Traceability and Biogeochemical Process of Nitrate in the Jinan Karst Spring Catchment, North China
Abstract
:1. Introduction
2. Study Area
3. Materials and Methods
3.1. Field Sampling and Analytical Methods
3.2. Mass-Balance Mixing Model
4. Results and Discussion
4.1. Genesis and Evolution of Hydrochemical Components
4.1.1. Hydrochemical Data Characteristics
4.1.2. Characteristics of Hydrochemical Evolution
4.2. Nitrate Migration and Transformations
4.2.1. Nitrate Distribution Characteristics
4.2.2. Identification of Nitrate Sources
4.2.3. Determination of Denitrification
- δs = delta value in the substrate (‰);
- δs,0 = initial delta value in the substrate (‰);
- ε = enrichment factor (‰, positive or negative);
- f = fraction of unreacted residual substrate;
- s = substrate concentration (mg/L);
- s0 = initial (reference) substrate concentration (mg/L).
4.3. Quantitative Estimation of Nitrate Transportation
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Bicalho, C.C.; Batiot-Guilhe, C.; Seidel, J.L.; Exter, S.V.; Jourde, H. Geochemical evidence of water source characterization and hydrodynamic responses in a karst aquifer. J. Hydrol. 2012, 450, 206–218. [Google Scholar] [CrossRef]
- De Salis, H.H.C.; Costa, A.M.D.; Vianna, J.H.; Schuler, M.A.; Kunne, A.; Fernandes, L.F.S.; Pacheco, F.A.L. Hydrologic modeling for sustainable water resources management in urbanized karst areas. Int. J. Environ. Res. Public Health 2019, 16, 2542. [Google Scholar] [CrossRef] [Green Version]
- Stevanovi’c, Z. Karst waters in potable water supply: A global scale overview. Environ. Earth Sci. 2019, 78, 662. [Google Scholar] [CrossRef]
- Leibundgut, C. Vulnerability of karst aquifers. Int. Assoc. Hydrol. Sci. 1998, 247, 45–60. [Google Scholar]
- Alley, W.M.; Healy, R.W.; LaBaugh, J.W.; Reilly, T.E. Flow and storage in groundwater systems. Science 2002, 296, 1985–1990. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yuan, D.X.; Jiang, Y.J.; Shen, L.C.; Pu, J.B.; Xiao, Q. Modern Karstology; Science Press: Beijing, China, 2016. [Google Scholar]
- Liu, F.M.; Yi, S.P.; Ma, H.Y.; Huang, J.Y.; Tang, Y.K.; Qin, J.B.; Zhou, W.H. Risk assessment of groundwater environmental contamination: A case study of a karst site for the construction of a fossil power plant. Environ. Sci. Pollut. Res. Int. 2019, 26, 30561–30574. [Google Scholar] [CrossRef]
- Gong, S.H.; Wang, S.J.; Bai, X.Y.; Luo, G.J.; Wu, L.H.; Chen, F.; Qian, Q.H.; Xiao, J.Y.; Zeng, C. Response of the weathering carbon sink in terrestrial rocks to climate variables and ecological restoration in China. Sci. Total Environ. 2021, 750, 141525. [Google Scholar] [CrossRef] [PubMed]
- Li, C.J.; Bai, X.Y.; Tan, Q.; Luo, G.J.; Wu, L.H.; Chen, F.; Xi, H.P.; Luo, X.L.; Ran, C.; Chen, H.; et al. High-resolution mapping of the global silicate weathering carbon sink and its long-term changes. Glob. Chang. Biol. 2022, 28, 4377–4394. [Google Scholar] [CrossRef] [PubMed]
- Xiong, L.; Bai, X.Y.; Zhao, C.W.; Li, Y.B.; Tan, Q.; Luo, G.J.; Wu, L.H.; Chen, F.; Li, C.J.; Ran, C.; et al. High-Resolution Data Sets for Global Carbonate and Silicate Rock Weathering Carbon Sinks and Their Change Trends. Earth’s Future 2022, 10, e2022EF002746. [Google Scholar] [CrossRef]
- Fu, B.L.; Zuo, P.P.; Liu, M.; Lan, G.W.; He, H.C.; Lao, Z.N.; Zhang, Y.; Fan, D.L.; Gao, E.T. Classifying vegetation communities karst wetland synergistic use of image fusion and object-based machine learning algorithm with Jilin-1 and UAV multispectral images. Ecol. Indic. 2022, 140, 108989. [Google Scholar] [CrossRef]
- Chenini, I.; BenMammou, A.; Turki, M.M. Groundwater resources of a multi-layered aquiferous system in arid area: Data analysis and water budgeting. Int. J. Environ. Sci. Technol. 2008, 5, 361–374. [Google Scholar] [CrossRef]
- Kang, F.X.; Jin, M.G.; Qin, P.R. Sustainable yield of a karst aquifer system: A case study of Jinan springs in northern China. Hydrogeol. J. 2011, 19, 851–863. [Google Scholar] [CrossRef]
