Search

Land development in the form of irrigation has led to increased agricultural productivity, but natural stores of connate salt have led to salinization. To manage salinity, baseline information about the electrical conductivity of a saturated soil paste extract (ECe – dS/m) is necessary. To value add to the limited ECe that can be collected, proximal sensed data from electromagnetic (EM) induction instruments (e.g. EM38) are increasingly being used because the measured apparent soil electrical conductivity (ECa – mS/m) can be correlated with measured topsoil (0–0.3 m), subsurface (0.3–0.6 m), subsoil (0.6–0.9 m) and deep subsoil (0.9–1.2 m) ECe. However, errors may be introduced in prediction, given an EM38 measures ECa at depths of 0–1.5 m in vertical (EM38v) and 0–0.75 m in horizontal (EM38h) mode. To overcome this, we develop a linear regression (LR) between estimates of electrical conductivity (σ – mS/m), inverted from EM38v and EM38h using a quasi‐3d algorithm and measured ECe at the same depths. First, the LR was established (using R2) between estimates of σ inverted from ECa at heights of 0.5 (EM38v0.5 and EM38h0.5) and 0 m (EM38v0 and EM38h0), either alone or in combination, as well as in vertical mode (i.e. EM38v0.5 and EM38v0). ECa were also degraded (100%, 80%, 60% and 40%) to compare loss of prediction agreement (Lin's concordance) and accuracy (root mean square error). We use Normalized Difference Vegetation Index (NDVI) to qualitatively indicate crop growth. Moderate coefficient of determination (R2) was achieved between σ and ECe when we use the EM38v0.5 and EM38h0.5 (0.65) and EM38v0.5 and EM38v0 (0.69), but strong R2 was achieved using EM38v0 and EM38h0 (0.78) and in combination with the EM38v0.5 and EM38h0.5 (0.71). However, while good agreement (Lin's > 0.8) was achieved, during a leave‐one‐out cross‐validation for most EM38 combinations, the best result was achieved using EM38v0 and EM38h0 (Lin's = 0.87). There was also loss in prediction agreement and accuracy using any of the degraded ECa data sets, however. The final 3d map of ECe, as well as NDVI, showed where highly saline (>8 dS/m) areas in the west of most fields resulted as a function of leakage from the Kham‐rean Canal and topography (i.e. lower lying areas). We conclude the approach has broad application to map, potentially manage and monitor large areas of north‐east Thailand. [ABSTRACT FROM AUTHOR]

Most cultivated upland areas of northeast Thailand are characterized by sandy and infertile soils, which are difficult to improve agriculturally. Information about the clay (%) and cation exchange capacity (CEC—cmol(+)/kg) are required. Because it is expensive to analyse these soil properties, electromagnetic (EM) induction instruments are increasingly being used. This is because the measured apparent soil electrical conductivity (ECa—mS/m), can often be correlated directly with measured topsoil (0–0.3 m), subsurface (0.3–0.6 m) and subsoil (0.6–0.9 m) clay and CEC. In this study, we explore the potential to use this approach and considering a linear regression (LR) between EM38 acquired ECa in horizontal (ECah) and vertical (ECav) modes of operation and the soil properties at each of these depths. We compare this approach with a universal LR relationship developed between calculated true electrical conductivity (σ—mS/m) and laboratory measured clay and CEC at various depths. We estimate σ by inverting ECah and ECav data, using a quasi-3D inversion algorithm (EM4Soil). The best LR between ECa and soil properties was between ECah and subsoil clay (R2 = 0.43) and subsoil CEC (R2 = 0.56). We concluded these LR were unsatisfactory to predict clay or CEC at any of the three depths, however. In comparison, we found that a universal LR could be established between σ with clay (R2 = 0.65) and CEC (R2 = 0.68). The LR model validation was tested using a leave-one-out-cross-validation. The results indicated that the universal LR between σ and clay at any depth was precise (RMSE = 2.17), unbiased (ME = 0.27) with good concordance (Lin's = 0.78). Similarly, satisfactory results were obtained by the LR between σ and CEC (Lin's = 0.80). We conclude that in a field where a direct LR relationship between clay or CEC and ECa cannot be established, can still potentially be mapped by developing a LR between estimates of σ with clay or CEC if they all vary with depth. [ABSTRACT FROM AUTHOR]