A new methodological framework coupling computational fluid dynamics and fingerprinting for assessment of aeolian sediment transport processes

Abstract A systematic understanding of the transport processes of aeolian sand from source to sedimentary areas is important for both hazard control and fundamental mechanism research. This study proposes a methodological framework consisting of wind data standardisation, computational fluid dynamics (CFD) simulation and fingerprinting technology to clarify aeolian sediment transport processes. The methodological framework was applied to the Cuona Lake section of the Qinghai-Tibetan Railway as a case study. One main finding was that the mountain passes located on the west of the lake act as outlets that converge and accelerate the predominant wind. The Basuoqu river valley and Amdo-Cuona down-faulted valley act as a ventilation tunnel in the sedimentary area. The CFD simulation clearly showed the influence of the complex terrain on the wind flow field. Second, the area southwest of the lake was predicted to be the main sediment source; a large portion of this area has an annual wind power density exceeding 1000 W/m2. Third, the fingerprinting estimation results revealed that the predicted main source area contributed more than 80% to the target sediment, which was in good agreement with the CFD simulation result. A decision-tree is provided to guide interested users in critical choices for different situations and research objectives. This CFD- and fingerprinting- based framework has the potential to contribute significantly to aeolian research and facilitate the development of a more detailed methodology.