26 Jul 2022
 | 26 Jul 2022
Status: this preprint is currently under review for the journal HESS.

Uncertainty in water transit time estimation with StorAge Selection functions and tracer data interpolation

Arianna Borriero, Rohini Kumar, Tam V. Nguyen, Jan H. Fleckenstein, and Stefanie R. Lutz

Abstract. Transit time distributions (TTDs) of streamflow are useful descriptors for understanding flow and solute transport in catchments. Catchment-scale TTDs can be modeled using tracer data (e.g., δ18O; oxygen isotopes) in inflow and outflows, with StorAge Selection (SAS) functions. However, tracer data are often sparse in space and time, so they can be interpolated to increase their spatio-temporal resolution. Also, SAS functions can be parameterized with different forms, but there is no general agreement on which one should be used. Both of these aspects induce uncertainty in the simulated TTDs, and the individual uncertainty sources as well as their combined effect have not been fully investigated. This study provides a comprehensive analysis of the TTD uncertainty resulting from twelve model setups obtained by combining different interpolation schemes for δ18O in precipitation, and distinct SAS functions. Furthermore, we evaluated the value of the young water fraction (Fyw) as an additional constraint for the TTD uncertainty. For each model setup, we found behavioral solutions with satisfactory model performances for instream δ18O (Kling-Gupta Efficiency, KGE>0.57). Differences in KGE values were statistically significant, thus showing the relevance of the chosen setup for simulating TTDs. We found a large uncertainty in the simulated TTDs, with a 90 % confidence interval varying between 286 and 895 days across all tested setups. Uncertainty in TTDs was mainly associated with the temporal interpolation of δ18O in precipitation, time-variant SAS function and low flow conditions. The use of Fyw as an additional constraint substantially reduced the uncertainty in the predicted TTDs by up to 49 %. We discussed the implications of these results with respect to the study area and the SAS framework, in order to identify ways to improve uncertainty characterization and water age simulations in TTD-based models.

Arianna Borriero et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2022-222', Ciaran Harman, 22 Dec 2022
    • AC1: 'Reply on RC1', Arianna Borriero, 09 Mar 2023
  • RC2: 'Comment on hess-2022-222', Anonymous Referee #2, 11 Jan 2023
    • AC2: 'Reply on RC2', Arianna Borriero, 09 Mar 2023

Arianna Borriero et al.

Arianna Borriero et al.


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Short summary
We analyzed the uncertainty of water transit time distribution (TTD) resulting from model input (interpolated tracer data) and structure (StorAge Selection (SAS) functions). We found that uncertainty was mainly associated with tracer data time interpolation, time-variant SAS function and low flow conditions. We convey the importance to characterize the specific uncertainty sources, and their combined effects on predicted TTDs, as it has relevant implications for both water quantity and quality.