Innovative Approaches for Monitoring Water Quality and Environmental Health

Dear Colleagues,

Researching innovative approaches to monitoring water quality and environmental health is crucial given the current challenges terrestrial water ecosystems face. Rivers such as the Ganges in India and the Yangtze in China are heavily polluted due to industrial discharge, agricultural runoff, and untreated sewage, and this pollution degrades water quality and negatively impacts aquatic life and the surrounding environments. Similarly, lakes like Lake Victoria in Africa and Lake Erie in North America are experiencing eutrophication due to excess nutrients from agricultural runoff and wastewater, which leads to harmful algal blooms that deplete oxygen in the water and damage aquatic life and ecosystem health. Stormwater runoff, pollutants, and habitat modification impact wetlands and urban streams and innovative approaches need to provide timely, accurate, and cost-effective monitoring data to plan, manage, and assess alternative control measures.

Innovations in water quality and environmental health monitoring include:

• Remote sensing technologies, including hyperspectral and multispectral satellite imagery, which are used to detect and monitor pollution levels over large areas. Remote sensing through synthetic aperture radar (SAR) technology also provides detailed information on wetland extent, water flow, and vegetation health, supporting conservation and restoration efforts and helping to maintain the environmental functions of wetlands. Thermal infrared sensors further complement these methods by assessing water temperature variations, which can indicate thermal pollution and other environmental changes. Light detection and ranging (LiDAR ) technology provides high-resolution elevation maps and helps assess riverbank erosion and contaminant dispersion. Additionally, unmanned aerial vehicles (UAVs) equipped with remote sensing devices enable high-resolution, real-time monitoring of specific sites, facilitating targeted investigations and timely interventions.
• Smart buoy systems equipped with sensors that can measure water temperature, nutrient levels, and algal concentrations in real-time.
• Integrated IoT sensors and machine learning algorithms to monitor water levels, quality, and ecosystem health. Sensors can also monitor water quality parameters such as pH, dissolved oxygen, and pollutant levels.
• Machine learning integration: applying machine learning algorithms to enhance the analysis of remote sensing data and improve water quality and ecosystem health predictions.

These are examples of innovative approaches, but researchers may propose other approaches. By enhancing our ability to detect, quantify, and respond to water quality and environmental health issues, we can better protect and sustain the health of our terrestrial water ecosystems.

Dr. Mohamed Hamouda
Dr. Mohammad Reza Nikoo
Dr. Bassem Mokhtar
Dr. Gilbert Hinge
Guest Editors

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• water quality sensors
• field monitoring of emerging contaminants
• reservoir, groundwater, and river water quality monitoring
• remote sensing of water quality
• hybrid approaches for better accuracy
• environmental water monitoring
• advanced machine learning, deep learning, and federated learning models for environmental monitoring
• physics-informed machine learning and deep learning models for water quality modeling
• unmanned aerial vehicles (UAVs) for environmental monitoring
• edge and edge-of-things computing architectures for water quality monitoring-related data analysis and prompt actions