Abstract:

In order to make full use of irrigation water resources and improve irrigation water production efficiency, this paper proposed a model predictive control irrigation decision-making method considering water sensitivity. This method first used the water sensitivity index of crops in each period and the Jensen model, and used the nonlinear programming method to determine the daily irrigation upper limit of each growth stage of crops. Then the irrigation upper limit was incorporated into the model predictive control (MPC) framework as a limiting condition to construct a MPC irrigation decision-making model considering water sensitivity. Summer corn simulation irrigation experiments were conducted in Yuanyang County, Henan Province by using three methods: conventional MPC decision-making, MPC decision-making in this article, and decision-making based on the Jensen model. The simulation experiment results showed that compared with the conventional MPC irrigation decision-making, although the yield of the MPC irrigation decision-making in this paper was somewhat reduced, it saved more irrigation water and improved irrigation water productivity. Compared with the decision-making based on the Jensen model, the MPC irrigation decision-making in this paper not only saved irrigation water, but also increased yield and significantly improved irrigation water production efficiency. The method in this article can further save water resources, enhance irrigation water production efficiency, and effectively serve smart irrigation of agricultural water.

Key words: Yuanyang County of Henan Province, irrigation decision, model predictive control, Jensen model, irrigation water production efficiency, water sensitivity