نوع مقاله : مقاله پژوهشی
نویسندگان
1 گروه آبخیزداری
2 گروه مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه ارومیه، ارومیه
3 گروه خاکشناسی، دانشکده کشاورزی، دانشگاه ارومیه
4 گروه مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه ارومیه
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Soil erodibility is influenced by environmental and management factors and serves as a critical quantitative and qualitative indicator for estimating soil loss potential. This parameter is essential for planning soil conservation strategies and prioritizing protective measures. This study aimed to identify the direct and indirect environmental variables affecting the soil erodibility index (K) in sub-watersheds of West Azerbaijan Province. A total of 131 soil samples were collected from representative rangeland sites across the province, with adequate spatial distribution, from the surface layer (0–20 cm). Soil properties, including sand, silt, clay, organic carbon, lime content, saturated moisture, pH, and electrical conductivity, were measured in the laboratory. Additionally, soil permeability class and structure were determined. Topographic characteristics, such as slope gradient, slope aspect, and elevation of sampling points, were recorded using a clinometer, azimuth meter, and Global Positioning System (GPS). Maps of temperature and precipitation distribution were generated using the Inverse Distance Weighting (IDW) method in ArcGIS 10.3.1, and corresponding values for sampling points were extracted. The soil erodibility factor (K) was calculated using the equation proposed by Wischmeier and Smith. Stepwise regression analysis was used to examine the relationship between the soil erodibility factor (K) and environmental variables. Regression coefficients and steps were determined for environmental parameters, and the statistical significance of the regression model was assessed through analysis of variance (ANOVA) across four steps. Correlation coefficients for vegetation cover, precipitation, slope, and elevation with the soil erodibility factor (K) were calculated at each step. ANOVA results indicated that the model was significant at the 1% level, confirming its reliability. The student’s t-test was used to determine the constant and variable coefficients of the models. Standardized coefficients for vegetation cover, precipitation, slope, and elevation were -0.231, -0.203, 0.194, and -0.187, respectively. Vegetation cover showed the highest correlation (R = 0.320), while elevation showed the lowest correlation (R = 0.469) with the soil erodibility factor (K). The spatial distribution of the K factor was mapped using geostatistical techniques, with the IDW method selected due to its lowest Root Mean Square Error (RMSE). The K factor map indicated the highest erodibility in the northern regions of the province, corresponding to areas with excessive livestock grazing and reduced vegetation cover due to overgrazing.
کلیدواژهها [English]
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