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Modeling of Drinking Water Distribution Networks Using Stochastic Demand

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Abstract

Residential water demand is one of the most difficult parameters to determine when modeling drinking water distribution networks. It has been proven to be a stochastic process that can be characterized as a series of rectangular pulses with a set intensity, duration and frequency. These parameters can be determined using stochastic models such as the Neyman-Scott Rectangular Pulse (NSRP) model. The NSRP model is based on the solution of a non-linear optimization problem. This solution involves theoretical moments that represent the synthetic demand series (equiprobable) and the observed moments (field measurements) that statistically establish the measured demand series. The NSRP model has been applied for residential demand, and the results have been published. However, this model has not been validated for a real distribution network or compared with traditional methods. The present study compared the results of synthetic stochastic demand series, which were calculated using the NSRP model, applied to the determination of pressures, flow rates and leaks; to the results obtained using traditional simulation methods, which use the curve of hourly variation in demand, and to actual pressure and flow rate measurements. The Humaya sector of Culiacan, Sinaloa, Mexico, was used as the study area.

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Authors and Affiliations

  1. Mexican Institute of Water Technology, Paseo Cuauhnahuac 8532, Col. Progreso, Jiutepec, Morelos, CP 62550, Mexico

    Victor H. Alcocer-Yamanaka & Velitchko G. Tzatchkov

  2. Comision Nacional del Agua, Insurgentes Sur 2416, Col. Copilco El Bajo, Delegacion Coyoacan, Mexico, DF, CP 04340, Mexico

    Felipe I. Arreguin-Cortes

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  1. Victor H. Alcocer-Yamanaka
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  2. Velitchko G. Tzatchkov
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  3. Felipe I. Arreguin-Cortes
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Correspondence to Velitchko G. Tzatchkov.

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Alcocer-Yamanaka, V.H., Tzatchkov, V.G. & Arreguin-Cortes, F.I. Modeling of Drinking Water Distribution Networks Using Stochastic Demand. Water Resour Manage 26, 1779–1792 (2012). https://doi.org/10.1007/s11269-012-9979-2

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  • DOI: https://doi.org/10.1007/s11269-012-9979-2

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