Technical Papers
Jan 8, 2016

Estimating Water Supply Infrastructure Cost Using Regression Techniques

Publication: Journal of Water Resources Planning and Management
Volume 142, Issue 4

Abstract

The current paper aims at the establishment and validation of reference cost functions for different types of assets of water supply systems based on known hydraulic (e.g., flow, pump head, pump power) and physical (e.g., volume, material, nominal pressure, diameter) characteristics of the assets. A five-step methodology was followed: (1) database construction and asset characterization; (2) present cost value calculation; (3) key parameters and cost function establishment; (4) model specification; and (5) model testing and validation. A sample of cost and infrastructure data from several Portuguese water utilities has been used. Multiple linear regression analysis has been carried out to obtain cost functions. Cost modeling also includes the estimation of prediction bands to describe cost uncertainty. Developed cost functions have been tested and validated using 10% of randomly selected data.

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Acknowledgments

The authors would like to thank to the AdP group, especially Nuno Lopes and Luis Mamouros, that have provided data and supported this research project. They would also like to thank Susana Lopes and David Figueiredo for the help in data treatment. A special thanks goes to the Ministry of Environment, Territory Planning and Energy, which has partially funded this research through Programa Operacional Sustentabilidade e Eficiência no Uso de Recursos (POSEUR) funds.

References

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Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 142Issue 4April 2016

History

Received: Apr 22, 2015
Accepted: Oct 21, 2015
Published online: Jan 8, 2016
Published in print: Apr 1, 2016
Discussion open until: Jun 8, 2016

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Authors

Affiliations

Valentina Marchionni [email protected]
Research Fellow, Civil Engineering Research and Innovation for Sustainability, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisbon, Portugal (corresponding author). E-mail: [email protected]; [email protected]
Marta Cabral [email protected]
Research Fellow, Civil Engineering Research and Innovation for Sustainability, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisbon, Portugal. E-mail: [email protected]
Conceição Amado [email protected]
Assistant Professor, Center for Computational and Stochastic Mathematics, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisbon, Portugal. E-mail: [email protected]
Dídia Covas [email protected]
Associate Professor, Civil Engineering Research and Innovation for Sustainability, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisbon, Portugal. E-mail: [email protected]

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