2023IOP Conference Series Earth and Environmental ScienceOpen access

Estimation of Saturated Hydraulic Conductivity using Pedotransfer Function (PTFS) in Gypsiferous Soil

Ahmed Abd El Fattah, Ramzi M. Shihab

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Abstract

Abstract This study was conducted to evaluate the performance of pedotransfer functions (PTFS) in estimating the saturated hydraulic conductivity in gypsum soil. The saturated hydraulic conductivity was measured for 26 unexcited samples using the permeability of the falling head, and then some chemical and physical properties of the study soil were measured. Rosetta and a number of models were used to predict the saturated hydraulic conductivity. Three statistical criteria, namely NSE, RMSE, and R2, were used to evaluate the performance of the models. The results showed that the second model of Rosetta, which depends on sand, silt, clay, and bulk density as input, is the best, as the values of NSE and RMSE were -13.28 and 0.31, respectively, while the other models, Puckett, Smettem, Bristow, and Saxton, were the best in predicting the saturated hydraulic conductivity of Among the models, the RMSE values were 0.52, 0.54, and 0.47, respectively, and the NSE values were 0.92, 0.91, and 0.93, respectively.

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Abstract This study was conducted to evaluate the performance of pedotransfer functions (PTFS) in estimating the saturated hydraulic conductivity in gypsum soil. The saturated hydraulic conductivity was measured for 26 unexcited samples using the permeability of the falling head, and then some chemical and physical properties of the study soil were measured. Rosetta and a number of models were used to predict the saturated hydraulic conductivity. Three statistical criteria, namely NSE, RMSE, and R2, were used to evaluate the performance of the models. The results showed that the second model of Rosetta, which depends on sand, silt, clay, and bulk density as input, is the best, as the values of NSE and RMSE were -13.28 and 0.31, respectively, while the other models, Puckett, Smettem, Bristow, and Saxton, were the best in predicting the saturated hydraulic conductivity of Among the models, the RMSE values were 0.52, 0.54, and 0.47, respectively, and the NSE values were 0.92, 0.91, and 0.93, respectively.

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Available abstract

Abstract This study was conducted to evaluate the performance of pedotransfer functions (PTFS) in estimating the saturated hydraulic conductivity in gypsum soil. The saturated hydraulic conductivity was measured for 26 unexcited samples using the permeability of the falling head, and then some chemical and physical properties of the study soil were measured. Rosetta and a number of models were used to predict the saturated hydraulic conductivity. Three statistical criteria, namely NSE, RMSE, and R2, were used to evaluate the performance of the models. The results showed that the second model of Rosetta, which depends on sand, silt, clay, and bulk density as input, is the best, as the values of NSE and RMSE were -13.28 and 0.31, respectively, while the other models, Puckett, Smettem, Bristow, and Saxton, were the best in predicting the saturated hydraulic conductivity of Among the models, the RMSE values were 0.52, 0.54, and 0.47, respectively, and the NSE values were 0.92, 0.91, and 0.93, respectively.

Key concepts: Hydraulic conductivity, Pedotransfer function, Soil science, Bulk density, Mean squared error, Silt, Environmental science, Mathematics

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