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Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information

Water Resources Research · 1998 · Vol. 34(4) · pp. 751–763

Abstract

Several contributions to the hydrological literature have brought into question the continued usefulness of the classical paradigm for hydrologic model calibration. With the growing popularity of sophisticated “physically based” watershed models (e.g., land‐surface hydrology and hydrochemical models) the complexity of the calibration problem has been multiplied many fold. We disagree with the seemingly widespread conviction that the model calibration problem will simply disappear with the availability of more and better field measurements. This paper suggests that the emergence of a new and more powerful model calibration paradigm must include recognition of the inherent multiobjective nature of the problem and must explicitly recognize the role of model error. The results of our preliminary studies are presented. Through an illustrative case study we show that the multiobjective approach is not only practical and relatively simple to implement but can also provide useful information about the limitations of a model.

Hydrology and Watershed Management StudiesGroundwater flow and contamination studiesFlood Risk Assessment and ManagementWatershedCalibrationComputer sciencePopularityField (mathematics)Hydrological modellingSimple (philosophy)Hydrology (agriculture)Machine learningMathematics
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References
Multi-objective global optimization for hydrologic models
Journal of Hydrology · 1998 · 932 citations
Multi-Objective Decision Analysis with Engineering and Business Applications
Journal of the Operational Research Society · 1983 · 697 citations
Genetic Algorithms in Search
Medical Entomology and Zoology · 1989 · 10,051 citations
Genetic algorithms in search, optimization, and machine learning
Choice Reviews Online · 1989 · 49,283 citations
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