Abstract
The non-stationarity of identifying hydrological extreme sequences is essential for understanding the patterns of hydrological systems and conducting reasonable risk assessments. Currently, research on detecting non-stationarity primarily determines whether the parameters of the sequence change through statistical tests. The study introduces the concept of distribution change to detect non-stationarity and proposes the Cumulative Distribution function Change Indicator (CDCI) to quantify the degree of non-stationarity in extreme sequences. Based on Hourly Precipitation Data from 102 U.S. Weather Stations, 1975–2021. Comparison with other methods commonly used for non-stationarity identification validates the reasonableness of CDCI. Additionally, it explores the relationship between non-stationarity, distribution, and return period based on CDCI. The research results demonstrate that: (1) Distribution change can reflect the non-stationarity of sequences, and CDCI is more sensitive compared to conventional non-stationarity identification methods; (2) By combining CDCI with return period change, the response of distribution to non-stationarity can be identified, including the location and degree of distributional change. The study demonstrates the feasibility and validity of distributional change being used as a measure of non-stationarity in hydrological extreme sequences. Furthermore, the results reveal the possible relationship between non-stationarity, distribution change, and return period change.
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The research data obtained by the NCEI and the authors would like to express much gratitude to the data provider. Matters related to data analysis in the research are available from the first or corresponding author upon request.
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Funding
This research was supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), the Graduate Research and Innovation Projects of Jiangsu Province (No.KYCX23_3547) and the Science and Technology Innovation Fund of Yangzhou University (No.135030607).
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All authors contributed to the design and research of the manuscript. Junbo Shao and Wenyue Wang were responsible for the data collecting and made a lot of work for the compiling of tables and plotting of graphs. Junbo Shao and Jingcai Wang carried out the data analysis and prepared the draft of the manuscript. Fan Li and Chen Wu participated in the research work and offered many important suggestions for the manuscript structure. All authors commented on previous versions of the manuscript.
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Shao, J., Wang, J., Wang, W. et al. Research on the Degree of Non-Stationarity in Extreme Precipitation in the Continental United States. Water Resour Manage 38, 537–551 (2024). https://doi.org/10.1007/s11269-023-03683-x
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DOI: https://doi.org/10.1007/s11269-023-03683-x