LAUSR

Soil salinity is one of the most limiting factors in land evaluation and management for agricultural use as it impacts directly on crop cultivation and production. The laboratory soil salinity analysis (electrical conductivity, EC) is an essential procedure to determine the suitability of soils for different uses. The main goal of this research is to quantify the statistical relationship between surface altitude (based on digital elevation model, DEM) and soil salinity (based on EC) in a desert depression in the arid region. A total of 40 surface soil samples collected from different altitudes in Wadi El Farigh depression, western desert, Egypt. The co-kriging geostatistical model was applied to interpolate the laboratory-measured EC values as the primary variable and the elevation as a covariate. Based on the altitude variations, the dataset classified into two groups; soil samples within the altitude of ≤20 m and > 20 m. Both linear and logistic (power) regression models were employed to predict the EC values based on the elevation of the study area using all dataset and the two classified groups. The results show a strong correlation between EC values and surface elevation. The linear regression models produced R2s of 0.67, 0.86, and 0.74 using all dataset, ≤ 20 and > 20 m, respectively. Stronger relationships with respective R2s of 0.94, 0.86, and 0.84 achieved when power model was applied. No significant differences observed between the models’ results and validation datasets. Generally, the regression analysis shows a promising technique for predicting the soil salinity based on surface altitude in the enclosed depressions of the arid region.