Adaptive urban drinking water supply model using the effect of node elevation and head loss formula: A case study

Area of Science:

• Hydraulic Engineering
• Urban Water Management
• Computational Fluid Dynamics

Background:

• Increasing urbanization and population growth drive demand for effective water supply network (WSN) management.
• Software modeling aids in evaluating WSNs for pressure control, leakage analysis, and demand determination.
• Large, complex WSNs pose significant management challenges, as seen with the Metropolitan Waterworks Authority (MWA) in Thailand.

Purpose of the Study:

• To enhance the accuracy of WSN modeling for demand and pressure analysis.
• To address limitations in existing EPANET models, particularly regarding elevation data and head loss calculations.
• To improve water supply management strategies for densely populated urban areas.

Main Methods:

• Developed an EPANET-based WSN model incorporating node elevation data derived from road surface maps.
• Compared the performance of the Hazen-William head loss model with the Darcy-Weisbach model.
• Analyzed model accuracy improvements based on the inclusion of elevation data and the application of different head loss models.

Main Results:

• The model incorporating node elevation data achieved a 3.95% improvement in accuracy over the existing model.
• The Darcy-Weisbach head loss model demonstrated an 8.65% greater accuracy compared to the Hazen-William model.
• The combined improvements indicate a significant potential for more precise WSN management.

Conclusions:

• Node elevation data is a critical parameter for accurate WSN pressure and demand modeling.
• The Darcy-Weisbach model offers superior accuracy for head loss calculations in WSNs across various flow regimes.
• Optimized WSN models integrating elevation and advanced head loss calculations can lead to more efficient urban water supply management.