Vegetation can significantly mitigate soil erosion through diminishing surface runoff, improving soil properties, and intercepting rainfall. Increased vegetation coverage strengthens these effects by enhancing canopy density, surface roughness, and litter accumulation. To quantify these effects, multiple coverage-based equations have been proposed for estimating vegetation-related factors within major erosion assessment frameworks, including the Universal Soil Loss Equation (USLE) and the Chinese Soil Loss Equation (CSLE). However, these equations often neglect understory vegetation, inadequately incorporate vegetation types, and rely on region-specific data, limiting their broader applicability across China's diverse ecosystems. To address these limitations, this study developed three equations applicable nationwide for estimating the biological control factor (B) based on vegetation coverage for grassland, shrubland, and woodland. The method underwent calibration and validation on a dataset from 54 sites, with subsequent performance assessment at 8 independent sites. Results revealed substantial enhancements in sediment yield prediction accuracy relative to the storm-based CSLE. During calibration, Nash-Sutcliffe Efficiency (NSE) values increased from 55.76% to 70.25% for grassland, from 44.08% to 81.95% for shrubland, and from-61.18% to 73.12% for woodland. Validation results exhibited parallel improvements, with NSE increasing from 61.07% to 74.55% for grassland, 48.44% to 77.41% for shrubland, and-77.00% to 68.23% for woodland. These results highlight the proposed method's key advantages: enhanced predictive accuracy and broader applicability across China's diverse ecosystems.