Decharme (2025) A process-based modeling of soil organic matter physical properties for land surface models – Part 1: Soil mixture theory

Identification

• Journal: Geoscientific model development
• Year: 2025
• Date: 2025-12-02
• Authors: Bertrand Decharme
• DOI: 10.5194/gmd-18-9349-2025

Research Groups

• Météo-France, CNRS, Univ. Toulouse, CNRM, Toulouse, France

Short Summary

This study proposes a process-based framework, grounded in soil mixture theory, to accurately model soil organic matter physical properties in land surface models, demonstrating significant improvements over empirical approaches through validation against experimental and in situ datasets.

Objective

• To propose a robust, process-based framework for accurately representing the physical properties of soil organic matter (SOM) in Land Surface Models (LSMs).
• To derive a physically consistent volumetric fraction of SOM using mass-volume relationships and a refined soil organic carbon (SOC)-to-SOM conversion.
• To propose accurate parameterizations for SOM hydrodynamic properties (specifically for the Brooks and Corey model) as functions of bulk density and depth, informed by recent observational datasets.

Study Configuration

• Spatial Scale: Global and regional (LSMs), validated with local experimental binary mixtures and large in situ datasets across Europe and globally.
• Temporal Scale: Focuses on static soil physical properties, which are parameterized for use in dynamic land surface models operating over various temporal scales (e.g., present-day climate, centennial-scale processes).

Methodology and Data

• Models used:
  • Soil mixture theory (Stewart et al., 1970; Adams, 1973; Raats, 1987; Rühlmann et al., 2006; Reynolds et al., 2020)
  • Brooks and Corey (1964) model for soil water retention and hydraulic conductivity.
  • H-model (Ruehlmann, 2020) for SOC-to-SOM conversion and mineral particle density.
  • Pedotransfer functions (PTFs) from Liu and Lennartz (2019) and Liu et al. (2022) for SOM hydrodynamic properties.
  • PTF from Morris et al. (2022) for saturated hydraulic conductivity of peat.
  • Cosby et al. (1984) PTF for mineral soil hydraulic properties.
  • Lawrence and Slater (2008) and Chen et al. (2012) parameterizations as benchmarks.
  • Arithmetic, geometric, harmonic, and geo-harmonic mixing rules for combining mineral and organic properties.
• Data sources:
  • Experimental binary mixtures:
    • Walczak et al. (2002) (peat-sand mixtures, porosity)
    • Willaredt and Nehls (2021) (compost-crushed brick mixtures, porosity)
    • Arkhangelskaya and Telyatnikova (2023) (peat-sand mixtures, thermal diffusivity)
  • Natural soils (in situ/laboratory measurements):
    • Keller and Håkansson (2010) (Nordic agricultural soils, bulk density, texture, SOM)
    • Arkhangel'skaya (2009) (Russian soils, thermal and structural properties)
    • Kristensen et al. (2019) (SPADE14 harmonized European soil profile database, bulk density, porosity, SOC, water retention)
    • Gupta et al. (2021) (SoilKsatDB global database, saturated hydraulic conductivity, water retention, texture, bulk density, SOC)

Main Results

• The proposed process-based framework provides a physically consistent estimation of the soil organic matter volumetric fraction (fvom), resolving conceptual inconsistencies in previous SOC-based empirical parameterizations.
• Validation against experimental binary mixtures confirms the internal consistency of the soil mixture theory for porosity and dry thermal conductivity, with non-linear mixing rules (geometric, geo-harmonic mean) outperforming arithmetic means for conductivity.
• The framework significantly improves predictions of soil porosity (w_sat) and water retention properties (volumetric water content at various matric potentials) across diverse natural soil datasets, particularly in SOM-rich soils, compared to mineral-only or simplified SOC-based approaches.
• Reconstructed apparent bulk density of SOM (ρbom) and organic porosity (wsatom) are consistent with observed ranges for peat soils (ρbom mainly between 10 kg/m³ and 400 kg/m³, wsatom from 0.8 to 0.95 m³/m³).
• For saturated hydraulic conductivity (k_sat), the framework shows improved predictive skill (r² = 0.21, 0.46 on log-transformed scale) over existing methods, with non-negligible improvements observed specifically in SOM-rich soils (SOC > 8%).

Contributions

• Introduces a novel, physically consistent, process-based framework for representing soil organic matter physical properties in Land Surface Models (LSMs), grounded in soil mixture theory.
• Resolves a long-standing conceptual inconsistency in LSMs by accurately distinguishing between soil organic carbon (SOC) and total soil organic matter (SOM) and deriving the "true" volumetric fraction of SOM from fundamental mass-volume relationships.
• Provides new, observationally informed parameterizations for the hydrodynamic properties (air-entry pressure head, pore-size distribution index, saturated hydraulic conductivity) of the organic matter domain for the Brooks and Corey model, as functions of its apparent bulk density and depth.
• Demonstrates improved accuracy for predicting soil porosity and water retention curves across a wide range of soil types and organic matter contents, offering a more realistic representation of soil structure and water dynamics.
• Proposes and validates appropriate mixing rules (arithmetic for porosity and heat capacity, geometric/geo-harmonic for conductivities) for combining mineral and organic soil components.
• The framework is designed for direct implementation in global and regional LSMs, requiring only standard input data (SOC content, dry bulk density, soil texture) commonly available in global soil databases, without needing additional calibration.

Funding

• ANR – France 2030 (PEPR TRACCS program, grant no. ANR-22-EXTR-0009)
• European Union (Horizon 2020, grant no. 101003536, ESM2025 Earth System Models for the Future)
• French National Research Agency (ANR) (Arctic-Peat, grant no. ANR-20-CE01-0001)
• French National Research Agency (ANR) (PEACE within the FairCarboN exploratory program of France 2030, grant no. ANR-22-PEXF-0011)

Citation

@article{Decharme2025processbased,
  author = {Decharme, Bertrand},
  title = {A process-based modeling of soil organic matter physical properties for land surface models – Part 1: Soil mixture theory},
  journal = {Geoscientific model development},
  year = {2025},
  doi = {10.5194/gmd-18-9349-2025},
  url = {https://doi.org/10.5194/gmd-18-9349-2025}
}