Zhang et al. (2026) Can Conceptual Rainfall‐Runoff Models Capture Multi‐Annual Storage Dynamics?

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Water Resources Research
• Year: 2026
• Date: 2026-03-01
• Authors: Ziqi Zhang, Keirnan Fowler, Murray Peel
• DOI: 10.1029/2025wr042226

Research Groups

Not specified in the provided abstract.

Short Summary

This study investigated if specific structural components enable conceptual rainfall-runoff models to capture multi-annual storage dynamics during droughts. It found that models incorporating a long-term store, its disconnection from direct streamflow, and a water loss mechanism from it were significantly more successful in representing long-term hydrological memory and drought response.

Objective

• To test the hypothesis that three specific structural components (a long-term store, its disconnection from direct streamflow generation, and a water loss mechanism from it) are necessary for conceptual rainfall-runoff models to represent multi-annual storage dynamics.

Study Configuration

• Spatial Scale: Three Australian headwater catchments.
• Temporal Scale: Daily time step for model operation, evaluated over multi-annual periods (e.g., 13 years for the Millennium Drought, 1997–2010) and an idealized multi-annual drought scenario.

Methodology and Data

• Models used: 46 daily conceptual rainfall-runoff models from the Modular Assessment of Rainfall-Runoff Models Toolbox.
• Data sources: Observational data from three Australian headwater catchments (implied rainfall and streamflow), and a synthetic scenario designed to evaluate delayed streamflow recovery after an idealized multi-annual drought.

Main Results

• Models possessing all three hypothesized structural components (long-term store, disconnection from direct streamflow, water loss mechanism) were significantly more successful, with 5 out of 9 such models passing both evaluation tests, compared to only 1 out of 37 models lacking the full structure.
• Structural presence alone was not sufficient; some models with the hypothesized structure failed due to restrictive internal formulations or calibration outcomes that prevented the activation of intended slow-storage processes.

Contributions

• Provides critical guidance for selecting or adapting conceptual rainfall-runoff models for applications requiring accurate representation of hydrological memory and long-term drought response.

Funding

Not specified in the provided abstract.

Citation

@article{Zhang2026Can,
  author = {Zhang, Ziqi and Fowler, Keirnan and Peel, Murray},
  title = {Can Conceptual Rainfall‐Runoff Models Capture Multi‐Annual Storage Dynamics?},
  journal = {Water Resources Research},
  year = {2026},
  doi = {10.1029/2025wr042226},
  url = {https://doi.org/10.1029/2025wr042226}
}