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Sediment Dispersal off a High-Yield River: Observations and Modeling of Gravity-Driven Transport and Deposition

Sediment Dispersal off a High-Yield River: Observations and Modeling of Gravity-Driven Transport and Deposition
高产河流的沉积物扩散:重力驱动输送和沉积的观测和建模
批准号:
0326831
负责人:
Steven Kuehl
金额:
$69.34万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2003
资助国家:
美国
项目状态:
已结题
起止时间:
2003-11-15 至 2006-10-31

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中文摘要
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英文摘要
Under this funding, the PIs will study, through direct observations and modeling, the occurrence of hyperpycnal flows, their transport and extinction, and their stratigraphic record in an environment where annual river flooding generates sediment concentrations in excess of 20 g/l, the expected threshold for the formation of such flows. The Waiapu River, New Zealand is one of the most sediment-laden rivers in the world, with an average annual suspended sediment concentration exceeding 10g/L, and routinely generates hyperpycnal flows during annual flooding. This proposal hypothesizes that annual Waiapu floods result in hyperpycnal flows that would settle near shore in the absence of waves due to the low seabed gradient. Wave agitation, however, mobilizes these sediments and sustains suspensions dense enough to cause further downslope transport. In the proposed study, bottom-boundary layer measurements of sediment gravity flows, resuspension, and transport by waves and currents will be made under a range of forcing conditions on the inner and middle shelf using near-bottom tripods. Seabed sampling and measurements will document deposition from the initial flood pulse as well as the subsequent redistribution of material by waves and currents, and will examine both the fine-scale stratigraphy developed over a flood season and longer-term accumulation and stratigraphic signatures. All of these observations will be used to calibrate and refine analytical and numerical modeling efforts for sediment transport and deposition, and to evaluate dispersal patterns over time and spatial scales longer than the available bottom boundary layer observations.
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