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An error budget for mapping field-scale soil salinity at various depths using different sources of ancillary data
Journal article   Peer reviewed

An error budget for mapping field-scale soil salinity at various depths using different sources of ancillary data

J. Huang, E.G. Barrett-Lennard, T. Kilminster, A. Sinnott and J. Triantafilis
Soil Science Society of America Journal, Vol.79(6), pp.1717-1728
2015
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Abstract

To manage soil salinity, farmers need to map its variation, often quantified as the electrical conductivity of a saturated soil-paste extract (ECe, dS m-1). However, ECe determination is time-consuming and expensive. Previous studies have evaluated the use of digital elevation models (DEMs, i.e., elevation), airborne γ-ray (γ-ray) spectrometry (i.e., K, U, and Th) and electromagnetic (EM, i.e., EM38 and EM34) data to map ECe at the district scale. Herein we use similar ancillary data set and empirical best linear unbiased prediction (E-BLUP) to make maps of ECe at different depth intervals (0–0.25, 0.25–0.50, and 0.50–0.75 m) at the field scale. The ancillary data was collected using a ground-based mobile sensing system which included; a GPS which provided spatial coordinates (Easting, Northing), a RS700 (γ-ray) mobile spectrometer, and a DUALEM-1. An error budget procedure was conducted to quantify the model, input, and individual covariate errors of ECe. Results show that while none of the γ-ray data were significant, scaled Easting, elevation, and 1-m horizontal coplanar (1mHcon) were optimal for mapping ECe at 0 to 0.25 m, while 1mHcon was optimal at 0.25 to 0.50 m and 0.50 to 0.75 m. Among all the individual covariate errors for mapping 0- to 0.25-m ECe, elevation (0.40 dS m-1) was smallest, followed by 1mHcon (2.23 dS m-1). To reduce error, additional soil samples are necessary to prevent the edge effect of the kriging process. Additionally, inversion of EM data could be used to improve ECe mapping considering the relatively large model error associated with EM data in the subsoil of inverted salinity profiles.

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Collaboration types
Domestic collaboration
Citation topics
3 Agriculture, Environment & Ecology
3.45 Soil Science
3.45.1109 Soil Mapping
Web Of Science research areas
Soil Science
ESI research areas
Agricultural Sciences
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