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Do we need research results from small basins for the further development of hydrological models?

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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Do we need research results from small basins for the further development of hydrological models? / Beven, Keith.
Status of Perspectives of Hydrology in Small Basins. Vol. 336 2010. p. 279-285.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Beven, K 2010, Do we need research results from small basins for the further development of hydrological models? in Status of Perspectives of Hydrology in Small Basins. vol. 336, pp. 279-285, International Workshop on Status and Perspectives of Hydrology in Small Basins, Goslar-Hahnenklee, Germany, 30/03/09.

APA

Beven, K. (2010). Do we need research results from small basins for the further development of hydrological models? In Status of Perspectives of Hydrology in Small Basins (Vol. 336, pp. 279-285)

Vancouver

Beven K. Do we need research results from small basins for the further development of hydrological models? In Status of Perspectives of Hydrology in Small Basins. Vol. 336. 2010. p. 279-285

Author

Beven, Keith. / Do we need research results from small basins for the further development of hydrological models?. Status of Perspectives of Hydrology in Small Basins. Vol. 336 2010. pp. 279-285

Bibtex

@inproceedings{89f701d2128d4cafa44201ce2fc85a7e,
title = "Do we need research results from small basins for the further development of hydrological models?",
abstract = "Small basins are well suited to testing models as hypotheses about the function of the basin system, in that they may allow more detailed testing on internal state variables and tracer residence time data as well as the reproduction of hydrographs. However, in this type of hypothesis testing, account must be taken of the potential for epistemic errors in input data, evaluation observations and model structures as well as aleatory errors that can be dealt with by statistical theory. Treating errors as if they were aleatory might result in overestimation of the information content of observations in model inference. This then poses the question of what constitutes an adequate hypothesis test in the face of such (unknown) epistemic errors. One possible framework is outlined, making use of the limits of acceptability approach within the GLUE methodology. This results in treating model testing as a learning process, with the possibility of learning most from rejecting all the models tried.",
keywords = "Commensurability, Internal states, Multiple working hypotheses, Tracer data, Uncertainty",
author = "Keith Beven",
year = "2010",
month = dec,
day = "1",
language = "English",
isbn = "9781907161087",
volume = "336",
pages = "279--285",
booktitle = "Status of Perspectives of Hydrology in Small Basins",
note = "International Workshop on Status and Perspectives of Hydrology in Small Basins ; Conference date: 30-03-2009 Through 02-04-2009",

}

RIS

TY - GEN

T1 - Do we need research results from small basins for the further development of hydrological models?

AU - Beven, Keith

PY - 2010/12/1

Y1 - 2010/12/1

N2 - Small basins are well suited to testing models as hypotheses about the function of the basin system, in that they may allow more detailed testing on internal state variables and tracer residence time data as well as the reproduction of hydrographs. However, in this type of hypothesis testing, account must be taken of the potential for epistemic errors in input data, evaluation observations and model structures as well as aleatory errors that can be dealt with by statistical theory. Treating errors as if they were aleatory might result in overestimation of the information content of observations in model inference. This then poses the question of what constitutes an adequate hypothesis test in the face of such (unknown) epistemic errors. One possible framework is outlined, making use of the limits of acceptability approach within the GLUE methodology. This results in treating model testing as a learning process, with the possibility of learning most from rejecting all the models tried.

AB - Small basins are well suited to testing models as hypotheses about the function of the basin system, in that they may allow more detailed testing on internal state variables and tracer residence time data as well as the reproduction of hydrographs. However, in this type of hypothesis testing, account must be taken of the potential for epistemic errors in input data, evaluation observations and model structures as well as aleatory errors that can be dealt with by statistical theory. Treating errors as if they were aleatory might result in overestimation of the information content of observations in model inference. This then poses the question of what constitutes an adequate hypothesis test in the face of such (unknown) epistemic errors. One possible framework is outlined, making use of the limits of acceptability approach within the GLUE methodology. This results in treating model testing as a learning process, with the possibility of learning most from rejecting all the models tried.

KW - Commensurability

KW - Internal states

KW - Multiple working hypotheses

KW - Tracer data

KW - Uncertainty

M3 - Conference contribution/Paper

AN - SCOPUS:79551507636

SN - 9781907161087

VL - 336

SP - 279

EP - 285

BT - Status of Perspectives of Hydrology in Small Basins

T2 - International Workshop on Status and Perspectives of Hydrology in Small Basins

Y2 - 30 March 2009 through 2 April 2009

ER -