Spatial variability of source contributions to nitrate in regional groundwater based on the positive matrix factorization and Bayesian model

Hairu Mao; Guangcai Wang; Fu Liao; Zheming Shi; Hongyu Zhang; Xianglong Chen; Zhiyuan Qiao; Bo Li; Yunfei Bai

doi:10.1016/j.jhazmat.2022.130569

Spatial variability of source contributions to nitrate in regional groundwater based on the positive matrix factorization and Bayesian model

J Hazard Mater. 2023 Mar 5:445:130569. doi: 10.1016/j.jhazmat.2022.130569. Epub 2022 Dec 9.

Authors

Hairu Mao¹, Guangcai Wang², Fu Liao¹, Zheming Shi¹, Hongyu Zhang¹, Xianglong Chen¹, Zhiyuan Qiao¹, Bo Li¹, Yunfei Bai¹

Affiliations

¹ State Key Laboratory of Biogeology and Environmental Geology & MOE Key Laboratory of Groundwater Circulation and Environmental Evolution, China University of Geosciences, Beijing 100083, China; School of Water Resources and Environment, China University of Geosciences, Beijing 100083, China.
² State Key Laboratory of Biogeology and Environmental Geology & MOE Key Laboratory of Groundwater Circulation and Environmental Evolution, China University of Geosciences, Beijing 100083, China; School of Water Resources and Environment, China University of Geosciences, Beijing 100083, China. Electronic address: wanggc@pku.edu.cn.

PMID: 37055948
DOI: 10.1016/j.jhazmat.2022.130569

Abstract

Groundwater nitrate (NO₃^-) pollution has attracted widespread attention; however, accurately evaluating the sources of NO₃^- and their contribution patterns in regional groundwater is difficult in areas with multiple sources and complex hydrogeological conditions. In this study, 161 groundwater samples were collected from the Poyang Lake Basin for hydrochemical and dual NO₃^- isotope analyses to explore the sources of NO₃^- and their spatial contribution using the Positive Matrix Factorization (PMF) and Bayesian stable isotope mixing (MixSIAR) models. The results revealed that the enrichment of NO₃^- in groundwater was primarily attributed to sewage/manure (SM), which accounted for more than 50 %. The contributions of nitrogen fertilizer and soil organic nitrogen should also be considered. Groundwater NO₃^- sources showed obvious spatial differences in contributions. Regions with large contributions of SM (>90 %) were located in the southeastern part of the study area and downstream of Nanchang, which are areas with relatively high population density. Nitrogen fertilizer and soil organic nitrogen showed concentrated contributions in paddy soil in the lower reaches of the Gan and Rao Rivers, and these accumulations were mainly driven by the soil type, land use type, and topography. This study provides insight into groundwater NO₃^- contamination on a regional scale.

Keywords: Bayesian mixing model; Groundwater nitrate; Positive matrix factorization; Source apportionment; Spatial variability.