- Kazakis, N.; Voudouris, K.S. Groundwater vulnerability and pollution risk assessment of porous aquifers to nitrate: Modifying the DRASTIC method using quantitative parameters. J. Hydrol. 2015, 525, 13–25. [Google Scholar] [CrossRef]
- Panno, S.V.; Hackley, K.C.; Hwang, H.H.; Kelly, W.R. Determination of the sources of nitrate contamination in karst springs using isotopic and chemical indicators. Chem. Geol. 2001, 179, 113–128. [Google Scholar] [CrossRef]
- Hu, M.M.; Wang, Y.C.; Du, P.C.; Shui, Y.; Cai, A.M.; Lv, C.; Bao, Y.F.; Li, Y.H.; Li, S.Z.; Zhang, P.W. Tracing the sources of nitrate in the rivers and lakes of the southern areas of the Tibetan Plateau using dual nitrate isotopes. Sci. Total Environ. 2019, 658, 132–140. [Google Scholar] [CrossRef]
- Gulis, G. An ecologic study of nitrate in municipal drinking water and cancer incidence in Trnava District, Slovakia. Environ. Res. 2002, 3, 182–187. [Google Scholar] [CrossRef]
- Davidson, E.A.; David, M.B.; Galloway, J.N.; Goodale, C.L.; Haeuber, R.; Harrison, J.A.; Howarth, R.W.; Jaynes, D.B.; Lowrance, R.R.; Thomas, N.B.; et al. Excess nitrogen in the U.S. environment: Trends, risks, and solutions. Issues Ecol. 2012, 15, 1–16. [Google Scholar]
- Ming, X.X.; Groves, C.; Wu, X.Y.; Chang, L.R.; Zheng, Y.L.; Yang, P.H. Nitrate migration and transformations in groundwater quantified by dual nitrate isotopes and hydrochemistry in a karst World Heritage site. Sci. Total Environ. 2020, 735, 138907. [Google Scholar] [CrossRef]
- Li, S.L.; Liu, C.Q.; Li, J.; Liu, X.L.; Chetelat, B.; Wang, B.L.; Wang, F.S. Assessment of the sources of nitrate in the Changjiang River, China using a nitrogen and oxygen isotopic approach. Environ. Sci. Technol. 2010, 44, 1573–1578. [Google Scholar] [CrossRef]
- Zhang, X.; Davidson, E.A.; Mauzerall, D.L.; Searchinger, T.D.; Dumas, P.; Shen, Y. Managing nitrogen for sustainable development. Nature 2015, 528, 51–59. [Google Scholar] [CrossRef] [Green Version]
- Chen, J.; Wu, H.; Qian, H. Assessing nitrate and fluoride contaminants in drinking water and their health risk of rural residents living in a semiarid region of northwest China. Expos. Health 2017, 9, 183–195. [Google Scholar] [CrossRef]
- Kohl, D.H.; Shearer, G.B.; Commoner, B. Fertilizer nitrogen: Contribution to nitrate in surface water in a corn belt watershed. Science 1971, 174, 1331–1334. [Google Scholar] [CrossRef] [PubMed]
- Heaton, T.H.E. Isotopic studies of nitrogen pollution in the hydrosphere and atmosphere: A review. Chem. Geol. 1986, 59, 87–102. [Google Scholar] [CrossRef]
- Amiri, H.; Zare, M.; Widory, D. Assessing sources of nitrate contamination in the Shiraz urban aquifer (Iran) using the δ15N and δ18O dual-isotope approach. Isot. Environ. Health Stud. 2015, 51, 392–410. [Google Scholar] [CrossRef] [PubMed]
- Kong, X.L.; Wang, S.Q.; Ding, F.; Liang, H.Y. Source of nitrate in surface water and shallow groundwater around Baiyangdian Lake area based on hydrochemical and stable isotopes. Environ. Sci. 2018, 39, 2624–2631. [Google Scholar]
- Liu, J.; Chen, Z.Y. Using stable isotope to trace the sources of nitrate in groundwater in Shijiazhuang. Environ. Sci. 2009, 30, 1602–1607. [Google Scholar]
- Xu, Z.W.; Zhang, X.Y.; Yu, G.R.; Sun, X.M.; Wen, X.F. Review of dual stable isotope technique for nitrate source identification in surface- and groundwater in China. Environ. Sci. 2014, 35, 3230–3238. [Google Scholar]
- Zhao, Q.L.; Ma, H.Y.; Ren, Y.F.; Wang, X.K.; Peng, J.F.; He, C.W.; Wu, J.L.; Liu, M.Z.; Yan, M.M. δ15N-NO3 and δ18O-NO3 tracing of nitrate sources in Beijing Urban Rivers. Environ. Sci. 2016, 37, 1692–1698. [Google Scholar]
- Nanus, L.; Campbell, D.H.; Lehmann, C.M.B.; Mast, A. Spatial and temporal variation in sources of atmospheric nitrogen deposition in the Rocky Mountains using Nitrogen isotopes. Atmos. Environ. 2018, 176, 110–119. [Google Scholar] [CrossRef]
- Wassenaar, L.I. Evaluation of the origin and fate of nitrate in the Abbotsford aquifer using the isotopes of 15N and 18O in NO3−. Appl. Geochem. 1995, 10, 391–405. [Google Scholar] [CrossRef]
- Chen, F.J.; Jia, G.D.; Chen, J.Y. Nitrate sources and watershed denitrification inferred from nitrate dual isotopes in the Beijiang River, South China. Biogeochemistry 2009, 94, 163–174. [Google Scholar] [CrossRef]
