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Quantitative mapping of soil salinity using the DUALEM‐21S instrument and EM inversion software

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Title Quantitative mapping of soil salinity using the DUALEM‐21S instrument and EM inversion software
Not Available
 
Creator Triven Koganti
Bhaskar Narjary
Ehsan Zare
Aslam Latif Pathan
Jingyi Huang
John Triantafilis
 
Subject digital soil mapping (DSM)
electrical conductivity
electromagnetic induction
quasi‐3d inversion
soil salinity
 
Description Not Available
To generate baseline data for the purpose of monitoring the efficacy of remediation
of a degraded landscape, we demonstrate a method for 3‐dimensional mapping of
electrical conductivity of saturated soil paste extract (ECe) across a study field in central
Haryana, India. This is achieved by establishing a linear relationship between calculated
true electrical conductivity (σ) and laboratory measured ECe at various depths
(0–0.3, 0.3–0.6, 0.6–0.9, and 0.9–1.2 m). We estimate σ by inverting DUALEM‐21S
apparent electrical conductivity (ECa) data using a quasi‐3‐dimensional inversion algorithm
(EM4Soil‐V302). The best linear relationship (ECe = −11.814 + 0.043 × σ) was
achieved using full solution (FS), S1 inversion algorithm, and a damping factor (λ) of 0.6
that had a large coefficient of determination (R2 = 0.84). A cross‐validation technique
was used to validate the model, and given the high accuracy (RMSE = 8.31 dS m−1),
small bias (mean error = −0.0628 dS m−1), large R2 = 0.82, and Lin's concordance
(0.93), between measured and predicted ECe, we were well able to predict the ECe
distribution at all the four depths. However, the predictions made in the topsoil (0–
0.3 m) at a few locations were poor due to limited data availability in areas where
ECa changed rapidly. In this regard, improvements in prediction can be achieved by
collection of ECa in more closely spaced transects, particularly in areas where ECa varies
over short spatial scales. Also, equivalent results can be achieved using smaller
combinations of ECa data (i.e., DAULEM‐1S, DUALEM‐2S), although with some loss in
precision, bias, and concordance.
 
Date 2019-10-28T04:24:15Z
2019-10-28T04:24:15Z
2018-04-11
 
Type Research Paper
 
Identifier Koganti T, Narjary B, Zare E, Pathan AL, Huang J, Triantafilis J. Quantitative mapping of soil salinity using the DUALEM‐21S instrument and EM inversion software. Land Degrad Dev. 2018;29:1768–1781
Not Available
http://krishi.icar.gov.in/jspui/handle/123456789/24067
 
Language English
 
Relation Not Available;
 
Publisher Wiley