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Human Impacts on Karst Groundwater Contamination Deduced by Coupled Nitrogen with Strontium Isotopes in the Nandong Underground River System in ...
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Environ. Sci. Technol. 2009, 43, 7676–7683

Human Impacts on Karst Groundwater Contamination Deduced by Coupled Nitrogen with Strontium Isotopes in the Nandong Underground River System in Yunan, China Y O N G J U N J I A N G , * ,†,‡,§ Y U E X I A W U , | A N D D A O X I A N Y U A N †,‡,⊥ School of Geographical Sciences, Southwest University, Chongqing 400715, China, Institute of Karst Environment and Rock Desertification Rehabilitation, Chongqing 400715, China, Hoffman Environmental Research Institute, Western Kentucky University, Bowling Green, Kentucky 42101, Centre of Hydrogeology (CHYN), University of Neuchaˆtel, 11 Rue Emile-Argand, CH-2000 Neuchaˆtel, Switzerland, and CAGS, Karst Dynamics Laboratory, Institute of Karst Geology, M L R Guilin 541004, China

Received June 22, 2009. Revised manuscript received September 5, 2009. Accepted September 7, 2009.

With the rapid increase in population and economy, groundwater quality has degraded in the Nandong Underground River System (NURS), a typical karst underground river developed in carbonate rocks (limestone and dolomite), which is located in an agriculture-dominated area in the southeast Yunnan Province, China. Determining sources of contamination in the groundwater is an important first step toward us improving its quality by emission control. It is with this aim that we reviewed here the benefit of using a coupled isotopic approach (δ15N and 87Sr/86Sr) to trace the origin of contamination in groundwater. Thirty-six representative groundwater samples, which were collected at different aquifers and land use types, showed significant disparities for major element concentrations and Sr and N isotopic composition in the NURS. Nitrate, along with Cl- and SO42- and some Na+ and K+, pollution of groundwater is a significant problem in the NURS. The joint use of nitrogen and strontium isotope systematics in each context deciphered the origin of contamination in groundwater in the NURS as agricultural fertilizers and sewage effluents. Therefore, an increase in knowledge of groundwater geochemistry by means of hydrochemical and isotopic data will be helpful for understanding water-rock interactions and the influence of human activities on the hydrogeochemical environment of karst groundwater and provide a scientific basis for protection and rational utilization of groundwater resources in karst regions. * Correspondingauthorphone:+862368254191;fax:+862368252425; e-mail: [email protected] or [email protected]. † Southwest University. ‡ Institute of Karst Environment and Rock Desertification Rehabilitation. § Western Kentucky University. | University of Neuchaˆtel. ⊥ Institute of Karst Geology. 7676

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Introduction Increasing environmental pollution, both deliberate and unintentional forms as consequence of human activities, has to a great extent spoiled sensitive karst ecosystems in China (1-3). There are a myriad of potential sources of groundwater pollution, including point sources, nonpoint sources, and linear sources. It is often difficult to define the specific contamination source(s) around a spring or underground river. For effective pollution control, however, it is necessary to identify pollution sources. The isotopic technique is a powerful tool used for tracing the source(s) of dissolved elements in aquifer systems (4). Many studies have demonstrated the use of δ34S (5, 6), δ15N (7-10), δ18O (11), δ13C (12), and δ37Cl (13, 14) as tools for tracing anthropogenic inputs in groundwater originating from industrial sources, wastewater, and fertilizers. Recently, the combined use of isotope ratios of δ15N-δ18O in NO3- (15-21), δ34S-δ18O (22, 23) in SO42-, and δ11B-δ15N (18, 24, 25) of groundwater has been proven to be successful as an isotopic multitrace approach for tracing contaminants in groundwater. However, limits on these methods used for contaminant source identification are isotopic fractionation, which leads to masking the effect of the original contaminants source on the isotope fingerprint during biological and physicochemical processes and, for the same element, different isotope signatures in the groundwater. Specifically, some of the studies (15, 26) based on the dual isotope (δ15N-δ18O) approach in agricultural areas reported no significant differences in δ18O values of NO3- and, therefore, could not distinguish between the various possible nitrate sources. The power of Sr isotopes lies in the fact that the 87Sr/ 86 Sr ratio of surface water and groundwater is determined primarily by the isotopic characteristics of the watershed area as natural processes do not produce fractionation. Thus, when the strontium isotopic composition of natural and anthropogenic sources is different, the isotopic signature of the dissolved strontium in groundwater will show a mixing of different endmembers (27-36). Therefore, the coupled use of strontium isotopes with other isotopes is a powerful tool to trace contamination in groundwater, but it has not received much attention (29, 37). This study presents newly determined nitrogen and strontium isotopes, which are lacking in the Nandong Underground River System (NURS), and major element concentrations. These data are used to discuss a general view of the source(s) of groundwater contamination in a karst underground river system of China.

