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Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
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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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Schlagwörter
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
Zeitschrift
Geophysical Research Letters
Quellenangaben
Band: 42,
Heft: 3,
Seiten: 789-796
Verlag
Wiley
Verlagsort
Hoboken, NJ
Nichtpatentliteratur
Publikationen
Begutachtungsstatus
Peer reviewed
Institut(e)
Institute of Soil Ecology (IBOE)