Application of Modern Methods: Modeling of Sedimentary Soil ESP Content

20 Pages Posted: 28 Dec 2018 Last revised: 8 Mar 2019

See all articles by Sorush Niknamian

Sorush Niknamian

Board Member of Weston A Price Foundation (WAPF), Washington DC, United States; Liberty University

Date Written: June 17, 2018

Abstract

Knowing the exchangeable sodium percentage (ESP) variations and its values in sodic or saline-sodic soils is essential in order to estimate the amount of soil amendments and better land management. ESP calculated from cation exchange capacity (CEC), and since CEC measurement is difficult and time-consuming, ESP computation is costly and subject to error. Thus, presenting a method to estimate ESP indirectly, by an easily available index is much more efficient and economical. In this study, 296 soil samples collected and analyzed from Sistan plain, southeastern Iran. Soil ESP were predicted by using artificial neural networks, comprising radial basis functions (RBFN) and multilayer perceptron (MLP) and adaptive neuro-fuzzy inference systems (ANFIS), and results compared with stepwise linear regression method. Results indicated that the linear regression models performed poorly in order to estimate ESP (R2 ≤ 0.58 and root mean square error (RMSE) ≥ 4.31). Applying fewer inputs (electrical conductivity (EC) and pH), ANFIS showed better results (R2=0.80, RMSE=2.34), while increasing inputs (clay and organic carbon) decreased the accuracy (R2=0.82, RMSE=4.20). Using more inputs, RBFN resulted in better performance in comparison with other methods (R2=0.83, RMSE=2.85). Sensitivity analysis using the connection weight method demonstrated that EC, pH, clay percentage and bulk density are the most important variables in order to explain ESP variability in the region, respectively. Generally, considering the evaluation criteria and the number of used variables of models, ANFIS (with EC and pH as inputs) is the most appropriate method for estimating ESP in Sistan plain.

Keywords: Saline-Sodic Soils, Exchangeable Sodium Percentage, PTFS, Artificial Intelligence, Sistan Plain

JEL Classification: Q00

Suggested Citation

Niknamian, Sorush, Application of Modern Methods: Modeling of Sedimentary Soil ESP Content (June 17, 2018). Available at SSRN: https://ssrn.com/abstract=3202217

Sorush Niknamian (Contact Author)

Board Member of Weston A Price Foundation (WAPF), Washington DC, United States ( email )

NW Washington, DC 20016 USA.
Washington, WA Washington 20016
United States

Liberty University ( email )

1971 University Blvd, Lynchburg, VA 24515
Lynchburg, VA Lynchburg 24515
United States
6125035141 (Phone)

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