Outline of Study Area The NURS is located in the southeast of the Yun-Gui Plateau in Yunnan Province, China. The underground drainage area of the system is about 1618 km2 (Figure 1). The climate condition is primarily subtropical monsoon with a mean annual precipitation of 830 mm and mean air temperature of 19.8 °C. In 2007, the total population in the area was about 0.4 million, about 60% of which or 0.24 million lived in rural areas. The gross domestic product (GDP) in 2006 was about 9.1 × 108 U.S. dollars, about 1/3 of which or 3.1 × 108 U.S. dollars was from agricultural production. Geology and Hydrogeology. The geologic layers of the study area are shown in Figure 2. It is mainly underlain by Mesozoic Triassic strata. Carbonate rocks cover about 950 km2 or 58.7% of the total area. Limestone and dolomite each account for approximately 50% of the carbonate rock area (Figure 2). The 10.1021/es901502t CCC: $40.75

 2009 American Chemical Society

Published on Web 09/18/2009

FIGURE 1. Location of the NURS.

FIGURE 2. Geological map and distribution of groundwater and surface water samples in the NURS. central basin is covered by the Quaternary Mal lateritic clay, which is underlain by the Triassic Gejiu formation. The length of the main underground river from the Mingjiu cave to Nandong is about 75 km, and two other underground river branches are about 40 km long. The average discharge of the Nandong Underground River was 9.4 m3/s.

Land Use Pattern. There were five land use categories, i.e., forested land, grass land, cultivated land (dry and paddy land), water bodies, and construction land (towns and other urbanized areas) in the NURS. Land use data was obtained by interpreting 2007 Thematic Mapper (TM) images. The percentages of land use for each type were 29.5 for cultivated VOL. 43, NO. 20, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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pH

7.1 7.1 7.9 7.9 7.9 7.4 7.0 7.2 7.1 8.5 7.0 7.6 7.0 8.0 7.5 7.2 7.6 7.8 7.5 8.5 7.8 7.8 7.0 7.3 7.3 7.4 7.0 8.2 7.1 7.1 7.1 7.1 7.1 7.0 7.1 7.2

7.8 8.5 8.7 7.5 7.8 9.2 8.0

5.8 5.7 5.6

sample point

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

37 38 39 40 41 42 43

44 45 46

150 168 163

674 849 727 788 1385 481 733

651 444 480 395 2087 685 1862 465 470 545 1963 642 762 721 1015 307 306 634 852 485 367 401 469 457 720 619 598 865 657 447 436 449 487 419 381 496

299 225 349

2345 1198 2295 2495 1846 1148 1447

3044 3493 2295 2645 4691 2994 6238 2495 3693 3942 4890 3194 3393 3892 3443 3244 3293 3244 2395 2345 2345 2295 2221 2695 3393 3094 3543 5389 2595 2146 2096 2146 1996 1946 4691 6138

7 5 5

232 485 536 402 674 690 713

1135 557 772 251 539 199 650 580 490 613 1019 488 441 490 512 563 585 444 441 474 513 495 246 581 511 474 633 1222 634 605 626 589 722 575 991 1227

19 20 19

637 728 1019 400 770 507 813

291 363 207 453 1836 1063 788 405 273 532 1019 371 449 732 493 161 166 143 303 383 90 244 200 147 533 575 492 706 1026 266 276 275 145 131 85 266

15 12 14

324 167 224 172 428 263 362

142 31 70 343 2214 389 316 136 12 308 861 137 136 1510 318 27 28 89 137 176 6 139 19 26 285 339 316 426 275 135 136 136 22 4 273 104

20 22 19

1073 1053 2077 854 1019 1087 1248

1283 369 175 904 2513 1823 2218 826 233 1220 2082 1186 1916 1427 825 146 87 535 505 665 87 469 126 75 870 1039 1361 1416 1560 471 471 478 131 96 797 237

groundwater 5898 6638 4899 3878 5998 6098 5299 4999 4777 4966 7024 6016 6998 5938 3799 3938 3838 3538 3338 3294 3978 4038 5299 4991 5798 5038 5577 8637 5638 4499 4599 4699 3799 4378 7477 7959 surface water 3599 1800 1704 3770 3099 400 3099 rainwater 1999 2196 2589 11 13 9

