Please use this identifier to cite or link to this item:
Title: A review of demand models for water systems in buildings including a Bayesian approach
Authors: Wong, LT 
Mui, KW 
Keywords: Bayesian estimates
Deterministic models
Probabilistic models
Probable maximum simultaneous demand
Water demand time series
Water systems
Issue Date: 2018
Publisher: Molecular Diversity Preservation International (MDPI)
Source: Water, 2018, v. 10, no. 8, 1078, p. 1-25 How to cite?
Journal: Water 
Abstract: Instantaneous flow rate estimation is essential for sizing pipes and other components of water systems in buildings. Although various demand models have been developed in line with design and technology trends, most water supply system designs are routinely and substantially over-sized to keep failure risks to a minimum. Three major types of demand models from the literature are reviewed in this paper: (1) deterministic approach; (2) probabilistic approach; and (3) demand time-series approach. As findings show some widely used model estimates are much larger than the field measurements, this paper proposes a Bayesian approach to bridge the gap between model-based and field-measured values for the probable maximum simultaneous water demand. The proposed approach is flexible to adopt estimates as its prior values from a wide range of existing water demand models for determining the Bayesian coefficients for reference models, codes, and design standards with relevant measurement data. The approach provides a useful method not only for evaluating the corresponding demand values from various design references, but also for responding to the call for sustainable building design.
ISSN: 2073-4441
DOI: 10.3390/w10081078
Rights: © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
The following publication Wong, L. -., & Mui, K. -. (2018). A review of demand models for water systems in buildings including a Bayesian approach. Water (Switzerland), 10(8), 1078, 1-25 is available at
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Wong_Models_Water_Systems_Bayesian.pdf1.11 MBAdobe PDFView/Open
View full-text via PolyU eLinks SFX Query
Show full item record
PIRA download icon_1.1View/Download Contents

Page view(s)

Citations as of Jan 15, 2019


Citations as of Jan 15, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.