Multi-objective Optimization by an Evolutionary Algorithm for Calibrating an Hydrological Model

Hydrologic models simulate the river flow from the contributing basin for a given river. For the simulation process, the integration domain is discretized into computational cells. The inputs for such models are precipitation ratio and the initial flow. There are many parameters to be determined for an operational model, including the type of soil (porosity field, water flux between the bottom of the river and the water layer, among others). However, there is no unique set of parameters for representing the hydrology cycle. A multi-objective approach is employed to address the problem. The Pareto set is calculated for the IPH2 model by an epidemic genetic algorithm.