1360 827 1092 838 370 839 632

1056 61 31 1041 4410 121 3449 515 86 881 4338 231 538 560 525 85 74 124 115 124 11 237 6 20 443 596 604 3817 1666 171 171 166 53 100 701 132

10 11 9

453 714 613 495 270 609 475

446 52 20 540 644 30 1160 334 15 596 682 222 122 374 269 15 15 16 33 125 22 230 23 22 24 440 454 616 564 130 133 132 51 27 340 75

0.33 0.31 0.30

5.33 4.82 5.48 5.01 4.59 4.19 4.96

3.15 2.24 1.95 6.51 4.82 4.30 5.04 5.08 2.21 5.63 7.43 4.68 3.46 3.71 4.34 2.05 1.48 2.97 3.65 3.06 1.79 3.30 2.17 1.93 3.70 3.79 3.60 4.85 3.94 3.81 3.95 4.11 2.42 0.82 4.66 1.46 0.71273 0.71169 0.71096 0.71099 0.71088 0.71195 0.71026 0.70822 0.70910 0.70860

-1.6155 1.8932 1.0354

0.71032 0.70962 0.70925 0.70994 0.71101 0.71037 0.71097 0.70879 0.70758 0.70814 0.71035 0.71058 0.70926 0.71033 0.71079 0.70942 0.70932 0.70950 0.70833 0.70827 0.70788 0.70970 0.70789 0.70843 0.71089 0.71092 0.71097 0.71089 0.71021 0.70825 0.70825 0.70824 0.70789 0.70793 0.70893 0.70778

Sr/86Sr

87

4.0115 1.8425 16.5385 13.3155 2.6535 16.9725 2.4925

4.9485 1.1475 3.4155 9.5995 20.6245 -1.8815 23.3335 2.3515 2.8935 -3.7605 21.4355 13.7635 -0.8795 16.3945 9.1035 1.9735 3.4665 5.5745 1.8265 5.4755 0.5150 3.7060 2.0005 3.7310 4.8230 4.5935 -1.5625 21.5655 4.0995 2.7135 2.1725 1.3185 3.7335 1.2053 4.9270 3.1565

EC (µs/cm) Ca (µmol/L) Mg (µmol/L) Na (µmol/L) K (µmol/L) Cl (µmol/L) HCO3 (µmol/L) NO3 (µmol/L) SO4 (µmol/L) Sr (µmol/L) δ15N (‰)

TABLE 1. Analytical Results for Groundwater, Surface Water, and Rainwater of NURS

cultivated land cultivated land construction land construction land cultivated land construction land cultivated land

cultivated land grass land grass land construction land construction land cultivated land construction land cultivated land grass land cultivated land construction land construction land cultivated land construction land construction land forested land forested land cultivated land cultivated land cultivated land forested land cultivated land forested land grass land cultivated land cultivated land cultivated land construction land cultivated land cultivated land cultivated land cultivated land grass land forested land cultivated land forested land

land use

dolomite dolomite dolomite limestone dolomite limestone dolomite limestone limestone limestone limestone dolomite limestone limestone limestone dolomite dolomite limestone limestone limestone limestone limestone limestone dolomite dolomite dolomite dolomite dolomite dolomite limestone limestone limestone limestone limestone limestone limestone

aquifer

FIGURE 3. δ15N versus NO3- concentrations of groundwater, surface water, and rainwater samples in the NURS. land, 27.5 for forested land, 37.7 for grass land, 2.8 for construction land, and 2.5 for water bodies.

were 0.710238 ( 0.000022 (2σ, n ) 42). Uncertainties on individual 87Sr/86Sr measurements were 8.10-6 (at the 2σ level) on average (Table 1).

