Soil Salinity Assessing and Mapping Using Several Statistical and Distribution Techniques in Arid and Semi-Arid Ecosystems, Egypt

Bibliographic Details
Title: Soil Salinity Assessing and Mapping Using Several Statistical and Distribution Techniques in Arid and Semi-Arid Ecosystems, Egypt
Authors: 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
Source: Agronomy, Vol 13, Iss 2, p 583 (2023)
Publisher Information: MDPI AG, 2023.
Publication Year: 2023
Collection: LCC:Agriculture
Subject Terms: soil salinity, statistical analyses, remote sensing, El-Farafra Oasis, Agriculture
More Details: 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 < 0.01) level between SI 9 and ECe (r = 0.514), a non-significant correlation at the (p < 0.05) level between soil ECe 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.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2073-4395
Relation: https://www.mdpi.com/2073-4395/13/2/583; https://doaj.org/toc/2073-4395
DOI: 10.3390/agronomy13020583
Access URL: https://doaj.org/article/ec78f0c2bb92496d891e8ba6298c6c4a
Accession Number: edsdoj.78f0c2bb92496d891e8ba6298c6c4a
Database: Directory of Open Access Journals
More Details
ISSN:20734395
DOI:10.3390/agronomy13020583
Published in:Agronomy
Language:English