MULTIOBJECTIVE GLOBAL OPTIMIZATION FOR HYDROLOGIC-MODELS

The development of automated (computer-based) calibration methods has focused mainly on the selection of a single-objective measure of the d istance between the model-simulated output and the data and the select ion of an automatic optimization algorithm to search for the parameter values which minimize that distance. However, practical experience wi th model calibration suggests that no single-objective function is ade quate to measure the ways in which the model fails to match the import ant characteristics of the observed data. Given that some of the lates t hydrologic models simulate several of the watershed output fluxes (e .g. water, energy, chemical constituents, etc.), there is a need for e ffective and efficient multiobjective calibration procedures capable o f exploiting all of the useful information about the physical system c ontained in the measurement data time series. The MOCOM-UA algorithm, an effective and efficient methodology for solving the multiple-object ive global optimization problem, is presented in this paper. The metho d is an extension of the successful SCE-UA single-objective global opt imization algorithm. The features and capabilities of MOCOM-UA are ill ustrated by means of a simple hydrologic model calibration study. (C) 1998 Elsevier Science B.V.