Enhancing basin sustainability: Integrated RUSLE and SLCC in land use decision-making

Abstract

Sustainable agriculture and eco-environment conservation face constant threats from soil erosion in mountainous regions. This study utilizes remote sensing and GIS support to predict soil erosion and sediment yield by applying the Revise Universal Equation Soil Loss (RUSLE) and Sediment Delivery Ratio (SDR) models. The findings highlight that the basin adversely experiences an average annual soil erosion rate of 108.47 t ha−1 yr−1, leading to a significant sediment influx of 206.03 × 106 t/yr at downstream. The RUSLE-SDR model performs satisfactorily, with percent bias (PBIAS) values below 25%. Based on the RUSLE output, the study integrates a threshold of over 100 t ha−1 yr−1 into the adapted slopeland capability classification (SLCC), along with slope gradient derived from Digital Elevation Model (DEM) and soil depth, to categorize the entire basin into five capability classes. Each class is associated with specific soil erosion control treatments for agricultural activities and forestry. The study suggests the four land use/land cover (LULC) scenarios with different prioritizations, aimed to optimize land resource utilization and conserve the eco-environment. Scenarios #3 and #4, in particular, demonstrate promising benefits for the eco-environment by substantially increasing forest coverage to 81.27% and 85.07% of the total area, respectively. In contrast, scenarios #1 and #2 prioritize agricultural development. Due to the challenge posed by rugged terrains, the application of LULC scenarios must be adhered strictly, considering a specific class of the SLCC with its treatments. The study offers a timely and feasible approach for soil erosion investigation and land use adjustment to support effective basin management. However, ensuring the health and sustainability of the basin ecosystem may necessitate additional measures, such as proper planning for riparian zones and engineering solutions.