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Estimation of soil water content using electromagnetic induction sensors under different land uses

Clinton Mensah, Yeukai Katanda, Mano Krishnapillai, Mumtaz Cheema, Lakshman Galagedara

2023Environmental Research Communications12 citationsDOIOpen Access PDF

Abstract

Abstract The complex nature of podzolic soils makes investigating their subsurface challenging. Near-surface geophysical techniques, like electromagnetic induction (EMI), offer significant assistance in studying podzolic soils. Multi-coil (MC-EMI) and multi-frequency (MF-EMI) sensors were selected to maximize soil water content (SWC) prediction in this study. The objectives were to (i) compare apparent electrical conductivity (EC a ) measurements from the MC and MF-EMI sensors under different land use conditions, (ii) investigate the spatial variation of EC a , SWC, texture, soil organic matter (SOM), and bulk density (BD) under different land use conditions, and (iii) use statistical and geostatistical analysis to evaluate the effectiveness of EC a measurements in characterizing SWC under different land use conditions, considering the texture, SOM, and BD contents. The study found that MC-EMI had statistically significant relations (p-value < 0.05) with SWC relative to the MF-EMI. Multiple linear regression (MLR) models were also shown to be more effective in representing SWC variations (higher coefficient of determination and lower root mean square error) than simple linear regression models. MC-EMI sensor provided better SWC predictions compared to the MF-EMI sensor, possibly due to larger sampling depths differences between time domain reflectometry measured SWC (SWC TDR ) and MF-EMI sensor than those between SWC TDR and MC-EMI sensor. Lastly, cokriging of measured SWC was found to offer more accurate maps than cokriging of predicted SWC obtained from MLR across different land use conditions. The study has shown that EMI may not be highly effective for shallow depths, and EC a can be affected by various soil properties, making it difficult to extrapolate other parameters. However, EMI still shows promise as a reliable method for predicting SWC in boreal podzolic soils. Research into EMI’s usefulness for this purpose has yielded promising results, as indicated in this study. Further investigation is needed to fully harness the potential of this promising technique.

Topics & Concepts

EMISoil textureSoil waterSoil scienceEnvironmental scienceReflectometryLinear regressionSampling (signal processing)Electromagnetic interferenceWater contentMean squared errorRemote sensingStatisticsMathematicsGeologyTime domainEngineeringComputer scienceGeotechnical engineeringElectronic engineeringElectrical engineeringComputer visionFilter (signal processing)Soil Moisture and Remote SensingSoil Geostatistics and MappingSoil and Unsaturated Flow
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