, Volume 22, Issue 3, pp 677–698 | Cite as

Quantifying the Uncertainty in Modeled Water Drainage and Nutrient Leaching Fluxes in Forest Ecosystems

  • Gregory van der HeijdenEmail author
  • Armand Hinz
  • Serge Didier
  • Claude Nys
  • Etienne Dambrine
  • Arnaud Legout


In terrestrial ecosystem studies, water drainage and nutrient leaching in the soil profile are estimated with hydrological models. Comparing modeled results to empirical data or comparing data from different models is, however, difficult because the uncertainty of input–output budget predictions is often unknown. In this study, we developed a procedure combining a Generalized Likelihood Uncertainty Estimation and a Monte-Carlo modeling approach to estimate uncertainty in model parameter estimates and model outputs water drainage and nutrient leaching fluxes for the WatFor water balance model. This procedure was then applied to compare different model optimization strategies (daily soil moisture measurements, monthly measurements of chloride concentrations in soil solution, and the elution of a concentrated chloride) at the same experimental site in a 90-year-old European beech (Fagus sylvatica L.) forest in Brittany (France). We show that the monitoring data of natural variations of chloride concentrations in soil solution were the most efficient dataset to calibrate the WatFor model compared to the soil moisture and chloride tracing experimental data. We also show that water tracing experimental data are the most efficient data to estimate the preferential flow generation model parameters. The optimization strategy had little influence on the predicted water drainage flux and nutrient leaching flux at the root zone boundary on a yearly time scale but influenced water and nutrient fluxes in the topsoil layers.


water tracing water balance model chloride uncertainty input–output budget forest ecosystem preferential flow nutrient leaching soil hydrology 



We would like to thank all the technicians without whom this project would not have been possible, in particular C. Antoine, L. Gelhaye and S. Bienaimé from INRA Nancy. This work was financed by the EFPA department (INRA), the GIP ECOFOR and by the Office National des Forêts in the context of one of the Environmental Research sites on “Lowland beech” part of F-ore-T network. The UR-1138 INRA—Biogéochimie des Ecosystèmes Forestiers is supported by a grant overseen by the French National Research Agency (ANR) as part of the “Investissements d’Avenir” program (ANR-11-LABX-0002-01, Lab of Excellence ARBRE).

Supplementary material

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Supplementary material 1 (PDF 161 kb)


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Gregory van der Heijden
    • 1
    Email author
  • Armand Hinz
    • 1
  • Serge Didier
    • 1
  • Claude Nys
    • 1
  • Etienne Dambrine
    • 2
  • Arnaud Legout
    • 1
  1. 1.INRA UR 1138 BEFChampenouxFrance
  2. 2.INRA UMR CARRTELL (INRA-Univ Savoie)Le Bourget-du-LacFrance

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