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Modeling Anchor Ice Presence-absence In Gravel Bed Rivers

机译:砾石床河流中锚固冰缺失的建模

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We studied the meteorological and hydraulic conditions conducive to anchor ice formation in three gravel bed rivers of southern Quebec (Beauport, Duberger and York rivers). First, a dataset including the dichotomous response variable presence-absence of anchor ice in a river reach, and ten continuous predictors related to air temperature (freezing degree-hours FDH cumulated over 6, 8, 12, 24 and 48 h) and water temperature (W averaged over 6, 8, 12, 24 and 48 h) was used to develop a logistic regression model of anchor ice presence at the river reach level. The model developed in this study used the variable FDH-12 to correctly predict 80.9% of the anchor ice presence-absence observations. More specifically, it predicted that anchor ice is more likely to form when a threshold FDH-12 value of 111.7 ℃-h is exceeded. Second, data on the presence of anchor ice at the parcel level (0.25 m~2) was collected at the Beauport and Duberger study reaches in order to determine the effect of local hydraulic conditions on the formation of anchor ice. Covariates common to all parcels within a river reach (air and water temperature) and hydraulic variables specific to each parcel (flow velocity, water depth, Froude and Reynolds numbers) were used as explanatory variables. The results of the stepwise hierarchical logistic regression analysis showed that the Froude number was the first variable to enter the model and that it could not be improved significantly by adding any other variable. The model correctly classified 67.5% of the presence-absence observations of anchor ice on the parcels and indicated that anchor ice was most likely to form at Froude values larger than 0.1.
机译:我们研究了有利于在魁北克省南部的三条砾石床河(波波特河,杜伯格河和约克河)锚固冰形成的气象和水力条件。首先,一个数据集包括河段中锚冰的二分响应变量的存在与缺失,以及与气温(在6、8、12、24和48小时内累积的FDH小时数)和水温有关的十个连续预测变量(在6、8、12、24和48 h内平均得到W)被用于建立河流河段锚固冰存在的逻辑回归模型。在这项研究中开发的模型使用变量FDH-12正确预测了80.9%的锚冰存在与否的观察结果。更具体地说,它预测,当超过111.7℃-h的FDH-12阈值时,更有可能形成锚冰。其次,在Beauport和Duberger研究中心收集了包裹水平(0.25 m〜2)处锚固冰存在的数据,以确定局部水力条件对锚固冰形成的影响。将河段内所有地块共有的协变量(气温和水温)和每个地块特有的水力变量(流速,水深,弗洛德和雷诺数)用作解释变量。逐步分层逻辑回归分析的结果表明,弗洛德数是进入模型的第一个变量,并且无法通过添加任何其他变量来对其进行显着改善。该模型正确分类了包裹上锚固冰存在与否的67.5%观测值,并表明在Froude值大于0.1的情况下,锚固冰最有可能形成。

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