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WATER RESOURCES RESEARCH, VOL. 39, NO. 8, 1214, doi:10.1029/2002WR001746, 2003

Effective and efficient algorithm for multiobjective optimization of hydrologic models

Jasper A. Vrugt

Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, Netherlands


Hoshin V. Gupta

Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona, USA


Luis A. Bastidas

Department of Civil and Environmental Engineering, Utah State University, Logan, Utah, USA


Willem Bouten

Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, Netherlands


Soroosh Sorooshian

Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona, USA


Abstract

Practical experience with the calibration of hydrologic models suggests that any single-objective function, no matter how carefully chosen, is often inadequate to properly measure all of the characteristics of the observed data deemed to be important. One strategy to circumvent this problem is to define several optimization criteria (objective functions) that measure different (complementary) aspects of the system behavior and to use multicriteria optimization to identify the set of nondominated, efficient, or Pareto optimal solutions. In this paper, we present an efficient and effective Markov Chain Monte Carlo sampler, entitled the Multiobjective Shuffled Complex Evolution Metropolis (MOSCEM) algorithm, which is capable of solving the multiobjective optimization problem for hydrologic models. MOSCEM is an improvement over the Shuffled Complex Evolution Metropolis (SCEM-UA) global optimization algorithm, using the concept of Pareto dominance (rather than direct single-objective function evaluation) to evolve the initial population of points toward a set of solutions stemming from a stable distribution (Pareto set). The efficacy of the MOSCEM-UA algorithm is compared with the original MOCOM-UA algorithm for three hydrologic modeling case studies of increasing complexity.

Received 2 October 2002; accepted 7 April 2003; published 20 August 2003.

Index Terms: 1869 Hydrology: Stochastic processes; 1836 Hydrology: Hydrologic budget (1655); 1894 Hydrology: Instruments and techniques.

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Citation: Vrugt, J. A., H. V. Gupta, L. A. Bastidas, W. Bouten, and S. Sorooshian (2003), Effective and efficient algorithm for multiobjective optimization of hydrologic models, Water Resour. Res., 39(8), 1214, doi:10.1029/2002WR001746.