Samples and Methods

Results and Discussion

A total of 36 groundwater samples from representative epikarst springs at different aquifer and land use backgrounds, 7 surface water samples from rivers and reservoirs, and 3 rainwater samples were collected in July 2008 (Table 1). Sampling locations are shown in Figure 2. The water temperature, pH, and electrical conductance (EC, at 25 °C) were measured by a hand-held water quality meter (WTW MultiLine P3 pH/LF-SET), and Ca2+ and HCO3- were tested by a test kit with a titration pipet Aquamerck in the field. In addition, the water samples (200-2000 mL) were collected for the determination of major ion and Sr2+ concentrations, δ15N and 87Sr/86Sr, respectively. They were filtered through 0.2 µm cellulose-acetate filter paper and collected in polyethylene bottles with airtight caps before storing. Filtered samples for Sr2+ concentration were acidified to pH 2 with ultra pure acetic acid and pH 2.5-3.0 with distilled 6N HCly. The SO42- contained in the acidified samples was collected as BaSO4 by adding 10% BaCl2. All samples were stored at 4 °C before analyses. Concentrations in the water samples were measured by inductively coupled plasma atomic emission mass spectrometry (ICP-AES) for Mg2+, Na+, K+, and Sr2+ (uncertainty 5-10%) and by ion chromatography for Cl-, NO3-, and SO42(uncertainty 5-10%) at the water environmental laboratory of Southwest University. The δ15N values were determined by isotope ratio mass spectrometer (Thermo Scientific Finnigan MAT Delta Plus) at the Isotope Geochemistry Laboratory of Southwest University, and the analytical precision was (0.15‰. Strontium for isotopic analysis was separated using an ion exchange column (Sr-Spec resin). Procedural blank levels were lower than 0.5 ng. The87Sr/86Sr values were determined using a Finnigan MAT 262 multiple collector mass spectrometer at the Isotope Geochemistry Laboratory of the Chinese Academy of Geological Science. The 87Sr/86Sr values were normalized to 86Sr/88S ) 0.1194, and the 87Sr/86Sr of the NIST-NBS987 throughout this study

Chemical Characteristics of Groundwater. Groundwater from the NURS showed strong geographical variations in major element concentrations, N and Sr isotopic composition (Table 1), which strongly suggested spatial heterogeneities of sources of dissolved elements in groundwater in the NURS. Such spatial disparities observed for elemental concentrations, δ15N and 87Sr/86Sr values, for groundwater reflected the impacts of natural processes and human activities on groundwater quality in the NURS. As shown in Table 1, the concentrations of Ca2+, Mg2+, and HCO3- in groundwater were generally higher than those in surface water and rainwater, indicating extensive dissolution of carbonate rocks and greater solubility of the dissolved solutes. The outcrops in the study area are mainly carbonate rocks of Triassic age and Quaternary deposits underlain by Triassic carbonate rocks, with a minor amount of sandstone (Figure 2). This geological feature of the study area is responsible for the high concentrations of Ca2+, Mg2+, and HCO3- in the groundwater. Major anions such as NO3- and Cl- could be useful indicators of contamination. The average concentration of NO3- (757 umol/L) in groundwater was very close to the limit of drinking water standards in China (806 umol/L), of which NO3- concentration in 8 groundwater samples exceeds the drinking water standards (Table 1). Potential sources of NO3- in the study area include chemical fertilizer (urea, ammonium sulfate, and N/P/K fertilizer mix) used in the cultivated land, soil organic matter, effluents, and atmospheric deposition. As shown in Table 1, NO3- concentrations in atmospheric deposition were so much less than those in the groundwater and surface water that atmospheric deposition was not considered to be a major source of the NO3concentrations in the groundwater and surface water. Also, the significant NO3- concentrations observed in the groundwater collected from the construction and cultivated land compared to lower NO3-concentrations in the groundwater VOL. 43, NO. 20, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 4.

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Sr/86Sr vs Sr2+concentrations of groundwater, surface water, and rainwater samples in the NURS.

collected from the forested and grass land suggested that NO3- in the groundwater was mainly attributed to contaminations by human activities. Potential sources for Cl- include natural sources, atmospheric deposition, agricultural chemicals (potash or KCl), and sewage effluents in the study area. There is little significant lithological origin for Cl- in the carbonate rocks of the Triassic age, so it originates from rainfall recharge and human activity over the study area. As shown in Table 1, groundwater samples collected in the construction and cultivated land displayed significantly higher Cl- concentrations, and all of the samples plot above the seawater dilution line and local rainfall dilution line (Na/ Cl molar ratios are 0.86 and 0.97, respectively), suggesting that Cl- in these samples was affected by anthropogenic 7680

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inputs, related most probably to fertilizer applications and domestic sewage. Groundwater samples collected in the forested and grass land displayed element compositions that were close to the local rainfall dilution line, indicating that Cl- in these samples came from atmospheric deposition. There were significant positive correlations (>0.7) between NO3- and Cl-, NO3- and SO42-, NO3- and Na+, Cl- and Na+, Cl- and SO42-, and Na+ and K+, respectively, which indicated such ions in the groundwater were derived from the same sources that were associated with pollution sources. Therefore, nitrate, along with Cl- and SO42- and some Na+ and K+, pollution of groundwater is the main problem in the study area. N Isotopes. The δ15N of NO3- in the groundwater and surface water ranged from -3.76 to +23.34 ‰ and from 1.85

FIGURE 5.

