INCORPORATING AQUIFER MODELING INTO A MULTI-PERIOD NETWORK FLOW PROGRAMMING OPTIMIZATION MODEL FOR WATER RESOURCES MANAGEMENT

Aquifers provide a very important source of water in river basins under great surface water stress, and conjunctive use represents sometimes the only way of supplying all the different demands within the basin in drought periods. On the other hand, optimization models help decision makers to depict the operations which should be done in a water resources system in order to maximize the benefits and minimize the costs while keeping a certain supply level and complying with some other constrains. Therefore, including aquifers modeling, and all their surrounding aspects, in a river basin optimization model does not only increase the representation of the model itself but also offers the possibility of studying the optimal pumping rules in a similar way as other operation rules are dealt with via the pumping control parameters. This article presents the development and integration of a groundwater module in an already existing water resources optimization model based in network flow programming. Network flow programming is an efficient form of linear programming, hence incorporating aquifer modeling that is a highly non-linear process supposes a big challenge. Moreover, in order to consider aquifers in a river basin model always implies considering as well some other non-linear related aspects such as seepage from reservoirs, river bed and irrigation schemes, additional pumping and pumping from demands, natural and artificial recharge, and water exchanges between river and aquifer, all aspects that must be incorporated to the network flow in form of new arcs and nodes and be dealt with in the optimization process. All these non-linearities have been approximated through iterations which have shown to be sufficient to yield proficient results in the example cases carried out during the development process. As an addition, different aquifer models have been considered so future modelers can choose among them one that better fits their needs.