- Yang, P.H.; Wang, Y.Y.; Wu, X.Y.; Chang, L.R.; Ham, B.; Song, L.S.; Groves, C. Nitrate sources and biogeochemical processes in karst underground rivers impacted by different anthropogenic input characteristics. Environ. Pollut. 2020, 265, 114835. [Google Scholar] [CrossRef]
- Zhang, Z.X.; Wang, W.P.; Qu, S.S.; Huang, Q.; Liu, S.; Xu, Q.Y.; Ni, L.D. A new perspective to explore the hydraulic connectivity of karst aquifer system in Jinan spring catchment, China. Water 2018, 10, 1368. [Google Scholar] [CrossRef] [Green Version]
- Guo, Y.; Qin, D.J.; Li, L.; Sun, J.; Li, F.L.; Huang, J.W. A complicated karst spring system: Identified by karst springs using water level, hydrogeochemical, and isotopic data in Jinan, China. Water 2019, 11, 947. [Google Scholar] [CrossRef] [Green Version]
- Liang, Y.P.; Gao, X.B.; Zhao, C.H.; Tang, C.L.; Shen, H.Y.; Wang, Z.H.; Wang, Y.X. Review: Characterization, evolution, and environmental issues of karst water systems in Northern China. Hydrogeol. J. 2018, 26, 1371–1385. [Google Scholar] [CrossRef]
- Xing, L.T.; Li, C.S.; Zhou, J.; Song, G.Z.; Xing, X.R. The characteristics of karst channel in the spring of Jinan spring region. Sci. Technol. Eng. 2017, 17, 57–65. [Google Scholar]
- Gao, Z.J.; Liu, J.T.; Xu, X.Y.; Wang, Q.B.; Wang, M.; Feng, J.G.; Fu, T.F. Temporal variations of spring water in karst areas: A case study of Jinan spring area, Northern China. Water 2020, 12, 1009. [Google Scholar] [CrossRef] [Green Version]
- Li, Y.; Wang, J.L.; Jin, M.G.; Ma, H.K.; Liu, H.R.; Peng, T. Hydrodynamic characteristics of Jinan karst spring system identified by hydrologic time-series data. Earth Sci. 2021, 46, 2583–2593. [Google Scholar]
- Xu, H.Z.; Duan, X.M.; Gao, Z.D.; Wang, Q.B.; Li, W.P.; Yin, X.L. Hydrochemical study of karst groundwater in the Jinan spring catchment. Hydrogeol. Eng. Geol. 2007, 3, 15–19. [Google Scholar]
- Gao, Z.J.; Xu, J.X.; Wang, S.C.; Li, C.S.; Han, K.; Li, J.J.; Luo, F.; Ma, H.K. The distribution characteristics and hydrogeological significance of trace elements in karst water, Jinan, China. Earth Sci. Front. 2014, 21, 135–146. [Google Scholar]
- Zhou, J.; Xing, L.T.; Zhang, F.J.; Han, Z.; Peng, T.Q.; Xu, M.T.; Yang, Y. Chemical characteristics research on karst water in Jinan spring area. Adv. Mater. Res. 2015, 1092–1093, 593–596. [Google Scholar] [CrossRef]
- Sun, B.; Xing, L.T.; Li, C.S. Variation of typical pollution components and pollution way of karst water in Baotu spring region. Carsologica Sin. 2018, 37, 810–818. [Google Scholar]
- Guan, Q.H.; Li, F.L.; Wang, A.Q.; Feng, P.; Tian, C.J.; Chen, X.Q.; Liu, D. Hydrochemistry characteristics and evolution of karst spring groundwater system in Jinan. Carsologica Sin. 2019, 38, 653–662. [Google Scholar]
- Yang, L.Z.; Liu, C.H.; Qi, X.F. Study on characteristic variation of hydro-chemistry of Jinan spring. J. Water Resour. Water Eng. 2016, 27, 59–64. [Google Scholar]
- Xing, L.T.; Zhou, J.; Song, G.Z.; Xing, X.R. Mixing ratios of recharging water sources for the four larging spring groups in Jinan. Earth Sci. Front. 2018, 25, 260–272. [Google Scholar]
- Yin, X.L.; Wang, Q.B.; Feng, W. Hydro-chemical and isotopic study of the karst spring catchment in Jinan. Acta Geol. Sin. 2017, 91, 1651–1660. [Google Scholar]
- Gao, S.; Li, C.S.; Jia, C.; Sun, B.; Zhang, H.L.; Pang, W. Spatiotemporal difference study of karst hydrochemical characteristics in the Baotu Spring area of Jinan. Acta Geol. Sin. 2018, 93, 61–70. [Google Scholar]
- Xu, H.Z.; Li, W.P.; Yin, X.L.; Duan, X.M.; Gao, Z.D.; Wang, Q.B. Hydrochemistry and isotopes of shallow groundwater in the Jinan spring catchment. Hydrogeol. Eng. Geol. 2008, 3, 65–69. [Google Scholar]
- Wang, J.Y.; Wang, J.L.; Jin, M.G. Hydrochemical characteristics and formation causes of karst water in Jinan Spring Catchment. Earth Sci. 2017, 42, 821–831. [Google Scholar]
- GB 12998-91; Water Quality-Guidance on Sampling Techniques. PRC National Standard: China, 1992; pp. 1–11.
