Using magnetic susceptibility mapping for assessing soil degradation due to water erosion

Ondřej Jakšík, Radka Kodešová, Aleš Kapička, Aleš Klement, Miroslav Fér and Antonín Nikodem
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Ondřej Jakšík: Department of Soil Science and Soil Protection, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic;
Radka Kodešová: Department of Soil Science and Soil Protection, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic;
Aleš Kapička: Institute of Geophysics of the CAS, Prague, Czech Republic
Aleš Klement: Department of Soil Science and Soil Protection, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic;
Miroslav Fér: Department of Soil Science and Soil Protection, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic;
Antonín Nikodem: Department of Soil Science and Soil Protection, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic;

Soil and Water Research, 2016, vol. 11, issue 2, 105-113

Abstract: This study focused on developing a method for estimating topsoil organic carbon content from measured mass-specific magnetic susceptibility in Chernozems heavily affected by water erosion. The study was performed on a 100 ha area, whereby 202 soil samples were taken. A set of soil samples was divided into 3 subsets: A (32 samples), B (67 samples), and C (103 samples). The mass-specific magnetic susceptibility using low (χlf) and high (χhf) frequency, and organic carbon content were measured at all soil samples. The contents of iron and manganese, extracted with a dithionite-citrate solution (Fed, Mnd) and ammonium oxalate (Feo, Mno), were quantified in A and B samples. Models for predicting organic carbon content from magnetic susceptibilities were designed as follows: (1) subset A was used as the training set for calibration, and subsets B and C were used as the test sets for model validation, either separately (subset B only), or together (merged subsets B and C); (2) merged subsets A and B were used as the training set and subset C was used as the test set. Results showed very close correlations between organic carbon content and all measured soil properties. Obtained models relating organic carbon content to mass-specific magnetic susceptibility successfully predicted soil organic carbon contents.

Keywords: arable land; geomorphologically diverse areas; Chernozem; magnetic susceptibility; soil organic carbon; spatial variability (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnlswr:v:11:y:2016:i:2:id:233-2015-swr

DOI: 10.17221/233/2015-SWR

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