Conjunctive use of surface and ground water resources using the ant system optimization

Conjunctive use of surface and ground water resources forms an important part of integrated water resource planning and management in a basin-wide scale. This paper presents a simulation/optimization model based on artificial neural networks (ANNs) and an ant system optimization (AS) for solving the monthly conjunctive supply of irrigation water. The study area is Najafabad Plain located in the semi-arid west central Iran. The water resources in the region are under increasing pressure to meet the growing irrigation water demand despite the dire decline in its surface water resources due to climate changes. The main objective of the conjunctive use model developed in this study is to minimize the water deficit in the three irrigation zones subject to constraints on groundwater levels and cumulative drawdown for each zone. The results indicate that the simulation model is capable of predicting the behavior of the study aquifer and that it may be used as a decision support system. Moreover, both the simulation and the optimization models are found capable of determining water extraction quantities required so that not only will the present water deficit decline but aquifer conditions will improve as well.