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Cited by 20Irrigation Practices and Water ManagementWater resources management and optimizationAdvanced Control Systems Optimization

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Optimal Control for Precision Irrigation of a Large‐Scale Plantation

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Kassing, Ruud, De Schutter, Bart, Abraham, Edo·2020·Water Resources Research
DOI 10.1029/2019wr026989
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Abstract

Distributing water optimally is a complex problem that many farmers face yearly, especially in times of drought. In this work, we propose optimization‐based feedback control to improve crop yield and water productivity in agriculture irrigation for a plantation consisting of multiple fields. The interaction between soil, water, crop (sugarcane in this work), and the atmosphere is characterized by an agrohydrological model using the crop water productivity modeling software AquaCrop‐OS. To optimally distribute water over the fields, we propose a two‐level optimal control approach. In this approach, the seasonal irrigation planner determines the optimal allocation of water over the fields for the entire growth season to maximize the crop yield, by considering an approximation of the crop productivity function. In addition, the model predictive controller takes care of the daily regulation of the soil moisture, respecting the water distribution decided on by the seasonal planner. To reduce the computational complexity of the daily controller, a mixed‐logic dynamical model is identified based on the AquaCrop‐OS model. This dynamical model incorporates saturation dynamics explicitly to improve model quality. To further improve performance, we create an evapotranspiration model by considering the expected development of the crop over the season using remote‐sensing‐based measurements of the canopy cover. The performance of the two‐level approach is evaluated through a closed‐loop simulation in AquaCrop‐OS of a real sugarcane plantation in Mozambique. Our optimal control approach boosts water productivity by up to 30% compared to local heuristics and can respect water use constraints that arise in times of drought.

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Metadata

Authors
Kassing, R., De Schutter, B., & Abraham, E.
Affiliations
  • Delft University of Technology (NL)
  • Delft Center for System and Control Delft University of Technology Delft The Netherlands
Corresponding author
Abraham, Edo
ORCID
Venue
Water Resources Research
Publisher
American Geophysical Union (AGU)
Published
2020-10
Volume
56
Issue
10
ISSN
  • 0043-1397 (ISSN-L)
  • 1944-7973
DOI
10.1029/2019wr026989
OpenAlex
W3087475754
Cited by
20
References
0
Citations by year
2026: 4 · 2025: 2 · 2024: 1 · 2023: 6 · 2022: 6 · 2020: 1
FWCI
2.15
Type
journal article
Language
en
Open access
Licence
Locations
  • Water Resources Research (publishedVersion, cc-by-nc-nd)
  • Research Repository (Delft University of Technology) (submittedVersion, cc-by-nc-nd)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Soil Science › Irrigation Practices and Water Management
  • Physical Sciences › Environmental Science › Water Science and Technology › Water resources management and optimization
  • Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Optimization
Keywords
precision irrigation, optimal control, water allocation, sugar plantations, crop water productivity, model predictive control, two-level control, evapotranspiration modeling, canopy cover, soil moisture control, drought, crop yield

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CoChat. (2026). Citation check: Optimal Control for Precision Irrigation of a Large‐Scale Plantation. https://app.cochat.ai/papers/10.1029/2019wr026989
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Kassing, R., De Schutter, B., & Abraham, E. (2020). Optimal Control for Precision Irrigation of a Large‐Scale Plantation. Water Resources Research. https://doi.org/10.1029/2019wr026989