Abstract

Diagnosis of soil salinity and characterizing its spatial variability both vertically and horizontally are needed to establish control measures in irrigated agriculture. In this regard, it is essential that salinity development in varying soil depths be known temporally and spatially. Apparent soil electrical conductivity, measured by electromagnetic induction instruments, has been widely used as an auxiliary variable to estimate spatial distribution of field soil salinity. The main objectives of this paper were adopted a mobile electromagnetic induction (EMI) system to perform field electromagnetic (EM) survey in different soil layers, to evaluate the uncertainty through Inverse Distance Weighted (IDW) and Ordinary Kriging (OK) methods, and to determine which algorithm is more reliable for the local and spatial uncertainty assessment. Results showed that EM38 data from apparent soil electrical conductivity are highly correlated with salinity, more accurate for estimating salinity from multiple linear regression models, which the correlation coefficient of 0 - 20, 20 - 40, 40 - 60 and 60 - 80 cm were 0.9090, 0.9228, 0.896 and 0.9085 respectively. The comparison showed that the prediction accuracy of two methods also displays good performance for soil salinity, the estimation precision of IDW method (with E = 0.8873, 0.9075, 0.8483 and 0.901, RPD = 9.64, 8.01, 8.17 and 11.23 in 0 - 20, 20 - 40. 40 - 60 and 60 - 80 cm soil layers, respectively) was superior to that of OK (with E = 0.8857, 0.872, 0.8744 and 0.8822, RPD = 9.44, 7.83, 8.52 and 10.88, respectively), but differences of two methods in predictions are not significant. The obtained salinity map was helpful to display the spatial patterns of soil salinity and monitor and evaluate the management of salinity.

Highlights

  • Soil salinity is the most serious environmental issue, and the most frequently cited soil and agricultural utilization problem for farmers in the arid or semi-arid regions, especially the newly-reclaimed desertification lands in China [1]

  • Fifty sites out of the 70 in situ sampling sites were selected for the spatial simulation of soil salinity, and the rest 20 sites were used for validation of Inverse Distance Weighted (IDW), Ordinary Kriging (OK) algorithms

  • The total dissolved salts (TDS) data was selected as the dependent variable and apparent soil electrical conductivity (EMh and EMv) made by the EM38 as the independent variable

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Summary

Introduction

Soil salinity is the most serious environmental issue, and the most frequently cited soil and agricultural utilization problem for farmers in the arid or semi-arid regions, especially the newly-reclaimed desertification lands in China [1]. Salinization of irrigated lands is a common phenomenon wherever irrigation is practiced under arid or semi-arid conditions. Salinization is accelerated when the field is underlain with a shallow, semi-confined aquifer exerting upward hydraulic pressure, thereby impeding drainage of the overlying soil layers [2]-[4]. To prevent further soil degradation, soil salinity monitoring is essential so that proper and timely decisions regarding soil management can be made. For this purpose, precision agriculture can be used. The EM38 offer the potential to measure numerous soils attributes without the need for destructive sampling

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