Modeling Retention of Sorbing Solutes in Streams Based on Tracer Experiment Using
            <sup>51</sup>
            Cr

Wörman, Anders; Forsman, Jonas; Johansson, Håakan

doi:10.1061/(asce)0733-9372(1998)124:2(122)

Cited by 32 publications

(24 citation statements)

References 23 publications

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“…Assumption of equilibrium chemistry in hyporheic exchange models [e.g., Runkel et al ., , , ; Runkel , ; Wörman et al ., ; A. F. Aubeneau et al, submitted manuscript, 2014] also depends on hyporheic exchange rates. Numerically, these models instantaneously reequilibrate chemical constituents following each transport step.…”

Section: Hyporheic Biogeochemistrymentioning

confidence: 99%

Hyporheic flow and transport processes: Mechanisms, models, and biogeochemical implications

et al. 2014

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Fifty years of hyporheic zone research have shown the important role played by the hyporheic zone as an interface between groundwater and surface waters. However, it is only in the last two decades that what began as an empirical science has become a mechanistic science devoted to modeling studies of the complex fluid dynamical and biogeochemical mechanisms occurring in the hyporheic zone. These efforts have led to the picture of surface-subsurface water interactions as regulators of the form and function of fluvial ecosystems. Rather than being isolated systems, surface water bodies continuously interact with the subsurface. Exploration of hyporheic zone processes has led to a new appreciation of their wide reaching consequences for water quality and stream ecology. Modern research aims toward a unified approach, in which processes occurring in the hyporheic zone are key elements for the appreciation, management, and restoration of the whole river environment. In this unifying context, this review summarizes results from modeling studies and field observations about flow and transport processes in the hyporheic zone and describes the theories proposed in hydrology and fluid dynamics developed to quantitatively model and predict the hyporheic transport of water, heat, and dissolved and suspended compounds from sediment grain scale up to the watershed scale. The implications of these processes for stream biogeochemistry and ecology are also discussed.

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Section: Hyporheic Biogeochemistrymentioning

confidence: 99%

Hyporheic flow and transport processes: Mechanisms, models, and biogeochemical implications

et al. 2014

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“…To calculate the observed key parameters for the transient storage zone model from the solute concentration curves measured in these streams, the routing method developed by Cheong and Seo (2003) was used. The measured key parameters for the transient storage zone model obtained from the routing method and calculated Damkohler I (DaI) number defined as (1 + ε)T −1 L/U (Harvey Wagner, 2000;Wagner and Harvey, 1997;Wörman et al, 1998), in which L is total reach length, are listed in Table 1. The experimental reach lengths yielding DaI values for the key parameters for the transient storage zone model between 2.43 and 61.1 have been obtained from the observed data.…”

Section: Evaluation Of Prior Researchmentioning

confidence: 99%

“…Amongst these are transient storage zone models (Bencala et al, 1990;Runkel et al, 1996a;Runkel et al, 1996b;Thackston and Schnelle, 1970) and diffusive exchange models (Cerling et al, 1990;Richardson and Parr, 1988;Wörman et al, 1998) both types of which have been successfully used to interpret longitudinal solute transport in natural streams (Bencala et al, 1990;Johansson et al, 2000;Wörman et al, 1998). To successfully apply these transient storage zone models, appropriate values for various parameters such as the free-flowing water zone dispersion coefficient, the residence time of the tracer in the transient storage zone, the area ratio of transient storage zone area to stream cross sectional area, and the transient storage exchange coefficient are required.…”

