Vertical simulation of soil salinity using Markov chain in Ardakan pistachio gardens

In this research, a first order Markov chain model was applied to simulate soil salinity in nine standard depths and 10 classes in the cultivated pistachio areas of Ardakan city. Transition probability matrix, kernel and uniform distribution were used to simulate 500000 soil profiles. Results indicate kernel function could reproduce soil salinity values with statistical criteria (i.e. mean, standard deviation, skewness and kurtosis) more closely to the observed data when compared to data simulated by uniform function. Moreover, simulation processes from down-up is more accurate than that of up-down method. Overall, Makov simulation technique is able to consider the relationship between different classes.