Calibration of water distribution hydraulic models: A comparison between pressure dependent and demand driven analyses

Tabesh, Massoud; Jamasb, M.; Moeini, Ramtin

doi:10.1080/1573062x.2010.548525

Cited by 40 publications

(9 citation statements)

References 36 publications

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“…The PDA has been compared with DDA for a variety of WDN problems such as hydraulic modelling (Nyende-Byakika et al 2012), water quality modelling (Seyoum and Tanyimboh 2013), parameter calibration (Tabesh et al 2011), evaluating reliability indicators (Liserra et al 2014). Some other applications are as below: Bhave (1981) expected the application of pressure-dependent analysis in reliabilitybased analysis and design of water distribution networks.…”

Section: Applications Of Pressure-dependent Analysismentioning

confidence: 99%

History of Pressure-Dependent Analysis of Water Distribution Networks and Its Applications

Gupta¹

2015

World Environmental and Water Resources Congress 2015

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An analysis that considers a relationship between nodal demand and available nodal pressure to determine the outflow at that node is carried out and mostly referred as pressure-dependent analysis (PDA). Further, not only the outflow but some demand itself such as leakage losses and water demand at sprinklers, faucets etc., are also considered dependent on pressure. Several node head-flow relationships (NHFRs) have been suggested along with the methodologies for their solution in the last three decades. Further, efforts have been also made to carry out PDA by using an efficient DDA based hydraulic network solver, EPANET. The PDA has been used in tackling a variety of problems on water distribution systems such as: assessing reliability, reliability-based design, parameter calibration, vulnerability analysis, placement of isolation valves, water quality analysis, flushing of contaminated water, leakage modelling, and multi-objective evolutionary optimization. This paper provides a complete development in PDA along with future research need.

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Section: Applications Of Pressure-dependent Analysismentioning

confidence: 99%

History of Pressure-Dependent Analysis of Water Distribution Networks and Its Applications

Gupta¹

2015

World Environmental and Water Resources Congress 2015

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“…Therefore, another model known as the pressure-driven analysis model was developed and applied to account for this effect. To replace the nodal demand in the general hydraulic equations, a relationship between nodal head and nodal demand is given as [104]:…”

Section: Demand-driven and Pressure-driven Analysis Modelsmentioning

confidence: 99%

Solving Management Problems in Water Distribution Networks: A Survey of Approaches and Mathematical Models

Bello

Abu‐Mahfouz

Hamam

et al. 2019

Water

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Modern water distribution networks (WDNs) are complex and difficult to manage due to increased level of urbanization, varying consumer demands, ageing infrastructure, operational costs, and inadequate water resources. The management problems in such complex networks may be classified into short-term, medium-term, and long-term, depending on the duration at which the problems are solved or considered. To address the management problems associated with WDNs, mathematical models facilitate analysis and improvement of the performance of water infrastructure at minimum operational cost, and have been used by researchers, water utility managers, and operators. This paper presents a detailed review of the management problems and essential mathematical models that are used to address these problems at various phases of WDNs. In addition, it also discusses the main approaches to address these management problems to meet customer demands at the required pressure in terms of adequate water quantity and quality. Key challenges that are associated with the management of WDNs are discussed. Also, new directions for future research studies are suggested to enable water utility managers and researchers to improve the performance of water distribution networks.

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“…Nevertheless, the reliable use of these models must be exposed to a correct and systematic calibration process, generally related with the study of pressures and roughness (Braun et al, 2010;Tabesh et al, 2011). Some models for determining flows can be found in the references consulted (e.g., the method presented by Preis et al (2009)).…”

Section: Introductionmentioning

confidence: 99%

Calibrating a flow model in an irrigation network: Case study in Alicante, Spain

Sánchez

Sánchez‐Romero

Ramos

et al. 2017

Span. j. agric. res.

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The usefulness of models depends on their validation in a calibration process, ensuring that simulated flows and pressure values in any line are really occurring and, therefore, becoming a powerful decision tool for many aspects in the network management (i.e., selection of hydraulic machines in pumped systems, reduction of the installed power in operation, analysis of theoretical energy recovery). A new proposed method to assign consumptions patterns and to determine flows over time in irrigation networks is calibrated in the present research. As novelty, the present paper proposes a robust calibration strategy for flow assignment in lines, based on some key performance indicators (KPIF) coming from traditional hydrological models: Nash-Sutcliffe coefficient (non-dimensional index), root relative square error (error index) and percent bias (tendency index). The proposed strategy for calibration was applied to a real case in Alicante (Spain), with a goodness of fit considered as "very good" in many indicators. KPIF parameters observed present a satisfactory goodness of fit of the series, considering their repeatability. Average Nash-Sutcliffe coefficient value oscillated between 0.30 and 0.63, average percent bias values were below 10% in all the range, and average root relative square error values varied between 0.65 and 0.80.Additional key words: water management; calibration model; Key Performance Indicators.Correspondence should be addressed to P. Amparo López-Jiménez: palopez@upv.es Abbreviations used: E (Nash-Sutcliffe coefficient); KPIF (key performance indicators for goodness of fit); O (observed values); P (simulated values); PBIAS (percent bias); RMSE (root mean square error); RN (random number); RRSE (root relative square error); SCADA (supervisory control and data acquisition); WDN (water distribution network). Funding:The authors received no specific funding for this work.

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Calibration of water distribution hydraulic models: A comparison between pressure dependent and demand driven analyses

Cited by 40 publications

References 36 publications

History of Pressure-Dependent Analysis of Water Distribution Networks and Its Applications

History of Pressure-Dependent Analysis of Water Distribution Networks and Its Applications

Solving Management Problems in Water Distribution Networks: A Survey of Approaches and Mathematical Models

Calibrating a flow model in an irrigation network: Case study in Alicante, Spain

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