Hydrological optimization applies mathematical optimization techniques (such as linear programming) to water-related problems. These problems may be for surface water, groundwater, or the combination. The work is interdisciplinary, and may be done by hydrologists, civil engineers, environmental engineers, and operations researchers.
Groundwater and surface water flows can be studied with hydrologic simulation. A typical program used for this work is MODFLOW. However, simulation models cannot easily help make management decisions, as simulation is descriptive. Simulation shows what would happen given a certain set of conditions. Optimization, by contrast, finds the best solution for a set of conditions. Optimization models have three parts: (1) an objective, such as "Minimize cost", (2) decision variables, which correspond to the options available to management, and (3) constraints, which describe the technical or physical requirements imposed on the options.
To use hydrological optimization, a simulation is run to find constraint coefficients for the optimization. An engineer or manager can then add costs or benefits associated with a set of possible decisions, and solve the optimization model to find the best solution.
Examples of problems solved with hydrological optimization:
- Contaminant remediation in aquifers. The decision problem is where to locate wells, and choose a pumping rate, to minimize the cost to prevent spread of a contaminant. The constraints are associated with the hydrogeological flows.
- Maximizing well abstraction subject to environmental flow constraints (Wagner 1995, Feyen and Gorelick 2005). The goal is to measure the effects of each user's water use on other users and on the environment, as accurately as possible, and then optimize over the available feasible solutions.
- Hydrological optimization is now being proposed for use with smart markets for water-related resources.