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Functional classification and evaluation of hydrographs based on multicomponent mapping (Mx)

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Functional classification and evaluation of hydrographs based on multicomponent mapping (Mx). / Pappenberger, Florian; Beven, Keith J.
In: International Journal of River Basin Management, Vol. 2, No. 2, 2004, p. 89-100.

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

Harvard

Pappenberger, F & Beven, KJ 2004, 'Functional classification and evaluation of hydrographs based on multicomponent mapping (Mx)', International Journal of River Basin Management, vol. 2, no. 2, pp. 89-100. https://doi.org/10.1080/15715124.2004.9635224

APA

Pappenberger, F., & Beven, K. J. (2004). Functional classification and evaluation of hydrographs based on multicomponent mapping (Mx). International Journal of River Basin Management, 2(2), 89-100. https://doi.org/10.1080/15715124.2004.9635224

Vancouver

Pappenberger F, Beven KJ. Functional classification and evaluation of hydrographs based on multicomponent mapping (Mx). International Journal of River Basin Management. 2004;2(2):89-100. doi: 10.1080/15715124.2004.9635224

Author

Pappenberger, Florian ; Beven, Keith J. / Functional classification and evaluation of hydrographs based on multicomponent mapping (Mx). In: International Journal of River Basin Management. 2004 ; Vol. 2, No. 2. pp. 89-100.

Bibtex

@article{33a17de82bf549e097e1f3ea018f0bc4,
title = "Functional classification and evaluation of hydrographs based on multicomponent mapping (Mx)",
abstract = "The literature offers a wealth of different performance measures to evaluate model results. However, visual graphical evaluation based on the simple plotting of two curves is still the most intuitive and favoured approach by many modellers. This paper introduces a performance measure, which is based on this method (the Multicomponent Mapping (Mx)). The hydrograph is subdivided into box areas to which membership values according to the distance to the hydrograph are assigned. The box size is influenced by the expected effective observation error structure. It is demonstrated that this method can be used not only to calculate a quantitative performance measure but also to classify hydrograph outputs of Monte Carlo runs into functional classes in order to enable, for example, the cascading of uncertainties in large modelling systems. A comparison to traditional measures like the Nash-Sutcliffe and the Cumulative Absolute Error is performed.",
keywords = "Cluster analysis, Hydrograph evaluation, Model calibration, Nash-Sutcliffe, Uncertainty",
author = "Florian Pappenberger and Beven, {Keith J.}",
year = "2004",
doi = "10.1080/15715124.2004.9635224",
language = "English",
volume = "2",
pages = "89--100",
journal = "International Journal of River Basin Management",
issn = "1571-5124",
publisher = "International Association of Hydraulic Engineering Research",
number = "2",

}

RIS

TY - JOUR

T1 - Functional classification and evaluation of hydrographs based on multicomponent mapping (Mx)

AU - Pappenberger, Florian

AU - Beven, Keith J.

PY - 2004

Y1 - 2004

N2 - The literature offers a wealth of different performance measures to evaluate model results. However, visual graphical evaluation based on the simple plotting of two curves is still the most intuitive and favoured approach by many modellers. This paper introduces a performance measure, which is based on this method (the Multicomponent Mapping (Mx)). The hydrograph is subdivided into box areas to which membership values according to the distance to the hydrograph are assigned. The box size is influenced by the expected effective observation error structure. It is demonstrated that this method can be used not only to calculate a quantitative performance measure but also to classify hydrograph outputs of Monte Carlo runs into functional classes in order to enable, for example, the cascading of uncertainties in large modelling systems. A comparison to traditional measures like the Nash-Sutcliffe and the Cumulative Absolute Error is performed.

AB - The literature offers a wealth of different performance measures to evaluate model results. However, visual graphical evaluation based on the simple plotting of two curves is still the most intuitive and favoured approach by many modellers. This paper introduces a performance measure, which is based on this method (the Multicomponent Mapping (Mx)). The hydrograph is subdivided into box areas to which membership values according to the distance to the hydrograph are assigned. The box size is influenced by the expected effective observation error structure. It is demonstrated that this method can be used not only to calculate a quantitative performance measure but also to classify hydrograph outputs of Monte Carlo runs into functional classes in order to enable, for example, the cascading of uncertainties in large modelling systems. A comparison to traditional measures like the Nash-Sutcliffe and the Cumulative Absolute Error is performed.

KW - Cluster analysis

KW - Hydrograph evaluation

KW - Model calibration

KW - Nash-Sutcliffe

KW - Uncertainty

U2 - 10.1080/15715124.2004.9635224

DO - 10.1080/15715124.2004.9635224

M3 - Journal article

AN - SCOPUS:85009648006

VL - 2

SP - 89

EP - 100

JO - International Journal of River Basin Management

JF - International Journal of River Basin Management

SN - 1571-5124

IS - 2

ER -