- McIlvin, M.R.; Altabet, M.A. Chemical conversion of nitrate and nitrite to nitrous oxide for nitrogen and oxygen isotopic analysis in freshwater and seawater. Anal. Chem. 2005, 77, 5589–5595. [Google Scholar] [CrossRef]
- Kendall, C.; Elliott, E.M.; Wankel, S.D. Tracing Anthropogenic Inputs of Nitrogen to Ecosystems; Blackwell: Hoboken, NJ, USA, 2007. [Google Scholar]
- Deutsch, B.; Mewes, M.; Liskow, I.; Voss, M. Quantification of diffuse nitrate inputs into a small river system using stable isotopes of oxygen and nitrogen in nitrate. Org. Geochem. 2006, 37, 1333–1342. [Google Scholar] [CrossRef]
- Voss, M.; Deutsch, B.; Elmgren, R.; Humborg, C.; Kuuppo, P.; Pastuszak, M.; Rolff, C.; Schulte, U. Source identification of nitrate by means of isotopic tracers in the Baltic Sea catchments. Biogeosciences 2006, 3, 663–676. [Google Scholar] [CrossRef] [Green Version]
- Kaushal, S.S.; Groffman, P.M.; Band, L.; Elliott, E.M.; Shields, C.A.; Kendall, C. Tracking nonpoint source nitrogen pollution in human-impacted watersheds. Environ. Sci. Technol. 2011, 45, 8225–8232. [Google Scholar] [CrossRef] [PubMed]
- Sheng, T.; Yang, P.H.; Xie, G.W.; Hong, A.H.; Cao, C.; Xie, S.Y.; Shi, W.Y. Nitrate-nitrogen pollution sources of an underground river in karst agricultural area using 15N and 18O isotope technique. Environ. Sci. 2018, 39, 4547–4555. [Google Scholar]
- Phillips, D.L.; Newsome, S.D.; Gregg, J.W. Combining sources in stable isotope mixing models: Alternative methods. Oecologia 2005, 144, 520–527. [Google Scholar] [CrossRef]
- Phillips, D.L.; Gregg, J.W. Source partitioning using stable isotopes: Coping with too many sources. Oecologia 2003, 136, 261–269. [Google Scholar] [CrossRef]
- Xu, Z.F.; Liu, C.Q. Water geochemistry of the Xijiang basin rivers, South China: Chemical weathering and CO2 consumption. Appl. Geochem. 2010, 25, 1603–1614. [Google Scholar] [CrossRef]
- Deng, Y.H.; Wang, S.J.; Bai, X.Y.; Luo, G.J.; Wu, L.H.; Chen, F.; Wang, J.F.; Li, Q.; Li, C.J.; Yang, Y.J.; et al. Spatiotemporal dynamics of soil moisture in the karst areas of China based on reanalysis and observations data. J. Hydrogeol. 2020, 585, 124744. [Google Scholar] [CrossRef]
- Zhang, S.R.; Bai, X.Y.; Zhao, C.W.; Tan, Q.; Luo, G.J.; Wang, J.F.; Li, Q.; Wu, L.H.; Chen, F.; Li, C.J.; et al. Global CO2 Consumption by Silicate Rock Chemical Weathering: Its Past and Future. Earth’s Future 2021, 9, e2020EF001938. [Google Scholar] [CrossRef]
- Tian, S.Q.; Wang, S.J.; Bai, X.Y.; Luo, G.J.; Li, Q.; Yang, Y.J.; Hu, Z.Y.; Li, C.J.; Deng, Y.H. Global patterns and changes of carbon emissions from land use during 1992–2015. Environ. Sci. Ecotechnol. 2021, 7, 100108. [Google Scholar] [CrossRef]
- Xiao, B.Q.; Bai, X.Y.; Zhao, C.W.; Tan, Q.; Li, Y.B.; Luo, G.J.; Wu, L.H.; Chen, F.; Li, C.J.; Ran, C.; et al. Responses of carbon and water use efficiencies to climate and land use changes in China’s karst areas. J. Hydrogeol. 2023, 617 Pt A, 128968. [Google Scholar] [CrossRef]
- Li, L.Q.; Xu, E.Q. Scenario analysis and relative importance indicators for combined impact of climate and land-use change on annual ecosystem services in the Karst mountainous region. Ecol. Indic. 2023, 147, 109991. [Google Scholar] [CrossRef]
- Gibrilla, A.; Fianko, J.R.; Ganyaglo, S.; Adomako, D.; Zakaria, N. Nitrate contamination and source apportionment in surface and groundwater in Ghana using dual isotopes (15N and 18O-NO3) and a Bayesian isotope mixing model. J. Contam. Hydrol. 2020, 233, 103658. [Google Scholar] [CrossRef] [PubMed]
