Properties of the dead-zone model of longitudinal dispersion in rivers

Czernuszenko, W.; Rowiński, Paweł M.

doi:10.1080/00221689709498407

Cited by 66 publications

(37 citation statements)

References 8 publications

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“…Exchange between streams and groundwater aquifers has Rowinski, 1997;Czernuszenko et al, 1998]. A new model explicitly represents stream-subsurface exchange as a diffusive process [Worman, 1998] but still requires curve fitting to determine the exchange coefficient.…”

Section: Introductionmentioning

confidence: 99%

A physicochemical model for colloid exchange between a stream and a sand streambed with bed forms

Packman¹,

Brooks²,

Morgan³

2000

Water Resources Research

156

236

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Abstract. Fine sediment exchange between a stream and the surrounding subsurface influences downstream contaminant transport and stream ecology. Fundamental models for this exchange were developed on the basis of (1) the hydraulics of bed form-driven advective pore water flow and (2) subsurface colloid transport processes. First, a model was developed to predict the advective flow induced in a sand bed by stream flow over bedforms. The resulting "pumping" exchange rate was calculated based on the streamflow conditions, bed form geometry, and bed depth. The pumping exchange of suspended sediment was then calculated by superimposing advective transport and particle settling in the bed and including the effect of physicochemical filtration by bed sediment. The filtration coefficient approach was used to predict the reduction in the concentration of transported particles. Both settling and filtration cause colloids to be trapped in stream beds, producing a higher net exchange rate relative to conservative solutes. When transported particles are completely trapped in a single pass through the bed, the exchange calculation is simplified because only the particle flux to the bed must be considered. In this case, the net exchange rate may be adequately represented by an effective piston velocity (flux/concentration) or loss rate to the bed in the advectiondispersion equation for the stream. Solute and colloid exchanges are predicted by the models without the use of fitting coefficients; only measurable hydraulic and particle parameters were used as model inputs. Simulations are presented which show the effect of stream parameters, settling, and filtration on net particle exchange. This fundamental approach to modeling stream-subsurface exchange potentially has great utility for understanding and predicting the transport and fate of reactive substances in streams.

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Section: Introductionmentioning

confidence: 99%

A physicochemical model for colloid exchange between a stream and a sand streambed with bed forms

Packman¹,

Brooks²,

Morgan³

2000

Water Resources Research

156

236

View full text Add to dashboard Cite

show abstract

“…Simulation of non-equilibrium exchange processes along with advection and dispersion is not a simple case due the complexity of the processes of exchange (Cameron and Klute, 1977). Numerous investigators (Bencala and Walters, 1983;Runkel and Broshears, 1991;Runkel and Chapra, 1993;Czernuszenko and Rowinski, 1997;Runkel, 1998;Worman et al, 2002) have studied exchange of the pollutant between main stream and porous soil media. The concentrationtime profile of pollutant transport in such case is influenced significantly by the mass exchange.…”

Section: Formulation Of the Model Considering Non-equilibrium Mass Exmentioning

confidence: 99%

Simulation of Stream Pollutant Transport with HyporheicExchangeforWaterResourcesManagement

Kumarasamy¹

2011

Current Issues of Water Management

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“…Nordin & Troutman, 1980;Bencala & Walters, 1983;Czernuszenko & Rowinski, 1997;Worman, 2000), but they require estimation of too many parameters to be used efficiently for ungauged reaches.…”

Section: Modelling Approachmentioning

confidence: 99%

Evaluation of temporal concentration profiles for ungauged rivers following pollution incidents

Piotrowski

Napiorkowski

Rowiński

et al. 2011

Hydrological Sciences Journal

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In order to predict the impact of pollution incidents on rivers, it is necessary to predict the dispersion coefficient and the flow velocity corresponding to the discharge in the river of interest. This paper explores methods for doing this, particularly with a view to applications on ungauged rivers, i.e. those for which little hydraulic or morphometric data are available. An approach based on neural networks, trained on a wide-ranging database of optimized parameter values from tracer experiments and corresponding physical variables assembled for American and European rivers, is proposed. Tests using independent cases showed that the neural networks generally gave more reliable parameter estimates than a second-order polynomial regression approach. The quality of predictions of temporal concentration profiles was heavily influenced by the accuracy of the velocity prediction.Key words longitudinal dispersion; pollutant transport; ungauged river; neural networks; data-based modelling Evaluation des profils temporels de concentration de cours d'eau non jaugés à la suite d'incidents de pollution Résumé Afin de prévoir l'impact des incidents de pollution dans les rivières, il est nécessaire de prévoir le coefficient de dispersion et la vitesse d'écoulement correspondant au débit dans la rivière considérée. Cet article explore les méthodes pour ce faire, en particulier en vue d'applications à des rivières non jaugées, c'est-à-dire pour lesquelles peu de données hydrauliques ou morphométriques sont disponibles. Une approche basée sur des réseaux neuronaux, entraînés avec une importante base de données de valeurs de paramètres optimisés à partir d'expériences de traçage et de variables physiques correspondantes, assemblée pour des rivières américaines et européennes, est proposée. Des tests utilisant des cas indépendants ont montré que les réseaux de neurones ont généralement donné des estimations de paramètres plus fiables qu'une approche de régression polynomiale du second ordre. La qualité des prévisions des profils temporels de concentration a été fortement influencée par la précision de la prévision de la vitesse.

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Properties of the dead-zone model of longitudinal dispersion in rivers

Cited by 66 publications

References 8 publications

A physicochemical model for colloid exchange between a stream and a sand streambed with bed forms

A physicochemical model for colloid exchange between a stream and a sand streambed with bed forms

Simulation of Stream Pollutant Transport with HyporheicExchangeforWaterResourcesManagement

Evaluation of temporal concentration profiles for ungauged rivers following pollution incidents

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