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Utilizing a DUALEM ‐421 and inversion modelling to map baseline soil salinity along toposequences in the Hunter Valley Wine district
Author(s) -
Stockmann U.,
Huang J.,
Minasny B.,
Triantafilis J.
Publication year - 2017
Publication title -
soil use and management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.709
H-Index - 81
eISSN - 1475-2743
pISSN - 0266-0032
DOI - 10.1111/sum.12352
Subject(s) - soil science , soil salinity , salinity , electrical resistivity and conductivity , inversion (geology) , soil water , conductivity , environmental science , electromagnetic induction , geology , hydrology (agriculture) , geotechnical engineering , geomorphology , electromagnetic coil , chemistry , physics , oceanography , quantum mechanics , structural basin
Abstract In the oldest commercial wine district of Australia, the Hunter Valley, there is the threat of soil salinization because marine sediments underlie the area. To understand the risk requires information about the spatial distribution of soil properties. Electromagnetic ( EM ) induction instruments have been used to identify and map the spatial variation of average soil salinity to a certain depth. However, soils vary with depth dependent on soil forming factors. We collected data from a single‐frequency and multiple‐coil DUALEM ‐421 along a toposequence. We inverted this data using EM 4Soil software and evaluated the resultant 2‐dimensional model of true electrical conductivity ( σ – mS /m) with depth against electrical conductivity of saturated soil pastes ( EC p – dS /m). Using a fitted linear regression ( LR ) model calibration approach and by varying the forward model (cumulative function‐ CF and full solution‐ FS ), inversion algorithm (S1 and S2), damping factor ( λ ) and number of arrays, we determined a suitable electromagnetic conductivity image ( EMCI ), which was optimal ( R 2 = 0.82) when using the full solution, S2, λ = 3.6 and all six coil arrays. We conducted an uncertainty analysis of the LR model used to estimate the electrical conductivity of the saturated soil‐paste extract ( EC e – dS /m). Our interpretation based on estimates of EC e suggests the approach can identify differences in salinity, how these vary with parent material and how topography influences salt distribution. The results provide information leading to insights into how soil forming factors and agricultural practices influence salinity down a toposequence and how this can guide soil management practices.