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Analyzing Soil Physical Properties in Kirkuk City, Iraq, Utilizing a Geographic Information System – Based Inverse Distance-Weighted Technique
 
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Technical Engineering College, Northern Technical University, Kirkuk, Iraq
 
 
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Parzhen Abdullah Mohammed   

Technical Engineering College, Northern Technical University, Kirkuk
 
 
Ecol. Eng. Environ. Technol. 2024; 11:118-133
 
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ABSTRACT
In this research, the distribution and physical characteristics of soils are the main topics. The inverse distance weighting (IDW) method is used in conjunction with GIS to forecast the physical properties of the soil. This study involved a detailed analysis of 65 soil samples collected across Kirkuk City to investigate its physical properties and behavior. Through the creation of 10 digital maps using the inverse distance weighting (IDW) technique, the distribution of soil types such as gravel, sand, silt, clay, dry density, specific gravity, Atterberg limits, and water content was illustrated. Variations in these properties were observed across different sectors of the city, with specific districts showing notable differences. The gravel content was particularly high in certain northeastern zones, while sand was the predominant soil type overall, and the silt content exhibited significant variability. Clay content, which is concentrated in the eastern and southern regions, has implications for agriculture and contamination control. A direct correlation between the clay content and Atterberg limits was observed, with the liquid and plastic limits (LL and PL) increasing with increasing clay content. Additionally, dry density was highest in the northwestern region, and the water content generally remained high except in specific areas. The specific gravity values exhibited consistency across most regions. These findings offer valuable insights for geotechnical and engineering practices in Kirkuk City and are supported by a cross-validation technique that assesses the relationships between basic and studied physical attributes. The coefficient of determination, R squared (R²), for the IDW maps indicated varying degrees of model fit to the data, with lower root mean square error (RMSE) values suggesting improved prediction accuracy. Overall, the study revealed strong correlations ranging from good to excellent across the examined regions. The use of GIS techniques has demonstrated significant effectiveness in modeling and quantifying soil properties, offering benefits in protecting and improving soil health through effective soil management strategies and treatments.
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