Ph.D, Tongji University, China
Qing Wei, a dedicated researcher from China, specializes in watershed eco-hydrology and environmental flow studies. Currently, a doctoral candidate at Tongji University, Qing’s work focuses on the interactions between hydrological processes and ecological systems. By developing mathematical models and tools, Qing aims to support sustainable water resource management, ensuring the health of aquatic ecosystems while meeting human demands.
Profile
Orcid
Education 🎓
Qing Wei has a strong academic background in environmental science and engineering. Qing is pursuing a Doctoral Degree at Tongji University (2020-2024). Prior to this, Qing earned a Master’s Degree from Hohai University (2017-2020), and a Bachelor’s Degree from Chang’an University (2013-2017), specializing in environmental science and hydrology.
Experience 💼
Qing has accumulated valuable experience in both academia and research. Recognized as an outstanding graduate student multiple times at Hohai University, Qing has contributed to significant projects like the National Natural Science Foundation of China and the Jiangsu Provincial Water Science and Technology Project. These experiences have honed Qing’s expertise in eco-hydrological research and water resources management.
Research Interests 🔬
Qing’s research interests are centered on urban sewerage systems, machine learning applications in hydrology, mathematical modeling of pipe networks, ecological water protection, and comprehensive water resources management. Qing’s work aims to develop innovative solutions for sustainable water use and environmental protection.
Awards 🏆
Qing Wei has been honored with numerous awards, including the 2020 and 2019 Outstanding Graduate Student of the University at Hohai University, and the First Prize in the 15th China Postgraduate Mathematical Modeling Competition. These accolades reflect Qing’s commitment to excellence in research and academia.
Publications Top Notes📚
“Analysis of driving forces on ecohydrological regime and environmental flow changes in Hongze Lake, China”
Ecological Informatics (2024)
DOI: 10.1016/j.ecoinf.2023.102423
Cited by several subsequent studies exploring ecohydrological changes.
“A hybrid deep learning approach to improve real-time effluent quality prediction in wastewater treatment plant”
Water Research (2024)
DOI: 10.1016/j.watres.2023.121092
Cited for advancing real-time monitoring techniques in wastewater treatment.
“Analysis on water use efficiency of Populus euphratica forest ecosystem in arid area”
Theoretical and Applied Climatology (2021)
DOI: 10.1007/s00704-021-03636-7
Noted for its insights into water use efficiency in arid ecosystems.
“Spatial and temporal evolution of water structure and spatial matching analysis of water resources in Manas River Basin”
Water Resources Protection (2021)
This work contributes to understanding water resource distribution in river basins.
“Cumulative ecohydrological response to hydrological processes in arid basins”
Ecological Indicators (2020)
DOI: 10.1016/j.ecolind.2019.106005
Influential in studies of hydrological impacts on ecological systems.