Evaluation of soil loss estimation using RUSLE model and SCS-CN method in hilltop mining areas (original) (raw)

Mining operations result in the generation of barren land and spoil heaps which are subject to high erosion rate during the rainy season. The present study uses Revised Universal Soil Loss Equation (RUSLE) and SCS-CN (Soil Conservation Service-Curve Number) process to conclude the soil loss estimation in Kiruburu and Meghahatuburu mining sites area. The geospatial model of yearly soil loss rate has been driving through integrating environmental variables parameters in a raster pixels-based GIS framework. GIS layers with, rainfall passivity or runoff erosivity (R), soil erosivity (K), slope length and steepness (LS), cover management(C) and conservation practice (P) factors were calculated to condition their special effects on yearly soil erosion in the study area. The coefficient of determination (r 2) is 0.834, which indicates a strong correlation in runoff and rainfall. Sub-watershed 5,9,10 and 2 was highly runoff. Average annual soil loss was calculated (30*30 m raster grid cell) to recognize the critical soil loss areas (Sub-watershed 9 and 5). Total soil erosion area was classified five class, slight (10,025.2 ha), moderate (3124.62), high (973.17 ha), very high (260.02 ha) and severe (52.83 ha). The resulting map shows highest soil erosion of 440 t h-1 y-1 (severe) through connection to grassland, degraded and open forestry on the erect mining side-escutcheon. The Landsat pan sharpening image and DGPS survey field data were used in the justification of soil erosion results.