Characterization of The Spatial Variability of Some Soil Physicochemical Properties of The El-Gallaba Plain, New Aswan City, Aswan Governorate, Egypt.

Abd El-Aziz, Salah Hassanien; Ibrahim, Ahmed Gh. M.; Mohamed, Esraa Gamal; Abd El-Azem, Alaa H.

doi:10.21608/ejss.2023.237046.1663

Characterization of The Spatial Variability of Some Soil Physicochemical Properties of The El-Gallaba Plain, New Aswan City, Aswan Governorate, Egypt.

Document Type : Original Article

Authors

¹ Soils and Water Department, College of Agriculture, Assiut University, Assiut, Egypt

² Department of Lands and Natural Resources, Faculty of Agriculture and Natural Resources, Aswan University, Aswan Governorate, Egypt

10.21608/ejss.2023.237046.1663

Abstract

The major aim of the study was to assess and map the spatial variability of some soil properties in El-Gallaba Plain, New Aswan City, using a geostatistical technique. Forty topsoil samples were selected from forty profiles that were dug to represent the study area. The variability of the soil maps was drawn based on the ordinary kriging interpolation method based on the geostatistical analysis. The data indicates that most of the soil samples were rough in texture. The organic matter was extremely low in most soil samples (≤ 4.03 g kg−1). The salinity of soil paste extract (ECe) ranges from 0.84 to 28.21 dSm-1. The soil reaction (pH) values of the surface soils vary between 7.69 and 8.89. The calcium carbonate values extend between 0.43 and 9.74 %. Gypsum contents in the soil samples range between 0.49 to 4.07%. The CEC of soil samples ranged between 3.73 and 25.35 cmol (+)/kg. The coefficient of variation of soil pH was low (CV<5%), medium for sand fraction (CV<25%), and the rest of the soil properties were high to very high in the coefficient of variation.
The normal histogram and QQPlots analysis of the physicochemical properties of the studied soil samples was applied to make the data more normally distributed. Logarithmic transformation of the soil properties data was used to normalize highly skewed and distant datasets because ordinary kriging methods work best if the data are approximately normally distributed. The ordinary Kriging (OK) method was used in the present study as an interpolation method compared to other Kriging methods due to it being simple and having high accuracy for prediction. The data reveal that the Gaussian, J-Bessel, Exponential, Rational Quadratic, and K-Bessel are the best-fitted semivariogram models for all properties selected. Accurate maps efficiently generated using geostatistics were essential to properly understand the spatial variability of the area under study. This study gives useful information about the physical and chemical characteristics and the spatial diversity of this soil.

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