu L (2007) Well water contaminated by acidic mine water from the Dabaoshan Mine, South China: chemistry and toxicity. Chemosphere 70(2):248–255. https://doi.org/10.1016/j.chemosphere.2007.06.041
Chowdary VM, Rao NH, Sarma PBS (2005) Decision support framework for assessment of non-point-source pollution of groundwater in large irrigation projects. Agric Water Manag 75(3):194–225. https://doi.org/10.1016/j.agwat.2004.12.013
Gimeno MJALGJ (ed) (2008) Water–rock interaction modelling and uncertainties of mixing modelling. Swedish Nuclear Fuel & Waste Management Co, Stockholm
Goienaga N, Carrero JA, Zuazagoitia D, Baceta JI, Murelaga X, Fernández LA, Madariaga JM (2015) Recrystallization and stability of Zn and Pb minerals on their migration to groundwater in soils affected by acid mine drainage under CO2 rich atmospheric waters. Chemosphere 119:727–733. https://doi.org/10.1016/j.chemosphere.2014.07.081
Gómez JB, Gimeno MJ, Auqué LF, Acero P (2014) Characterisation and modelling of mixing processes in groundwaters of a potential geological repository for nuclear wastes in crystalline rocks of Sweden. Sci Total Environ 468–469:791–803. https://doi.org/10.1016/j.scitotenv.2013.09.007
González E, Felipe-Lucia MR, Bourgeois B, Boz B, Nilsson C, Palmer G, Sher AA (2017) Integrative conservation of riparian zones. Biol Conserv 211:20–29. https://doi.org/10.1016/j.biocon.2016.10.035
Gribovszki Z, Kalicz P, Szilágyi J, Kucsara M (2008) Riparian zone evapotranspiration estimation from diurnal groundwater level fluctuations. J Hydrol 349(1–2):6–17. https://doi.org/10.1016/j.jhydrol.2007.10.049
Han DM, Song XF, Currell MJ, Yang JL, Xiao GQ (2014) Chemical and isotopic constraints on evolution of groundwater salinization in the coastal plain aquifer of Laizhou Bay, China. J Hydrol 508:12–27. https://doi.org/10.1016/j.jhydrol.2013.10.040
Han D, Cao G, McCallum J, Song X (2015) Residence times of groundwater and nitrate transport in coastal aquifer systems: Daweijia area, northeastern China. Sci Total Environ 538:539–554. https://doi.org/10.1016/j.scitotenv.2015.08.036
Huang G, Sun J, Zhang Y, Chen Z, Liu F (2013) Impact of anthropogenic and natural processes on the evolution of groundwater chemistry in a rapidly urbanized coastal area, South China. Sci Total Environ 463–464:209–221. https://doi.org/10.1016/j.scitotenv.2013.05.078
Iepure S, Meffe R, Carreño F, Rasines RL, de Bustamante I (2014) Geochemical, geological and hydrological influence on ostracod assemblages distribution in the hyporheic zone of two Mediterranean rivers in central Spain. Int Rev Hydrobiol 99(6):435–449. https://doi.org/10.1002/iroh.201301727
Jiang Y, Wu Y, Groves C, Yuan D, Kambesis P (2009) Natural and anthropogenic factors affecting the groundwater quality in the Nandong karst underground river system in Yunan, China. J Contam Hydrol 109(1–4):49–61. https://doi.org/10.1016/j.jconhyd.2009.08.001
Katz BG (2004) Sources of nitrate contamination and age of water in large karstic springs of Florida. Environ Geol 46(6–7):689–706. https://doi.org/10.1007/s00254-004-1061-9
Lin CY, Abdullah MH, Praveena SM, Yahaya AHB, Musta B (2012) Delineation of temporal variability and governing factors influencing the spatial variability of shallow groundwater chemistry in a tropical sedimentary island. J Hydrol 432–433:26–42. https://doi.org/10.1016/j.jhydrol.2012.02.015
Liu F, Song X, Yang L, Han D, Zhang Y, Ma Y, Bu H (2015) The role of anthropogenic and natural factors in shaping the geochemical evolution of groundwater in the Subei Lake basin, Ordos energy base, Northwestern China. Sci Total Environ 538:327–340. https://doi.org/10.1016/j.scitotenv.2015.08.057
Mander Ü, Tournebize J (2015) Riparian buffer zones: functions and dimensioning. In: 2010 4th international conference on bioinformatics and biomedical engineering (iCBBE), pp 20151–20154
Meyer LD, Johnson CB, Foster GR (1972) Stone and woodchip mulches forerosion control on construction sites. Soil Water Conserv 27:246–269
Molson J, Aubertin M, Bussière B (2012) Reactive transport modelling of acid mine drainage within discretely fractured porous media: plume evolution from a surface source zone. Environ Model Softw 38:259–270. https://doi.org/10.1016/j.envsoft.2012.06.010
Qiao X, Li G, Li M, Zhou J, Du J, Du C, Sun Z (2011) Influence of coal mining on regional karst groundwater system: a case study in West Mountain area of Taiyuan City, northern China. Environ Earth Sci 64(6):1525–1535. https://doi.org/10.1007/s12665-010-0586-3
Rahman MM, Worch E (2005) Nonequilibrium sorption of phenols onto geosorbents: the impact of pH on intraparticle mass transfer. Chemosphere 61(10):1419–1426. https://doi.org/10.1016/j.chemosphere.2005.04.085
Schilling KE, Jacobson PJ, Wolter CF (2018) Using riparian zone scaling to optimize buffer placement and effectiveness. Landsc Ecol 33(1):141–156. https://doi.org/10.1007/s10980-017-0589-5
Szilágyi J, Gribovszki Z, Kalicz P, Kucsara M (2008) On diurnal riparian zone groundwater-level and streamflow fluctuations. J Hydrol 349(1–2):1–5. https://doi.org/10.1016/j.jhydrol.2007.09.014
