A more accurate approach to estimate the C-factor of RUSLE by coupling stratified vegetation cover index in southern China

Abstract

Timely and accurate monitoring and forecasting of the cover and management factor (C-factor) is critical for soil erosion assessment at the national or regional scale. The stratified vegetation cover index (Cs) considers both the horizontal and vertical structure of vegetation. It is an ideal indicator for estimating the C-factor, but its applicability is limited in southern China where evergreen species dominate. To address this issue, this study proposed to reconstruct the structured vegetation index (S-Cs) in Nanjing, China, and sift out the optimal vegetation index for assessing the C-factor by establishing regression equations between the measured C-factor and S-Cs, fractional vegetation cover (FVC), Cs, and green coverage (VG). The results indicated that S-Cs can fully reflect the soil and water conservation benefits of different vegetation types and structures in southern China. Also, mixed coniferous and broadleaf forests had stronger soil and water conservation benefits than monocultures, and shrub-grass mixtures reduced soil erosion more than tree-grass mixtures. Besides, S-Cs was proved to be the best index to estimate the C-factor compared with Cs, FVC, and VG. Additionally, the C-factor fitting equation based on S-Cs was established as C = 0.213exp(−5.995 × S-Cs), which had good performance (R2 = 0.743, NSE = 0.507). This study broadened the application area of structured vegetation index and provided a new perspective for national or regional soil erosion assessment by coupling the S-Cs and the C-factor.