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Improvement of Rainwater Harvesting Analysis Through an Hourly Timestep Model in Comparison with a Daily Timestep Model

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  • Monzur Alam Imteaz

    (Swinburne University of Technology)

  • Vassiliki Boulomytis

    (Federal Institute of Science)

Abstract

For the analysis of rainwater tank outcomes, some researchers used monthly water balance model, which ignores an important factor such as overflow from the tank. Recently, to improve the accuracy of such analysis facilitated by the availability of daily rainfall data, many researchers started using daily timestep models. In the daily timestep models, the daily rainwater demand is deducted from the available storage, once in a day and there are debates on whether to apply that deduction at the beginning of the day or at the end of the day. Moreover, there is significant diurnal variation of water demand, which can not be accounted for in a daily timestep model. To overcome this, current study investigates an hourly timestep model considering hourly rainfall data and hourly variable rainwater demands. Hourly rainfall data was collected from the Australian Bureau of Meteorology for a raingauge station located in Melbourne. An earlier developed daily water balance model was converted to hourly scale incorporating hourly variable rainwater demands. Model simulated results for three distinct years (dry, average and wet) were compared with the results using a daily timestep model with the same data. Variations of water savings and overflow amounts are presented under four combinations of roof area and daily rainwater demand with tank sizes varying from 2500 L to 20,000 L. It is found that in all the selected years, the daily timestep model underestimated the annual water savings compared to the hourly timestep model and the highest difference was estimated to be 13,750 L for a smaller tank size connected with a bigger roof having higher rainwater demand.

Suggested Citation

  • Monzur Alam Imteaz & Vassiliki Boulomytis, 2022. "Improvement of Rainwater Harvesting Analysis Through an Hourly Timestep Model in Comparison with a Daily Timestep Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(8), pages 2611-2622, June.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:8:d:10.1007_s11269-022-03162-9
    DOI: 10.1007/s11269-022-03162-9
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    References listed on IDEAS

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    1. Chidozie Charles Nnaji & Clinton Aigbavboa, 2020. "A Scenario-Driven Assessment of the Economic Feasibility of Rainwater Harvesting Using Optimized Storage," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(1), pages 393-408, January.
    2. Chidozie Charles Nnaji & Clinton Aigbavboa, 2020. "Correction to: A Scenario-Driven Assessment of the Economic Feasibility of Rainwater Harvesting Using Optimized Storage," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 885-886, January.
    3. Karim, Md. Rezaul & Bashar, Mohammad Zobair Ibne & Imteaz, Monzur Alam, 2015. "Reliability and economic analysis of urban rainwater harvesting in a megacity in Bangladesh," Resources, Conservation & Recycling, Elsevier, vol. 104(PA), pages 61-67.
    4. Olanike Aladenola & Omotayo Adeboye, 2010. "Assessing the Potential for Rainwater Harvesting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(10), pages 2129-2137, August.
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    1. Monzur A. Imteaz & Hassaan Ahmad & Iqbal Hossain, 2023. "Pioneer Use of Pseudo Sub-Daily Timestep Model for Rainwater Harvesting Analysis: Acceptance over Hourly Model and Exploring Accuracy of Different Operating Algorithms," Sustainability, MDPI, vol. 15(5), pages 1-13, February.

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