From Source Tracking to Predictive Modeling: The Evolving Research Landscape of Heavy Metal Transport in Watersheds

This study conducts a comprehensive bibliometric analysis of literature from 2000 to 2025, aiming to map the intellectual landscape and evolving trends in research on heavy metal transport within watershed ecosystems. By leveraging the Citespace literature visualization tool, we analyzed publication trends, intellectual bases, and, most importantly, the dynamic shifts in research fronts through keyword co-occurrence and clustering analysis. The findings reveal a clear trajectory from basic geochemical theories to specific applications, characterized by three prominent themes: (1) the evolution of pollution source tracking from single-method tracing to coupled multi-method quantitative modeling; (2) the establishment of a comprehensive risk evaluation chain spanning regional assessments to targeted analyses of sensitive receptors; and (3) the analysis indicates that the current research on heavy metal transport in watershed environments remains somewhat fragmented, with limited cross-comparative synthesis across different metal species and watershed contexts, and uneven progress in applying advanced data-driven and multi-model approaches. Addressing these issues is crucial for enhancing the predictive power of models and formulating effective strategies. This study thus provides a detailed overview of the field’s development while highlighting critical pathways for future research to strengthen the scientific foundation for preventing and controlling heavy metal pollution in watershed ecosystems.

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Publication Details

Journal
Water
Published
2025-12-19
DOI
https://doi.org/10.3390/w18010001
Citations
1
Primary Topic
Heavy metals in environment
Type
article
Field-Weighted Citation Impact
0.50

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article

From Source Tracking to Predictive Modeling: The Evolving Research Landscape of Heavy Metal Transport in Watersheds

Zhongyun Ni, Qian Zhang, Jingxian Qi, Xu Liu et al.
1 citations
Water
Heavy metals in environment
0.50
article

From Source Tracking to Predictive Modeling: The Evolving Research Landscape of Heavy Metal Transport in Watersheds

Zhongyun Ni, Qian Zhang, Jingxian Qi, Xu Liu, Shujun Wang, Huimin Wu, Difu Wu, Anfu Liu
article en
1 citations

Abstract

This study conducts a comprehensive bibliometric analysis of literature from 2000 to 2025, aiming to map the intellectual landscape and evolving trends in research on heavy metal transport within watershed ecosystems. By leveraging the Citespace literature visualization tool, we analyzed publication trends, intellectual bases, and, most importantly, the dynamic shifts in research fronts through keyword co-occurrence and clustering analysis. The findings reveal a clear trajectory from basic geochemical theories to specific applications, characterized by three prominent themes: (1) the evolution of pollution source tracking from single-method tracing to coupled multi-method quantitative modeling; (2) the establishment of a comprehensive risk evaluation chain spanning regional assessments to targeted analyses of sensitive receptors; and (3) the analysis indicates that the current research on heavy metal transport in watershed environments remains somewhat fragmented, with limited cross-comparative synthesis across different metal species and watershed contexts, and uneven progress in applying advanced data-driven and multi-model approaches. Addressing these issues is crucial for enhancing the predictive power of models and formulating effective strategies. This study thus provides a detailed overview of the field’s development while highlighting critical pathways for future research to strengthen the scientific foundation for preventing and controlling heavy metal pollution in watershed ecosystems.

WaterVol. 18(1)
Ministry of Ecology and Environment (CN), Chengdu University of Technology (CN), Chinese Research Academy of Environmental Sciences (CN), Zhengzhou University of Industrial Technology (CN), Xiangtan University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 30%
Heavy metals in environment
0.50
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