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首页> 外文期刊>Journal of Hydroinformatics >A bottom-up approach of stochastic demand allocation in a hydraulic network model: a sensitivity study of model parameters
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A bottom-up approach of stochastic demand allocation in a hydraulic network model: a sensitivity study of model parameters

机译：水力网络模型中随机需求分配的自下而上方法：模型参数的敏感性研究

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摘要

An "all pipes" hydraulic model of a drinking water distribution system was constructed with a bottom-up approach of demand allocation. This means that each individual home is represented by one demand node with its own stochastic water demand pattern. These water demand patterns were constructed with the end-use model SIMDEUM. A sensitivity test with respect to the resulting residence times was performed for several model parameters: time step, spatial aggregation, spatial correlation, demand pattern and number of simulation runs. The bottom-up approach of demand allocation was also compared to the conventional top-down approach, i.e. a single demand multiplier pattern is allocated to all demand nodes with the base demand to account for the average water demand on that node. The models were compared to measured flows and residence times in a small network. The study showed that the bottom-up approach leads to realistic water demand patterns and residence times, without the need for any flow measurements. The stochastic approach of hydraulic modelling, with a 15 minute time step, some spatial aggregation and 10 simulation runs, gives insight into the variability of residence times as an added feature beyond the conventional way of modelling.
机译：使用自下而上的需求分配方法构建了饮用水分配系统的“全管道”液压模型。这意味着每个单独的房屋由一个具有自己的随机用水需求模式的需求节点表示。这些用水模式是通过最终使用模型SIMDEUM构建的。针对几个模型参数执行了关于最终停留时间的敏感性测试：时间步长，空间聚集，空间相关性，需求模式和模拟运行次数。自下而上的需求分配方法也与传统的自上而下的方法进行了比较，即，将单个需求乘数模式分配给所有具有基本需求的节点，以说明该节点上的平均需水量。将模型与在小型网络中测得的流量和停留时间进行比较。研究表明，自下而上的方法可以实现现实的用水需求模式和停留时间，而无需进行任何流量测量。水力建模的随机方法具有15分钟的时间步长，一些空间聚集和10次模拟运行，它提供了对停留时间可变性的洞察力，这是传统建模方法之外的一项附加功能。

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  • 来源
    《Journal of Hydroinformatics》 |2011年第4期|p.714-728|共15页
  • 作者

    E. J. M. Blokker; H. Beverloo; A. J. Vogelaar; J. H. G. Vreeburg; J. C. van Dijk;

  • 作者单位

    KWR Watercycle Research Institute, P.O. BOX 1072, 3430 BB, Nieuwegein, The Netherlands;

    KWR Watercycle Research Institute, P.O. BOX 1072, 3430 BB, Nieuwegein, The Netherlands;

    KWR Watercycle Research Institute, P.O. BOX 1072, 3430 BB, Nieuwegein, The Netherlands;

    KWR Watercycle Research Institute, P.O. BOX 1072, 3430 BB, Nieuwegein, The Netherlands Delft University of Technology, Department of Civil Engineering and Geosciences, P.O. BOX 5048, 2600 GA Delft, The Netherlands;

    Delft University of Technology, Department of Civil Engineering and Geosciences, P.O. BOX 5048, 2600 GA Delft, The Netherlands;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    demand allocation; stochastic modelling; water quality modelling;

    机译：需求分配;随机建模;水质模拟;

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