Sayed, Y., Khalafalla, M. (2024). Using GIS and Geostatistics to Monitoring Spatial Variability in Soil Chemical Properties Impacted by Cultivation Practices. Journal of Soil Sciences and Agricultural Engineering, 15(4), 93-98. doi: 10.21608/jssae.2024.272934.1220
Y. A. Sayed; M. Y. Khalafalla. "Using GIS and Geostatistics to Monitoring Spatial Variability in Soil Chemical Properties Impacted by Cultivation Practices". Journal of Soil Sciences and Agricultural Engineering, 15, 4, 2024, 93-98. doi: 10.21608/jssae.2024.272934.1220
Sayed, Y., Khalafalla, M. (2024). 'Using GIS and Geostatistics to Monitoring Spatial Variability in Soil Chemical Properties Impacted by Cultivation Practices', Journal of Soil Sciences and Agricultural Engineering, 15(4), pp. 93-98. doi: 10.21608/jssae.2024.272934.1220
Sayed, Y., Khalafalla, M. Using GIS and Geostatistics to Monitoring Spatial Variability in Soil Chemical Properties Impacted by Cultivation Practices. Journal of Soil Sciences and Agricultural Engineering, 2024; 15(4): 93-98. doi: 10.21608/jssae.2024.272934.1220
Using GIS and Geostatistics to Monitoring Spatial Variability in Soil Chemical Properties Impacted by Cultivation Practices
Department of Soils and Water, Faculty of Agriculture, Al-Azhar University, Assiut, Egypt
Abstract
The investigation is crucial for understanding and managing the spatial variability of soil chemical properties, which is essential for effective soil management practices and ecological protection on the experimental farm. Therefore, 36 soil samples were taken (0-30 cm depth) from a 100-meter grid of experimental farm is part of the Faculty of Agriculture, Al-Azahar University, Assuit (27° 12ʹ 16.67ʺ N latitude and 31° 09ʹ 36.86ʺ E longitude). Geographic information systems (GIS) and geo-statistics were practiced to assess the impact of cultivation practices on soil chemical properties and their spatial variability. Spherical model was used to forecast most soil parameters, while Gaussian model was used to estimate soil CO2-C flux and Exponential model was used to predict available nitrogen (N) and soil EC. The results showed that the coefficient of soil variation values was weak for soil salinity, soil reaction (pH), organic matter (OM) and CO2-C flux whereas they were moderate for available NPK and carbon storage. Except for soil salinity (EC), which had a range of 480 m, all variables showed a range of less than 55.1 m. All soil qualities have a nugget to sill ratio < 25%, which generally shows a substantial spatial dependence. These maps could be recommended to improve monitoring of soil properties and minimize the spatial variability of soil fertility.
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