Articles | Volume 30, issue 6
https://doi.org/10.5194/hess-30-1449-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-1449-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Mar 2026
Research article |
| 20 Mar 2026
| 20 Mar 2026
Impact of occurrence conditions on NO3−-N source apportionment in groundwater: insights from PCA-APCS-MLR and MixSIAR methods
Yang Liu
College of Environmental Science and Engineering, Ocean University of China, Qingdao 266100, China
Shandong Provincial Key Laboratory of Marine Engineering Geology and the Environment, Ocean University of China, Qingdao 266100, China
Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao 266100, China
Jian Luo
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
College of Engineering, Ocean University of China, Qingdao 266100, China
Ziyang Zhang
College of Environmental Science and Engineering, Ocean University of China, Qingdao 266100, China
Shandong Provincial Key Laboratory of Marine Engineering Geology and the Environment, Ocean University of China, Qingdao 266100, China
Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao 266100, China
Xilai Zheng
College of Environmental Science and Engineering, Ocean University of China, Qingdao 266100, China
Shandong Provincial Key Laboratory of Marine Engineering Geology and the Environment, Ocean University of China, Qingdao 266100, China
Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao 266100, China
College of Environmental Science and Engineering, Ocean University of China, Qingdao 266100, China
Shandong Provincial Key Laboratory of Marine Engineering Geology and the Environment, Ocean University of China, Qingdao 266100, China
Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao 266100, China
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Cited articles
Cui, R., Zhang, D., Hu, W., Zhao, X., Yan, H., Liu, G., and Chen, A.: Nitrogen in soil, manure and sewage has become a major challenge in controlling nitrate pollution in groundwater around plateau lakes, Southwest China, J. Hydrol. 620, 129541, https://doi.org/10.1016/j.jhydrol.2023.129541, 2023.
Dai, H., Zhang, Y., Fang, W., Liu, J., Hong, J., Zou, C., and Zhang, J.: Microbial community structural response to variations in physicochemical features of different aquifers, Front. Microbiol., 14, 1025964, https://doi.org/10.3389/fmicb.2023.1025964, 2023.
Díaz-Cruz, M. S. and Barceló, D.: Trace organic chemicals contamination in ground water recharge, Chemosphere, 72, 333–342, https://doi.org/10.1016/j.chemosphere.2008.02.031, 2008.
Gibrilla, A., Fianko, J. R., Ganyaglo, S., Adomako, D., Anornu, G., and 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., 233, 103658, https://doi.org/10.1016/j.jconhyd.2020.103658, 2020.
Greenberg, A. E., Trussell, R. R., Clesceri, L. S., and Association, A. W. W.: Standard methods for the examination of water and wastewater: supplement to the 16th edition, Am. J. Public Health N., 56, 387, https://doi.org/10.2105/AJPH.56.4.684-a, 2005.
Gutiérrez, M., Biagioni, R. N., Alarcón-Herrera, M. T., and Rivas-Lucero, B. A.: An overview of nitrate sources and operating processes in arid and semiarid aquifer systems, Sci. Total Environ., 624, 1513–1522, https://doi.org/10.1016/j.scitotenv.2017.12.252, 2018.
Hao, Y., Zheng, T., Liu, L., Li, P., Ma, H., Zheng, Z., Zheng, X., and Luo, J.: Occurrence of dissimilatory nitrate reduction to ammonium (DNRA) in groundwater table fluctuation zones during dissolved organic nitrogen leaching through unsaturated zone, J. Hazard. Mater., 489, 137501, https://doi.org/10.1016/j.jhazmat.2025.137501, 2025.
Huang, X., Jin, M., Ma, B., Liang, X., Cao, M., Zhang, J., Zhang, Z., and Su, J.: Identifying nitrate sources and transformation in groundwater in a large subtropical basin under a framework of groundwater flow systems, J. Hydrol., 610, 127943, https://doi.org/10.1016/j.jhydrol.2022.127943, 2022.
Ji, X., Shu, L., Chen, W., Chen, Z., Shang, X., Yang, Y., Dahlgren, R. A., and Zhang, M.: Nitrate pollution source apportionment, uncertainty and sensitivity analysis across a rural-urban river network based on δ15N/δ18O-NO
Kellman, L. M. and Hillaire-Marcel, C.: Evaluation of nitrogen isotopes as indicators of nitrate contamination sources in an agricultural watershed, Agr. Ecosyst. Environ., 95, 87–102, https://doi.org/10.1016/s0167-8809(02)00168-8, 2003.
Li, J., Liu, Y., Dai, W., Li, J., Yang, P., Tian, L., Yu, S., Zuo, R., Zhai, Y., and Song, W.: Nitrate attenuation with rising groundwater levels: An integrated assessment using isotope tracers and microbial signatures, J. Hydrol., 624, 129911, https://doi.org/10.1016/j.jhydrol.2023.129911, 2023.
