Predicting Agricultural Potentiality using Land Degradation Factors in East of Rosetta Branch, Nile Delta, Egypt
Abuzaid, A., Bassouny, M., Abdellatif, A. (2018). Predicting Agricultural Potentiality using Land Degradation Factors in East of Rosetta Branch, Nile Delta, Egypt. EKB Journal Management System, 9(5), 229-236. doi: 10.21608/jssae.2018.35725
A. Abuzaid; M. Bassouny; A. Abdellatif. "Predicting Agricultural Potentiality using Land Degradation Factors in East of Rosetta Branch, Nile Delta, Egypt". EKB Journal Management System, 9, 5, 2018, 229-236. doi: 10.21608/jssae.2018.35725
Abuzaid, A., Bassouny, M., Abdellatif, A. (2018). 'Predicting Agricultural Potentiality using Land Degradation Factors in East of Rosetta Branch, Nile Delta, Egypt', EKB Journal Management System, 9(5), pp. 229-236. doi: 10.21608/jssae.2018.35725
Abuzaid, A., Bassouny, M., Abdellatif, A. Predicting Agricultural Potentiality using Land Degradation Factors in East of Rosetta Branch, Nile Delta, Egypt. EKB Journal Management System, 2018; 9(5): 229-236. doi: 10.21608/jssae.2018.35725

Predicting Agricultural Potentiality using Land Degradation Factors in East of Rosetta Branch, Nile Delta, Egypt

Journal of Soil Sciences and Agricultural Engineering
Article 3, Volume 9, Issue 5, May 2018, Page 229-236  XML PDF (555.45 K)
Document Type: Original Article
DOI: 10.21608/jssae.2018.35725
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Authors
A. Abuzaid1; M. Bassouny1; A. Abdellatif2
1Soil and Water Department, Faculty of Agriculture, Benha University, Egypt
2Soil, Water and Environment Research Institute, Agricultural Research Center, Egypt
Abstract
The Nile Delta is the backbone of agriculture in Egypt and undergoes land degradation, thus predicting land performance is of great concern. Chemical and physical processes and risks of degradation were evaluated for 887.09 km2 (88709 ha) in Kafr El-Sheikh Governorate, along the eastern bank of the Nile River (Rosetta branch). The revised Storie index and the Applied System for Land Evaluation (ASLE) were used to calculate land productivity index (LPI) and land capability index (LCI), respectively. Twenty soil profiles were dug to a depth of 150 cm. The multiple linear regression (MLR) was operated to predict LPI and LCI based on land degradation factors (LDF) including EC, ESP, bulk density, depth, slope, silt, and clay. Based on Landsat 8 satellite imagery and digital elevation model (DEM), the main landforms include levee, overflow mantle, recent terraces, middle terraces and old terraces. The area was affected by slight to moderate salinity hazards, slight to severe sodicity hazards, and moderate to extreme compaction hazards due to Mediterranean seawater intrusion besides mismanagement practices. The area was affected by low chemical degradation risks, but moderate to very high physical risks. The LP ranged from good to poor, while LC was good to fair. The MLR models showed high accuracy when predicting LPI and LCI based on EC, ESP, bulk density, silt, and clay. The models would be effective to verify the impacts of LDF on land's agricultural potential. 
Keywords
land degradation; Land productivity; Land capability; regression; North Nile Delta
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