87

Sr/86Sr vs δ15N of groundwater, surface water, and rainwater samples in the NURS.

to +16.98 ‰ (Table 1), respectively, which indicated that NO3- was derived from different sources. The rainwater showed lower δ15N values (Table 1, Figure 3) as compared to the groundwater and surface water in the study area, supporting the idea that rainwater was probably not significant as a major cause of nitrate pollution in groundwater and surface water. Because groundwater and surface water samples were highly concentrated in NO3- and most of the groundwater developed basically in epikarst areas, it could be assumed that denitrification, which causes increasing δ15N values in groundwater (7), would not be significant. As shown in Figure 3, the δ15N values of NO3- in the groundwater and surface water distributed on two arrays, which ranged from +9 to +24 ‰ with high NO3- concentrations (from 231 to 4410 µmol/L) and from -5 to +6 ‰ with disparate NO3- concentrations (from 85 to1666 µmol/L), respectively, suggesting that NO3- is derived from different sources in the study area. The former array groundwater samples showed high δ15N values and high NO3- concentrations characterized by domestic wastewater and sewage origin (8, 9, 24, 25, 38); however, the latter array groundwater samples showed relatively low δ15N values with disparate NO3- concentrations, indicating fertilizers or soil organic matter origin (4, 16, 21, 38-41). According to the land use data (Table 1, Figure 3), the former array groundwater samples were collected in residential zones, whereas the latter array groundwater samples were collected in agricultural, forested, and grass zones, suggesting that the δ15N values of NO3- in the groundwater is consistent with the land use conditions. However, the nitrate sources for the latter array groundwater samples can not be distinguished by using the N isotopes only because there is an overlapping of N isotope signatures between fertilizers and soil origin, of which δ15N values range between -6 and +6 ‰ for fertilizers (4, 16, 21, 37, 39, 41) and δ15N values range between 0 and +8 ‰ for soil (4, 38, 40, 41). Sr Isotopes. Sr isotopic compositions of groundwater and surface water ranged from 0.70758 to 0.71101 and from 0.71026 to 0.71273 (Table 1, Figure 4a,b), respectively, which indicated that Sr was derived from different sources. As shown in Table 1, because the dissolved concentrations of Sr in the groundwater and surface water were significantly higher than

