Using complex network analysis for water quality assessment in large water distribution systems

Area of Science:

• Environmental Engineering
• Network Science
• Water Resource Management

Background:

• Water quality assessment in water distribution systems (WDS) is crucial for public health.
• High computational demands of traditional models limit their application in large WDS and complex simulations.
• Existing simplifications or surrogate models may neglect critical aspects of water quality dynamics.

Purpose of the Study:

• To develop a computationally efficient approach for water quality assessment in WDS.
• To address the limitations of current methods in handling large-scale networks and recurrent simulations.
• To improve the accuracy and speed of water quality analysis for design and optimization tasks.

Main Methods:

• Development of a novel complex network analysis-based approach.
• Comprehensive testing and validation against state-of-the-art water quality models.
• Application in a design study to identify water quality threshold exceedances.

Main Results:

• Achieved median R² values of 0.95 compared to state-of-the-art nodal water qualities.
• Demonstrated a computational efficiency improvement by a factor of 4.2e-06.
• Correct identification rate of 96%–100% for design solutions exceeding water quality thresholds.

Conclusions:

• The proposed complex network analysis model significantly enhances computational efficiency for water quality assessment in large WDS.
• The method provides accurate results, enabling better decision-making in WDS design and management.
• This approach facilitates more extensive analyses like sensitivity and uncertainty assessments.