| Water demand modelling plays a key role in urban water resources planning and management. Although climatic variations cause significant changes in water use, their effect on urban water demand is not quantified explicitly by most existing water demand models.; The relationship between monthly time series urban water demand and climatic factors such as temperature, rainfall, potential evapotranspiration, effective rainfall, and number of rainy days for an arid/semi-arid region is analyzed. Models for estimating changes in residential and commercial/industrial water demands based on climatic change are presented.; Conclusions include potential evapotranspiration as a better indicator of the residential water demand than temperature, which has often been used as the principal climatic factor. Also use of effective rainfall does not indicate better results than total seasonal rainfall, which is typically used. For commercial and industrial water demand, temperature was the best climatic indicator found in this study.; Monthly disaggregation models and non-parametric probability distributions for maximum temperature, minimum temperature and precipitation for Salt Lake County are developed.; Models developed in this research are used to estimate the influence of global warming on the magnitude and temporal pattern of urban water demand. |
