How does reach‐scale stream‐hyporheic transport vary with discharge? Insights from rSAS analysis of sequential tracer injections in a headwater mountain stream

Abstract

The models of stream reach hyporheic exchange that are typically used to interpret tracer data assume steady‐flow conditions and impose further assumptions about transport processes on the interpretation of the data. Here we show how rank Storage Selection (rSAS) functions can be used to extract “process‐agnostic” information from tracer breakthrough curves about the time‐varying turnover of reach storage. A sequence of seven slug injections was introduced to a small stream at base flow over the course of a diel fluctuation in stream discharge, providing breakthrough curves at discharges ranging from 0.7 to 1.2 L/s. Shifted gamma distributions, each with three parameters varying stepwise in time, were used to model the rSAS function and calibrated to reproduce each breakthrough curve with Nash‐Sutcliffe efficiencies in excess of 0.99. Variations in the fitted parameters over time suggested that storage within the reach does not uniformly increase its turnover rate when discharge increases. Rather, changes in transit time are driven by both changes in the average rate of turnover (external variability) and changes in the relative rate that younger and older water contribute to discharge (internal variability). Specifically, at higher discharge, the turnover rate increased for the youngest part of the storage (corresponding to approximately 5 times the volume of the channel), while discharge from the older part of the storage remained steady, or declined slightly. The method is shown to be extensible as a new approach to modeling reach‐scale solute transport that accounts for the time‐varying, discharge‐dependent turnover of reach storage.

Transient Groundwater Travel Time Distributions and Age‐Ranked Storage‐Discharge Relationships of Three Lowland Catchments

“…The time variation in groundwater TTs can be represented by dynamic TTDs (Botter et al, 2010;Engdahl et al, 2016;Harman, 2015;Heidbüchel et al, 2012;van der Velde et al, 2012;van der Velde et al, 2010) and occurs due to external variability of the input (i.e., groundwater recharge) as well as internal variability where shallow flow paths become active as the groundwater table rises (Harman et al, 2016;Kim et al, 2016;Rozemeijer & Broers, 2007). Additional information about flow paths combined with the contribution of different ages to streamflow allows direct correlation of, for instance, water chemistry with a specific flow path, which can thus explain variations in water chemistry throughout the year (Benettin et al, 2013;Hrachowitz et al, 2016).…”

Solute Transport and Transformation in an Intermittent, Headwater Mountain Stream with Diurnal Discharge Fluctuations

“…Moreover, common model formulations are not appropriate for interpreting experimental data in intermittent streams, as they require the presence of a continuously flowing stream [91][92][93], though exceptions do exist [23]. To overcome these limitations, new approaches, such as the StorAge Selection (SAS) model, take transport as a continuum and can simulate continuously variable discharge [94][95][96].…”

Characterizing hyporheic exchange processes using high‐frequency electrical conductivity‐discharge relationships on subhourly to interannual timescales

“…Consistent with other field‐based studies in nonpolar settings [e.g., Loheide and Lundquist , ; Covino et al ., ; Ward et al ., ; Harman et al ., ], we argue that seasonal trends in EC and EC‐Q dynamics are signatures of the positive scaling between hyporheic exchange and Q, and subsequent effects on hyporheic turnover rates. The subhysteretic analysis of long‐term, continuous, high‐frequency C‐Q data highlights the need to more directly quantify scaling relationships between hyporheic exchange and Q variability across timescales and to resolve the influence of highly unsteady flows on the hyporheic zone solute budget.…”

“…Interestingly, the application of subhysteretic analysis techniques identifies a variable hyporheic exchange process (positive scaling of HZ exchange and turnover with Q) that operates to control EC‐Q relationships at daily, annual, and interannual timescales in MDV streams. Thus, our results reflect the stability of this process in a system across a wider range of timescales than previous studies, which tend to focus on a single timescale (i.e., hourly or seasonal) [e.g., Loheide and Lundquist , ; Covino et al ., ; Ward et al ., ; Harman et al ., ]. Of course, interannual variability in other parameters (e.g., reduced hyporheic exchange, weathering production rates, relative size of channel to HZ cross‐sectional areas due to variability in the depth of permafrost thawing, etc.…”