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首页> 外文期刊>Water Resources Management >Estimation of the Parameters of Wakeby Distribution by a Numerical Least Squares Method and Applying it to the Annual Peak Flows of Turkish Rivers
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Estimation of the Parameters of Wakeby Distribution by a Numerical Least Squares Method and Applying it to the Annual Peak Flows of Turkish Rivers

机译：数值最小二乘法估算维克比分布参数并将其应用于土耳其河流的年高峰流量

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摘要

In this study, a numerical least squares (NLS) method for estimating the parameters of five-parameter Wakeby distribution was introduced. To asses the right tail estimate performances of the method, Monte Carlo simulated data and annual peak flows of 50 stations on Turkish rivers were used. Its results were compared to those by L-moments (LM) and curve fitting method of MATLAB. The biases from the LM for non-exceedence probability (F) of 0.999 mostly were less than those by the NLS. However, the values of relative root mean square error (rrmse) statistics from the NLS were better than those by the LM. In addition, the statistic of average deviation from the observed annual peak flows showed that NLS method exhibited mostly better results than those by LM for right tail predictions. Lastly, except the convergence problem of MATLAB, while both of the NLS and MATLAB produced the same determination coefficient (r~2) for the majority of data set, the NLS produced lower rrmse values than MATLAB.
机译：在这项研究中，介绍了一种用于估计五参数Wakeby分布参数的数值最小二乘（NLS）方法。为了评估该方法的右尾估计性能，使用了蒙特卡罗模拟数据和土耳其河流上50个站点的年峰值流量。将其结果与MATLAB的L矩（LM）和曲线拟合方法进行了比较。 LM的非超出概率（F）的偏差为0.999，大多数小于NLS的偏差。但是，来自NLS的相对均方根误差（rrmse）统计值比LM更好。此外，从观测到的年度峰值流量的平均偏差统计数据表明，对于右尾预测，NLS方法显示的结果要比LM方法的结果更好。最后，除了MATLAB的收敛性问题外，尽管NLS和MATLAB对于大多数数据集产生相同的确定系数（r〜2），但NLS产生的rrmse值低于MATLAB。

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