Journal Article

FZJ-2015-01605

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Predicting subgrid variability of soil water content from basic soil information

Qu, W. (Corresponding Author)FZJ* ; Bogena, H. R. ; Huisman, J. A.FZJ* ; Vanderborght, J.FZJ* ; Schuh, M. ; Priesack, E. ; Vereecken, H.FZJ*

2015
Wiley Hoboken, NJ

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Please use a persistent id in citations: http://hdl.handle.net/2128/16082  doi:10.1002/2014GL062496

Abstract: 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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Contributing Institute(s):

1. Agrosphäre (IBG-3)

Research Program(s):

1. 255 - Terrestrial Systems: From Observation to Prediction (POF3-255) (POF3-255)

Appears in the scientific report 2015

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Database coverage:
; ; Current Contents - Physical, Chemical and Earth Sciences ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection

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