You are in:Home/Publications/Abdelatif, D. A. and Abuzaid, A. S. 2021. Integration of multivariate analysis and spatial modeling to assess agricultural potentiality in Farafra Oasis, western desert of Egypt. Egyptian Journal of Soil Science, 61 (2): 201 – 2018, DOI: 10.21608/ejss.2021.71312.1440

Prof. Ahmed Saeed Fathi Yousef Abuzaid :: Publications:

Title:
Abdelatif, D. A. and Abuzaid, A. S. 2021. Integration of multivariate analysis and spatial modeling to assess agricultural potentiality in Farafra Oasis, western desert of Egypt. Egyptian Journal of Soil Science, 61 (2): 201 – 2018, DOI: 10.21608/ejss.2021.71312.1440
Authors: Abdelatif D. Abdelatif; Ahmed S. Abuzaid
Year: 2021
Keywords: Multivariate analysis; Spatial modeling; GIS; Farafra Oasis; Western Desert
Journal: Egyptian Journal of Soil Science
Volume: 61
Issue: 2
Pages: 201-2018
Publisher: National Information and Documentation Centre (NIDOC)
Local/International: International
Paper Link:
Full paper Ahmed Saeed Fathi Yousef Abuzaid_Integration of Multivariate Analysis and Spatial Modeling.pdf
Supplementary materials Not Available
Abstract:

PRECISE assessment of land and water resources in the newly reclaimed desert land in Egypt is a pillar of sustainable agricultural production. The principal component analysis (PCA), factor analysis (FA) and spatial modeling were integrated to develop a GIS-based model for agricultural potentiality in Farafra Oasis, Western Desert of Egypt. The studied area (167.98 km2, i.e. 16798 ha) is located between 27° 01ʹ 35.71ʺ to 27° 10ʹ 5.38ʺ N and 28° 16ʹ 34.95ʺ to 28° 22ʹ 58.71ʺ E. Twenty-two soil profiles were dug, and samples were collected and analyzed. Groundwater samples were collected from ten wells and analyzed. Slope, aspect, surface roughness, and topographic wetness index were extracted from a digital elevation model. The groundwater showed no limitations for irrigation. Soil properties and topographic attributes showed linear correlations among each other. The results of the PCA/FA were sufficient to estimate a weight for each parameter. The most effective factors determining agricultural potentiality were soil physical properties (0.36) followed by chemical properties (0.31) and topography (0.26), while erosion was the least one (0.07). The GIS-based model showed that the area belongs to moderate (62%) and high potentiality (35%) classes under sprinkler irrigation, while moderate (1%), high (94%) and very high potentiality (2%) under drip irrigation. Combined use of multivariate and spatial analysis would help in developing sustainable agricultural strategies in such desert areas.

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