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Use of spatially distributed water table observations to constrain uncertainty in a rainfall-runoff model

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Use of spatially distributed water table observations to constrain uncertainty in a rainfall-runoff model. / Lamb, Rob; Beven, Keith; Myrabo, S.

In: Advances in Water Resources, Vol. 22, No. 4, 20.10.1998, p. 305-317.

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

Harvard

Lamb, R, Beven, K & Myrabo, S 1998, 'Use of spatially distributed water table observations to constrain uncertainty in a rainfall-runoff model', Advances in Water Resources, vol. 22, no. 4, pp. 305-317. https://doi.org/10.1016/S0309-1708(98)00020-7

APA

Lamb, R., Beven, K., & Myrabo, S. (1998). Use of spatially distributed water table observations to constrain uncertainty in a rainfall-runoff model. Advances in Water Resources, 22(4), 305-317. https://doi.org/10.1016/S0309-1708(98)00020-7

Vancouver

Lamb R, Beven K, Myrabo S. Use of spatially distributed water table observations to constrain uncertainty in a rainfall-runoff model. Advances in Water Resources. 1998 Oct 20;22(4):305-317. doi: 10.1016/S0309-1708(98)00020-7

Author

Lamb, Rob ; Beven, Keith ; Myrabo, S. / Use of spatially distributed water table observations to constrain uncertainty in a rainfall-runoff model. In: Advances in Water Resources. 1998 ; Vol. 22, No. 4. pp. 305-317.

Bibtex

@article{33a87fa7bec9426aa59563f1f7883206,
title = "Use of spatially distributed water table observations to constrain uncertainty in a rainfall-runoff model",
abstract = "The Generalised Likelihood Uncertainty Estimation (GLUE) methodology is used to investigate how distributed water table observations modify simulation and parameter uncertainty for the hydrological model TOPMODEL, applied to the S{\ae}ternbekken Minifelt catchment in Norway. Errors in simulating observed flows, continuously-logged borehole water levels and more extensive, spatially distributed water table depths are combined using Bayes' equation within a {\textquoteleft}likelihood measure' L. It is shown how the distributions of L for the TOPMODEL parameters change as the different types of observed data are considered. These distributions are also used to construct corresponding simulation uncertainty bounds for flows, borehole water levels, and water table depths within the spatially-extensive piezometer network. Qualitatively wide uncertainty bounds for water table simulations are thought to be consistent with the simplified nature of the distributed model.",
keywords = "distributed hydrological models, TOPMODEL, uncertainty, water table predictions, CALIBRATION, PREDICTION",
author = "Rob Lamb and Keith Beven and S. Myrabo",
year = "1998",
month = oct,
day = "20",
doi = "10.1016/S0309-1708(98)00020-7",
language = "English",
volume = "22",
pages = "305--317",
journal = "Advances in Water Resources",
issn = "0309-1708",
publisher = "Elsevier Limited",
number = "4",

}

RIS

TY - JOUR

T1 - Use of spatially distributed water table observations to constrain uncertainty in a rainfall-runoff model

AU - Lamb, Rob

AU - Beven, Keith

AU - Myrabo, S.

PY - 1998/10/20

Y1 - 1998/10/20

N2 - The Generalised Likelihood Uncertainty Estimation (GLUE) methodology is used to investigate how distributed water table observations modify simulation and parameter uncertainty for the hydrological model TOPMODEL, applied to the Sæternbekken Minifelt catchment in Norway. Errors in simulating observed flows, continuously-logged borehole water levels and more extensive, spatially distributed water table depths are combined using Bayes' equation within a ‘likelihood measure' L. It is shown how the distributions of L for the TOPMODEL parameters change as the different types of observed data are considered. These distributions are also used to construct corresponding simulation uncertainty bounds for flows, borehole water levels, and water table depths within the spatially-extensive piezometer network. Qualitatively wide uncertainty bounds for water table simulations are thought to be consistent with the simplified nature of the distributed model.

AB - The Generalised Likelihood Uncertainty Estimation (GLUE) methodology is used to investigate how distributed water table observations modify simulation and parameter uncertainty for the hydrological model TOPMODEL, applied to the Sæternbekken Minifelt catchment in Norway. Errors in simulating observed flows, continuously-logged borehole water levels and more extensive, spatially distributed water table depths are combined using Bayes' equation within a ‘likelihood measure' L. It is shown how the distributions of L for the TOPMODEL parameters change as the different types of observed data are considered. These distributions are also used to construct corresponding simulation uncertainty bounds for flows, borehole water levels, and water table depths within the spatially-extensive piezometer network. Qualitatively wide uncertainty bounds for water table simulations are thought to be consistent with the simplified nature of the distributed model.

KW - distributed hydrological models

KW - TOPMODEL

KW - uncertainty

KW - water table predictions

KW - CALIBRATION

KW - PREDICTION

U2 - 10.1016/S0309-1708(98)00020-7

DO - 10.1016/S0309-1708(98)00020-7

M3 - Journal article

VL - 22

SP - 305

EP - 317

JO - Advances in Water Resources

JF - Advances in Water Resources

SN - 0309-1708

IS - 4

ER -