Articles | Volume 27, issue 12
https://doi.org/10.5194/hess-27-2325-2023
https://doi.org/10.5194/hess-27-2325-2023
Research article
 | 
28 Jun 2023
Research article |  | 28 Jun 2023

Study on a mother wavelet optimization framework based on change-point detection of hydrological time series

Jiqing Li, Jing Huang, Lei Zheng, and Wei Zheng

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Short summary
Under the joint action of climate–human activities the use of runoff data whose mathematical properties have changed has become the key to watershed management. To determine whether the data have been changed, the number and the location of changes, we proposed a change-point detection framework. The problem of determining the parameters of wavelet transform has been solved by comparing the accuracy of identifying change points. This study helps traditional models adapt to environmental changes.