Abstract Sufficient hydrological data, such as streamflow, are important to represent the long-term characteristics of a watershed in order to support decision-making, policy and management. Lack of data remains one of the main challenges of hydrological analyses. Therefore, the main goal of this study is to extend streamflow records using a proposed approach where the wavelet transform (WT) is incorporated as a pre-processing method into eight existing record extension techniques, namely the ordinary least-square regression (OLS), maintenance of variance (MOVE) types 1–4, Kendall-Theil robust line (KTRL), KTRL2 and robust line of organic correlation (RLOC). The performance of the WT-based methods in estimating individual data values, means and standard deviations of the extended records, and a series of percentiles of the extended records was then compared with that of the respective conventional methods (i.e., without the WT). The data used in the analysis consisted of 67 pairs of target-index stations that were obtained from Canada’s Reference Hydrometric Basin Network database, all of which contain outliers. As such, the results and discussions obtained are applicable for cases where the data contain outliers. The WT-based methods (particularly the KTRL-WT, KTRL2-WT and RLOC-WT) demonstrated consistent improvements in precision and accuracy compared with their conventional counterparts, especially in estimating the means and standard deviations of the extended records. In estimating individual data values, the WT-based methods showed inconsistent improvements. Finally, in terms of percentiles, greater improvements were seen in the estimation of higher percentiles, more specifically for the MOVE1-WT, MOVE2-WT, KTRL2-WT and RLOC-WT compared with their conventional counterparts.

中文翻译：

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基于小波变换的传统流记录扩展方法的比较

摘要 充足的水文数据（如流量）对于表示流域的长期特征以支持决策、政策和管理非常重要。缺乏数据仍然是水文分析的主要挑战之一。因此，本研究的主要目标是使用建议的方法扩展流记录，其中将小波变换 (WT) 作为预处理方法合并到八种现有的记录扩展技术中，即普通最小二乘回归 (OLS)，方差维持 (MOVE) 类型 1-4、Kendall-Theil 稳健线 (KTRL)、KTRL2 和有机相关稳健线 (RLOC)。基于 WT 的方法在估计扩展记录的单个数据值、均值和标准差方面的性能，然后将扩展记录的一系列百分位数与相应的常规方法（即，没有 WT）的百分位数进行比较。分析中使用的数据包括从加拿大参考水文盆地网络数据库中获得的 67 对目标索引站，所有这些站都包含异常值。因此，获得的结果和讨论适用于数据包含异常值的情况。与传统方法相比，基于 WT 的方法（特别是 KTRL-WT、KTRL2-WT 和 RLOC-WT）在精确度和准确度方面表现出持续的改进，尤其是在估计扩展记录的均值和标准偏差方面。在估计单个数据值时，基于 WT 的方法显示出不一致的改进。最后，就百分位数而言，