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Towards integrated environmental models of everywhere: Uncertainty, data and modelling as a learning process

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Towards integrated environmental models of everywhere: Uncertainty, data and modelling as a learning process. / Beven, Keith.
In: Hydrology and Earth System Sciences, Vol. 11, No. 1, 17.01.2007, p. 460-467.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Beven, K 2007, 'Towards integrated environmental models of everywhere: Uncertainty, data and modelling as a learning process', Hydrology and Earth System Sciences, vol. 11, no. 1, pp. 460-467. https://doi.org/10.5194/hess-11-460-2007

APA

Beven, K. (2007). Towards integrated environmental models of everywhere: Uncertainty, data and modelling as a learning process. Hydrology and Earth System Sciences, 11(1), 460-467. https://doi.org/10.5194/hess-11-460-2007

Vancouver

Beven K. Towards integrated environmental models of everywhere: Uncertainty, data and modelling as a learning process. Hydrology and Earth System Sciences. 2007 Jan 17;11(1):460-467. doi: 10.5194/hess-11-460-2007

Author

Beven, Keith. / Towards integrated environmental models of everywhere : Uncertainty, data and modelling as a learning process. In: Hydrology and Earth System Sciences. 2007 ; Vol. 11, No. 1. pp. 460-467.

Bibtex

@article{2b18f8910f3c4e2c881d06be5c7bff89,
title = "Towards integrated environmental models of everywhere: Uncertainty, data and modelling as a learning process",
abstract = "Developing integrated environmental models of everywhere such as are demanded by the requirements of, for example, implementing the Water Framework Directive in Europe, is constrained by the limitations of current understanding and data availability. The possibility of such models raises questions about system design requirements to allow modelling as a learning and data assimilation process in the representation of places, which might well be treated as active objects in such a system. Uncertainty in model predictions not only poses issues about the value of different types of data in characterising places and constraining predictive uncertainty but also about how best to present the pedigree of such uncertain predictions to users and decision-makers.",
keywords = "Characterising places, Hydroecological models, Hydrological models, Prediction uncertainty",
author = "Keith Beven",
year = "2007",
month = jan,
day = "17",
doi = "10.5194/hess-11-460-2007",
language = "English",
volume = "11",
pages = "460--467",
journal = "Hydrology and Earth System Sciences",
issn = "1027-5606",
publisher = "Copernicus Gesellschaft mbH",
number = "1",

}

RIS

TY - JOUR

T1 - Towards integrated environmental models of everywhere

T2 - Uncertainty, data and modelling as a learning process

AU - Beven, Keith

PY - 2007/1/17

Y1 - 2007/1/17

N2 - Developing integrated environmental models of everywhere such as are demanded by the requirements of, for example, implementing the Water Framework Directive in Europe, is constrained by the limitations of current understanding and data availability. The possibility of such models raises questions about system design requirements to allow modelling as a learning and data assimilation process in the representation of places, which might well be treated as active objects in such a system. Uncertainty in model predictions not only poses issues about the value of different types of data in characterising places and constraining predictive uncertainty but also about how best to present the pedigree of such uncertain predictions to users and decision-makers.

AB - Developing integrated environmental models of everywhere such as are demanded by the requirements of, for example, implementing the Water Framework Directive in Europe, is constrained by the limitations of current understanding and data availability. The possibility of such models raises questions about system design requirements to allow modelling as a learning and data assimilation process in the representation of places, which might well be treated as active objects in such a system. Uncertainty in model predictions not only poses issues about the value of different types of data in characterising places and constraining predictive uncertainty but also about how best to present the pedigree of such uncertain predictions to users and decision-makers.

KW - Characterising places

KW - Hydroecological models

KW - Hydrological models

KW - Prediction uncertainty

U2 - 10.5194/hess-11-460-2007

DO - 10.5194/hess-11-460-2007

M3 - Journal article

AN - SCOPUS:33846366974

VL - 11

SP - 460

EP - 467

JO - Hydrology and Earth System Sciences

JF - Hydrology and Earth System Sciences

SN - 1027-5606

IS - 1

ER -