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Scaling analysis of soil water storage with missing measurements using the second‐generation continuous wavelet transform
Author(s) -
Biswas A.
Publication year - 2014
Publication title -
european journal of soil science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.244
H-Index - 111
eISSN - 1365-2389
pISSN - 1351-0754
DOI - 10.1111/ejss.12145
Subject(s) - transect , spatial variability , wavelet , temporal scales , soil science , neutron probe , spatial ecology , continuous wavelet transform , environmental science , geology , wavelet transform , scale (ratio) , hydrology (agriculture) , discrete wavelet transform , mathematics , geography , statistics , cartography , neutron , oceanography , physics , artificial intelligence , ecology , neutron cross section , neutron temperature , computer science , biology , quantum mechanics , geotechnical engineering
Summary Information on the spatial variability of soil water storage ( SWS ) at different scales is important for understanding various hydrological, ecological and biogeochemical processes in the landscape. However, various obstructions such as roads or water bodies may result in missing measurements and create an irregular spatial series. The wavelet transform can quantify spatial variability at different scales and locations but is restricted to regular measurements. The objective of this study was to analyse the spatial variability of SWS with missing measurements using the second‐generation continuous wavelet transform ( SGCWT ). Soil water content (converted to SWS by multiplying with depth) was measured with a neutron probe and time‐domain reflectrometry along a transect of 128 points. Because there were missing measurements, I used SGCWT to partition the total variation into different scales and locations. Whilst there were some small‐scale variations (< 20 m) along the transect, the medium scale variations (20–70 m with an average of about 30–45 m) were mainly concentrated within the depressions along the transect. The strongest variations were observed at around 90–110 m scale, representing the variations resulting from alternating knolls and depressions. Similar spatial patterns at different scales were observed during different seasons, indicating temporal stability in the spatial pattern of SWS . Among the controlling factors, the wavelet spectra of relative elevation ( RE ) and organic carbon ( OC ) were very similar to that of SWS . The wavelet covariance was also large between SWS and RE and OC at all seasons. As the OC reflects the long‐term history of water availability and might be controlled by topographic setting or elevation, it can be concluded that elevation is an important controlling factor of SWS irrespective of seasons in this type of landscape. The SGCWT provides a new way of analysing the spatial variability of regularly measured soil properties or those with missing measurements.