Shaoting Wang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Shaoting Wang has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Anfu Liu
Technical Centre For Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China
1 shared publication - Dingyu Wu
Henan Recycling Technology Industrial Group, Zhengzhou 450003, China
1 shared publication - Huimin Wu
School of Environmental and Resources, Xiangtan University, Xiangtan 411105, China
1 shared publication - Jingxian Qi
Technical Centre For Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China
1 shared publication - Qingpo Zhang
School of Environmental and Resources, Xiangtan University, Xiangtan 411105, China
1 shared publication - Xu Liu
Technical Centre For Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China
1 shared publication
Latest Publications
- Open Access
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.
Open AccessFrom 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.