- Yang, P.H.; Li, Y.; Groves, C.; Hong, A.H. Coupled hydrogeochemical evaluation of a vulnerable karst aquifer impacted by septic effluent in a protected natural area. Sci. Total Environ. 2019, 658, 1475–1484. [Google Scholar] [CrossRef] [PubMed]
- Gillham, R.W.; Cherry, J.A. Field evidence of denitrification in shallow groundwater flow systems. Water Qual. Res. J. 1978, 13, 53–71. [Google Scholar] [CrossRef]
- Desimone, L.A.; Howes, B.L. Nitrogen transport and transformations in a shallow aquifer receiving wastewater discharge: A mass balance approach. Water Resour. Res. 1998, 34, 271–285. [Google Scholar] [CrossRef]
- Böttcher, J.; Strebel, O.; Voerkelius, S.; Schmidt, H.L. Using isotope fractionation of nitrate-nitrogen and nitrate-oxygen for evaluation of microbial denitrification in a sandy aquifer. J. Hydrol. 1990, 114, 413–424. [Google Scholar] [CrossRef]
Coordinates | pH | EC μS/cm | TDS | K+ | Na+ | Ca2+ | Mg2+ | HCO3− | Cl− | NO3− | SO42− | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
N | E | mg/L | ||||||||||||
Rainy season | G1 | 116°54′56″ | 36°31′24″ | 7.79 | 716 | 463.86 | 3.08 | 57.99 | 77.06 | 16.92 | 220.77 | 39.54 | 13.06 | 133.03 |
G2 | 116°56′19″ | 36°30′56″ | 7.62 | 851 | 550.61 | 0.92 | 30.66 | 129.50 | 15.65 | 234.71 | 35.25 | 29.58 | 174.23 | |
G3 | 117°03′45″ | 36°27′08″ | 7.28 | 742 | 451.70 | 2.14 | 18.30 | 109.26 | 16.71 | 283.51 | 26.41 | 32.59 | 85.23 | |
G4 | 117°02′03″ | 36°29′48″ | 7.20 | 1251 | 892.74 | 3.41 | 21.05 | 203.13 | 36.36 | 304.43 | 27.10 | 79.54 | 346.05 | |
G5 | 117°07′15″ | 36°30′00″ | 7.18 | 1044 | 671.46 | 4.35 | 18.60 | 146.35 | 28.55 | 309.07 | 30.71 | 145.70 | 118.82 | |
G6 | 117°06′52″ | 36°33′44″ | 7.47 | 755 | 433.32 | 1.91 | 11.02 | 124.82 | 15.17 | 339.28 | 9.15 | 14.13 | 79.34 | |
G7 | 117°10′25″ | 36°28′46″ | 7.59 | 605 | 369.61 | 0.83 | 4.80 | 89.72 | 26.28 | 288.16 | 9.31 | 25.95 | 59.99 | |
G8 | 117°09′27″ | 36°32′21″ | 7.75 | 608 | 353.71 | 0.92 | 6.10 | 95.85 | 15.46 | 246.33 | 10.70 | 27.24 | 65.73 | |
G9 | 117°11′19″ | 36°32′11″ | 7.56 | 719 | 420.78 | 2.96 | 12.27 | 111.80 | 15.40 | 267.24 | 17.11 | 33.13 | 84.84 | |
G10 | 116°58′26″ | 36°24′17″ | 7.48 | 550 | 337.55 | 1.49 | 8.52 | 82.00 | 15.69 | 218.44 | 12.44 | 34.32 | 61.87 | |
G11 | 116°53′18″ | 36°32′41″ | 7.59 | 884 | 569.83 | 2.37 | 80.86 | 93.06 | 16.72 | 220.77 | 75.30 | 9.92 | 168.19 | |
G12 | 116°54′40″ | 36°35′28″ | 7.28 | 795 | 451.47 | 0.48 | 24.70 | 105.21 | 17.54 | 313.72 | 40.75 | 21.21 | 70.27 | |
G13 | 117°02′46″ | 36°33′02″ | 7.60 | 644 | 386.67 | 0.78 | 8.69 | 109.62 | 10.18 | 223.09 | 21.78 | 42.07 | 71.79 | |
G14 | 117°03′30″ | 36°36′01″ | 8.93 | 476 | 185.79 | 8.38 | 24.30 | 17.07 | 10.29 | 76.69 | 14.87 | 0.75 | 68.23 | |
G15 | 117°06′35″ | 36°37′22″ | 7.27 | 1176 | 754.93 | 2.03 | 43.97 | 161.77 | 34.61 | 290.48 | 81.75 | 68.86 | 205.02 | |
G16 | 117°03′56″ | 36°38′14″ | 7.92 | 1143 | 782.09 | 28.54 | 84.67 | 123.25 | 18.80 | 151.05 | 69.11 | 13.37 | 352.93 | |
G17 | 117°00′55″ | 36°37′47″ | 7.14 | 934 | 571.36 | 0.54 | 34.81 | 135.93 | 20.41 | 288.16 | 68.86 | 42.60 | 108.07 | |
G18 | 117°10′27″ | 36°38′28″ | 7.95 | 654 | 386.36 | 0.67 | 7.34 | 97.12 | 20.75 | 250.98 | 18.79 | 39.64 | 67.90 | |
G19 | 116°55′56″ | 36°37′28″ | 7.01 | 1107 | 694.81 | 0.46 | 28.12 | 178.32 | 22.62 | 313.72 | 99.67 | 85.65 | 106.83 | |
G20 | 116°53′14″ | 36°36′51″ | 7.24 | 809 | 483.21 | 0.71 | 15.67 | 117.16 | 21.29 | 290.48 | 39.18 | 47.65 | 78.38 | |
