Abstract

Limited research is available on sediment provenance of snowmelt erosion. In this study, a Bayesian mixing model-based fingerprint tracing technique was used to estimate the relative sediment source contributions for snowmelt erosion in the black soil region of Northeast China, which experiences severe snowmelt erosion. Relative sediment contributions were estimated under two source classification schemes (Scheme 1: cultivated land, forest, and gully; Scheme 2: Scheme 1 + unpaved road) using the geochemical tracers. Kruskal–Wallis test and discriminant function analysis revealed different optimum composite fingerprints for Scheme 1 (Br, Cu, Fe2O3, CaO, and K2O) and Scheme 2 (Cr, Ba, Fe2O3, CaO, and K2O). Cultivated land, forest, and gully accounted for 52.1%, 1.4%, and 46.5%, respectively, of sediment contributions with a goodness of fit (GOF)= 0.89 and the mean absolute fit (MAF)= 0.62 in Scheme 1. However, gully-derived sediment from snowmelt erosion dominated the sediment contribution (66.1%) while cultivated land, forest, and unpaved track contributed 18.4%, 13.5%, and 2.0% (GOF=0.97, MAF=0.85), respectively, in Scheme 2. However, common tracer properties (Fe2O3, CaO, and K2O) as composite fingerprints contributed 13.5%, 13.4%, and 73.1% (GOF = 0.97, MAF = 0.86) of sediment from cultivated land, forest, and gully, respectively, for Scheme 1 while cultivated land, forest, gully, and unpaved road contributed 15.9%, 12.0%, 69.8%, and 2.4%, respectively (GOF=0.98, MAF=0.89), for Scheme 2. Our results demonstrated that the gully, owing to snowmelt erosion, is the dominant sediment source and more attention should be paid to prevent and control gully erosion in the black soil region of Northeast China during spring thawing period.

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