The Effect of Sample Size on the Accuracy of Estimation of the Soil Salinity and Sodicity Status using Different Estimators

Soil salinity and sodicity are considered as the important factors limiting the plants growth. This study was conducted to assess the influence of the sample size on the accuracy of estimation of soil salinity and sodicity status, made by ordinary kriging, inverse distance weighting and spline estimators in Eslamieh area, Rafsanjan city. First, electrical conductivity (EC) and sodium adsorption ratio (SAR) were measured for 100 observation points, collected from three depths using a regular grid sampling pattern with an interval of 500 meter. These properties were mapped using aforesaid estimators. Then, random omission of 20, 40 and 60 samples from the total primary dataset (100 samples), was done and in each new situation, EC and SAR were mapped again. At the end of all 10 stages used to omit the samples, the index of standardized root mean square error (RMSE%) was measured for each estimator. Finally, the obtained contents of RMSE% were statistically compared using Friedman and Wilcoxon tests. The results showed using relatively high number of samples (all 100 observation points), three analyzed estimators have no significant difference (95% confidence level). In the cases of lower sample sizes, Friedman test revealed a significant difference among the estimators; whereas using Wilcoxon test, as a supplementary procedure, no significant difference was observed between the results obtained from ordinary kriging and inverse distance weighting. Hence, thanks to the relatively good precision, ease of processing and lower required sampling points, the inverse distance weighting estimator is recommended for future studies in the studied area.