Digital mapping of soil salinity in Ardakan region, central Iran

Salinization and alkalinization are the most important land degradation processes in central Iran. In this study we modelled the vertical and lateral variation of soil salinity (measured as electrical conductivity in saturation paste, ECe) using a combination of regression tree analysis and equal-area smoothing splines in a 72,000 ha area located in central Iran. Using the conditioned Latin hypercube sampling method, 173 soil profiles were sampled from the study area, and then analysed for ECe and other soil properties. Auxiliary data used in this study to represent predictive soil forming factors were terrain attributes (derived from a digital elevation model), Landsat 7 ETM+ data, apparent electrical conductivity (ECa)-measured using an electromagnetic induction instrument (EMI), and a geomorphologic surfaces map. To derive the relationships between ECe (from soil surface to 1 m) and the auxiliary data, regression tree analysis was applied. In general, results showed that the ECa surfaces are the most powerful predictors for ECe at three depth intervals (i.e. 0-15, 15-30 and 30-60 cm). In the 60-100 cm depth interval, topographic wetness index was the most important parameter used in regression tree model. Validation of the predictive models at each depth interval resulted in R-2 values ranging from 78% (0-15 cm) to 11% (60-100 cm). Thus we can recommend similar applications of this technique could be used for mapping soil salinity in other parts in Iran. (C) 2013 Elsevier B.V. All rights reserved.