Influence of distributed flow losses and gains on the estimation of transient storage parameters from stream tracer experiments

Abstract

Interactions between mobile stream water and transient storage zones have been the subject of careful attention for decades. However, few studies have considered explicitly the influence of water exchange between the channel and neighbouring hydrological units when modelling transient storage processes, especially the lateral inflow coming from hillslope contributions and outflow to a deep aquifer or to hyporheic flow paths extending beyond the study reach. The objective of this study was to explore the influence of different conceptualizations of these hydrologic exchanges on the estimation of transient storage parameters. Slug injections of sodium chloride (NaCl) were carried out in eight contiguous reaches in the Cotton Creek Experimental Watershed (CCEW), located in south-east British Columbia. Resulting breakthrough curves were subsequently analysed using a Transient Storage Model (TSM) in an inverse modelling framework. We estimated solute transport parameters using three distinct, hypothetical spatial patterns of lateral inflow and outflow, all based on variations of the same five-parameter model structure. We compared optimized parameter values to those resulting from a distinct four-parameter model structure meant to represent the standard application of the TSM, in which only lateral inflow was implemented for net gaining reaches or only lateral outflow for net losing reaches. In the five-parameter model, solute mass was stored predominantly in the transient storage zone and slowly released back to the stream. Conversely, solute mass was predominantly removed from the stream via flow losses in the four-parameter model structure. This led to contrasting estimates of solute transport parameters and subsequent interpretation of solute transport dynamics. Differences in parameter estimates across variations of the five-parameter model structure were small yet statistically significant, except for the transient storage exchange rate coefficient α, for which unique determination was problematic. We also based our analysis on F med 200 , the fraction of median transport time due to transient storage. Differences across configurations in F med 200 estimates were consistent but small when compared to the variability of F med 200 among reaches. Optimized parameter values were influenced dominantly by the model structure (four versus five parameters) and then by the conceptualization of spatial arrangement of lateral fluxes along the reach for a set model structure. When boundary conditions are poorly defined, the information contained in the stream tracer breakthrough curve is insufficient to identify a single, unambiguous model structure representing solute transport simulations. Investigating lateral fluxes prior to conducting a study on transient storage processes is necessary, as assuming a certain spatial organization of these fluxes might set ill-defined bases for inter-reach comparisons. Given the difficulty in quantifying the spatial patterns and magnitudes of lateral inputs and outputs, we recommend small-scale laboratory tracer experiments with well-defined and variable boundary conditions as a complement to field studies to provide new insights into stream solute dynamics.