Sustainable Research on Water Quality Monitoring and Nutrient Pollution Control
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Quality and Contamination".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 885
Special Issue Editors
Interests: water pollution; hydrodynamic modeling; water quality modeling
Special Issues, Collections and Topics in MDPI journals
Interests: water management; hydrology; urban water; coastal flooding
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Excessive nutrient pollution from agricultural runoff, wastewater, and industrial discharges leads to eutrophication, harmful algal blooms, and hypoxia, threatening freshwater and coastal ecosystems. These issues are further exacerbated by the complex and intensifying impacts of anthropogenic activities and climate change. This Special Issue focuses on sustainable approaches for monitoring and mitigating water pollution.
Advanced technologies like remote sensing, IoT sensor networks, environmental DNA (eDNA), and digital twins offer eco-friendly, real-time monitoring and predictive modeling of water quality. These innovations help assess nutrient dynamics, predict algal blooms, and manage hypoxia, promoting sustainable water management and ecosystem health. Machine learning and AI models, along with biogeochemical models, provide valuable insights for developing early warning systems and nature-based solutions. These tools support adaptive, policy-driven water management strategies aimed at long-term sustainability and ecosystem restoration.
The scope of this research topic includes, but is not limited to, the following (all experimental, observational, investigative, and modeling research are welcomed):
- Sustainable management of eutrophication and nutrient dynamics;
- Monitoring and forecasting of algal blooms;
- Hypoxia formation, early detection, and mitigation strategies;
- Applications of remote sensing, IoT, eDNA, etc., in sustainable water quality monitoring;
- Machine learning, AI, and digital twin applications for sustainable water systems;
- Coupled physical–biogeochemical modeling to support restoration and policy;
- Nature-based solutions and ecosystem-based management strategies.
We look forward to receiving your contributions.
Dr. Yang Song
Dr. Yi Hong
Dr. Chunqi Shen
Guest Editors
Manuscript Submission Information
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Keywords
- sustainable water management
- eutrophication
- harmful algal blooms
- hypoxia
- environmental DNA
- digital twin
- IoT and remote sensing
- machine learning and AI
- biogeochemical modeling
- ecosystem restoration
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