Li, S., Chow, R., Su, H., Han, F., and Li, Z.: Multiple isotopes and GIS analyses reveal sources and drivers of nitrate in the Loess Plateau's groundwater, Environ. Pollut., 127022, https://doi.org/10.1016/j.envpol.2025.127022, 2025.
Liang, X., Zhan, H., Zhang, Y. K., and Schilling, K.: Base flow recession from unsaturated-saturated porous media considering lateral unsaturated discharge and aquifer compressibility, Water Resour. Res., 53, 7832–7852, https://doi.org/10.1002/2017wr020938, 2017.
Liu, S., Zheng, T., Li, Y., and Zheng, X.: A critical review of the central role of microbial regulation in the nitrogen biogeochemical process: New insights for controlling groundwater nitrogen contamination, J. Environ. Manage., 328, 116959, https://doi.org/10.1016/j.jenvman.2022.116959, 2023.
Liu, W., Du, Y., Qiu, W., Deng, Y., and Wang, Y.: Constraints on vertical variability of geogenic ammonium in multi-layered aquifer systems, Water Res., 268, 122639, https://doi.org/10.1016/j.watres.2024.122639, 2025.
Liu, Y., Xin, J., Wang, Y., Yang, Z., Liu, S., and Zheng, X.: Dual roles of dissolved organic nitrogen in groundwater nitrogen cycling: nitrate precursor and denitrification promoter, Sci. Total Environ., 811, 151375, https://doi.org/10.1016/j.scitotenv.2021.151375, 2022.
Ma, J., Liu, H., Tong, L., Wang, Y., Chen, R., Liu, S., Zhao, L., Li, Z., and Cai, L.: Relationships between microbial communities and groundwater chemistry in two pristine confined groundwater aquifers in central China, Hydrol. Process., 33, 1993–2005, https://doi.org/10.1002/hyp.13437, 2019.
Liu, Y.: Data Availability for HESS, V2, Mendeley Data [data set], https://doi.org/10.17632/53d3ktbg8d.2, 2026.
Mao, H., Wang, G., Liao, F., Shi, Z., Zhang, H., Chen, X., Qiao, Z., Li, B., and Bai, Y.: Spatial variability of source contributions to nitrate in regional groundwater based on the positive matrix factorization and Bayesian model, J. Hazard. Mater., 445, 130569, https://doi.org/10.1016/j.jhazmat.2022.130569, 2023.
McDonough, L. K., Andersen, M. S., Behnke, M. I., Rutlidge, H., Oudone, P., Meredith, K., O Carroll, D. M., Santos, I. R., Marjo, C. E., and Spencer, R. G.: A new conceptual framework for the transformation of groundwater dissolved organic matter, Nat. Commun., 13, 2153, https://doi.org/10.1038/s41467-022-29711-9, 2022.
Meng, L., Zuo, R., Wang, J., Yang, J., Teng, Y., Shi, R., and Zhai, Y.: Apportionment and evolution of pollution sources in a typical riverside groundwater resource area using PCA-APCS-MLR model, J. Contam. Hydrol., 218, 70–83, https://doi.org/10.1016/j.jconhyd.2018.10.005, 2018.
Minet, E. P., Goodhue, R., Meier-Augenstein, W., Kalin, R. M., Fenton, O., Richards, K. G., and Coxon, C. E.: Combining stable isotopes with contamination indicators: a method for improved investigation of nitrate sources and dynamics in aquifers with mixed nitrogen inputs, Water Res., 124, 85–96, https://doi.org/10.1016/j.watres.2017.07.041, 2017.
Moore, J. W. and Semmens, B. X.: Incorporating uncertainty and prior information into stable isotope mixing models, Ecol. Lett., 11, 470–480, https://doi.org/10.1111/j.1461-0248.2008.01163.x, 2008.
Niu, X., Jia, X., Yang, X., Wang, J., Wei, X., Wu, L., and Shao, M.: Tracing the sources and fate of NO
Picetti, R., Deeney, M., Pastorino, S., Miller, M. R., Shah, A., Leon, D. A., Dangour, A. D., and Green, R.: Nitrate and nitrite contamination in drinking water and cancer risk: A systematic review with meta-analysis, Environ. Res., 210, 112988, https://doi.org/10.1016/j.envres.2022.112988, 2022.
Ransom, K. M., Grote, M. N., Deinhart, A., Eppich, G., Kendall, C., Sanborn, M. E., Souders, A. K., Wimpenny, J., Yin, Q. Z., and Young, M.: Bayesian nitrate source apportionment to individual groundwater wells in the Central Valley by use of elemental and isotopic tracers, Water Resour. Res., 52, 5577–5597, https://doi.org/10.1002/2015wr018523, 2016.
Rivett, M. O., Buss, S. R., Morgan, P., Smith, J. W., and Bemment, C. D.: Nitrate attenuation in groundwater: a review of biogeochemical controlling processes, Water Res., 42, 4215–4232, https://doi.org/10.1016/j.watres.2008.07.020, 2008.
