Using five long time series hydrometeorological data to calibrate a dynamic sediment delivery ratio algorithm for multi-scale sediment yield predictions.

Abstract

The sediment delivery ratio (SDR) is a key link between slope erosion and river sediment transport but the accurate quantification of sediment yield in different catchments has been hampered by a lack of dynamic multi-scale information on SDR. A dynamic multi-scale SDR algorithm was innovatively applied in the modified sediment yield model to quantify the spatiotemporal evolutions of sediment delivery and inventory the relationships between sediment yield and different hydrometeorological and landscape factors in the loess hilly and gully catchment. Results indicate that (i) The sloping farmland (dry lands in hilly areas) in the upstream catchment of Ansai hydrological station was an important sediment source because its soil erosion grade was between intensive and extremely intensive. The high-risk regions of sediment yield were primarily concentrated in the sloping farmlands locating at both sides of the river banks. (ii) The large-scale soil conservation practices since the late 1990s have played a very significant role in sediment reduction. The annual sediment yield rate showed an overall decreasing trend from 1981 to 2015, particularly, it decreased dramatically from 11,844.08t•km-2 in 2005 to 65t•km-2 in 2015. (iii) The correlations between SDR and sediment yield rate, maximum peak flow, or runoff amount were all greater than that of rainfall parameters, indicating that there was no direct causal relationship between SDR and rainfall indicators in loessial ecological restoration watersheds. Results provide scientific insights needed to guide model modifications and sustainable soil conservation planning in the Loess Plateau.