Soil Salinity Assessing and Mapping Using Several Statistical and Distribution Techniques in Arid and Semi-Arid Ecosystems, Egypt
Mohamed E. Fadl,
Mohamed E. M. Jalhoum,
Mohamed A. E. AbdelRahman,
Elsherbiny A. Ali,
Wessam R. Zahra,
Ahmed S. Abuzaid,
Costanza Fiorentino,
Paola D’Antonio,
Abdelaziz A. Belal,
Antonio Scopa
Affiliations
Mohamed E. Fadl
Division of Scientific Training and Continuous Studies, National Authority for Remote Sensing and Space Sciences (NARSS), Cairo 11769, Egypt
Mohamed E. M. Jalhoum
Division of Agricultural Applications, Soil and Marine Sciences, National Authority for Remote Sensing and Space Sciences (NARSS), Cairo 11769, Egypt
Mohamed A. E. AbdelRahman
Division of Environmental Studies and Land Use, National Authority for Remote Sensing and Space Sciences (NARSS), Cairo 11769, Egypt
Elsherbiny A. Ali
Geography Department, Faculty of Arts, Zagazig University, Zagazig 44519, Egypt
Wessam R. Zahra
Soils and Water Department, Faculty of Agriculture, Benha University, Benha 13518, Egypt
Ahmed S. Abuzaid
Soils and Water Department, Faculty of Agriculture, Benha University, Benha 13518, Egypt
Costanza Fiorentino
Scuola di Scienze Agrarie, Forestali, Alimentari ed Ambientali (SAFE), Università degli Studi della Basilicata, Via dell’Ateneo Lucano, 10-85100 Potenza, Italy
Paola D’Antonio
Scuola di Scienze Agrarie, Forestali, Alimentari ed Ambientali (SAFE), Università degli Studi della Basilicata, Via dell’Ateneo Lucano, 10-85100 Potenza, Italy
Abdelaziz A. Belal
Division of Agricultural Applications, Soil and Marine Sciences, National Authority for Remote Sensing and Space Sciences (NARSS), Cairo 11769, Egypt
Antonio Scopa
Scuola di Scienze Agrarie, Forestali, Alimentari ed Ambientali (SAFE), Università degli Studi della Basilicata, Via dell’Ateneo Lucano, 10-85100 Potenza, Italy
Oasis lands in Egypt are commonly described as salty soils; therefore, waterlogging and higher soil salinity are major obstacles to sustainable agricultural development. This study aims to map and assess soil salinization at El-Farafra Oasis in the Egypt Western Desert based on salinity indices, Imaging Spectroscopy (IS), and statistical techniques. The regression model was developed to test the relationship between the electrical conductivity (ECe) of 70 surface soil samples and seven salinity indices (SI 1, SI 2, SI 5, SI 6, SI 7, SI 8, and SI 9) to produce soil salinity maps depending on Landsat-8 (OLI) images. The investigations of soil salinization and salinity indices were validated in a studied area based on 30 soil samples; the obtained results represented that all salinity indices have shown satisfactory correlations between ECe values for each soil sample site and salinity indices, except for the SI 5 index that present non-significant correlations with R2 value of 0.2688. The SI 8 index shows a higher negative significant correlation with ECe and an R2 value of 0.6356. There is a significant positive correlation at the (p e (r = 0.514), a non-significant correlation at the (p e and SI 1 index (r = 0.495), and the best-verified salinity index was for SI 7 that has a low estimated RMSE error of 8.58. Finally, the highest standard error (R2) was represented as ECe (dS m−1) with an R2 of 0.881, and the lowest one was SI 9 with an R2 of 0.428, according to Tukey’s test analysis. Therefore, observing and investigating soil salinity are essential requirements for appropriate natural resource management plans in the future.