Romanelli, A., Soto, D. X., Matiatos, I., Martínez, D. E., and Esquius, S.: A biological and nitrate isotopic assessment framework to understand eutrophication in aquatic ecosystems, Sci. Total Environ., 715, 136909, https://doi.org/10.1016/j.scitotenv.2020.136909, 2020.
Ruan, D., Bian, J., Wang, Y., Wu, J., and Gu, Z.: Identification of groundwater pollution sources and health risk assessment in the Songnen Plain based on PCA-APCS-MLR and trapezoidal fuzzy number-Monte Carlo stochastic simulation model, J. Hydrol., 632, 130897, https://doi.org/10.1016/j.jhydrol.2024.130897, 2024.
Schot, P. P. and Wassen, M. J.: Calcium concentrations in wetland groundwater in relation to water sources and soil conditions in the recharge area, J. Hydrol., 141, 197–217, https://doi.org/10.1016/0022-1694(93)90050-j, 1993.
Shu, L., Chen, W., Liu, Y., Shang, X., Yang, Y., Dahlgren, R. A., Chen, Z., Zhang, M., and Ji, X.: Riverine nitrate source identification combining δ15N/δ18O-NO
Thurston, G. D. and Spengler, J. D.: A quantitative assessment of source contributions to inhalable particulate matter pollution in metropolitan Boston, Atmos. Environ., 19, 9–25, https://doi.org/10.1016/0004-6981(85)90132-5, 1985.
Wan, Y., Li, R., Yao, K., Peng, C., Wang, W., Li, N., and Wang, X.: Bioelectro-barriers prevent nitrate leaching into groundwater via nitrogen retention, Water Res., 249, 120988, https://doi.org/10.1016/j.watres.2023.120988, 2024.
Wang, D., Li, P., Yang, N., Yang, C., Zhou, Y., and Li, J.: Distribution, sources and main controlling factors of nitrate in a typical intensive agricultural region, northwestern China: vertical profile perspectives, Environ. Res., 237, 116911, https://doi.org/10.1016/j.envres.2023.116911, 2023.
Wong, W. W., Grace, M. R., Cartwright, I., and Cook, P. L.: Unravelling the origin and fate of nitrate in an agricultural–urban coastal aquifer, Biogeochemistry, 122, 343–360, https://doi.org/10.1007/s10533-014-0045-4, 2015.
Xie, L., Li, P., Fida, M., and Elumalai, V.: Characteristics and potential health risk of inorganic nitrogen in phreatic water in the central and southern parts of Yinchuan Plain (Northwest China), Expo. Health, 17, 581–598, https://doi.org/10.1007/s12403-024-00679-9, 2025.
Xin, J., Liu, Y., Chen, F., Duan, Y., Wei, G., Zheng, X., and Li, M.: The missing nitrogen pieces: A critical review on the distribution, transformation, and budget of nitrogen in the vadose zone-groundwater system, Water Res., 165, 114977, https://doi.org/10.1016/j.watres.2019.114977, 2019.
Xin, J., Wang, Y., Shen, Z., Liu, Y., Wang, H., and Zheng, X.: Critical review of measures and decision support tools for groundwater nitrate management: A surface-to-groundwater profile perspective, J. Hydrol., 598, 126386, https://doi.org/10.1016/j.jhydrol.2021.126386, 2021.
Yang, L., Han, J., Xue, J., Zeng, L., Shi, J., Wu, L., and Jiang, Y.: Nitrate source apportionment in a subtropical watershed using Bayesian model, Sci. Total Environ., 463, 340–347, https://doi.org/10.1016/j.scitotenv.2013.06.021, 2013.
Yu, L., Zheng, T., Zheng, X., Hao, Y., and Yuan, R.: Nitrate source apportionment in groundwater using Bayesian isotope mixing model based on nitrogen isotope fractionation, Sci. Total Environ., 718, 137242, https://doi.org/10.1016/j.scitotenv.2020.137242, 2020.
Yu, L., Zheng, T., Yuan, R., and Zheng, X.: APCS-MLR model: a convenient and fast method for quantitative identification of nitrate pollution sources in groundwater, J. Environ. Manage., 314, 115101, https://doi.org/10.1016/j.jenvman.2022.115101, 2022.
Zhang, T., Lei, Q., Liu, H., Ding, K., Luo, J., Qiu, W., Ma, Y., Xu, Q., Zhao, Y., and Liu, X.: Vertical migration of multi-source nitrates driven by multiple water inputs in groundwater base on combined nitrogen-oxygen and hydrogen-oxygen isotopes, J. Hazard. Mater., 141181, https://doi.org/10.1016/j.jhazmat.2026.141181, 2026.
Short summary
The accurate identification of NO3--N pollution sources are pivotal to the assessment of groundwater pollution risks. However, current studies on NO3--N source apportionment simplifies complex multi-layer aquifer systems into single-layer models without accounting for the impact of occurrence conditions. In this study, we quantitatively identify distinct NO3--N pollution sources in unconfined and confined groundwater, highlighting the critical role of occurrence conditions for management.
The accurate identification of NO3--N pollution sources are pivotal to the assessment of...
