Discharge dependent pollutant dispersion in rivers : estimation of aggregated dead zone parameters with surrogate data.

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

Published

Standard

Discharge dependent pollutant dispersion in rivers : estimation of aggregated dead zone parameters with surrogate data. / Smith, Paul ; Beven, Keith ; Tawn, Jon et al.
In: Water Resources Research, Vol. 42, No. W04412, 20.04.2006.

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

Harvard

Smith, P , Beven, K , Tawn, J, Blazkova, S & Merta, L 2006, 'Discharge dependent pollutant dispersion in rivers : estimation of aggregated dead zone parameters with surrogate data.', Water Resources Research, vol. 42, no. W04412. https://doi.org/10.1029/2005WR004008

APA

Smith, P., Beven, K., Tawn, J., Blazkova, S., & Merta, L. (2006). Discharge dependent pollutant dispersion in rivers : estimation of aggregated dead zone parameters with surrogate data. Water Resources Research, 42(W04412). https://doi.org/10.1029/2005WR004008

Vancouver

Smith P , Beven K , Tawn J, Blazkova S, Merta L. Discharge dependent pollutant dispersion in rivers : estimation of aggregated dead zone parameters with surrogate data. Water Resources Research. 2006 Apr 20;42(W04412). doi: 10.1029/2005WR004008

Author

Smith, Paul ; Beven, Keith ; Tawn, Jon et al. / Discharge dependent pollutant dispersion in rivers : estimation of aggregated dead zone parameters with surrogate data. In: Water Resources Research. 2006 ; Vol. 42, No. W04412.

Bibtex

@article{63542a0cc1a846d2b859ec3850b2945d,

title = "Discharge dependent pollutant dispersion in rivers : estimation of aggregated dead zone parameters with surrogate data.",

abstract = "Much has been done to mitigate the effects of intermittent discharges of pollutants; however, pollution incidents still occur, and the downstream transport and dispersion of pollutants must be predicted. The application of transient storage models based on the advection dispersion equation is often limited by the strong dependence of the parameters on changes in discharge. In this paper a methodology is outlined for estimating the parameters of the simple aggregated dead zone model using surrogate data derived from continuous water quality measurements such as conductivity, including a full treatment of the errors and prediction uncertainties within a Bayesian framework. This methodology is demonstrated in the prediction of a tracer experiment on a reach of the river Elbe in the Czech Republic.",

keywords = "Keywords, aggregated dead zone model, pollution prediction, river pollution.",

author = "Paul Smith and Keith Beven and Jon Tawn and Sarka Blazkova and Ladislav Merta",

year = "2006",

month = apr,

day = "20",

doi = "10.1029/2005WR004008",

language = "English",

volume = "42",

journal = "Water Resources Research",

issn = "1944-7973",

publisher = "AMER GEOPHYSICAL UNION",

number = "W04412",

}

RIS

TY - JOUR

T1 - Discharge dependent pollutant dispersion in rivers : estimation of aggregated dead zone parameters with surrogate data.

AU - Smith, Paul

AU - Beven, Keith

AU - Tawn, Jon

AU - Blazkova, Sarka

AU - Merta, Ladislav

PY - 2006/4/20

Y1 - 2006/4/20

N2 - Much has been done to mitigate the effects of intermittent discharges of pollutants; however, pollution incidents still occur, and the downstream transport and dispersion of pollutants must be predicted. The application of transient storage models based on the advection dispersion equation is often limited by the strong dependence of the parameters on changes in discharge. In this paper a methodology is outlined for estimating the parameters of the simple aggregated dead zone model using surrogate data derived from continuous water quality measurements such as conductivity, including a full treatment of the errors and prediction uncertainties within a Bayesian framework. This methodology is demonstrated in the prediction of a tracer experiment on a reach of the river Elbe in the Czech Republic.

AB - Much has been done to mitigate the effects of intermittent discharges of pollutants; however, pollution incidents still occur, and the downstream transport and dispersion of pollutants must be predicted. The application of transient storage models based on the advection dispersion equation is often limited by the strong dependence of the parameters on changes in discharge. In this paper a methodology is outlined for estimating the parameters of the simple aggregated dead zone model using surrogate data derived from continuous water quality measurements such as conductivity, including a full treatment of the errors and prediction uncertainties within a Bayesian framework. This methodology is demonstrated in the prediction of a tracer experiment on a reach of the river Elbe in the Czech Republic.

KW - Keywords

KW - aggregated dead zone model

KW - pollution prediction

KW - river pollution.

U2 - 10.1029/2005WR004008

DO - 10.1029/2005WR004008

M3 - Journal article

VL - 42

JO - Water Resources Research

JF - Water Resources Research

SN - 1944-7973

IS - W04412

ER -

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