Scaling effect for the quantification of soil loss using GIS spatial analysis

Abstract

Accurate estimation of soil loss/deposition forced by rainfall events plays a major role in water resources management, which directly affects the quality of agricultural land and water storage capacity in reservoirs. In this paper, the soil loss model, Geographic Information System (GIS) based Universal Soil Loss Equation (USLE) was used to quantify soil loss in a small basin located in the southern part of Korea. The surface characteristics, such as soil texture, elevation and vegetation type, are needed to run the USLE model. Geospatial data has been successfully used to derive suitable model factors for this purpose. However, it is difficult to select the grid size of elements for the best fit, which is often decided in a subjective and intuitive way. A GIS spatial analysis was performed to investigate the scaling effect to estimate the soil loss in the USLE model using remotely sensed geospatial data. The results showed that the slope length factor (L) and slope steepness factor (S) were sensitive to the grid size; the optimal resolution for quantifying soil loss in the USLE model for the study site was 125 m. This approach presents a method for the selection of a suitable scale for estimating soil loss using remotely sensed geospatial data, which eventually improves the prediction of soil loss on a basin scale.