An Approach to Demand Pattern Estimation: Monte Carlo Simulation and Fractal Analysis.

Area of Science:

• Environmental Engineering
• Urban Water Management
• Hydrology

Background:

• Urban water supply systems significantly impact daily life.
• Water demand patterns are influenced by societal factors like working hours and living standards.
• Accurate demand forecasting is essential for water supply agencies to ensure reliability.

Purpose of the Study:

• To estimate short-term (hourly and daily) water demand for urban populations.
• To derive a time series distribution of water consumption for various household activities.
• To provide a basis for designing water infrastructure and assessing system performance.

Main Methods:

• Utilized the Bureau of Indian Standards (BIS) standard of 135 lpcd (liters per capita per day).
• Incorporated socioeconomic survey data to inform water consumption patterns.
• Employed Monte Carlo simulation (MCS) to generate random distributions of water consumption.

Main Results:

• Hourly water consumption exhibited persistent behavior, indicated by Hurst coefficients between 0.592 and 0.837.
• The estimated demand pattern showed a peak flow factor of 5.
• Developed a time series distribution of water consumption for different activities.

Conclusions:

• The derived hourly water demand patterns are valuable for designing service reservoirs and optimizing pump scheduling.
• The findings are important for performance assessment studies of water distribution systems (WDS).
• Accurate demand pattern analysis enhances the efficiency and reliability of urban water supply.