Root-zone ECa measurement using EM38 and investigation of spatial interpolation techniques

Abstract

In arable farming (e.g. sugar-beet, onion, potato, carrot, etc.), plant root activities primarily occur within the top 0.3 m of soil layer. Therefore, measurement of soil spatial variability and identifying field-scale heterogeneities of this top layer is very important from the perspective of site specific crop management. Apparent soil electrical conductivity (EC_a), which is related to different soil physical properties, such as clay content, moisture content, bulk density, pH and salinity, can be used to determine the soil spatial variability in a convenient way. Electromagnetic induction based EM38 instrument when placed on ground can measure soil EC_a upto a depth of 0.75 m in horizontal dipole mode and 1.5 m in vertical dipole mode. Numerous researchers used EM38 to measure depth weighted EC_a for discrete soil depth intervals; however, there is no simple technique that can be used to measure EC_a in top 0.3 m soil layer. To visualize EC_a variations in a field, EC_a mapping is also an important aspect of precision agriculture. Furthermore, the accuracy of interpolation methods for spatially varying soil properties has been analysed in several studies. However, a large discrepancy exists among the findings of the researchers. <br/>The objectives of this study were to find a simple method to measure root-zone (top 0.3m) soil EC_a with the help of an EM38 and to check if it can be representative of the measured soil physical properties. Further intent of this study was to investigate different deterministic, geo-statistical and hybrid interpolation techniques for EC_a and soil properties mapping. To evaluate the accuracy of maps using relatively a fine (e.g. 10.5x10.5 m) and a coarse (21x21 m) grid size was also a sub-objective of this study.<br/> A simple method has been developed based on the electromagnetic induction theory to determine the EC_a of root-zone soil layer. The EM38 was placed in both horizontal and vertical modes at 0, 15, 30. 60, 90 and 120 cm above soil surface to get the depth weighted EC_a. From this depth weighted EC_a profile, root-zone EC_a was calculated. Two equations were derived for both horizontal and vertical dipole modes. The EC_a measured from top 0.3 m in horizontal and vertical dipole modes was correlated with soil physical properties such as, clay content, moisture content, bulk density, pH and electrical conductivity. Mapping techniques investigated in this study were comprised on deterministic (inverse distance weighting, spline), geostatistical (ordinary kriging, universal kriging) and hybrid (Co-kriging) interpolation techniques. Root mean square error (RMSE) was used to compare the accuracy of different interpolation techniques for EC_a and different soil properties mapping. To evaluate the accuracy of maps between a fine and a coarse grid size, cross validation technique was used.<br/> In horizontal dipole mode, about 57.70, 19.00, 11.15 and 7.27% response was calculated whereas in vertical dipole mode 50.20, 19.60, 13.40 and 9.25% response was calculated from 0-0.3, 0.3-0.6, 0.6-0.9 and 0.9-1.2 m depth respectively. As EC_a in horizontal mode can give better response from top soil, therefore, 57.70% of EC_a (H) is the root-zone EC_a. Positive correlation between EC_a and clay content, MC, pH and BD conclude that these soil properties contribute to soil EC_a. All techniques showed comparable results, however, Co-kriging outperformed slightly over other techniques. Ordinary kriging gave better predictions for clay (RMSE = 2.03) whereas universal kriging interpolated pH with lowest RMSE (RMSE = 0.226). The fine grid size (10.Sm) gave better result (R² = 0.67) than a coarse grid size (R² = 0.55).<br/> Our technique is very simple and can be used easily by taking a few EM38 readings at various height above ground on a field level. Different relations can be developed for different types of soils with varying soil properties. Root-zone EC_a measurement and mapping can be used for better soil management in arable farming.