Discussion of "Enhanced Predictions for Peak Outflow from Breached Embankment-猫眼课题宝

DOI：

10.1061/(asce)he.1943-5584.0000470

发表时间：

2012-03

期刊：

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通讯作者：

中科院分区：

其他

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作者：

C. Thornton;Michael W. Pierce;S. Abt;V. Singh

本文通过对87个溃坝实例资料的多元回归分析，提出了改进的溃坝洪峰流量预报公式。他们列出了16个表达式，其中包括Pierce等人（2010年）的5个表达式，这些表达式涉及大坝水库在溃决时的水位高度（hw）或蓄水量（V），或两者都作为自变量来预测溃决后的洪峰流量。尽管这些方程是基于大量数据，但数据库固有的弱点削弱了其应用的信心。例如，如原始论文表2所示，各种几何元素的数据不可用，这暗示了数据库中的不一致性，这是由作者报告的溃坝取证方法的弱点引起的。人们认识到，在溃坝情况下收集数据是一项危险的工作;因此，无论收集到什么数据，都具有很高的价值。此外，尽管从各种违规案例研究中收集的数据在统计上呈现混乱状态，但每条数据都可能揭示高度相关的信息。因此，利用每一个可用的数据似乎是合乎逻辑的，以改善预测的洪峰流量，通过突破大坝的装饰。因此，本文中的方程确实是向前迈出了一步，因为它们将水位高度（h），破坏时的水量（V）和平均路堤长度（L）或宽度（W）作为三个独立变量。然而，如果存在所有相关变量的数据，最好利用这些数据。因此，多变量分析，将坝后的水的高度，水的体积，和一个复合变量，其中包括作为三个独立变量的路堤的平均宽度和长度在一个单一的方程进行，而不是双方程的讨论中的文件，只有三个变量组成的时间。路堤的平均宽度和长度的可用性因案例研究而异。因此，使用组合这些几何变量的复合变量来推导回归方程。路堤平均宽度和长度这两个几何变量的总和被用来构思一个复合变量（W L）。这就避免了乘法运算中可能出现的奇异性问题。因此，新提出的方程纳入了统一的effectofall四个变量，它充分处理的两个几何变量的任何一个的不可用性，使该变量值等于零。此外，为了消除从基于单自变量和双自变量的一组相关性中选择方程时的困难，即，本文还提出了一个适用于每种情况的单一表达式。预测方程(1)反映了路堤长度的重要性。2和3（根据

By using multivariate regression analysis of data from 87 dambreach cases, the authors of the paper under discussion proposed new equations for improved prediction of peak discharge through breached dam embankments. They tabulated 16 expressions, including five attributed to Pierce et al. (2010) that involved height of water in the dam reservoir at the time offailure (hw), or storage (V), or both as independent variables to predict peak discharge through breached embankments.Although these equationsare based ona large amount of data, the weaknesses inherent in the database undermine the confidence in their application. For example, the nonavailability of data for various geometric elements, as presented in Table 2 of the original paper, alludesto the inconsistency in the databasethatarises from the weakness of dam-failure forensics methodology, as reported by the authors. It is recognized that the collection of data under circumstances of breached dam embankments is a risky operation; and therefore, whatever data is collected is of high value. Further, although the data collected from the various breach case studies present statistically chaotic conditions, every piece of data may reveal information of high relevance. Therefore, the utilization of each available piece of data seems logical for improved prediction of peak discharge through breached dam embankments. Hence, the equations in the paper are, indeed, a step ahead, for they incorporate the height of water level (h), volume of water at the time of failure (V), and average embankment length (L )o r width (W )a s three independent variables. However, it would have been better to utilize the data of all pertinent variables, if they existed. Therefore, multivariate analysis incorporating the height of water behind the dam embankment, volume of water, and a composite variable that includes both the average width and length of the embankment as three independent variables in a single equation was carried out, as opposed to the double equations of the paper under discussion, consisting of only three variables at a time. The availability of average width and length of embankment varies from one case study to another. Thus, a composite variable combining these geometric variables was used to derive a regression equation. The summation of two geometric variables, average width and length of embankment, was used to conceive a composite variable (W þ L). This allowed to obviate the problem of singularity that might arise with the multiplication operation. Thus, the newly proposed equation incorporates the unified effectofall four variables,which adequately deals with the nonavailability of any of the two geometric variables by putting that variable value equal to zero. Further, to eliminate the difficulty while selecting an equation from a group of correlations on the basis of single and double independent variables, i.e., height of water, volume of water, or both together for predicting peak outflow through breached embankments, a single expression for each case is also proposed. Predictive Equations Eq. (1) of the original paper reflects the importance of the length of embankment, and Figs. 2 and 3 (of the paper under

Discussion of "Enhanced Predictions for Peak Outflow from Breached Embankment

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