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Nonlinear model predictive control of salinity and water level in polder networks: Case study of Lissertocht catchment

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  • Aydin, Boran Ekin
  • Oude Essink, Gualbert H.P.
  • Delsman, Joost R.
  • van de Giesen, Nick
  • Abraham, Edo

Abstract

A significant increase in surface water salinization in low-lying deltas is expected globally due to saline groundwater exfiltration driven by rising sea levels and decreasing freshwater availability. Sustaining fresh water-dependent agriculture in such areas will entail an increased demand for fresh water flushing. Unfortunately, the flushing of surface water is not operationally optimised and results in excessive use of scarce freshwater. To meet the increased demand for flushing, while minimizing the need for diverted freshwater, new operational designs are required. This paper presents a novel network model based approach that uses De Saint Venant (SV) and Advection Dispersion (AD) equations to optimize multiple objectives on water level and salinity control using a Nonlinear Model Predictive Control (NMPC). The resulting NMPC problem is solved with a receding horizon implementation, where the nonlinear program (NLP) at each iteration is solved using state-of-the-art large scale interior point solver (IPOPT). We evaluate the performance of the proposed approach and compare it to the traditional fixed flushing for a representative Dutch polder. Firstly, the approach is shown to be capable of controlling the water level and salinity level in the polder. Secondly, the results highlight that the network of canals, which were originally made for drainage, could not be made sufficiently fresh with current intake capacity. A simple design approach was used to identify appropriate new capacities for two of the gates that allow optimal flushing to guarantee the required water level and salinity constraints.

Suggested Citation

  • Aydin, Boran Ekin & Oude Essink, Gualbert H.P. & Delsman, Joost R. & van de Giesen, Nick & Abraham, Edo, 2022. "Nonlinear model predictive control of salinity and water level in polder networks: Case study of Lissertocht catchment," Agricultural Water Management, Elsevier, vol. 264(C).
    • Handle: RePEc:eee:agiwat:v:264:y:2022:i:c:s037837742200049x
    DOI: 10.1016/j.agwat.2022.107502
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    References listed on IDEAS

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    1. Romero, R. & Muriel, J.L. & García, I. & Muñoz de la Peña, D., 2012. "Research on automatic irrigation control: State of the art and recent results," Agricultural Water Management, Elsevier, vol. 114(C), pages 59-66.
    2. Hassani, Yousef & Hashemy Shahdany, Seied Mehdy & Maestre, J.M. & Zahraie, Banafsheh & Ghorbani, Mohammad & Henneberry, Shida Rastegari & Kulshreshtha, Suren N., 2019. "An economic-operational framework for optimum agricultural water distribution in irrigation districts without water marketing," Agricultural Water Management, Elsevier, vol. 221(C), pages 348-361.
    3. Raats, Peter A.C., 2015. "Salinity management in the coastal region of the Netherlands: A historical perspective," Agricultural Water Management, Elsevier, vol. 157(C), pages 12-30.
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    Cited by:

    1. Zhu, Zheli & Guan, Guanghua & Wang, Kang, 2023. "Distributed model predictive control based on the alternating direction method of multipliers for branching open canal irrigation systems," Agricultural Water Management, Elsevier, vol. 285(C).

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