Modeling of Soil Exchangeable Sodium Percentage Function to Soil Adsorption Ratio on Sandy Clay Loam Soil, Khartoum- Sudan
Mohammed M. A. Elbashier *
College Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, 210098, China and Department of Soil Conservation, Ministry of Agriculture, Khartoum State, Sudan
Shao Xiaohou
College Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, 210098, China and Key Laboratory of Efficient Irrigation-Drainage and Agricultural Soil-Water Environment in Southern China of Ministry of Education, Hohai University, China.
Albashir A. S. Ali
College Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, 210098, China and Department of Soil Science, Agricultural Research Corporation, Khartoum, Sudan
Bashir H. Osman
College Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, 210098, China and Faculty of Engineering, University of Sinnar, Sinnar, Sudan
*Author to whom correspondence should be addressed.
Abstract
An experiment was conducted at the Wadi Soba farm, Khartoum- Sudan. The aim of this study is to estimate the Exchangeable Sodium Percentage (ESP) function to Sodium Adsorption Ratio. In this study, linear regression model (ESP-SAR model) for predicting soil ESP from SAR was suggested. For this purpose, 30 soil samples were collected from the field of experiment, soil ESP was estimated from soil SAR in order to compare the predicted results with measured SAR using laboratory tests on saline and non- saline soil samples. The results show that on saline soil samples, the Standard Error of Mean (SEM) of predicted ESP obtained by ESP-SAR model was (0.9389) and the P-value was (0.0572). On non- saline soil samples, the Standard Error of Mean (SEM) of predicted ESP acquired by ESP-SAR model was (0.2920) and the P-value was (0.2628). The statistical results indicated that the linear regression model (ESP-SAR model), ESP= 0.84 × SAR + 2.17 with R2 = 0.7347 has a good performance in predicting soil ESP from SAR meanwhile the ESP-SAR model reflected more accuracy on non- saline soil samples and it can be recommended for both saline soil and non-saline soil samples.
Keywords: Electrical conductivity, exchangeable sodium percentage, cation exchange capacity, sodium adsorption ratio