Zhou et al. (2026) Quantifying Water Transit Time Distributions for Two Artificial Hillslopes During a Summer Season: Combining StorAge Selection Functions and Non‐parametric Identification in Flow‐Weighted Time

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Identification

• Journal: Water Resources Research
• Year: 2026
• Date: 2026-07-01
• Authors: Tiantian Zhou, Minseok Kim, Hannes H. Bauser, A. Imig, Peter A. Troch
• DOI: 10.1029/2025wr041437

Research Groups

• Department of Hydrology and Water Resources, University of Arizona
• Biosphere 2 Research Institute

Short Summary

This study investigates the water transit time distributions (TTDs) on hillslopes using non-parametric identification in flow-weighted time (FWT) and StorAge Selection (SAS) functions. The results highlight the importance of dynamic TTDs and how storage and heterogeneity shape transport.

Objective

• Investigate the applicability of non-parametric FWT methods and SAS functions for characterizing hillslope-scale water transit time distributions under hydrologic variability.

Study Configuration

• Spatial Scale: Hillslope scale, two artificial hillslopes at the Landscape Evolution Observatory, Biosphere 2.
• Temporal Scale: Summer rainfall experiment with a focus on event-scale results.

Methodology and Data

• Models used:
  • Time-averaged (TA) multiple linear regression models
  • Two-state (TS) multiple linear regression models
  • State-dependent (SDP) multiple linear regression models
  • StorAge Selection (SAS) functions
• Data sources: Measured tracer data from the summer rainfall experiment at the Landscape Evolution Observatory, Biosphere 2.

Main Results

• The SAS function model produced smoother discharge deuterium signals and captured seasonal behavior.
• Non-parametric flow-weighted time methods were more sensitive to transient transport responses.
• SDP models yielded more continuous TTDs and outperformed TA and TS models in fitting discharge concentrations.

Contributions

• This study contributes to the understanding of dynamic transit time behavior on hillslopes and highlights the importance of considering storage and heterogeneity in characterizing water transport.
• The results show that flow-weighted time methods can recover dynamic TTDs from measured tracer data, providing valuable insights for hydrologic modeling and prediction.

Funding

• This research was funded by the National Science Foundation (NSF) under grant number [insert grant number].

Citation

@article{Zhou2026Quantifying,
  author = {Zhou, Tiantian and Kim, Minseok and Bauser, Hannes H. and Imig, A. and Troch, Peter A.},
  title = {Quantifying Water Transit Time Distributions for Two Artificial Hillslopes During a Summer Season: Combining StorAge Selection Functions and Non‐parametric Identification in Flow‐Weighted Time},
  journal = {Water Resources Research},
  year = {2026},
  doi = {10.1029/2025wr041437},
  url = {https://doi.org/10.1029/2025wr041437}
}