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Impact of human activity and climate change on suspended sediment load: the upper Yellow River, China

Yao, Wenyi, Xu, Jiongxin
Environmental earth sciences 2013 v.70 no.3 pp. 1389-1403
air temperature, anthropogenic activities, climate, climate change, correlation, environmental management, evapotranspiration, minerals, pollutants, rivers, runoff, sand, sediment yield, soil erosion, storms, water conservation, watershed management, China, Yellow River
Fluvial suspended sediment has multi-fold environmental implications and the study of the variation in suspended sediment load (SSL) of rivers is important both in environmental earth sciences and in river environmental management. Based on data collected for the upper Yellow River of China in the past 50–60 years, the purpose of this study is to elucidate the impact of human activity and climate change on SSL, thereby to provide some knowledge for the improvement of the drainage basin management. The results show that the SSL of the upper Yellow River exhibited a remarkable decreasing trend. A number of reservoirs trapped a considerable amount of sediment, resulting in a reduction in SSL at Toudaoguai station, the most downstream station of the upper Yellow River. The analyses based on Mann–Kendall’U and double-mass plot indicate some turning points, which were caused by the Liujiaxia and Longyangxia Reservoirs, two major reservoirs on the upper Yellow River. The implementation of soil and water conservation measures reduced the runoff coefficient, and therefore, the intensity of soil erosion. The climate change also played a role in reducing sediment yield. The increase in air temperature enhanced the evapo-transpiration and reduced the runoff, by which the SSL decreased. The decreased frequency of sand-dust storms reduced the amount of wind-blown, sand and dust to the river reaches located in desert, also reducing the SSL. Seven influencing variables are selected to describe the changing human activity and climate. As some of the influencing variables are strongly inter-correlated, the principle component regression was used to establish the relationship between SSL and the influencing variables. The squared multiple correlation coefficient is R² = 0.823. Some further research is suggested with the minerals and pollutants related with the SSL.