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Water Irrigation Decision Support System for Practical Weir Adjustment Using Artificial Intelligence and Machine Learning Techniques

Author

Listed:
  • Benya Suntaranont

    (Department of Civil Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Somrawee Aramkul

    (Department of Computer, Faculty of Science and Technology, Chiang Mai Rajabhat University, Chiang Mai 50200, Thailand)

  • Manop Kaewmoracharoen

    (Department of Civil Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Paskorn Champrasert

    (CENDiM: Center of Excellence in Natural Disaster Management, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand)

Abstract

This research proposes a decision support system for weir sluice gate level adjusting. The proposed system, named AWARD (Appropriate Weir Adjustment with Water Requirement Deliberation), is composed of three modules, which are (1) water level prediction, (2) sluice gates setting period estimation, and (3) sluice gates level adjusting calculation. The AWARD system applies an artificial neural network technique for water level prediction, a fuzzy logic control algorithm for sluice gate setting period estimation, and hydraulics equations for sluice gate level adjusting. The water requirements and supplies are deducted from the field-survey and telemetry stations in Chiang Rai Province, Thailand. The results show that the proposed system can accurately estimate the water volume. Water level prediction shows high accuracy. The standard error of prediction (SEP) is 2.58 cm and the mean absolute percentage error (MAPE) is 7.38%. The sluice gate setting period is practically adjusted. The sluice gate level is adjusted according to the water requirement.

Suggested Citation

  • Benya Suntaranont & Somrawee Aramkul & Manop Kaewmoracharoen & Paskorn Champrasert, 2020. "Water Irrigation Decision Support System for Practical Weir Adjustment Using Artificial Intelligence and Machine Learning Techniques," Sustainability, MDPI, vol. 12(5), pages 1-18, February.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:5:p:1763-:d:325821
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    References listed on IDEAS

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