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Characterizing Scale‐ and Location‐Dependent Correlation of Water Retention Parameters with Soil Physical Properties Using Wavelet Techniques
Author(s) -
Shu Qiaosheng,
Liu Zuoxin,
Si Bingcheng
Publication year - 2008
Publication title -
journal of environmental quality
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.888
H-Index - 171
eISSN - 1537-2537
pISSN - 0047-2425
DOI - 10.2134/jeq2007.0179
Subject(s) - soil science , wavelet , water retention , water content , water retention curve , pedotransfer function , bulk density , environmental science , soil water , mathematics , geology , geotechnical engineering , hydraulic conductivity , artificial intelligence , computer science
Understanding the correlation between soil hydraulic parameters and soil physical properties is a prerequisite for the prediction of soil hydraulic properties from soil physical properties. The objective of this study was to examine the scale‐ and location‐dependent correlation between two water retention parameters (α and n ) in the van Genuchten (1980) function and soil physical properties (sand content, bulk density [Bd], and organic carbon content) using wavelet techniques. Soil samples were collected from a transect from Fuxin, China. Soil water retention curves were measured, and the van Genuchten parameters were obtained through curve fitting. Wavelet coherency analysis was used to elucidate the location‐ and scale‐dependent relationships between these parameters and soil physical properties. Results showed that the wavelet coherence between α and sand content was significantly different from red noise at small scales (8–20 m) and from a distance of 30 to 470 m. Their wavelet phase spectrum was predominantly out of phase, indicating negative correlation between these two variables. The strong negative correlation between α and Bd existed mainly at medium scales (30–80 m). However, parameter n had a strong positive correlation only with Bd at scales between 20 and 80 m. Neither of the two retention parameters had significant wavelet coherency with organic carbon content. These results suggested that location‐dependent scale analyses are necessary to improve the performance for soil water retention characteristic predictions.