Abstract

This study was conducted to examine spatial variability of soil fertility depending on the level of selected soil fertility parameters in Fener Village located on Bafra Alluvial Deltaic Plain by means of Soil Fertility Index (SFI) model using geostatistics and Geographic Information System (GIS) technique. Fifteen soil properties [available macronutrient elements (nitrogen, phosphorous, potassium, calcium, magnesium, sodium), available micronutrient elements (iron, copper, zinc, manganese), and other soil properties (texture class, organic matter, pH, electrical conductivity, CaCO3)] at the depths of 0-30 cm and 30-60 cm were evaluated using SFI model for each georeferenced point. A total of 140 grid points were obtained and soil samples collected from surface (0-30 cm) and subsurface (30-60 cm) depths of each grid centre are 131 and 124, respectively. Geostatistical method was used to generate SFI distribution maps for surface and subsurface soils of the study area. According to the results of SFI distributions for both depths, 80.18% of the study area has good (S1) and moderate fertility (S2), 19.06% has marginal fertility (S3), 0.75% has poor fertility in surface depth, while 38.83% of the study area has good (S1) and moderate fertility (S2), 41.30% marginal fertility (S3) and 19.87% has poor fertility in subsurface depth. Consequently, findings of this study showed that geostatistical modelling was useful in the determination of the spatial variability structure and spatial dependency of investigated soil properties and nutrients

Keywords

• Soil fertility index,physical and chemical properties,nutrients,spatial variability,geographic information system

Distribution and Evaluation of Soil Fertility Based on Geostatistical Approach in Bafra Deltaic Plain

Abstract

This study was conducted to examine spatial variability of soil fertility depending on the level of selected soil fertility parameters in FenerVillagelocated on Bafra Alluvial Deltaic Plain by means of Soil Fertility Index (SFI) model using geostatistics and Geographic Information System (GIS) technique. Fifteen soil properties [available macronutrient elements (nitrogen, phosphorous, potassium, calcium, magnesium, sodium), available micronutrient elements (iron, copper, zinc, manganese), and other soil properties (texture class, organic matter, pH, electrical conductivity, CaCO₃)] at the depths of 0-30 cm and 30-60 cm were evaluated using SFI model for each georeferenced point. A total of 140 grid points were obtained and soil samples collected from surface (0-30 cm) and subsurface (30-60 cm) depths of each grid centre are 131 and 124, respectively. Geostatistical method was used to generate SFI distribution maps for surface and subsurface soils of the study area. According to the results of SFI distributions for both depths, 80.18% of the study area has good (S1) and moderate fertility (S2), 19.06% has marginal fertility (S3), 0.75% has poor fertility in surface depth, while 38.83% of the study area has good (S1) and moderate fertility (S2), 41.30% marginal fertility (S3) and 19.87% has poor fertility in subsurface depth. Consequently, findings of this study showed that geostatistical modelling was useful in the determination of the spatial variability structure and spatial dependency of investigated soil properties and nutrients.

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