Simulation of solute transport in a mountain pool‐and‐riffle stream: A transient storage model

Abstract

The physical characteristics of mountain streams differ from the uniform and conceptually welldefined open channels for which the analysis of solute transport has been oriented in the past and is now well understood. These physical conditions significantly influence solute transport behavior, as demonstrated by a transient storage model simulation of solute transport in a very small (0.0125 m 3 s -•) mountain pool-and-riffle stream. The application is to a carefully controlled and intensively monitored chloride injection experiment. The data from the experiment are not explained by the standard convection-dispersion mechanisms alone. A transient storage model, which couples dead zones with the one-dimensional convection-dispersion equation, simulates the general characteristics of the solute transport behavior and a set of simulation parameters were determined that yield an adequate fit to the data. However, considerable uncertainty remains in determining physically realistic values of these parameters. The values of the simulation parameters used are compared to values used by other authors for other streams. The comparison supports, at least qualitatively, the determined parameter values.

Increasing parameter certainty and data utility through multi-objective calibration of a spatially distributed temperature and solute model

“…6), compared to Level 1 results, but there are still relatively large bounds. It should also be noted that this calibration does not capture the peak of the tracer at Site 3, nor the tail of the tracer curve at Site 2, which is critical to understanding the transient storage within the study reach (Bencala and Walters, 1983). Similar to what Neilson et al (2010a) found, comparing Level 1 and 2 results (Table 3) illustrates the relative benefit of using two-objective optimization compared to single-objective optimizations.…”

“…As discussed in Neilson et al (2010b), loss of Rhodamine WT due to sorption to streambed sediments (mineral and organic) was not a concern in this study because the organic matter content in the bed sediments was extremely low (averaging 0.05 % at four sampling locations). Additionally, a recent sorption study within this portion of the Virgin River (Bingham, 2010) provided average K d values of 1.5 mL g −1 , which is low based on other Rhodamine WT sorption studies (Bencala and Walters, 1983;Everts and Kanwar, 1994;Lin et al, 2003;Shiau et al, 1993).…”

“…The TZTS model separates transient storage (Bencala and Walters, 1983) into two zones, (1) dead zones or the surface transient storage (STS) zone that represents the eddies, recirculating zones, and side pockets of water and (2) subsurface or hyporheic transient storage (HTS) zone, that represents the flow into or out of the stream substrate. As discussed in Neilson et al (2010a), sources and sinks of heat include fluxes across the air-water interface, bed conduction, conduction between the bed and deeper ground substrate, HTS exchange, and STS exchange.…”

Coupled reversion and stream-hyporheic exchange processes increase environmental persistence of trenbolone metabolites

“…To quantify the potential impact of product-to-parent reversion on TBA metabolite persistence, we conducted numerical simulations of 17a-TBOH transport and fate in a stream-hyporheic system and compared cases with and without-reversion. The dominant transport processes simulated are advection, dispersion and transient storage in the hyporheic zone 24 . Key assumptions of this model include a well-mixed stream and hyporheic zone at each spatial step, an exponential residence time distribution in the hyporheic zone, and no down-stream transport in the hyporheic zone.…”

An assessment of steady-state propane-gas tracer method for reaeration coefficients — Cowaselon Creek, New York

“…Recent studies of the solute transport mechanics in natural channels indicate overhwelmingly that the long tail is due to the mechanism of solute storage in the dead water areas of channel boundaries. For example, the simulation study by Bencala and Walters (1983) shows that the Ipng tail of a chloride tracer plume behaves as if it is due to a first-order decay. Apparently a slow diffusive transfer of tracer from the storage area to the maini channel is the responsible mechanism, which causes the logarithm of concentration to decrease as a linear function of time.…”