Reference:
R.C. Kassing,
B. De Schutter, and
E. Abraham,
"Optimal control for precision irrigation of a large-scale
plantation," Water Resources Research, vol. 56, no. 10, Oct.
2020. Article e2019WR026989.
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
agro-hydrological 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.