How does reach‐scale stream‐hyporheic transport vary with discharge? Insights from rSAS analysis of sequential tracer injections in a headwater mountain stream. Issue 9 (22nd September 2016)

• Record Type: Journal Article
• Authors: Harman, C. J.; Ward, A. S.; Ball, A.
• Is Part Of: Water resources research. Volume 52:Issue 9(2016:Sep.)
• Page Start: 7130
• Page End: 7150
• Publication Date: 2016-09-22
• Subjects: Hyporheic -- rSAS -- transit time distribution -- storage selection function -- stream transport; Hydrology -- Periodicals; 333.91
• DOI: 10.1002/2016WR018832
• Languages: English
• ISSNs: 0043-1397

Abstract

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. Key Points: Seven tracer injections over 28 h analyzed using rank Storage Selection function theory of time‐varying transit time distributions rSAS results show fluctuations in turnover rate of reach storage at base flow limited to a volume 5 times larger than visible channel Method suggests an approach to parsimonious reach‐scale solute transport that accounts for time‐varying stream‐hyporheic exchange dynamics