Lei et al. (2026) Process diagnostics of snowmelt runoff in global hydrological and land surface models – Part 1: A systematic evaluation across basins of increasing complexity

Identification

• Journal: Hydrology and earth system sciences
• Year: 2026
• Date: 2026-08-21
• Authors: Xiangyong Lei, Hengxuan Lin, Kaihao Zheng, Peirong Lin
• DOI: 10.5194/hess-30-5343-2026

Research Groups

• Institute of Remote Sensing and Geographic Information Systems, School of Earth and Space Sciences, Peking University, Beijing, 100871, China
• Global Streamflow Characteristics, Hydrometeorology, and Catchment Attributes dataset (GSHA)

Short Summary

This study evaluates the performance of 15 state-of-the-art large-scale runoff models and data products in simulating snowmelt runoff across 1455 snow-dominated basins worldwide. The results reveal that most models exhibit underestimated total volume and peak flow, and predict centroid timing too early.

Objective

• Evaluate the performance of global hydrological and land surface models in simulating snowmelt runoff (SMR) characteristics.
• Assess the robustness of models across basin complexity gradients.

Study Configuration

• Spatial Scale: Global scale with a focus on 1455 snow-dominated basins worldwide.
• Temporal Scale: Daily time steps for model simulations, covering the period 1979–2019.

Methodology and Data

• Models used: 15 state-of-the-art large-scale runoff models, including six Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a) water-sector models, seven ISIMIP3a water-sector models, and two observation-constrained datasets.
• Data sources: ERA5 SWE data for defining the snowmelt period, Multi-Source Weighted-Ensemble Precipitation (Beck et al., 2019), Global Land Evaporation Amsterdam Model (Martens et al., 2017) for estimating ET.

Main Results

• Most models exhibit underestimated total volume and peak flow, and predict centroid timing too early.
• The robustness assessment shows that observation-constrained runoff products exhibit the most outstanding performance, followed by hydrological and land surface models.
• Global hydrological models generally exhibit stronger robustness in simulating total volume and peak flow, while land surface models show a clear advantage in simulating centroid timing.

Contributions

• This study provides a large-sample benchmark for SMR evaluation and complements existing model assessment approaches by examining model performance across basin complexity gradients.
• The results offer useful insights for future model development and uncertainty reduction.

Funding

• Not specified.

Citation

@article{Lei2026Process,
  author = {Lei, Xiangyong and Lin, Hengxuan and Zheng, Kaihao and Lin, Peirong},
  title = {Process diagnostics of snowmelt runoff in global hydrological and land surface models – Part 1: A systematic evaluation across basins of increasing complexity},
  journal = {Hydrology and earth system sciences},
  year = {2026},
  doi = {10.5194/hess-30-5343-2026},
  url = {https://doi.org/10.5194/hess-30-5343-2026}
}