Simulation-Optimization Modeling of Conjunctive Operation of Reservoirs and Ponds for Irrigation of Multiple Crops Using an Improved Artificial Bee Colony Algorithm

Seasonal drought has become an important factor in agricultural production in humid and semi-humid areas. In this study, to mitigate the impact of seasonal drought, a new integrated mathematical model is proposed for optimal multi-crop irrigation scheduling, which is associated with conjunctive operation of reservoirs and ponds to maximize the annual returns for a reservoir-pond irrigation system. This objective is achieved via the use of two models: an operating policy model, which considers the regulatory role of ponds and optimizes reservoirs and ponds releases in one third of a month, and an allocation model, which optimizes irrigation allocations across crops by addressing water production function. The uneven distribution of ponds is also considered by dividing the irrigation district into many sub-districts. Artificial bee colony algorithm is innovatively improved by incorporating differential evolution algorithm and particle swarm optimization algorithm to solve this nonlinear, high-dimensional and complex optimization problem. The methodology is applied to the Zhanghe Irrigation Distict, which is located in Hubei Province of China, to demonstrate its applicability, and three additional models are simulated to demonstrate the validity of the integrated model. The results indicate that the integrated model can alleviate the impact of the seasonal drought and has remarkable optimization effect, especially for drought years. The average annual return calculated by the integrated model is 7.9, 7.0 and 3.1 % higher than that of the remaining three models, respectively. And in the special dry year, in which the frequency of rainfall is 95 %, the annual return calculated by the integrated model is 24.5, 21.8 and 10.1 % higher than that of the remaining three models, respectively.