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

TLDR

Classical hydrologic model calibration paradigms are increasingly challenged by the growing complexity of physically based watershed models. The authors argue that model calibration will not vanish with more data and propose a new paradigm. They advocate a multiobjective calibration framework that explicitly incorporates model error. Preliminary studies and a case study demonstrate that this approach is practical, simple, and reveals model limitations.

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.