Abstract
Abstract. The young water fraction Fyw, defined as the proportion of catchment outflow younger than approximately 2–3 months, can be estimated directly from the amplitudes of seasonal cycles of stable water isotopes in precipitation and streamflow. Thus, Fyw may be a useful metric in catchment inter-comparison studies that investigate landscape and hydro-climatic controls on streamflow generation. Here, we explore how Fyw varies with catchment characteristics and climatic forcing, using an extensive isotope data set from 22 small- to medium-sized (0.7–351 km2) Swiss catchments. We find that flow-weighting the tracer concentrations in streamwater resulted in roughly 26 % larger young water fractions compared to the corresponding unweighted values, reflecting the fact that young water fractions tend to be larger when catchments are wet and discharge is correspondingly higher. However, flow-weighted and unweighted young water fractions are strongly correlated with each other among the catchments. They also correlate with terrain, soil, and land-use indices, as well as with mean precipitation and measures of hydrologic response. Within individual catchments, young water fractions increase with discharge, indicating an increase in the proportional contribution of faster flow paths at higher flows. We present a new method to quantify the discharge sensitivity of Fyw, which we estimate as the linear slope of the relationship between the young water fraction and flow. Among the 22 catchments, discharge sensitivities of Fyw are highly variable and only weakly correlated with Fyw itself, implying that these two measures reflect catchment behaviour differently. Based on strong correlations between the discharge sensitivity of Fyw and several catchment characteristics, we suggest that low discharge sensitivities imply greater persistence in the proportions of fast and slow runoff flow paths as catchment wetness changes. In contrast, high discharge sensitivities imply the activation of different dominant flow paths during precipitation events, such as when subsurface water tables rise into more permeable layers and/or the river network expands further into the landscape.
Highlights
Occurring variations in stable water isotopes (δ18O, δ2H) or chemically passive solutes are commonly used in catchment studies to track the flow of water and to gain insight into catchment storage and mixing behaviour (Buttle, 1994; Kendall and McDonnell, 1998; Klaus and McDonnell, 2013)
Because the mean transit time expresses the ratio between mobile catchment storage and the average flow rate, it is widely used in catchment inter-comparison studies (e.g. Hrachowitz et al, 2009; McGuire et al, 2005; Staudinger et al, 2017)
In the analysis presented below, we use interpolated precipitation isotope values obtained with method 1 that explicitly account for snowpack accumulation and melt in order to be consistent with previous studies where this data set has been used (Seeger and Weiler, 2014; Staudinger et al, 2017)
Summary
Occurring variations in stable water isotopes (δ18O, δ2H) or chemically passive solutes (e.g. chloride) are commonly used in catchment studies to track the flow of water and to gain insight into catchment storage and mixing behaviour (Buttle, 1994; Kendall and McDonnell, 1998; Klaus and McDonnell, 2013). If one measures precipitation to the snow surface as the catchment input, snowpack accumulation and melt are implicitly included in catchment storage (e.g. Staudinger et al, 2017) In this case, comparisons of seasonal cycles in precipitation and streamflow should reflect the young water fraction resulting from the combination of snowpack and subsurface storage. Previous studies that estimated young water fractions in snow-dominated watersheds (Jasechko et al, 2016; Song et al, 2017) did not differentiate between these two concepts of catchment storage and used incoming precipitation in the young water fraction calculations, implicitly considering snowpack storage as part of catchment storage (as in the first case outlined above) This approach is practical in view of the challenges of measuring or modelling snowmelt and its isotopic composition. Uncertainties in the calculated unweighted and flow-weighted young water fractions are expressed as standard errors (SEs) and are estimated using Gaussian error propagation
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
