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Rethinking Concepts of Information Content of Hydrological Data to Account for Epistemic Errors. /
Beven, K. J.; Smith, P. J. Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014. ed. / Jim W. Hall; Siu-Kui Au; Michael Beer. American Society of Civil Engineers (ASCE), 2014. p. 263-272.
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Beven, KJ & Smith, PJ 2014,
Rethinking Concepts of Information Content of Hydrological Data to Account for Epistemic Errors. in JW Hall, S-K Au & M Beer (eds),
Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014. American Society of Civil Engineers (ASCE), pp. 263-272, 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014, Liverpool, United Kingdom,
13/07/14.
https://doi.org/10.1061/9780784413609.027
APA
Beven, K. J., & Smith, P. J. (2014).
Rethinking Concepts of Information Content of Hydrological Data to Account for Epistemic Errors. In J. W. Hall, S.-K. Au, & M. Beer (Eds.),
Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014 (pp. 263-272). American Society of Civil Engineers (ASCE).
https://doi.org/10.1061/9780784413609.027
Vancouver
Beven KJ, Smith PJ.
Rethinking Concepts of Information Content of Hydrological Data to Account for Epistemic Errors. In Hall JW, Au SK, Beer M, editors, Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014. American Society of Civil Engineers (ASCE). 2014. p. 263-272 doi: 10.1061/9780784413609.027
Author
Bibtex
@inproceedings{d335681d65774076a0e6eb654066e27f,
title = "Rethinking Concepts of Information Content of Hydrological Data to Account for Epistemic Errors",
abstract = "There remains a great deal of uncertainty about uncertainty estimation in hydrological modelling. Given that hydrology is still a subject limited by the available measurement techniques, it does not appear that the issue of epistemic error in hydrological data will go away for the foreseeable future. It may be necessary to find a way of allowing for robust model conditioning and more subjective treatments of potential epistemic errors in model applications. In this study, we have made an attempt to analyse how this is the result of the epistemic uncertainties inherent in the hydrological modelling process and its impact on model conditioning and hypothesis testing. We propose some ideas about how to deal with assessing the information in hydrological data and how it might influence model conditioning based on hydrological reasoning, with an application to rainfall-runoff modelling of a catchment in Northern England where inconsistent data for some events can potentially introduce disinformation into the model conditioning process. A methodology is presented to make an assessment of the relative information content of calibration data before running a model that can then inform the evaluation of model runs and resulting simulation uncertainties.",
author = "Beven, {K. J.} and Smith, {P. J.}",
note = "Publisher Copyright: {\textcopyright} 2014 American Society of Civil Engineers.; 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014 ; Conference date: 13-07-2014 Through 16-07-2014",
year = "2014",
doi = "10.1061/9780784413609.027",
language = "English",
pages = "263--272",
editor = "Hall, {Jim W.} and Siu-Kui Au and Michael Beer",
booktitle = "Vulnerability, Uncertainty, and Risk",
publisher = "American Society of Civil Engineers (ASCE)",
address = "United States",
}
RIS
TY - GEN
T1 - Rethinking Concepts of Information Content of Hydrological Data to Account for Epistemic Errors
AU - Beven, K. J.
AU - Smith, P. J.
N1 - Publisher Copyright:
© 2014 American Society of Civil Engineers.
PY - 2014
Y1 - 2014
N2 - There remains a great deal of uncertainty about uncertainty estimation in hydrological modelling. Given that hydrology is still a subject limited by the available measurement techniques, it does not appear that the issue of epistemic error in hydrological data will go away for the foreseeable future. It may be necessary to find a way of allowing for robust model conditioning and more subjective treatments of potential epistemic errors in model applications. In this study, we have made an attempt to analyse how this is the result of the epistemic uncertainties inherent in the hydrological modelling process and its impact on model conditioning and hypothesis testing. We propose some ideas about how to deal with assessing the information in hydrological data and how it might influence model conditioning based on hydrological reasoning, with an application to rainfall-runoff modelling of a catchment in Northern England where inconsistent data for some events can potentially introduce disinformation into the model conditioning process. A methodology is presented to make an assessment of the relative information content of calibration data before running a model that can then inform the evaluation of model runs and resulting simulation uncertainties.
AB - There remains a great deal of uncertainty about uncertainty estimation in hydrological modelling. Given that hydrology is still a subject limited by the available measurement techniques, it does not appear that the issue of epistemic error in hydrological data will go away for the foreseeable future. It may be necessary to find a way of allowing for robust model conditioning and more subjective treatments of potential epistemic errors in model applications. In this study, we have made an attempt to analyse how this is the result of the epistemic uncertainties inherent in the hydrological modelling process and its impact on model conditioning and hypothesis testing. We propose some ideas about how to deal with assessing the information in hydrological data and how it might influence model conditioning based on hydrological reasoning, with an application to rainfall-runoff modelling of a catchment in Northern England where inconsistent data for some events can potentially introduce disinformation into the model conditioning process. A methodology is presented to make an assessment of the relative information content of calibration data before running a model that can then inform the evaluation of model runs and resulting simulation uncertainties.
U2 - 10.1061/9780784413609.027
DO - 10.1061/9780784413609.027
M3 - Conference contribution/Paper
AN - SCOPUS:84933525949
SP - 263
EP - 272
BT - Vulnerability, Uncertainty, and Risk
A2 - Hall, Jim W.
A2 - Au, Siu-Kui
A2 - Beer, Michael
PB - American Society of Civil Engineers (ASCE)
T2 - 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014
Y2 - 13 July 2014 through 16 July 2014
ER -
