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Open Access Green as soon as Postprint is submitted to ZB.
Predicting subgrid variability of soil water content from basic soil information.
Geophys. Res. Lett. 42, 789-796 (2015)
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.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Predict ; Soil Water Content ; Subgrid Variability; Remote-sensing Footprints; Moisture Variability; Temporal Dynamics; Heterogeneity; Patterns; Models; Field
ISSN (print) / ISBN
0094-8276
e-ISSN
1944-8007
Journal
Geophysical Research Letters
Quellenangaben
Volume: 42,
Issue: 3,
Pages: 789-796
Publisher
Wiley
Publishing Place
Hoboken, NJ
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Soil Ecology (IBOE)