On the relationship of transient storage and aggregated dead zone models of longitudinal solute transport in streams

Abstract

Abstract. The relationship between the distributed transient storage (TS) and lumped aggregate dead zone (ADZ) models of longitudinal solute transport in rivers and streams is examined by a parallel application to tracer data and through an investigation of parameter relationships. Both models accurately describe observed solute transport in a stream where the effects of storage or dead zones significantly affect longitudinal dispersion. A moment matching technique, based on theoretical temporal moments, is used to develop parameter relationships. Tests using the previously calibrated parameters, in addition to simulation experiments, show that the moment matching procedure allows ADZ model parameters to be reliably derived from TS model parameters and vice versa. An investigation of these parameter relationships reveals an important difference between the effective solute transport velocity and the average reach flow velocity in streams subject to transient storage or dead zone processes. A number of practical uses for the derived relationships are suggested, including the ability to utilize powerful methods of system identification in the estimation of TS model parameters.

Dilution and volatilization of groundwater contaminant discharges in streams

“…Marion et al, 2008;Silva et al 2009). Boundary conditions that deal with heterogeneous and transient aquifer boundaries, river bank effects and storage in low river bends have been proposed and implemented in the literature (e.g., Lees et al 2000;Silva et al 2009;Moench 1995;Gooseff et al 2011;Pedretti et al 2014). These mass transfer boundary conditions are usually adapted to model systems dominated by fast flow regions that receive solutes from less mobile regions.…”

A general real-time formulation for multi-rate mass transfer problems

“…For solute transport in rivers the governing Eqs. (5) and (6) are based on the conservation of mass principle for the stream and storage zone segments (Bencala and Walters, 1983;Lees et al, 2000;Zhang and Aral, 2004)…”

“…Non-equilibrium also has been observed in solute transport through rivers that are influenced by the exchange of water between the river and the underlying hyporheic zone (Fernald et al, 2001;Boano et al, 2007;Marion et al, 2008) or by aggregated dead-zones (Beer and Young, 1983;Lees et al, 1998Lees et al, , 2000Davis et al, 2000). Dead zones can be associated to a number of effects, such as reverse flows induced by bends and pools, side pockets, zones between dikes, turbulent eddies, and wakes behind bed irregularities and roughness elements (Deng et al, 2004).…”

Estimation of parameters of the transient storage model by means of multi-layer perceptron neural networks / Estimation des paramètres du modèle de transport TSM au moyen de réseaux de neurones perceptrons multi-couches

“…Nordin & Troutman, 1980;Bencala & Walters, 1983;Hart, 1995;Lees et al, 2000;De Smedt et al, 2005;Guymer & Dutton, 2005). Such a model may be used as a warning tool when catastrophic releases of toxic substances occur in rivers (Mazijk & Veling, 2005), if one knows the ways to evaluate the model parameters.…”