Soil organic carbon models need independent time-series validation for reliable prediction

Numerical models are crucial to understand and/or predict past and future soil organic carbon dynamics. For those models aiming at prediction, validation is a critical step to gain confidence in projections. With a comprehensive review of similar to 250 models, we assess how models are validated depending on their objectives and features, discuss how validation of predictive models can be improved. We find a critical lack of independent validation using observed time series. Conducting such validations should be a priority to improve the model reliability. Approximately 60% of the models we analysed are not designed for predictions, but rather for conceptual understanding of soil processes. These models provide important insights by identifying key processes and alternative formalisms that can be relevant for predictive models. We argue that combining independent validation based on observed time series and improved information flow between predictive and conceptual models will increase reliability in predictions.

To Access Resource:

Questions? Email Resource Support Contact:

  • opensky@ucar.edu
    UCAR/NCAR - Library

Resource Type publication
Temporal Range Begin N/A
Temporal Range End N/A
Temporal Resolution N/A
Bounding Box North Lat N/A
Bounding Box South Lat N/A
Bounding Box West Long N/A
Bounding Box East Long N/A
Spatial Representation N/A
Spatial Resolution N/A
Related Links

Related Dataset #1 : A Global Database of Soil Respiration Data, Version 5.0

Related Dataset #2 : Soil organic carbon models need independent time-series validation for reliable prediction
Additional Information N/A
Resource Format PDF
Standardized Resource Format PDF
Asset Size N/A
Legal Constraints

Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Access Constraints None
Software Implementation Language N/A

Resource Support Name N/A
Resource Support Email opensky@ucar.edu
Resource Support Organization UCAR/NCAR - Library
Distributor N/A
Metadata Contact Name N/A
Metadata Contact Email opensky@ucar.edu
Metadata Contact Organization UCAR/NCAR - Library

Author Le Noë, J.
Manzoni, S.
Abramoff, R.
Bölscher, T.
Bruni, E.
Cardinael, R.
Ciais, P.
Chenu, C.
Clivot, H.
Derrien, D.
Ferchaud, F.
Garnier, P.
Goll, D.
Lashermes, G.
Martin, M.
Rasse, D.
Rees, F.
Sainte-Marie, J.
Salmon, E.
Schiedung, M.
Schimel, J.
Wieder, William
Abiven, S.
Barré, P.
Cécillon, L.
Guenet, B.
Publisher UCAR/NCAR - Library
Publication Date 2023-05-08T00:00:00
Digital Object Identifier (DOI) Not Assigned
Alternate Identifier N/A
Resource Version N/A
Topic Category geoscientificInformation
Progress N/A
Metadata Date 2025-07-11T15:18:07.426373
Metadata Record Identifier edu.ucar.opensky::articles:26314
Metadata Language eng; USA
Suggested Citation Le Noë, J., Manzoni, S., Abramoff, R., Bölscher, T., Bruni, E., Cardinael, R., Ciais, P., Chenu, C., Clivot, H., Derrien, D., Ferchaud, F., Garnier, P., Goll, D., Lashermes, G., Martin, M., Rasse, D., Rees, F., Sainte-Marie, J., Salmon, E., Schiedung, M., Schimel, J., Wieder, William, Abiven, S., Barré, P., Cécillon, L., Guenet, B.. (2023). Soil organic carbon models need independent time-series validation for reliable prediction. UCAR/NCAR - Library. https://n2t.org/ark:/85065/d76t0rnw. Accessed 06 December 2025.

Harvest Source