in rainwater, atmospheric deposition was not considered to be a major cause of Sr in the groundwater and surface water in the study area. As indicated by panels a and b of Figure 4, the variations of the 87Sr/86Sr values of groundwater clearly depended upon the different types of host rocks and human activities, suggesting the Sr was derived from bedrock weathering and anthropogenic inputs. Because Sr isotopic compositions were derived from the dissolution of the calcite aquifer covered by forested and grass land (87Sr/86Sr values from 0.70758 to 0.70793 for samples 9, 21, 23, 33, 34, and 36) and from the dolomite aquifer covered by forested and grass land (87Sr/86Sr values from 0.70843 to 0.70962 for samples 2, 3, 16, 17, and 24), for which groundwater samples showed very low NO3-, Cl-, and SO42- concentrations, indicating the groundwater was not affected by anthropogenic inputs, the 87Sr/86Sr values could reflect the main contribution of Sr derived from bedrock weathering. Thus, it can be assumed that 87Sr/86Sr values for the dissolution of the Triassic calcite and dolomite aquifer ranged from 0.7075 to 0.7080 and from 0.7080 to 0.7100, respectively, in the study area as has been demonstrated by some studies in the southwest of China (42-44). However, under the conditions of the same aquifer, the groundwater samples collected in the construction and cultivated land showed higher 87Sr/86Sr values and Sr concentrations than those of groundwater samples collected in forested and grass land, with higher NO3-, SO42-, Cl-, Na+, and K+ concentrations, all of which are major components of anthropogenic inputs. It is concluded the geochemistry of Sr has been altered significantly by the addition of various components of fertilizers in agricultural zones and sewage effluents in residential zones in the study area. As has been demonstrated by some studies, fertilizers have a wide range of 87Sr/86Sr values, varying from 0.70335 to 0.83518 (45), of which the 87Sr/86Sr values of nitrogen fertilizers (ammonium, nitrate, and urea) and phosphorusbearing and potassic fertilizers (KCl and NPK) ranged from 0.7080 to 0.7095, 0.7086 to 0.7096, and 0.7150 to 0.8352, respectively, with higher Sr concentration (31, 32, 45). Therefore, the 87Sr/86Sr values of agricultural fertilizers derived ranged from 0.7080 to 0.8352 in the study area. Although, VOL. 43, NO. 20, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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there is not enough data on Sr isotopic compositions of domestic wastewater and sewage, it was reported by some studies that the 87Sr/86Sr values of urban sewage, detergents, and landfill leachate ranged from 0.7083 to 0.7085 (29), 0.70913 to 0.71008 (46), and 0.708431 to 0.708458 (47), respectively, and urban inputs showed higher 87Sr/86Sr ratios than fertilizers (29). Thus, the 87Sr/86Sr values of domestic wastewater or sewage derived should be >0.7080 at least, and maybe its 87Sr/86Sr values is higher than that of agricultural fertilizers. However, the sources for Sr of groundwater samples contaminated by agricultural fertilizers or sewage effluents cannot be distinguished on the basis of its 87Sr/86Sr ratio only. Coupling Nitrogen with Strontium Isotopes to Identify Contamination Sources of Groundwater. In the 87Sr/86Sr versus δ15N diagram (Figure 5), five groups of groundwater samples can be distinguished, of which 87Sr/86Sr values of 0.7075-0.7080 corresponding with δ15N values of -5 to +9 ‰ indicated that it was nonpolluted groundwater derived from the Triassic calcite aquifer, and 87Sr/86Sr values of 0.7100 -0.71101 corresponding with δ15N values from -5 to +9 ‰ indicated that groundwater derived from both of the Triassic calcite and dolomite aquifers was polluted by agricultural fertilizers. 87Sr/86Sr values of 0.7080 - 0.7110 corresponding with δ15N values from +9 to +24 ‰ indicated that groundwater derived from both Triassic calcite and dolomite aquifers was polluted by sewage effluents, and 87Sr/86Sr values of 0.7080-0.7100 corresponding with δ15N values from +9 to +24 ‰ indicated that groundwater derived from the Triassic calcite aquifer was polluted by sewage effluents. 87Sr/86Sr values of 0.7080-0.7100 corresponding with δ15N values from -5 to +9 ‰ indicated that groundwater derived from the Triassic calcite aquifer was polluted by agricultural fertilizers, but it was nonpolluted groundwater derived from the Triassic dolomite aquifer, respectively. Therefore, although there is overlapping among the N and Sr isotope signatures between the natural sources derived from different aquifers and soil and the anthropogenic inputs derived from agricultural fertilizers and sewage effluents, respectively, the contamination sources of groundwater have been successfully distinguished by the coupled use of nitrogen with strontium isotopes in the NURS. Though the results of this study are preliminary and site specific, the Sr hydrochemistry and 87Sr/86Sr compositions of groundwater tend to be simple in the NURS: a single dominant Sr source in the epikarst groundwater derived from relatively pure carbonate aquifers (limestone and dolomite aquifer) with a narrow range of 87Sr/86Sr values. Sr isotopic ratios (87Sr/86Sr) can provide key information on the source of mineral elements, including natural and anthropogenic origins in groundwater. Also, an increase in knowledge of groundwater geochemistry by means of hydrochemical and isotopic data should be very helpful for understanding water-rock interactions, provenances of contaminants, and the influence of human activities on the hydrogeochemical environment of karst groundwater, and provide a scientific basis for protection and rational utilization of groundwater resources in karst regions. However, limits on the methods used for contaminant source identification are caused by variable 87Sr/86Sr ratios in groundwater from variations in the types of aquifers, groundwater residence times, degree of water-aquifer-chemical interaction, and kinetic effects during groundwater chemical evolution.

Acknowledgments This research was funded by the National Basic Research Program of China (2008CB417208); China Environmental Health Project; Open Foundation of Karst Dynamics Laboratory (kdl2008-06); Academician Foundation of Science and Technology Committee of Chongqing (2007BC7001); and Key 7682

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Laboratory Cultivation Project, Guangxi Karst Dynamics Laboratory with the series number GuiKeNeng (0842008). Thanks are given to Yinggang Li, Qiong Xiao, and Junbing Pu for their help in field work. Thanks are also given to three anonymous reviewers and Prof. Laura Sigg whose constructive comments have largely improved this manuscript. The first author thanks Prof. Chris Groves for his support and help.

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