Impact of Slope Cutoff Factor on Soil Erosion Estimates: A Hilltop Mine-Based Comparative Geospatial Study

Abstract

The task of soil erosion estimation received a significant push by integrating remote sensing and geographical information systems (GIS) with the Revised Universal Soil Loss Equation (RUSLE) in the early 1990s due to its ease of applicability. The Topographic (LS) factor played a quintessential role in soil loss determination, especially for undulating regions. In most worldwide soil erosion studies, the topographic factor extracted from the Digital Elevation Model (DEM) using “LS equations” failed to account for the varying slopes before the material joins a stream or a river. In this study, the slope length (L) and slope steepness factor (S) derived without and with the slope cutoff factor are compared and analyzed for a hilltop mine. The results reflect that the LS factor and, ultimately, soil erosion are over-estimated owing to the absence of any limits on the slope length (L) factor in undulating terrains when used conventionally in a GIS environment. The mean soil erosion estimated with slope cutoff factor is 252.26 ton ha⁻¹ year⁻¹, whereas 332.81 ton ha⁻¹ year⁻¹ in the conventional application of the same LS equation. The overestimation of soil erosion was reduced by 35% as per the volume-based validation study. Thus, the study proves the usefulness of the slope cutoff factor, which, to date, has mostly been neglected in soil loss research and soil erosion studies for undulating terrains. The pattern of soil erosion also highlights the negating impact of vegetation on steep slopes, cementing their role as Nature based Solution (NbS) for soil erosion by dynamic landscapes like Mines.