Environmental Earth Sciences

, Volume 63, Issue 3, pp 595–608 | Cite as

Distinguishing potential sources of arsenic released to groundwater around a fault zone containing a mine site

Original Article

Abstract

Arsenic (As) contamination in groundwater in mineralized areas typically results from the oxidation of As-rich sulfide minerals in aquifers, from hydrothermal alteration of geothermal systems, or as a result of anthropogenic influences such as mining activity. The primary goal of this study was to determine the spatial and temporal variance in As concentrations in shallow groundwater in a mineralized area and to identify the main As source controlling the concentration patterns. To this end, a combination of a geostatistical technique for space–time modeling of As concentrations and a numerical simulation, which models the transport of As in groundwater, is implemented. A study site in North Sulawesi, Sulawesi Island, Indonesia was selected as it was suitable for investigating the importance of fault lines and metal mining on As contamination. Initially, stable isotope analysis was used to ascertain the groundwater source and the mixing mechanism of the shallow and deep groundwater. Geostatistical modeling revealed consistent general patterns of As concentrations during the past 10 years, with high concentrations found along a NW–SE axis. By matching the geostatistical results with the distributions of As concentrations obtained through transport modeling, the deep-seated hydrothermal system along the fault zone was found to be the major As source. Wastewater from the mine was also observed to be a local As source. Another important influence on the As concentration pattern was a river, which acted as a boundary to separate the groundwater systems into two regions.

Keywords

Arsenic contamination Kriging Stable isotopes Advection dispersion Fault zone Hydrothermal system 

Supplementary material

12665_2010_727_MOESM1_ESM.tif (296 kb)
Fig. 1 Scattergram showing the correlation of solid As concentrations in sediments with soluble As concentrations in groundwater at the 17 sample points in Fig 2a. (TIFF 295 kb)
12665_2010_727_MOESM2_ESM.tif (1 mb)
Fig. 2 (a) Histogram of log-transformed As concentration data (log ppb). (b) Experimental semivariogram of the log-transformed As data for the temporal changes. (c) Omnidirectional experimental semivariograms of the annual averages of the log-transformed As concentration data in 1999 and 2003. (d) Scattergram comparing the values calculated by ordinary kriging and the observed values to cross-validate the accuracy of the estimations. (TIFF 1064 kb)
12665_2010_727_MOESM3_ESM.tif (2.7 mb)
Fig. 3 Representative spatial distributions of annual averages of sulfate, nitrate, and manganese (log ppb) by ordinary kriging. (TIFF 2733 kb)
12665_2010_727_MOESM4_ESM.tif (2.9 mb)
Fig. 4 (a) Comparison of simulated groundwater levels with measured levels at the steady state condition in groundwater flow. Average levels over 10 years of observation at the wells were used for the comparison. (b) Annual rainfall intensity in the period of groundwater flow simulation. (c) Comparison of simulated levels with measured levels at three wells situated upstream, midstream, and downstream under a transient condition that incorporates precipitation into the simulation. (TIFF 2932 kb)

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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Graduate School of Science and TechnologyKumamoto UniversityKumamotoJapan
  2. 2.Earth Resources Exploration Research Group, Faculty of Mining and Petroleum EngineeringInstitut Teknologi Bandung (ITB)BandungIndonesia
  3. 3.New Frontier Sciences, Graduate School of Science and TechnologyKumamoto UniversityKumamotoJapan

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