Nitrate dynamics in the Dongjiang River watershed: Human impacts in the context of an Anthropocene River

Yaotong Gao; Bingjun Liu; Qian Tan; Kai He; Wei Ouyang; Yaling Yu

doi:10.1016/j.jconhyd.2026.104843

Nitrate dynamics in the Dongjiang River watershed: Human impacts in the context of an Anthropocene River

J Contam Hydrol. 2026 Jan 4:277:104843. doi: 10.1016/j.jconhyd.2026.104843. Online ahead of print.

Authors

Yaotong Gao¹, Bingjun Liu¹, Qian Tan², Kai He³, Wei Ouyang⁴, Yaling Yu¹

Affiliations

¹ School of Civil Engineering, Sun Yat-sen University, Zhuhai 519082, China.
² Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds, Institute of Environmental and Ecological Engineering, Guangdong University of Technology, Guangzhou 510006, China; Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou 510006, China.
³ School of Civil Engineering, Sun Yat-sen University, Zhuhai 519082, China. Electronic address: hekai7@mail.sysu.edu.cn.
⁴ School of Environment, State Key Laboratory of Water Environment Simulation, Beijing Normal University, Beijing 100875, China; Advanced Interdisciplinary Institute of Environment and Ecology, Beijing Normal University, Zhuhai 519087, China. Electronic address: wei@bnu.edu.cn.

PMID: 41547076
DOI: 10.1016/j.jconhyd.2026.104843

Abstract

Rivers in the Anthropocene are increasingly impacted by human activities, with nitrate (NO₃^-) pollution posing a significant threat to water quality and ecosystem health. This study investigates the Dongjiang River watershed as a representative example of such systems impacted by human activities. Using nitrate dual isotopes (δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^-) and a Bayesian mixing model (MixSIAR), we identified the sources and transformation processes of NO₃^- in the downstream Dongjiang River. Our results indicate that manure and sewage (MS) account for the majority of NO₃^- inputs (64.52 %), followed by soil nitrogen (SN) at 18.88 %. The influence of MS is amplified in catchments with higher urbanization, while forested areas show more significant contributions from SN. Seasonal variations in nitrate sources were also observed, with MS dominating during the dry season and SN contributions increasing during the wet season. Nitrification and denitrification were relatively weak during our sampling periods, as indicated by the absence of a characteristic δ¹⁵N-NO₃^- versus δ¹⁸O-NO₃^- slope (∼50 %) and by low extent of denitrification values at most sites; thus, external inputs were likely the primary drivers of NO₃^- dynamics. Furthermore, we link socio-economic factors and water consumption patterns to specific NO₃^- sources, highlighting the role of urbanization, economic development, and agricultural practices in shaping nitrate pollution. These findings provide critical insights for managing water quality and mitigating anthropogenic impacts on the Dongjiang River in the Anthropocene.

Keywords: Anthropocene rivers; Bayesian mixing model; Land use change; Source apportionment; Stable isotopes.