Leakage Rate Model of Urban Water Supply Networks Using Principal Component Regression Analysis
- 108 Downloads
To analyze the factors affecting the leakage rate of water distribution system, we built a macroscopic “leakage rate–leakage factors” (LRLF) model. In this model, we consider the pipe attributes (quality, diameter, age), maintenance cost, valve replacement cost, and annual average pressure. Based on variable selection and principal component analysis results, we extracted three main principle components—the pipe attribute principal component (PAPC), operation management principal component, and water pressure principal component. Of these, we found PAPC to have the most influence. Using principal component regression, we established an LRLF model with no detectable serial correlations. The adjusted R 2 and RMSE values of the model were 0.717 and 2.067, respectively. This model represents a potentially useful tool for controlling leakage rate from the macroscopic viewpoint.
KeywordsWater distribution system Leakage rate Leakage influencing factor Quantitative model Principal component regression
This study was supported by the Ministry of Science and Technology of China (No. 2014ZX07203-009), the Fundamental Research Funds for the Central Universities, and the Program for New Century Excellent Talents at the University of China.
- 5.Kingdom B, Liemberger R, Marin P (2006) The challenge of reducing non-revenue water in developing countries. How the private sector can help: a look at performance-based service contracting. Water Supply Sanitation Sect Board Discuss Pap Ser 8:11–24Google Scholar
- 6.Lu T, Liu Y, Li J et al (2013) Leakage situation and control solution of China water supply pipeline. J Fudan Univ (Natural Science) 52(6):807–810 (in Chinese) Google Scholar
- 9.Kang J, Zou ZH (2010) Time prediction model for pipeline leakage based on grey relational analysis. In: International Conference on Circuit and Signal Processing & 2010 Second IITA International Joint Conference on Artificial Intelligence. 2019–2024Google Scholar
- 11.Zhang HW, Niu ZG, Chen CH et al (2001) Study on the prediction model for water supply net leakage. China Water Wastewater 17(6):7–9 (in Chinese) Google Scholar
- 12.Luo HL, Fu WX, Zhang Z (2010) Material and diameter selection of pipe network and its leakage control. Energy Conserv Environ Prot 1:44–46 (in Chinese) Google Scholar
- 15.National Bureau of Statistics of the People’s Republic of China. http://data.stats.gov.cn/search.htm?s=2016%20%E5%A4%A9%E6%B4%A5%20%E4%BA%BA%E5%8F%A3, 2016-04-04 (in Chinese)
- 16.Deng XT (2012) Urban water supply pipe network leakage factor analysis and control. Dissertation, School of Environmental Science and Engineering, Taiyuan University of Technology, Taiyuan, China (in Chinese)Google Scholar
- 17.Burn S, Desilva D, Eiswirth M et al (1999) Pipe leakage: future challenges and solutions. World Highw Routes Du Monde 19(4):80–90Google Scholar
- 19.Germanopoulos G, Jowitt PW (1989) Leakage reduction by excess pressure minimization in a water supply network. Proceedings of the Institution of Civil Engineers. Part 2. Res Theory 87:195–214Google Scholar
- 20.Wu TM (2013) Study on leakage cause and countermeasure of pipe network in Ningbo.http://www.chinacitywater.org/rdzt/guanwanglousun/7070-7.shtml,2013-05-21 (in Chinese)
- 21.Cui H (2007) Determination model for replacement of water pipeline. Eng Sci 9(9):68–71Google Scholar