Conjunctive Use of Surface and Groundwater Resources with Emphasis on Water Quality

Abstract

In this paper, a methodology for conjunctive use of surface and groundwater resources with emphasis on water quality is developed using Genetic Algorithms (GAs) and the Artificial Neural Networks (ANNs). Water supply with acceptable quality, reduction of pumping costs, and controlling the groundwater table fluctuations are considered in the objective function of the model. In the proposed methodology, the results of a groundwater simulation model are used to train the ANNs based simulation model. This model is then linked to the GA based optimization model to develop the monthly conjunctive use operating policies. The proposed model is applied to the surface and groundwater allocation in the irrigation networks in the southern part of Tehran, the capital city of Iran. Tehran metropolitan area has annual domestic water consumption close to one billion cubic meters. The sewer system is mainly consisted of the traditional absorption wells. Some part of this sewage is drained into local rivers and drainage channels and partially contaminates the surface runoff and local flows. These polluted surface waters are used in conjunction with groundwater for irrigation purposes in the Southern part of the Tehran. The results of the proposed model show the significance of an integrated and systems approach to surface and groundwater resources allocation in the study area. For example, the cumulative groundwater table variations in each zone, which has experienced a total fluctuation of more than ±20 meters in the last 20 years, is limited to ±5 meters over the planning horizon