Jahanshahi et al. (2026) A multi-catchment evaluation of hydrological model transferability and ensemble averaging under contrasting hydroclimatic conditions in Iran

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-06-15
• Authors: Afshin Jahanshahi, Martijn J. Booij
• DOI: 10.1016/j.jhydrol.2026.135878

Research Groups

• School of Engineering, College of Science and Engineering, University of Galway, Ireland
• Water Engineering and Management, Faculty of Engineering Technology, University of Twente, PO Box 217, 97500 AE Enschede, the Netherlands

Short Summary

This study evaluates the transferability of six hydrological models across 37 Iranian catchments under contrasting hydroclimatic conditions using Differential Split-Sample Testing (DSST). The results show that ensemble averaging generally outperforms individual models, with Bayesian Model Averaging (BMA) and Granger-Ramanathan Averaging (GRA) consistently outperforming the Simple Arithmetic Mean (SAM) and Akaike Information Criterion Averaging (AICA).

Objective

• Evaluate the transferability of six hydrological models across 37 Iranian catchments under contrasting hydroclimatic conditions using Differential Split-Sample Testing (DSST)
• Investigate the performance of ensemble averaging approaches, including Bayesian Model Averaging (BMA), Granger-Ramanathan Averaging (GRA), Simple Arithmetic Mean (SAM), and Akaike Information Criterion Averaging (AICA)

Study Configuration

• Spatial Scale: National scale in Iran, with 37 catchments distributed across the country
• Temporal Scale: Daily streamflow, precipitation, and potential evapotranspiration data for the period 1980–2020

Methodology and Data

• Models used: Six lumped conceptual rainfall-runoff models (Tank, GR4J, NAM, HyMod, HBV, and AWBM)
• Data sources: Observed streamflow data from the Iran Energy Ministry (IEM) and the Iran Meteorological Organisation (IRIMO), daily precipitation and potential evapotranspiration data

Main Results

• Model transferability varied substantially with the transfer setting, catchment attributes, and performance criterion
• Ensemble averaging generally outperformed most individual models, although performance depended on the averaging method
• BMA and GRA consistently outperformed SAM and AICA in terms of Nash-Sutcliffe Efficiency (NSE) metric

Contributions

• This study provides a coordinated DSST-based evaluation of conceptual rainfall-runoff models and ensemble-averaging approaches across a large set of Iranian catchments
• The results demonstrate how these established methods can be combined into a practical framework for climate-impact assessment in semi-arid, strongly seasonal regions

Funding

• Not specified

Citation

@article{Jahanshahi2026multicatchment,
  author = {Jahanshahi, Afshin and Booij, Martijn J.},
  title = {A multi-catchment evaluation of hydrological model transferability and ensemble averaging under contrasting hydroclimatic conditions in Iran},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.135878},
  url = {https://doi.org/10.1016/j.jhydrol.2026.135878}
}