title: Prediction of urban water demand on the basis of Engel's coefficient and Hoffmann index: case studies in Beijing and Jinan, China.
abstract: Domestic and industrial water uses are the most important segment of urban water consumption. Traditional urban water demand models are usually based on water consumption quotas or statistical relationships, which usually overestimate urban water demands. The efficiency of domestic and industrial water uses is associated with living standards and levels of industrialization. The correlation coefficient between per capita water consumption and Engel's Coefficient in Beijing and Jinan is 0.62 and 0.53, respectively. These values are much smaller than the correlation between added industrial value and the Hoffmann Index in Beijing (0.95) and Jinan (0.90). Demand models for urban water consumption, including a domestic water demand model based on Engel's Coefficient and an industrial water demand model based on the Hoffmann Index, were developed in this study to predict urban water demand in Beijing and Jinan for 2020. The results show that the models can effectively capture the trends of urban water demand. Urban water consumption in these two cities from 1995 to 2007 was used to calibrate the models. The coefficients of determination for residential and industrial water uses were 0.93 and 0.68 in Beijing, and 0.79 and 0.64 in Jinan. Social, economic and climate scenarios for Beijing and Jinan in 2020 were generated according to the Urban Master Plans for these two cities, and they formed the basis for predictions of water consumption in 2020. The results show that total water consumption will increase by 67.6% in Jinan and 33.0% in Beijing when compared with consumption from 2007.
authors.affiliation: College of Water Sciences, Beijing Normal University, Beijing, China. zhangzhiguo910@gmail.com
authors.forename: Zhang
authors.initials: Z
authors.lastname: Zhi-Guo
authors.forename: Shao
authors.initials: S
authors.lastname: Yi-sheng
authors.forename: Xu
authors.initials: X
authors.lastname: Zong-xue
mesh_terms: D002681:China; D002947:Cities; D005544:Forecasting; D014881:Water Supply / Q000706:statistics & numerical data*