Variable residence time–based model for solute transport in streams

Abstract

[1] A variable residence time (VART) model is developed for longitudinal dispersion and transport of solutes in natural streams. The VART model is based on a ''double-layer'' conceptual model of transient storage in streams. The upper layer is an advectiondominated transient storage zone which includes instream and shallow hyporheic storage. The lower layer is an effective diffusion-dominated storage zone that is deeper in the streambed and farther beneath the banks. The VART model is characterized by the following features. First, a varying residence time is used to simulate the transient storage process. Second, no user-specified residence time distribution (RTD) functions are required. Third, there are only four parameters to estimate. Fourth, the VART model is also able to accommodate stream water/solute gains or losses in the reach caused by groundwater exchanges. Fifth, the simple VART model is able to produce various compound solute concentration breakthrough curves (BTCs) commonly observed in streams. The early portion of BTCs follows exponential RTDs. The late portion of BTCs can essentially be any distribution. Sixth, performance of the VART model in reproducing various RTDs is comparable to other widely used 1-D solute transport models that commonly utilize five or more fitting parameters and are limited to the simulation of user-specified RTDs or underlying RTDs within them. Applications in hydrologically and geomorphically varied streams have indicated that the VART model is a powerful and flexible numerical tool for simulating solute transport in natural streams.

Thinking outside the channel: modeling nitrogen cycling in networked river ecosystems

“…We believe, however, that river‐network models incorporating both hydrogeomorphic and stoichiometric controls on biogeochemistry could be developed within the next decade. One promising approach would pair stream biogeochemical models with contemporary efforts by hydrologists to use theoretical approaches (Cardenas 2008) and simulation modeling (Deng and Jung 2009) as a means of scaling up the net effect of localized, off‐channel hydrologic processes, such as hyporheic water exchange. Thus, the next generation of models might emerge from coupling network‐scale hydrologic residence‐time distributions with a robust understanding of flow‐path biogeochemistry.…”

Mass transport of contaminated soil released into surface water by landslides (Göta River, SW Sweden)

“…There are various storage processes that influence the transport of fine particles and hence the spatial distribution of particles, which have been reported in numerous studies (see for example Atkinson and Davis, 2000;Chanson, 2004;Karwan and Saiers, 2009;Singh and Beck, 2003;Deng et al, 2001Deng et al, , 2002Bender et al, 2011;van Mazijk and Veling, 2005;Deng and Jung, 2009). Nevertheless, the study by Karwan and Saiers (2009) suggests that transient storage can often be neglected and that a model accounting for advection, dispersion, and first-order kinetic deposition only may be sufficient to describe micrometer-sized particles.…”

Characterisation of hyporheic exchange in a losing stream using radon-222

“…Interpretation of breakthrough curves using a transient storage model that does not assume an exponential residence time distribution (e.g. Deng andJung (2009), Boano et al (2007)) may provide a more realistic representation of the physical distribution of residence times in the hyporheic zone.…”