Uncertainty quantification of pressure-driven analysis for water distribution network modeling

Ho Min Lee, Do Guen Yoo, Doosun Kang, Hwandon Jun, Joong Hoon Kim

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


The hydraulic analysis of water distribution networks (WDNs) is divided into two approaches: namely, a demand-driven analysis (DDA) and a pressure-driven analysis (PDA). In the DDA, the basic assumption is that the nodal demand is fully supplied irrespective of the nodal pressure, which is mainly suitable for normal operating conditions. However, in abnormal conditions, such as pipe failures or unexpected increase in demand, the DDA approach may cause unrealistic results, such as negative pressure. To address the shortcomings of DDA, PDA has been considered in a number of studies. For PDA, however, the head-outflow relation (HOR) should be given, which is known to contain a high degree of uncertainty. Here, the DDA-based simulator, EPANET2 was modified to develop a PDA model simulating pressure deficient conditions and a Monte Carlo simulation (MCS) was performed to consider the quantitative uncertainty in HOR. The developed PDA model was applied to two networks (a well-known benchmark system and a real-life WDN) and the results showed that the proposed model is superior to other reported models when dealing with negative pressure under abnormal conditions. In addition, the MCS-based sensitivity analysis presents the ranges of pressure and available discharge, quantifying service reliability of water networks.

Original languageEnglish
Pages (from-to)599-610
Number of pages12
JournalWater Science and Technology: Water Supply
Issue number3
Publication statusPublished - 2016 Jun

Bibliographical note

Publisher Copyright:
© IWA Publishing 2016.


  • Hydraulic analysis
  • Pressure-driven analysis
  • Uncertainty analysis
  • Water distribution network

ASJC Scopus subject areas

  • Water Science and Technology


Dive into the research topics of 'Uncertainty quantification of pressure-driven analysis for water distribution network modeling'. Together they form a unique fingerprint.

Cite this