Belfort et al. (2025) Hydrodynamic Parameter Estimation for Simulating Soil-Vegetation-Atmosphere Hydrology Across Forest Stands in the Strengbach Catchment

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Identification

• Journal: Hydrology
• Year: 2025
• Date: 2025-12-24
• Authors: Benjamin Belfort, Aya Alzein, Solenn Cotel, Anthony Julien, Sylvain Weill
• DOI: 10.3390/hydrology13010011

Research Groups

• Hydro-Geochemical Environmental Observatory (Strengbach forested catchment), France

Short Summary

This study developed a methodology integrating pedotransfer functions and inverse modeling to determine optimal soil hydrodynamic parameters for contrasting forest plots, finding that a balanced calibration time series including both wet and dry phases is crucial for robust parameter estimation.

Objective

• To determine the optimal hydrodynamic parameters (α, Ks, and n) for soil water flow in two contrasting forest plots (spruce and beech) within the Strengbach forested catchment.
• To investigate the influence of different calibration time periods (chronicles) on the estimated hydrodynamic parameters.

Study Configuration

• Spatial Scale: Two contrasting forest plots (one spruce-dominated, one beech-dominated) within the Strengbach forested catchment, France.
• Temporal Scale: Multiple time periods used for calibration and evaluation, emphasizing the need for long simulation periods and balanced time series including both wet and dry phases.

Methodology and Data

• Models used:
  • Pedotransfer functions (PTFs), specifically Rosetta, for initial parameter estimation.
  • Inverse parameter estimation based on water content measurements to refine hydrodynamic parameters (α, Ks, n).
  • Mechanistic modeling of soil water flow (specific model not named, but parameters for hydraulic conductivity and water retention curves are targeted).
• Data sources:
  • Granulometric data across multiple soil layers.
  • In-situ water content measurements.
  • In-situ conductivity data.
  • Soil stoniness data for correction.
  • Observations from the Hydro-Geochemical Environmental Observatory (Strengbach).

Main Results

• The developed methodology, integrating PTFs and inverse modeling, is efficient for determining optimal soil hydrodynamic parameters.
• Correcting water content and conductivity data for soil stoniness improved the KGE and NSE metrics.
• The optimal calibration period does not correspond to the most severe drought conditions; instead, a balanced time series encompassing both wet and dry phases is preferable.
• KGE and NSE metrics must be interpreted with caution.
• Long simulation periods are essential for robust evaluation of estimated parameters.

Contributions

• Development and application of a comprehensive framework that combines pedotransfer functions (Rosetta) with inverse modeling for robust estimation of soil hydrodynamic parameters in complex forested environments.
• Demonstration of the critical importance of selecting a balanced calibration time series (including both wet and dry periods) over solely drought conditions for accurate parameter determination.
• Highlighting the necessity of long simulation periods for evaluating parameter robustness and the cautious interpretation of commonly used performance metrics like KGE and NSE.
• Integration of soil stoniness correction to improve the accuracy of water content and conductivity data, leading to better model performance.

Funding

• Not specified in the provided text.

Citation

@article{Belfort2025Hydrodynamic,
  author = {Belfort, Benjamin and Alzein, Aya and Cotel, Solenn and Julien, Anthony and Weill, Sylvain},
  title = {Hydrodynamic Parameter Estimation for Simulating Soil-Vegetation-Atmosphere Hydrology Across Forest Stands in the Strengbach Catchment},
  journal = {Hydrology},
  year = {2025},
  doi = {10.3390/hydrology13010011},
  url = {https://doi.org/10.3390/hydrology13010011}
}