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首页> 外文期刊>Journal of hydrologic engineering >Predicting Channel Conveyance in the Obion River Watershed Using SAMBLE Method
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Predicting Channel Conveyance in the Obion River Watershed Using SAMBLE Method

机译:用SAMBLE方法预测奥比恩河流域的河道输移。

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摘要

yy Digital elevation models (DEMs) are widely used for hydraulic modeling, but one of the challenges in using a DEM for hydraulic modeling is its limitations in accurately representing the channel conveyance. This limitation is usually disregarded because the collection of bathymetry data is time and resource intensive, and it is often unavailable for well-gauged watersheds as well. Thus, a DEM-based hydraulic model may lead to less accurate conclusions even if detailed hydrologic data are available. The situation is more challenging in large and morphologically active river systems because DEMs only represent the river condition of their acquisition time. Therefore, the objectives of this research are to (1) develop a DEM correction method for predicting channel conveyance at the watershed scale and (2) demonstrate the significance of riverbed-level change for flood risk assessment in the Obion River. The proposed DEM correction method is called Slope Adjusted Mean Bed Level Elevation (SAMBLE) and utilizes the hydrologic data of a watershed to predict average riverbed level and thus channel conveyance at a watershed scale. It is tested on the Obion River watershed in northwest Tennessee. Analysis of the results showed that the SAMBLE method can predict average riverbed level with less than 1 m error that is more accurate than the best available Light Detection and Ranging (LiDAR) DEM for the Obion River watershed. Additionally, it can predict riverbed-level changes using time series of hydrologic data. The significance of riverbed-level change on flood risk is also demonstrated by estimating aggradation-degradation (via SAMBLE) in a morphologically active segment of the Obion River. (C) 2019 American Society of Civil Engineers.
机译:yy数字高程模型(DEM)已广泛用于水力建模,但是使用DEM进行水力建模的挑战之一是其在准确表示通道传输方面的局限性。通常不会忽略此限制,因为测深数据的收集需要大量时间和资源,并且通常对于水准很高的流域也是不可用的。因此,即使有详细的水文数据,基于DEM的水力模型也可能导致不太准确的结论。在大型且形态活跃的河流系统中,这种情况更具挑战性,因为DEM仅代表其采集时间的河流状况。因此,本研究的目的是(1)开发一种DEM校正方法,以预测流域尺度上的河道输送量;(2)证明河床水位变化对奥比恩河洪水风险评估的重要性。提出的DEM校正方法称为“坡度调整平均河床水位高程(SAMBLE)”,并利用流域的水文数据预测平均河床水位,从而预测流域尺度的河道输送量。在田纳西州西北部的奥比恩河流域进行了测试。结果分析表明,SAMBLE方法可以预测平均河床水位,误差小于1 m,比Obion河流域的最佳可用光探测和测距(LiDAR)DEM更准确。此外,它可以使用水文数据的时间序列来预测河床水位的变化。河床水位变化对洪灾风险的重要性还可以通过估算奥比昂河形态活跃段的侵蚀-退化(通过SAMBLE)来证明。 (C)2019美国土木工程师学会。

著录项

  • 来源
    《Journal of hydrologic engineering》 |2020年第2期|05019033.1-05019033.12|共12页
  • 作者单位

    West Tennessee River Basin Author 3628 East End Dr Humboldt TN 38343 USA;

    Tennessee Technol Univ Civil & Environm Engn 1020 Stadium Dr Box 5015 Cookeville TN 38505 USA;

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  • 正文语种 eng
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