Attribution analysis of sediment transport variation in the Xihan River Basin, upper Jialing River, China

中国 水文学(农业) 泥沙输移 沉积物 地质学 流域 构造盆地 环境科学 地貌学 地理 岩土工程 地图学 考古
作者
Heng Liao,Yi He
出处
期刊:Earth Surface Processes and Landforms [Wiley]
卷期号:50 (10)
标识
DOI:10.1002/esp.70148
摘要

Abstract Over the past 50 years, the sediment load in the upper Jialing River has undergone significant changes, warranting a detailed analysis of the driving factors behind this variation—particularly the relative contributions of human activities and climate change. Using sediment observation data from 1965 to 2016, we examined sediment load trends in the Xihan River Basin, a key subregion of the upper Jialing River. Our analysis employed multiple methods, including the double mass curve (DMC), sediment identification factor assessment and the elasticity coefficient method, to investigate sediment discharge changes and quantify the relative impacts of human activities and precipitation. The results reveal a pronounced downward trend in sediment transport, while rainfall showed only a slight decrease over the same period. According to the DMC analysis, human activities accounted for approximately 73.4% of the sediment load reduction, with rainfall (as a proxy for climate change) contributing 26.6%. The sediment identification factor assessment further indicated that sediment concentration, runoff and precipitation contributed 66.2%, 30.9% and 2.9%, respectively, to sediment load variations. These findings were corroborated by the elasticity coefficient method, which attributed 74.1% of the changes to human activities and 25.9% to climate change. Collectively, these results highlight the dominant influence of human activities on sediment load variation in the Xihan River Basin. This underscores the importance of targeted human interventions to effectively manage sediment transport in the region. Moreover, the insights gained from this study provide valuable guidance for sediment management strategies applicable to other watersheds facing similar challenges.
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