Vengosh A, De Lange GJ, Starinsky A (1998) Boron isotope and geochemical evidence for the origin of Urania and Bannock brines at the eastern Mediterranean: effect of water-rock interactions. Geochim Cosmochim Acta 62:3221–3228. https://doi.org/10.1016/S0016-7037(98)00236-1
Vidal-Abarca Gutiérrez MR, Suárez Alonso ML (2013) Which are, what is their status and what can we expect from ecosystem services provided by Spanish rivers and riparian areas? Biodivers Conserv 22(11):2469–2503. https://doi.org/10.1007/s10531-013-0532-2
Vidon PGF, Hill AR (2004) Landscape controls on the hydrology of stream riparian zones. J Hydrol 292(1–4):210–228. https://doi.org/10.1016/j.jhydrol.2004.01.005
Woessner WW (2000) Stream and fluvial plain ground water interactions:rescaling hydrogeologic thought. Groundwater 38(3):423–429
Worch E (2004) Modelling the solute transport under nonequilibrium conditions on the basis of mass transfer equations. J Contam Hydrol 68(1–2):97–120. https://doi.org/10.1016/S0169-7722(03)00091-3
Yesilnacar MI, Kadiragagil Z (2013) Effects of acid mine drainage on groundwater quality: a case study from an open-pit copper mine in eastern Turkey. Bull Eng Geol Environ 72(3–4):485–493. https://doi.org/10.1007/s10064-013-0512-5
Zhao H, Xia B, Qin J, Zhang J (2012) Hydrogeochemical and mineralogical characteristics related to heavy metal attenuation in a stream polluted by acid mine drainage: a case study in Dabaoshan Mine, China. J Environ Sci China 24(6):979–989. https://doi.org/10.1016/S1001-0742(11)60868-1
Acknowledgements
Special thanks go to Lei Gao, Rui Li, Zewen Pan, Jiafu Zhao, Pengcheng Zhang and Chenglei Xie for technical support and guidance. We thank Dan Yao for article language help. Shangba villagers are also acknowledged for providing assistance during the sampling campaigns. This work was supported by the National Natural Science Foundation NSFC (no. 41471020), Science Research Programs of Guangzhou (no. 201510010300), and Youth Science Fund Project (no. 41501512).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendices
Appendix 1
To better estimate the permeability coefficient values, we use mathematical model to calibrate the parameter k. First, it is necessary to estimate the porosity of the aquifer. Several water level gauges had been set up in the study area to continuously observe the groundwater level fluctuations, which can be used to estimate the porosity based on the groundwater level fluctuations caused by several rainfall events. In addition, we also used a method of Meyer et al. (1972) and Brakensiek et al. (1986) to calculate the porosity of sediments with a large amount of gravel. The result showed that the porosity was approximate 0.31 which was consistent with the calculated result from the groundwater level fluctuations. Therefore, the calibration of the parameter k was carried out by constructing a mathematical model using software Visual MODFLOW. Compared the measured water head with calculated water head, the result from model inversion showed that k was a variable parameter, and varied from 60 m/day to 15 m/day to 60 m/day along the groundwater flow direction (Fig. 13). This indicates that the aquifer in the study area is not a homogeneous aquifer and the variable permeability coefficients divide the aquifer into five zones, in which the characteristics of groundwater flow are different. The estimate k values are in relative agreement with the characteristics of shallow alluvial sandy aquifers, and are relatively reasonable and feasible to estimate the groundwater flow rate in this paper.
The estimated results of k based on Visual MODFLOW (left) and the comparison between the simulated potentiometric map (left) and the measured potentiometric map (right) in study area (The result from the dry season is only listed here)
Based on the well-delineated groundwater potentiometric map, the groundwater flow rate can be quantitatively calculated by the Darcy’s equation (VD = k(H0 − HL)/L) when it flows in a distance L with hydraulic potential decrease of (H0 − HL). As a result, the groundwater residence time of each sampling sites was calculated and shown in Fig. 14.
The groundwater residence time at each sampling sites in the study area. Numbers beside the sampling sites represent the groundwater residence time with unit of year
Appendix 2
The average contribution and the standard deviation of three end members: precipitation (P), AMD, and irrigation (I) at each sampling sites are computed using Monte Carlo simulation for EMMA. The results are shown in Table 2.
Rights and permissions
About this article
Cite this article
Wen, J., Tang, C., Cao, Y. et al. Hydrochemical evolution of groundwater in a riparian zone affected by acid mine drainage (AMD), South China: the role of river–groundwater interactions and groundwater residence time. Environ Earth Sci 77, 794 (2018). https://doi.org/10.1007/s12665-018-7977-2
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12665-018-7977-2