Wetland Water Quality Monitoring and Assessment
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Quality and Contamination".
Deadline for manuscript submissions: 25 November 2025 | Viewed by 134
Special Issue Editors
Interests: water quality; monitoring and assessment; aquatic ecosystems; prediction model; sustainability
Interests: nitrogen; phosphorus; sediment; ice-covered; model; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The water quality of wetland ecosystems directly impacts biodiversity, ecological service functions, and sustainable human development. To advance innovations in wetland water quality monitoring technologies, optimize assessment methodologies, and promote science-based decision-making and practices for global wetland conservation, this Special Issue focuses on the theme of “Wetland Water Quality Monitoring and Assessment”.
We cordially invite scholars, research institutions, and practitioners worldwide to submit contributions, collectively advancing the frontier of knowledge in this field. Our topics of interest include, but are not limited to, the following: (1) the development and application of high-precision water quality sensors, remote sensing technologies, and in situ monitoring equipment; (2) the mechanisms of nitrogen, phosphorus, and other pollutant migration/transformations, and their ecological impact assessments; (3) dynamic modeling and prediction of hydro–water quality–biological synergy in wetlands; (4) applications of artificial intelligence and machine learning in wetland water quality data analysis; (5) health evaluation of wetland ecosystems based on water quality indicators; (6) efficacy verification and long-term management strategies for water quality improvement in wetland restoration projects. This Special Issue aims to bridge cutting-edge research with actionable solutions, fostering global collaboration for healthier wetland ecosystems.
Dr. Qi Huang
Dr. Tianxiang Wang
Guest Editors
Manuscript Submission Information
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Keywords
- water quality
- monitoring and assessment
- aquatic ecosystems
- model
- sustainability
- machine learning
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