Modeling of spatial change patterns of Sarıgöl district (Manisa) soil geography and some soil features by geostatistical methods

Soil is a vital natural resource that sustains life on Earth; however, in the present day, its value is often overlooked, and it remains difficult to regenerate. Therefore, research must be conducted on soil to strive for its effective and sustainable utilization. This study, carried out within the boundaries of Sarıgöl district, is a detailed soil investigation. The relationships between the major soil groups in the district and natural environment or physical geography factors—such as parent material, climate, vegetation, and topography—have been established. Accordingly, in areas where the Menderes Massif forms the basement, the distribution of plant nutrients is correlated with the parent material. The vast majority of soils have developed on slopes with gradients below 14°. The metamorphic rocks of the Menderes Massif, alluvial deposits in plains where the slope decreases, colluvial and sandy deposits at mountain foothills and plain margins, and Neogene-aged lacustrine sediments on the northern slopes of the Uşak-Gördes Plateau and Uysal Mountain constitute the principal soil parent materials. According to the genetic soil classification system, zonal, azonal, and intrazonal soils are present in the study area. Non-calcareous brown forest soils account for 50% of the soil presence. Other soil types consist of non-calcareous brown soils (23%), alluvial soils (24%), colluvial soils (4%), and rendzinas (2%). In the topography, which is constantly rejuvenated by geomorphological processes, elevation and temperature factors have also been decisive in the physico-chemical properties of the soils. In the second part of the study, data from 78 soil samples collected at depths of 0–30 cm and 30–60 cm were utilized. Laboratory analyses included saturation, salinity, pH, lime, organic matter, and plant-available macro-elements (K, Ca, P, Mg, N) and micro-elements (Fe, Cu, Mn). Subsequently, descriptive statistics and correlation relationships of the analysis results were calculated, and the findings were interpreted. Soil attributes identified based on the analysis results were modeled using semivariogram models in ARCMAP 10.5, and RMSE values were determined for the most suitable mapping. Each soil attribute was mapped according to the model yielding the lowest RMSE value; furthermore, fertility class distribution maps were generated based on agricultural evaluations recommended in the literature. Examination of the physico-chemical properties of surface soils revealed that 82% of the soils are loamy, 72% have a slightly alkaline reaction, 62% are non-calcareous, 69% have extremely low organic matter content, and 79% were identified as non-saline. The distribution of macro-elements, which are of great importance for soil fertility, is as follows: 100% of the soils have poor nitrogen levels, 59% have excessive potassium, phosphorus content is variable, 64% have high calcium, and 54% have sufficient magnesium levels. Another soil attribute identified is micro-elements. According to the research findings, 56% of surface soils have low iron levels, 68% have adequate copper, and almost all have low zinc and manganese content. Subsurface soil analyses yielded results similar to surface soils, and the analysis results obtained at a depth of 30–60 cm showed a more balanced distribution. The analysis results were correlated with geology, climate, soil groups, and anthropogenic activities. It was demonstrated that agricultural practices may influence the analysis results of the topsoil. The conclusions reached and the problems identified are gathered under the heading "Discussion, Conclusion, and Recommendations."