Abstract

AbstractSediment load of China's Yellow River has dramatically decreased due to the interplay of climate variability and human activities in the past decades. However, the contribution of individual driving factors and the detailed spatial distribution of sediment load at a catchment scale were not well understood. In the study, we quantitatively assessed the relative contributions of individual climatic (i.e. precipitation) and anthropogenic (i.e. vegetation restoration, terrace construction) driving factors to sediment load variations in the largest tributary of the Yellow River, Weihe River. The employed annual sediment load measurements and rainfall data for 1961–2015 were collected at 15 hydrological and 60 meteorological stations that were widely distributed in the basin. Changing trends, periodicity, and abrupt changes of hydro‐climatic variables were detected using the non‐parametric Mann–Kendall test, the empirical mode decomposition method, and Pettitt's test. Results showed that annual sediment load presented significantly decreasing trends at 12 hydrological stations. Annual rainfall erosivity showed a mixed tendency, with the changing trends varying among different regions. A 3‐year periodicity was identified in the annual sediment load at three main stream gauging stations. Abrupt changing points in sediment load primarily occurred in the 1990s and early 2000s at all of the 15 hydrological stations, which were largely attributed to human activities. The increase in vegetation cover was responsible for approximately 40.6%, 37.4%, and 54.7% of the sediment load reduction in the main stream of the Weihe River, the Jinghe River, and the Beiluohe River, respectively. Meanwhile, terrace construction accounted for 19.7%, 43.8%, and 9.9% of the sediment variation, respectively. Conversely, precipitation change accounted for 5.7%, 12.4%, and 8.3% of sediment load reduction, respectively. Overall, vegetation restoration and terrace construction were found to be the two dominating factors for sediment load reduction in the study area.

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