Use of class pedotransfer functions based on texture and bulk density of clods to generate water retention curves

By A. Bruand, P. Fernández, O. Duval. 2003

75 citations recorded by the source corpus.

Abstract. Water retention properties of 219 horizons were measured in Cambisols, Luvisols and Fluvisols, mainly from the Paris basin. We derived class pedotransfer functions (class PTFs) based on texture alone and in a second stage class PTFs based on classes combining texture and clod bulk density. The performance of these two types of PTFs were discussed at −330 and −15000 hPa water potential on an independent set of 221 horizons. Results showed that PTFs based on sets grouped by texture and clod bulk density provide estimates with an accuracy that is (i) greater than with class PTFs based on texture alone, and (ii) similar to the estimation accuracy recorded with continuous PTFs. As a consequence, the lack of interest in class PTFs should be reconsidered to bridge the gap between the available basic soil data and hydraulic properties which are generally missing, particularly when pertinent soil characteristics can be derived from the data available in soil databases. The two types of class PTFs providing gravimetric water contents at seven water potentials ranging from −10 to −15 000 hPa were converted to volumetric water content using the soil bulk density. Finally, the parameters of van Genuchten's water retention curve model were computed for every class PTF.

Subfields: Civil and Structural Engineering, Environmental Engineering, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/33e6e2720dd6522db0c083c0cd7dc3385760816e

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In Civil and Structural Engineering

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In Water Science and Technology

Citations in the corpus

Derivation and validation of pedotransfer functions for estimating soil water retention curve using a variety of soil data (2010, background): “Journal compilation ª 2010 British Society of Soil Science curve for each textural class (e.g. Nemes, 2002; Bruand et al., 2003; Al Majou et al., 2008b).”
Building and testing conceptual and empirical models for predicting soil bulk density (2007, background): “The effect of particle size fractions on soil bulk density is well known, with numerous functions developed using differing components (Manrique & Jones, 1991; Bruand et al., 2003; De Vos et al., 2005) although mostly used in conjunction with organic matter variables.”
Estimating forest soil bulk density using boosted regression modelling (2010, background): “Models can play a crucial role in investigating change in soil organic matter and these often require soil bulk density (q) as an input parameter for calculating hydraulic properties (Bruand et al., 2003) or assessing soil compaction (AbuHamdeh, 2003).”