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

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