Relief influences soil development indirectly, as it influences other pedogenetic factors. Out of several relief factors, in this final seminar paper we will only focus on the influence of incline and altitude. Through fieldwork, I will obtain data on incline, altitude and soil depth at selected sampling points. With the statistical processing of the data and with the help of geo-information software, I will use the spatial interpolation to show the distribution of soil depth in the studied area. The purpose of this paper is to determine the influence of altitude and incline on soil depth in the selected area and to statistically process and map the data using software. The studied area is located between the northern part of the Kamniška Bistrica valley and the highlands of the Kamnik-Savinja Alps.
At the selected points in the field, a soil hole drill was used to drill a borehole to the bedrock. We read the depth of the soil and the incline. Location and altitude were recorded for each sample point. Data were obtained at 27 sample points, in three different transects. Non-field work included preparation for fieldwork, literature review, statistical and cartographic data processing. After obtaining data through fieldwork, the statistical analysis was performed with the SPSS program. Further on, we applied “enter” method to calculate the regression model equation, using the dependent variable “depth” and the independent variables “altitude” and “incline”. The soil depth was calculated in ArcGIS, using the regression equation.
The mapping of soil depth was calculated on the basis of the linear regression model equation: Y=81,948-0,039*(Altitude)-0,585*(Incline)±11,2.
Using statistical analysis of field-acquired data, we found that soil depth (independent variable) and incline and altitude (dependent variable) are interrelated. Due to the relatively small sample included in the survey, the standard error of estimate is 11.2 cm, which is almost 20% of the value of the maximum depth calculated. The model is statistically significant and explains 51.4% of the variance of the dependent variable. In calculating the regression line equation, we found a negative correlation between soil depth and altitude (-0.039) and surface incline (0.585). Due to high altitude, pedogenetic processes are so slow that the soil is formed very slowly or practically not at all. At the same time, at high altitude, the climatic conditions are so severe that they prevent the growth of the vegetation cover, which provides the organic component of the soil. In addition, the bedrock is hard, made of carbonate rock, which makes it highly resistant to mechanical and chemical weathering. The incline of the surface is so significant that different sloping processes move all the potential tiny particles into the lower parts of the valley which is reflected in the creeks and scree slopes. Water plays a role in this as a pedogenetic factor, which enables these processes by abundant precipitation.
With all of the above, we achieved the purpose of the final seminar paper - determine the influence of altitude and incline on soil depth in the selected area, and use the software to statistically process and map the data.