Comparison of Ordinary and Generalised Least Squares Regression Models in Regional Flood Frequency Analysis: A Case Study for New South Wales
Comparison of Ordinary and Generalised Least Squares Regression Models in Regional Flood Frequency Analysis: A Case Study for New South Wales
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区域洪水频率分析中普通最小二乘回归模型与广义最小二乘回归模型的比较：以新南威尔士州为例
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发表时间：
2011
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通讯作者：
G. Kuczera
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作者：
K. Haddad;A. Rahman;G. Kuczera
摘要区域洪水频率分析（RFFA）技术常用于估算无资料集水区的设计洪水。在澳大利亚降雨和径流（ARR）中，概率理性方法（PRM）被推荐用于新南威尔士州东部（NSW）。最近在澳大利亚的研究表明，基于回归的RFFA方法可以提供比PRM更准确的设计洪水估计。本文比较了普通最小二乘（OLS）和广义最小二乘（GLS）的分位数回归技术，使用的数据从96个小型到中型的集水区在新南威尔士州的平均复发间隔为2至100年。GLS回归的优点是，这说明了站间的相关性和不同的记录长度从网站到网站。一个独立的测试的基础上分裂样本和一次一个验证方法采用了广泛的统计诊断表明，GLS回归提供了更准确的洪水分位数估计比OLS之一。开发的回归方程是比较容易应用，它只需要两到三个预测，集水面积，设计降雨强度和流密度的数据。这项研究的结果，以及正在审查的其他RFFA研究的一部分，ARR升级项目将告知RFFA技术的发展，包括在修订版的ARR。
Abstract Regional flood frequency analysis (RFFA) techniques are commonly used to estimate design floods for ungauged catchments. In Australian Rainfall and Runoff (ARR), the probabilistic rational method (PRM) was recommended for eastern New South Wales (NSW). Recent studies in Australia have shown that regression-based RFFA methods can provide more accurate design flood estimates than the PRM. This paper compares ordinary least squares (OLS) and generalised least squares (GLS) based quantile regression techniques using data from 96 small-to medium-sized catchments across NSW for average recurrence intervals of 2 to 100 years. The advantages of the GLS regression are that this accounts for the inter-station correlation and varying record lengths from site to site. An independent test based on both the split-sample and one-at-a-time validation approaches employing a wide range of statistical diagnostics indicates that the GLS regression provides more accurate flood quantile estimates than the OLS one. The developed regression equations are relatively easy to apply, which require data for only two to three predictors, catchment area, design rainfall intensity and stream density. The findings from this study together with those from other RFFA studies being examined as a part of ARR upgrade projects will inform the development of RFFA techniques for inclusion in the revised edition of ARR.