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A semi-physical sediment yield model for estimation of suspended sediment in loess region

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Abstract Sediment yield is a complex function of many environmental factors including climate, hydrology, vegetation, basin topography, soil types, and land cover. We present a new semi-physical watershed sediment yield… Click to show full abstract

Abstract Sediment yield is a complex function of many environmental factors including climate, hydrology, vegetation, basin topography, soil types, and land cover. We present a new semi-physical watershed sediment yield model for the estimation of suspended sediment in loess region. This model is composed by three modules in slope, gully, and stream phases. For slope sediment yield, a balance equation is established based on the concept of hydraulic erosion capacity and soil erosion resistance capacity. According to the statistical analysis of watershed characteristics, we use an exponential curve to approximately describe the spatial variability of watershed soil erosion resistance capacity. In gully phase, the relationship between gully sediment concentration and flow velocity is established based on the Bagnold׳ stream power function. In the stream phase, we assume a linear dependence of the sediment volume in the reach on the weighted sediment input and output. The proposed sediment yield model is operated in conjunction with a conceptual hydrologic model, and is tested over 16 regions including testing grounds, and small, medium and large watersheds in the loess plateau region in the mid-reach of Yellow River. Our results indicate that the model is reasonable in structure and is able to provide a good simulation of sediment generation and transportation processes at both flood event scale and inter-annual time scale. The proposed model is generally applicable to the watersheds with soil texture similar to that of the loess plateau region in the Yellow River basin in China.

Keywords: semi physical; sediment yield; yield model; model; region

Journal Title: International Journal of Sediment Research
Year Published: 2017

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