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Water Consumption Variability Based on Cumulative Data From Non-simultaneous and Long-term Measurements

Author

Listed:
  • Jacek Wawrzosek

    (University of Life Sciences in Lublin)

  • Syzmon Ignaciuk

    (University of Life Sciences in Lublin)

  • Justyna Stańczyk

    (Wroclaw University of Environmental and Life Sciences)

  • Joanna Kajewska-Szkudlarek

    (Wroclaw University of Environmental and Life Sciences)

Abstract

Devices for water consumption measurement provide data from periodical readings in a non-simultaneous and cumulative manner. This may result in inaccuracies within the process of inference about the short-term habitual patterns of water supply network users. Maintaining systems at the interface between periodic and continuous processes requires the continuous improvement of research methodology. To obtain reliable results regarding the variability of water consumption, the first step should be to estimate it for each observation day by periodic averaging and a possible water balancing approach, but the analysis of the value of estimators obtained in this way usually does not allow for studying autocorrelation. However, other methods indicate the existence of multiplicative parameters characterizing short- and long-term variations in water demand. The purpose of this study is to create a new and deterministic method for tackling the problem associated with a lack of short-term detailed data with fuzzy time series using a multiplicative model for water consumption. Satisfactory results have been obtained, demonstrating that the dispersed data, received in a cumulative manner for random periods of measurement, can be analyzed by the methodology of proposed statistical inference. The observed variability in water consumption may be used in the planning and modernization of water supply systems, development of water demand patterns, hydraulic models, and in the creation of forecasting models of water consumption.

Suggested Citation

  • Jacek Wawrzosek & Syzmon Ignaciuk & Justyna Stańczyk & Joanna Kajewska-Szkudlarek, 2021. "Water Consumption Variability Based on Cumulative Data From Non-simultaneous and Long-term Measurements," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(9), pages 2799-2812, July.
    • Handle: RePEc:spr:waterr:v:35:y:2021:i:9:d:10.1007_s11269-021-02868-6
    DOI: 10.1007/s11269-021-02868-6
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    References listed on IDEAS

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    1. Haidong Huang & Zhixiong Zhang & Fengxuan Song, 2021. "An Ensemble-Learning-Based Method for Short-Term Water Demand Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(6), pages 1757-1773, April.
    2. Siddappa Pallavi & Shivamurthy Ravindra Yashas & Kotermane Mallikarjunappa Anilkumar & Behzad Shahmoradi & Harikaranahalli Puttaiah Shivaraju, 2021. "Comprehensive Understanding of Urban Water Supply Management: Towards Sustainable Water-socio-economic-health-environment Nexus," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(1), pages 315-336, January.
    3. Diana Fiorillo & Zoran Kapelan & Maria Xenochristou & Francesco De Paola & Maurizio Giugni, 2021. "Assessing the Impact of Climate Change on Future Water Demand using Weather Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(5), pages 1449-1462, March.
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