Section: Introductionmentioning

confidence: 99%

Estimation of key parameters in model for solute transport in rivers and streams

Cheong

Younis

Seo

2006

Water Resour Manage

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The exchange mechanisms associated with transient storage zones of a natural heterogeneous environment are often modified by unsteady water flux in the transient storage zone. This phenomenon can play an important role in the mass exchange between the free flowing water zone and the transient storage zones and may be the cause of the plateau region of the tail of observed concentration curves in natural streams. Deterministic interpretation methods are often used to generate the shape of the solute concentration curves in natural streams based on representations of transient storage exchange. Although many models are available to predict the parameters for the deterministic interpretation method, none can be used with confidence unless previously calibrated in the particular river reach under consideration. Therefore, the availability of reliable means for the provision of these parameters is usually the primary difficulty in the prediction of the rate of movement, dilution, and mixing of solute in rivers and streams. Measured tracer-response curves produced from the injection of a known quantity of soluble tracer provide one means for obtaining the requisite parameters. In this work, we advance an alternative approach based on the use of hydraulic and geometric information that are easily obtained in natural streams. Empirical equations used to predict the parameters are also analyzed to evaluate their behavior in representing solute mixing in natural streams with transient storage zones. Finally, the present proposals are validated against field meausrements of the solute concentration curves of chloride along a 1.2 km reach of the Shingobee River, Minnesota, U.S.A.

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“…W6rman et al [1998] modeled the solute retention in streams, emphasizing the importance of first-order kinetic exchange of solute with the storage zones as well as diffusive exchange of solute to the permanent substratum. The effect of spatial variability in mass transfer parameters has also been considered, both in a deterministic framework [e.g., Thackston and Schnelle, 1970; Bencala and Walters, 1983c;Jackman et al, 1984;Runkel et al, 1996a] and a stochastic framework using Monte Carlo simulations [W6rman and Cvetkovic, 1995].…”

mentioning

confidence: 99%

“…The uncertainty of parameters is evaluated by studying the change of the temporal moments over limited stream reaches. An alternative approach is to measure and analyze directly the physicochemical processes [Harvey et al, 1996;W6rman et al, 1998]. However, the spatial variability of the stream-sediment zone requires a comparatively large amount of data in order to facilitate a reliable evaluation of the physicochemical mass transfer parameters.…”

mentioning

confidence: 99%

Temporal moment analysis of tracer discharge in streams: Combined effect of physicochemical mass transfer and morphology

Gupta¹,

Cvetković²

2000

Water Resources Research

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Abstract. In environmental applications it is often of interest to predict the rates at which contaminant mass is discharged at a given cross section of streams and rivers. We present a Lagrangian methodology for evaluating tracer discharge (mass per unit time) at specified control cross sections (CCS) of streams. The key transport processes included in the analysis are advection, degradation/decay, and kinetically controlled mass transfer in storage zones and in bed sediment. The transport in the bed sediment is described as a diffusion process, where the tracer may sorb onto the sediment. We have derived a general solution for tracer discharge in the Laplace domain wherefrom temporal moments are computed. The derived solutions may account for deterministic changes in morphological characteristics along stretches of streams. The results are illustrated for zeroth and first two moments where we show the combined effect of advection, degradation, physicochemical mass transfer, and morphology. For illustrative purposes, we assume morphology to change downstream following power laws suggested by Langbein [1947] and Leopold and Maddock [1953]. The moments depend nonlinearly on the downstream distance, following power laws that reflect the power laws for the hydraulic geometry. We define two main dimensionless parameters, namely, kinetic storage parameter a* and bed parameter M, that control the amount of tracer mass eventually discharged at any given CCS. For M •-• 0.3 the most dominant mechanism that controls the amount of ultimately discharged tracer mass is the exchange with the bed sediment. Once estimated from field data for stretches of specified streams, the dimensionless parameters can be used in the derived expressions for predictive purposes.

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Modeling Retention of Sorbing Solutes in Streams Based on Tracer Experiment Using ⁵¹ Cr

Cited by 32 publications

References 23 publications

Hyporheic flow and transport processes: Mechanisms, models, and biogeochemical implications

Hyporheic flow and transport processes: Mechanisms, models, and biogeochemical implications

Estimation of key parameters in model for solute transport in rivers and streams

Temporal moment analysis of tracer discharge in streams: Combined effect of physicochemical mass transfer and morphology

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Modeling Retention of Sorbing Solutes in Streams Based on Tracer Experiment Using 51 Cr

Cited by 32 publications

References 23 publications

Hyporheic flow and transport processes: Mechanisms, models, and biogeochemical implications

Hyporheic flow and transport processes: Mechanisms, models, and biogeochemical implications

Estimation of key parameters in model for solute transport in rivers and streams

Temporal moment analysis of tracer discharge in streams: Combined effect of physicochemical mass transfer and morphology

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Modeling Retention of Sorbing Solutes in Streams Based on Tracer Experiment Using ⁵¹ Cr