G21 | 116°51′01″ | 36°37′07″ | 7.61 | 606 | 375.12 | 1.07 | 18.61 | 89.13 | 15.81 | 209.15 | 39.17 | 25.11 | 67.95 | |
G22 | 117°00′56″ | 36°38′50″ | 7.05 | 873 | 514.11 | 4.15 | 31.06 | 106.91 | 35.19 | 453.15 | 42.27 | 7.79 | 42.32 | |
G23 | 117°02′35″ | 36°38′40″ | 7.92 | 803 | 464.22 | 3.46 | 49.98 | 49.18 | 42.94 | 153.37 | 90.18 | 15.81 | 131.52 | |
G24 | 117°11′12″ | 36°40′24″ | 7.58 | 639 | 382.54 | 1.05 | 13.05 | 92.11 | 16.74 | 188.23 | 36.85 | 33.66 | 82.60 | |
G25 | 117°00′33″ | 36°39′38″ | 7.37 | 872 | 543.44 | 1.50 | 32.49 | 125.64 | 22.48 | 269.57 | 62.16 | 45.53 | 104.44 | |
G26 | 117°01′38″ | 36°39′43″ | 7.29 | 972 | 610.62 | 1.29 | 41.90 | 136.66 | 23.29 | 290.48 | 75.43 | 51.24 | 121.88 | |
Mean | 7.53 | 816 | 503.92 | 3.06 | 28.06 | 111.83 | 21.23 | 257.50 | 42.07 | 37.91 | 117.59 | |||
Std | 0.39 | 204.7 | 158.69 | 5.48 | 21.33 | 37.83 | 8.24 | 72.2 | 27.06 | 6.87 | 78.65 | |||
CV | 0.05 | 0.25 | 0.31 | 1.79 | 0.76 | 0.34 | 0.39 | 0.28 | 0.64 | 0.8 | 0.67 | |||
Dry season | G1 | 116°54′56″ | 36°31′24″ | 7.57 | 886 | 559.51 | 3.19 | 42.04 | 108.41 | 26.50 | 190.06 | 94.24 | 8.86 | 173.51 |
G2 | 116°56′19″ | 36°30′56″ | 7.29 | 1003 | 681.89 | 8.28 | 30.74 | 160.26 | 20.92 | 288.79 | 60.64 | 83.7 | 157.71 | |
G3 | 117°03′45″ | 36°27′08″ | 7.20 | 721 | 454.59 | 1.67 | 18.73 | 116.17 | 15.36 | 288.79 | 29.47 | 27.32 | 87.62 | |
G4 | 117°02′03″ | 36°29′48″ | 7.32 | 1507 | 1231.09 | 5.27 | 24.17 | 261.26 | 60.28 | 264.11 | 25.69 | 73.38 | 629.37 | |
G5 | 117°07′15″ | 36°30′00″ | 7.25 | 1020 | 701.22 | 2.85 | 19.67 | 159.15 | 32.18 | 306.07 | 35.27 | 152.65 | 127.82 | |
G6 | 117°06′52″ | 36°33′44″ | 7.67 | 1749 | 1226.05 | 1.82 | 155.22 | 227.01 | 17.78 | 264.11 | 17.33 | 14.75 | 650.49 | |
G7 | 117°10′25″ | 36°28′46″ | 7.90 | 608 | 372.18 | 1.41 | 18.9 | 69.95 | 30.92 | 288.79 | 15.20 | 19.75 | 53.42 | |
G8 | 117°09′27″ | 36°32′21″ | 7.68 | 629 | 395.28 | 1.03 | 7.26 | 106.49 | 16.21 | 264.11 | 14.12 | 34.54 | 73.31 | |
G9 | 117°11′19″ | 36°32′11″ | 7.48 | 634 | 399.59 | 0.77 | 7.34 | 101.21 | 19.03 | 288.79 | 14.19 | 30.78 | 70.68 | |
G10 | 116°58′26″ | 36°24′17″ | 7.51 | 659 | 446.96 | 1.59 | 13.93 | 105.12 | 21.32 | 261.64 | 24.85 | 62.40 | 73.19 | |
G11 | 116°53′18″ | 36°32′41″ | 7.57 | 888 | 560.64 | 2.47 | 60.69 | 100.38 | 19.98 | 197.46 | 88.12 | 9.79 | 170.47 | |
G12 | 116°54′40″ | 36°35′28″ | 7.43 | 854 | 543.68 | 0.45 | 21.56 | 137.52 | 19.97 | 306.07 | 51.88 | 50.66 | 90.87 | |
G13 | 117°02′46″ | 36°33′02″ | 7.60 | 683 | 357.02 | 0.61 | 96.21 | 9.46 | 11.49 | 148.10 | 30.79 | 50.93 | 71.34 | |
G14 | 117°03′30″ | 36°36′01″ | 7.71 | 905 | 540.99 | 1.07 | 25.05 | 131.81 | 20.37 | 246.83 | 84.48 | 43.05 | 100.75 | |
G15 | 117°06′35″ | 36°37′22″ | 7.26 | 1178 | 833.23 | 2.34 | 46.67 | 174.43 | 36.07 | 298.66 | 98.96 | 85.34 | 224.58 | |
G16 | 117°03′56″ | 36°38′14″ | 7.40 | 1118 | 752.80 | 1.63 | 50.54 | 148.74 | 32.13 | 271.51 | 69.53 | 70.37 | 226.50 | |
G17 | 117°00′55″ | 36°37′47″ | 7.24 | 925 | 589.82 | 1.18 | 35.15 | 138.21 | 20.24 | 298.66 | 73.67 | 41.01 | 112.17 | |
G18 | 117°10′27″ | 36°38′28″ | 7.73 | 656 | 411.46 | 0.62 | 7.47 | 104.81 | 21.06 | 269.05 | 19.50 | 43.18 | 68.87 | |
G19 | 116°55′56″ | 36°37′28″ | 7.14 | 1110 | 700.83 | 0.38 | 27.7 | 176.52 | 23.79 | 306.07 | 110.86 | 79.85 | 109.86 | |
G20 | 116°53′14″ | 36°36′51″ | 7.32 | 875 | 592.64 | 0.72 | 13.26 | 150.47 | 22.36 | 288.36 | 50.96 | 91.41 | 97.62 | |
G21 | 116°51′01″ | 36°37′07″ | 7.74 | 615 | 380.70 | 1.01 | 17.85 | 90.11 | 16.11 | 214.74 | 40.92 | 25.24 | 68.49 | |
