Evaluation of the SEdiment Delivery Distributed (SEDD) model in the Shihmen Reservoir watershed

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Abstract

The sediment delivery ratio (SDR) connects the weight of sediments eroded and trans-ported from slopes of a watershed to the weight that eventually enters streams and rivers ending at the watershed outlet. For watershed management agencies, the estimation of annual sediment yield (SY) and the sediment delivery has been a top priority due to the influence that sedimentation has on the holding capacity of reservoirs and the annual economic cost of sediment-related disasters. This study establishes the SEdiment Delivery Distributed (SEDD) model for the Shihmen Reservoir watershed using watershed-wide SDRw and determines the geospatial distribution of individual SDRi and SY in its sub-watersheds. Furthermore, this research considers the statistical and geospa-tial distribution of SDRi across the two discretizations of sub-watersheds in the study area. It shows the probability density function (PDF) of the SDRi. The watershed-specific coefficient (β) of SDRi is 0.00515 for the Shihmen Reservoir watershed using the recursive method. The SY mean of the entire watershed was determined to be 42.08 t/ha/year. Moreover, maps of the mean SY by 25 and 93 sub-watersheds were proposed for watershed prioritization for future research and remedial works. The outcomes of this study can ameliorate future watershed remediation planning and sediment control by the implementation of geospatial SDRw/SDRi and the inclusion of the sub-watershed prioritiza-tion in decision-making. Finally, it is essential to note that the sediment yield modeling can be im-proved by increased on-site validation and the use of aerial photogrammetry to deliver more up-dated data to better understand the field situations.

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APA

Thomas, K., Chen, W., Lin, B. S., & Seeboonruang, U. (2020). Evaluation of the SEdiment Delivery Distributed (SEDD) model in the Shihmen Reservoir watershed. Sustainability (Switzerland), 12(15). https://doi.org/10.3390/su12156221

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