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Uncertainty and good practice in hydrological prediction

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Uncertainty and good practice in hydrological prediction. / Beven, Keith; Leedal, David; Alcock, Ruth.
In: Vatten, Vol. 66, 2010, p. 159-163.

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@article{feef5111369643da8e57a569ed4b2f18,
title = "Uncertainty and good practice in hydrological prediction",
abstract = "All forms of hydrological prediction involve many different sources of uncertainty. Many of these sources of uncertainty involve knowledge (epistemic) uncertainties that are not necessarily easy to represent statistically. This can create problems for communication and interpretation between modeller and users when uncertain predictions are presented. One way of dealing with this problem is to define Guidelines for Good Practice in the form of a set of decisions that must be agreed and recorded for later evaluation and review. The Catchment Change Network (CCN) is a knowledge transfer project, funded by the UK Natural Environment Research Council, that aims to bring academic research and practitioners together to produce guidelines for good practice for uncertainty estimation in predicting the future in the areas of flood risk, water quality and water scarcity all of which involve important epistemic uncertainties.",
keywords = "flood risk mapping, communication of uncertainty , epistemic error , hydraulic models, risk-based",
author = "Keith Beven and David Leedal and Ruth Alcock",
year = "2010",
language = "English",
volume = "66",
pages = "159--163",
journal = "Vatten",

}

RIS

TY - JOUR

T1 - Uncertainty and good practice in hydrological prediction

AU - Beven, Keith

AU - Leedal, David

AU - Alcock, Ruth

PY - 2010

Y1 - 2010

N2 - All forms of hydrological prediction involve many different sources of uncertainty. Many of these sources of uncertainty involve knowledge (epistemic) uncertainties that are not necessarily easy to represent statistically. This can create problems for communication and interpretation between modeller and users when uncertain predictions are presented. One way of dealing with this problem is to define Guidelines for Good Practice in the form of a set of decisions that must be agreed and recorded for later evaluation and review. The Catchment Change Network (CCN) is a knowledge transfer project, funded by the UK Natural Environment Research Council, that aims to bring academic research and practitioners together to produce guidelines for good practice for uncertainty estimation in predicting the future in the areas of flood risk, water quality and water scarcity all of which involve important epistemic uncertainties.

AB - All forms of hydrological prediction involve many different sources of uncertainty. Many of these sources of uncertainty involve knowledge (epistemic) uncertainties that are not necessarily easy to represent statistically. This can create problems for communication and interpretation between modeller and users when uncertain predictions are presented. One way of dealing with this problem is to define Guidelines for Good Practice in the form of a set of decisions that must be agreed and recorded for later evaluation and review. The Catchment Change Network (CCN) is a knowledge transfer project, funded by the UK Natural Environment Research Council, that aims to bring academic research and practitioners together to produce guidelines for good practice for uncertainty estimation in predicting the future in the areas of flood risk, water quality and water scarcity all of which involve important epistemic uncertainties.

KW - flood risk mapping

KW - communication of uncertainty

KW - epistemic error

KW - hydraulic models

KW - risk-based

M3 - Journal article

VL - 66

SP - 159

EP - 163

JO - Vatten

JF - Vatten

ER -