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Modeling point velocity and depth statistical distributions in steep tropical and alpine stream reaches

机译:在热带和高山急流中模拟点速度和深度统计分布

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摘要

[1] Statistical hydraulic models predict the frequency distributions of point hydraulic variables, relative to their reach-averaged values, in a stream reach based on its average characteristics (e.g., discharge, depth, width, average particle size). The models initially developed in Europe have not been tested for steeper streams (>4%) with coarse grain size. We recorded water velocities and depths in 44 reaches of steep streams in tropical islands and the Alps during 69 surveys. We fitted the observed distributions of velocities and depths using a mixture of two distributions, one with low variance and the other with a high variance. Then, we predicted the mixing parameter on the basis of the reach-averaged characteristics. We compared the observed and predicted frequencies for five classes of velocities, including a class of negative velocities, and four classes of water depths. The predictions of class frequencies have a bias of ≤5%. Our statistical model of velocity distribution predicts the frequencies of velocity classes with an explained variance between 33 and 72% for four classes of velocity and null for a class of intermediate velocity. The statistical model of depth distributions was less efficient with an explained variance between 25 and 38% for three classes of depth and null for large depths. The average Froude number, the total height of large drops relative to the reach length and the average slope are the main explanatory variables of velocity and depth distributions.
机译:[1]统计水力模型会根据点水力变量的平均特征(例如流量,深度,宽度,平均粒径)来预测点水力变量相对于其河水平均值的频率分布。最初在欧洲开发的模型尚未针对粗粒度的陡流(> 4%)进行过测试。在69次调查中,我们记录了热带岛屿和阿尔卑斯山44条陡峭溪流的水速和深度。我们使用两种分布的混合拟合观察到的速度和深度分布,一种分布具有低方差,另一种具有高方差。然后,我们根据到达平均特征预测混合参数。我们比较了五类速度(包括一类负速度)和四类水深的观测和预测频率。班级频率的预测偏差≤5%。我们的速度分布统计模型可预测速度类别的频率,其中四种速度类别的解释方差在33%到72%之间,而中间速度类别则为零。深度分布的统计模型效率较低,三类深度的解释方差在25%至38%之间,大深度则为零。平均弗洛德数,相对于到达长度的大液滴总高度和平均斜率是速度和深度分布的主要解释变量。

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  • 来源
    《Water resources research》 |2014年第1期|427-439|共13页
  • 作者

    V. Girard; N. Lamouroux; R. Mons;

  • 作者单位

    IRSTEA Lyon, UR MALY, Villeurbanne, France,ASCONIT Consultants, Espace Scientifique Tony Garnier, 6-8 Espace Henry Vallee, FR-69366 Lyon CEDEX, France;

    IRSTEA Lyon, UR MALY, Villeurbanne, France;

    IRSTEA Lyon, UR MALY, Villeurbanne, France;

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