Introducing the Model Fidelity Metric (MFM) for robust and diagnostic land surface model evaluation

Wu, Zezhen; Wei, Zhongwang; Lu, Xingjie; Wei, Nan; Li, Lu; Zhang, Shupeng; Yuan, Hua; Liu, Shaofeng; Dai, Yongjiu

doi:10.5194/hess-30-2651-2026

Articles | Volume 30, issue 9

https://doi.org/10.5194/hess-30-2651-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-30-2651-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 30, issue 9

Research article

|

06 May 2026

Research article |

| 06 May 2026

Introducing the Model Fidelity Metric (MFM) for robust and diagnostic land surface model evaluation

Zezhen Wu, Zhongwang Wei, Xingjie Lu, Nan Wei, Lu Li, Shupeng Zhang, Hua Yuan, Shaofeng Liu, and Yongjiu Dai

Supplement

https://doi.org/10.5194/hess-30-2651-2026-supplement

Data sets

CAMELS: Catchment Attributes and MEteorology for Large-sample Studies (1.2) A. J. Newman et al. https://doi.org/10.5065/D6MW2F4D

Model code and software

wuzezhen5577/Model-Fidelity-Metric: Model Fidelity Metric: A robust and diagnostic metric for land surface model evaluation (1.0.1) Z. Wu https://doi.org/10.5281/zenodo.18523829

The Open Source Land Surface Model Benchmarking System Z. Wei https://doi.org/10.5281/zenodo.15811122

Short summary

Land surface models simulate exchanges at the Earth's surface. Traditional evaluation methods can be misleading because they may hide errors or be overly sensitive to outliers. We introduce the Model Fidelity Metric, which measures model performance in terms of accuracy, variability and distribution similarity. Tests with synthetic data and real streamflow observations show that this metric provides more stable and informative assessments of model performance.