A long-term forecast of water demand for a desalinated dependent city: case of Riyadh City in Saudi Arabia

Abstract

The forecast of long-term water demand is important for the planning of future requirements for water supply, distribution, and wastewater systems. The forecast is particularly important for arid countries such as Saudi Arabia which rely on costly desalination plants to satisfy the growing water demand. This study develops a model for forecasting water demand for Riyadh city, the capital of the country. The development of a sound forecast model is complicated by the uncertainties associated with key factors, such as the population growth and the economic activity, which is largely dependent on fluctuating oil prices. The forecast is also made difficult by the inefficient management of unaccounted-for-water (UFW). All these factors limit the usefulness of any deterministic forecast model. This paper develops a probabilistic forecast model that incorporates explicitly the uncertainties associated with population growth, household size, household income as well as conservation measures, and UFW management. The methodology makes use of historic time series records of water consumption to forecast the future demand, and applies the Monte Carlo sampling to describe the associated uncertainties. Results show that future water demand in the city is governed equally by socioeconomic factors and weather conditions. The study also illustrates the importance of conservation measures and the need for reduction of UFW.

Keywords:

• Water demand forecast
• Uncertainties
• Probabilistic model
• Monte Carlo simulations
• Saudi Arabia

Acknowledgment

This work was made possible by a generous grant from the National Plan for Science and Technology (Project # 08-WAT229-02).