Multifrequency electromagnetic induction soil moisture characterization under different land uses in western Newfoundland
Identifying and characterizing the spatial patterns in soil moisture variability under different land use conditions is crucial for agriculture, forestry, and civil and environmental engineering. Yet employing multifrequency (MF) electromagnetic induction (EMI) techniques to carry out this task is u...
| Published in: | Canadian Journal of Soil Science |
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| Main Authors: | , , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Canadian Science Publishing
2023
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| Subjects: | |
| Online Access: | http://dx.doi.org/10.1139/cjss-2022-0102 https://cdnsciencepub.com/doi/full-xml/10.1139/cjss-2022-0102 https://cdnsciencepub.com/doi/pdf/10.1139/cjss-2022-0102 |
| Summary: | Identifying and characterizing the spatial patterns in soil moisture variability under different land use conditions is crucial for agriculture, forestry, and civil and environmental engineering. Yet employing multifrequency (MF) electromagnetic induction (EMI) techniques to carry out this task is under-represented in boreal podzolic soils. This study ( i) compared four frequencies (∼2.8–80 kHz) for shallow mapping of soil moisture measured with a time–domain reflectometry at 0–20 cm soil depth under three different land use conditions (agricultural land, field road, and a recently cleared natural forest), ( ii) developed a relationship between apparent electrical conductivity (EC a ) measured using multifrequency EMI (GEM-2) and soil moisture, and ( iii) assessed the effectiveness of EC a as an auxiliary variable in predicting soil moisture variations under different land use conditions. The means of EC a measurements were calculated for the exact sampling location (ground truth data) in each land use condition at a research site, Pasadena, NL, Canada. Soil moisture–EC a linear regression models for the three land use conditions were only statistically significant for 38.3 kHz frequency and were further analyzed. Further statistical analysis revealed that EC a was primarily controlled by soil moisture for the three land use conditions, with the natural forest possessing the highest mean EC a and soil moisture. Geostatistical analysis revealed that cokriging EC a with less densely collected soil moisture improved the characterization accuracy of soil moisture variability across the different land use conditions. These results reveal the effectiveness of the georeferenced MF–EMI technique to rapidly assess intrafield soil moisture variability under different land uses. |
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