G22 | 117°00′56″ | 36°38′50″ | 6.85 | 897 | 564.68 | 18.13 | 30.62 | 116.75 | 36.82 | 449.23 | 58.20 | 1.15 | 63.12 | |
G23 | 117°02′35″ | 36°38′40″ | 8.03 | 804 | 484.20 | 4.19 | 48.82 | 51.79 | 43.32 | 155.50 | 93.89 | 20.11 | 138.87 | |
G24 | 117°11′12″ | 36°40′24″ | 7.95 | 203.9 | 119.97 | 1.75 | 3.48 | 36.10 | 2.01 | 111.07 | 4.05 | 5.36 | 8.43 | |
G25 | 117°00′33″ | 36°39′38″ | 7.45 | 828 | 532.96 | 2.73 | 48.68 | 100.80 | 22.86 | 229.55 | 74.26 | 33.30 | 123.78 | |
G26 | 117°01′38″ | 36°39′43″ | 7.35 | 929 | 610.12 | 1.23 | 37.54 | 136.51 | 23.25 | 288.79 | 77.24 | 53.36 | 121.21 | |
Mean | 7.49 | 880 | 578.62 | 2.63 | 34.97 | 123.82 | 24.32 | 260.96 | 52.24 | 46.63 | 149.77 | |||
Std | 0.27 | 302.25 | 241.5 | 3.6 | 31.88 | 53.8 | 11.27 | 65.71 | 31.72 | 7.73 | 152.95 | |||
CV | 0.04 | 0.34 | 0.42 | 1.37 | 0.91 | 0.43 | 0.46 | 0.25 | 0.61 | 0.73 | 1.02 |
pH | EC | TDS | K+ | Na+ | Ca2+ | Mg2+ | HCO3− | Cl− | NO3− | SO42− | |
---|---|---|---|---|---|---|---|---|---|---|---|
pH | 1 | −0.54 | −0.54 | 0.36 | 0.1 | −0.75 | −0.35 | −0.82 | −0.28 | −0.52 | −0.03 |
EC | −0.39 | 1 | 0.98 | 0.29 | 0.49 | 0.82 | 0.57 | 0.37 | 0.63 | 0.55 | 0.74 |
TDS | −0.38 | 0.98 | 1 | 0.31 | 0.49 | 0.83 | 0.54 | 0.33 | 0.57 | 0.54 | 0.80 |
K+ | −0.46 | 0.16 | 0.17 | 1 | 0.57 | −0.06 | −0.01 | −0.37 | 0.15 | −0.18 | 0.61 |
Na+ | 0.07 | 0.60 | 0.51 | 0.01 | 1 | 0.01 | 0.19 | −0.25 | 0.70 | −0.22 | 0.60 |
Ca2+ | −0.51 | 0.86 | 0.90 | 0.11 | 0.37 | 1 | 0.32 | 0.59 | 0.28 | 0.68 | 0.49 |
Mg2+ | −0.25 | 0.53 | 0.59 | 0.41 | 0.52 | 0.49 | 1 | 0.36 | 0.44 | 0.33 | 0.32 |
HCO3− | −0.76 | 0.33 | 0.32 | 0.48 | 0.18 | 0.51 | 0.32 | 1 | −0.01 | 0.32 | −0.17 |
Cl− | −0.28 | 0.29 | 0.19 | 0.11 | 0.84 | 0.14 | 0.27 | 0.05 | 1 | 0.15 | 0.36 |
NO3− | −0.41 | 0.32 | 0.34 | −0.16 | 0.17 | 0.45 | 0.27 | 0.27 | 0.1 | 1 | 0.19 |
SO42− | −0.08 | 0.87 | 0.91 | 0.08 | 0.59 | 0.75 | 0.49 | 0.03 | −0.04 | 0.08 | 1 |
Rainy Season | Dry Season | |
---|---|---|
Indirect recharge area | 9.83 mg/L | 11.47 mg/L |
Direct recharge area | 6.73 mg/L | 11.13 mg/L |
Discharge area | 8.82 mg/L | 8.74 mg/L |
Sample | Rainy Season | Dry Season | ||||
---|---|---|---|---|---|---|
δ15N (‰) | δ18O (‰) | NNO3 (mg/L) | δ15N (‰) | δ18O (‰) | NNO3 (mg/L) | |
G1 | 11.72 | 1.6 | 2.95 | 11.36 | 5.13 | 2.00 |
G2 | 6.85 | −0.65 | 6.68 | 7.45 | 3.05 | 18.90 |
G3 | 9.83 | −7.92 | 7.36 | 10.17 | 3.18 | 6.17 |
G4 | 7.01 | −1.42 | 17.96 | 6.68 | 2.38 | 16.57 |
G5 | 5.52 | −3.24 | 32.90 | 4.71 | 0.50 | 34.47 |
G6 | 6.06 | 0.42 | 3.19 | 12.79 | 6.53 | 3.33 |
G7 | 1.05 | 4.98 | 5.86 | 2.01 | 7.89 | 4.46 |
G8 | 4.32 | 2.81 | 6.15 | 5.20 | 4.56 | 7.80 |
G9 | 7.93 | −1.71 | 7.48 | 6.00 | 3.62 | 6.95 |
G10 | 5.18 | 0 | 7.75 | 6.70 | 2.68 | 14.09 |
G11 | 12.78 | 2.28 | 2.24 | 9.55 | 6.91 | 2.21 |
G12 | 11.44 | 1.12 | 4.79 | 10.33 | 4.52 | 11.44 |
G13 | 7.75 | 0.27 | 9.50 | 6.90 | 3.70 | 11.50 |
G14 | 8.59 | 13.83 | 0.17 | 5.04 | 6.49 | 9.72 |
G15 | 8.22 | 1.57 | 15.55 | 10.19 | 3.49 | 19.27 |
G16 | 9.49 | 3.03 | 3.02 | 9.59 | 3.32 | 15.89 |
G17 | 10.07 | −0.16 | 9.62 | 9.76 | 3.46 | 9.26 |
G18 | 5.24 | 1.25 | 8.95 | 6.00 | 4.40 | 9.75 |
G19 | 9.24 | −0.85 | 19.34 | 8.60 | 2.00 | 18.03 |
G20 | 8.48 | −0.51 | 10.76 | 7.10 | 1.26 | 20.64 |
G21 | 9.11 | −0.95 | 5.67 | 9.27 | 3.65 | 5.70 |
G22 | 0.34 | 22.94 | 1.76 | 0.53 | 16.54 | 0.26 |
G23 | 13.86 | −0.76 | 3.57 | 12.46 | 2.48 | 4.54 |
G24 | 6.7 | 0.32 | 7.60 | −1.42 | 15.63 | 1.21 |
