Using five long time series hydrometeorological data to calibrate a dynamic sediment delivery ratio algorithm for...

Area of Science:

• Earth and Environmental Sciences
• Hydrology
• Soil Science

Background:

• Accurate quantification of sediment yield is crucial for understanding catchment dynamics.
• Lack of dynamic, multi-scale sediment delivery ratio (SDR) data hinders accurate sediment yield assessment.
• The Loess Plateau faces significant challenges from soil erosion and sediment transport.

Purpose of the Study:

• To apply a dynamic, multi-scale SDR algorithm in a modified sediment yield model.
• To quantify spatiotemporal sediment delivery and its relationship with hydrometeorological and landscape factors.
• To provide insights for sustainable soil conservation planning in the Loess Plateau.

Main Methods:

• Development and application of a dynamic multi-scale SDR algorithm.
• Modification of a sediment yield model to incorporate the SDR algorithm.
• Analysis of sediment yield, hydrometeorological data, and landscape factors in a loess hilly and gully catchment.

Main Results:

• Sloping farmlands in the upstream catchment were identified as major sediment sources with intensive erosion.
• Large-scale soil conservation practices since the late 1990s led to a significant decrease in annual sediment yield.
• Sediment delivery ratio (SDR) showed stronger correlations with peak flow and runoff amount than with rainfall parameters.

Conclusions:

• Soil conservation measures are highly effective in reducing sediment yield in the Loess Plateau.
• Sediment delivery dynamics are more influenced by runoff and flow characteristics than direct rainfall in this region.
• The study provides crucial data for refining sediment yield models and guiding future soil conservation strategies.