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Cited by 1,426

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

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

Open access
Gupta, Hoshin Vijai, Sorooshian, Soroosh, Yapo, Patrice Ogou·1998·Water Resources Research

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.

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Crossref · 10.1029/97wr03495

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Metadata

Authors
Gupta, H. V., Sorooshian, S., & Yapo, P. O.
Venue
Water Resources Research
Published
1998-04
Volume
34
Issue
4
Pages
751-763
ISSN
  • 0043-1397 (ISSN-L)
  • 1944-7973
OpenAlex
W2157539439
Cited by
1,426
References
1
FWCI
40.62
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information. https://app.cochat.ai/papers/10.1029/97wr03495
The paper
Gupta, H. V., Sorooshian, S., & Yapo, P. O. (1998). Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information. Water Resources Research. https://doi.org/10.1029/97wr03495

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.