G25 | 10.98 | −0.83 | 10.28 | 9.47 | 3.10 | 7.52 |
G26 | 11.39 | 0.27 | 11.57 | 11.06 | 2.78 | 12.05 |
S1 | 14.43 | 5.16 | 1.44 | 15.47 | 7.63 | 0.98 |
S2 | 11.18 | 2.79 | 2.69 | 11.98 | 5.69 | 1.12 |
S3 | 10.37 | 3.21 | 2.17 | 11.26 | 6.69 | 1.02 |
S4 | 8.65 | 6.02 | 2.87 | 10.91 | 10.80 | 1.36 |
Sample | Rainy Season | Dry Season | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
AD (%) | SON (%) | CF (%) | AF (%) | M&S (%) | AD (%) | SON (%) | CF (%) | AF (%) | M&S (%) | |
G1 | 2.7 | 19.5 | 6.8 | 14.7 | 56.4 | 5.3 | 18 | 10.4 | 13.5 | 52.8 |
G2 | 1 | 34.7 | 3.5 | 27.7 | 33.1 | 3.7 | 29.8 | 9.4 | 22.6 | 34.5 |
G3 | 3 | 29.6 | 8.1 | 29.6 | 29.6 | 3.8 | 22.3 | 9 | 16.8 | 48.1 |
G4 | 0.5 | 35.3 | 2.2 | 27.9 | 34.1 | 3.2 | 31.5 | 8.6 | 25.4 | 31.3 |
G5 | 2.7 | 29.9 | 7.6 | 29.9 | 29.9 | 1.8 | 33.8 | 5.7 | 33.5 | 25.2 |
G6 | 1.8 | 33.9 | 5.3 | 29.4 | 29.6 | 6.4 | 14 | 9.9 | 10.5 | 59.3 |
G7 | 5 | 31.9 | 13.1 | 34.2 | 15.8 | 7.2 | 28.4 | 17 | 29.4 | 17.9 |
G8 | 3.5 | 31.5 | 9.5 | 31.8 | 23.8 | 4.8 | 29.6 | 12 | 28.1 | 25.5 |
G9 | 0.3 | 33.7 | 1.5 | 25.4 | 39 | 4.1 | 30.6 | 10.5 | 26.5 | 28.3 |
G10 | 1.5 | 34.4 | 4.7 | 32.7 | 26.7 | 3.4 | 31.2 | 9 | 25 | 31.3 |
G11 | 3.2 | 16.3 | 7.3 | 12.2 | 61 | 6.6 | 21.4 | 12.7 | 16.1 | 43.2 |
G12 | 2.3 | 20.7 | 6.1 | 15.5 | 55.4 | 4.8 | 20.9 | 10.4 | 15.7 | 48.1 |
G13 | 1.7 | 31.9 | 5.1 | 24 | 37.3 | 4.2 | 30.1 | 10.4 | 23.6 | 31.7 |
G14 | 15.6 | 18.1 | 18.7 | 13.6 | 34 | 6.2 | 28 | 14.5 | 26.9 | 24.4 |
G15 | 2.6 | 29 | 7.1 | 21.9 | 39.4 | 4.1 | 22 | 9.4 | 16.5 | 48 |
G16 | 3.7 | 24.2 | 9 | 18.2 | 44.9 | 3.9 | 23.7 | 9.3 | 17.8 | 45.3 |
G17 | 1.4 | 25.4 | 4.2 | 19.2 | 49.8 | 4 | 23.1 | 9.4 | 17.4 | 46 |
G18 | 2.4 | 32.9 | 6.9 | 31.2 | 26.6 | 4.7 | 29.9 | 11.6 | 25.8 | 27.9 |
G19 | 1 | 28.5 | 3.1 | 21.4 | 46.1 | 3 | 27.5 | 7.7 | 20.7 | 41.1 |
G20 | 1.2 | 30.4 | 3.7 | 22.9 | 41.8 | 2.4 | 32.2 | 6.8 | 25 | 33.6 |
G21 | 0.9 | 29 | 2.9 | 21.8 | 45.4 | 4.2 | 24.3 | 9.8 | 18.3 | 43.5 |
G22 | 32.1 | 15.5 | 25.3 | 15.8 | 11.3 | 18.5 | 20 | 27.7 | 20.7 | 13 |
G23 | 1 | 16 | 3.1 | 12 | 68 | 3.4 | 16.9 | 7.6 | 12.7 | 59.4 |
G24 | 1.7 | 33.7 | 5.3 | 27.2 | 32.2 | 16.4 | 21.2 | 29.5 | 24.5 | 8.5 |
G25 | 1 | 23.7 | 3 | 17.8 | 54.5 | 3.8 | 24.2 | 9.1 | 18.2 | 44.8 |
G26 | 1.7 | 21.5 | 4.9 | 16.2 | 55.7 | 3.6 | 20.3 | 8.3 | 15.3 | 52.6 |
S1 | 5.3 | 10.8 | 7.8 | 8.1 | 67.9 | 6.4 | 8.2 | 6.6 | 6.1 | 72.7 |
S2 | 3.6 | 20 | 8.3 | 15 | 53.1 | 5.7 | 16.2 | 10.4 | 12.1 | 55.6 |
S3 | 3.9 | 21.8 | 9 | 16.4 | 49 | 6.5 | 17.4 | 11.4 | 13.1 | 51.7 |
S4 | 5.9 | 24.2 | 12.5 | 18.2 | 39.2 | 11 | 15.5 | 14.2 | 11.6 | 47.7 |
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Wang, K.; Chen, X.; Wu, Z.; Wang, M.; Wang, H. Traceability and Biogeochemical Process of Nitrate in the Jinan Karst Spring Catchment, North China. Water 2023, 15, 2718. https://doi.org/10.3390/w15152718
Wang K, Chen X, Wu Z, Wang M, Wang H. Traceability and Biogeochemical Process of Nitrate in the Jinan Karst Spring Catchment, North China. Water. 2023; 15(15):2718. https://doi.org/10.3390/w15152718
Chicago/Turabian StyleWang, Kairan, Xuequn Chen, Zhen Wu, Mingsen Wang, and Hongbo Wang. 2023. "Traceability and Biogeochemical Process of Nitrate in the Jinan Karst Spring Catchment, North China" Water 15, no. 15: 2718. https://doi.org/10.3390/w15152718
APA StyleWang, K., Chen, X., Wu, Z., Wang, M., & Wang, H. (2023). Traceability and Biogeochemical Process of Nitrate in the Jinan Karst Spring Catchment, North China. Water, 15(15), 2718. https://doi.org/10.3390/w15152718