Predicting subgrid variability of soil water content from basic soil information

W. Qu, H. R. Bogena, J. A. Huisman, J. Vanderborght, M. Schuh, E. Priesack, H. Vereecken

Research output: Contribution to journalArticlepeer-review

54 Scopus citations


Knowledge of unresolved soil water content variability within model grid cells (i.e., subgrid variability) is important for accurate predictions of land-surface energy and hydrologic fluxes. Here we derived a closed-form expression to describe how soil water content variability depends on mean soil water content (σθ(<θ>)) using stochastic analysis of 1-D unsaturated gravitational flow based on the van Genuchten-Mualem (VGM) model. A sensitivity analysis showed that the n parameter strongly influenced both the shape and magnitude of the maximum of σθ(<θ>). The closed-form expression was used to predict σθ(<θ>) for eight data sets with varying soil texture using VGM parameters obtained from pedotransfer functions that rely on available soil information. Generally, there was good agreement between observed and predicted σθ(<θ>) despite the obvious simplifications that were used to derive the closed-form expression. Furthermore, the novel closed-form expression was successfully used to inversely estimate the variability of hydraulic properties from observed σθ(<θ>) data.

Original languageEnglish
Pages (from-to)789-796
Number of pages8
JournalGeophysical Research Letters
Issue number3
StatePublished - 16 Feb 2015
Externally publishedYes


  • predict
  • soil water content
  • subgrid variability


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