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A framework for determining lowest navigable water levels with nonstationary characteristics

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Abstract

The Lowest navigable water level (LNWL) is an important indicator used for navigation design to balance the relationship between navigation safety and economic benefits of a waterway. However, it is a challenge of accurately estimating LNWLs due to the nonstationary characteristics of observed water level data series. In this study, a comprehensive framework was developed for handling this issue. In this framework, inter-annual variabilities in both the mean and variance of water level series were described by decomposing original series and were eliminated by composing new series. Intra-annual variability was determined by detecting indicators describing intra-annual water level distributions. Considerations of inter- and intra-annual variabilities were combined by designing annual water level processes for the past and current environments. Shipping risks during both annual and multi-annual periods were considered in the framework as well. The framework was demonstrated in estimating LNWLs at the Gaodao and Shijiao stations in the North River basin, southern China. The recommended LNWLs at the Gaodao station were 22.32 m for 95% guaranteed rate and 21.84 m for 98% guaranteed rate; LNWLs at the Shijiao station were 0.27 m for 95% guaranteed rate and 0.15 m for 98% guaranteed rate. The impact of variance variability on estimations of LNWLs was also evaluated. Results indicated that the recommended LNWLs would have errors of 0.11 ~ 0.48 m at the Gaodao station and 0.03 ~ 0.04 m at the Shijiao station if the variance variability was not considered. The proposed framework was then compared with Nonstationary synthetic duration curve (NSDC) method, and results illustrated that the duration curves plotted by NSDC method were unreasonable, leading to inaccurate design values. Overall, the developed framework is more reasonable and suitable for designing LNWLs of waterways where the variabilities of the water levels at different time scales are different or where the historical water level data contain various variations .

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Data Availability

The authors gratefully acknowledged the valuable hydrological data and information provided by the Hydrology Bureau of Guangdong Province, China. The data that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

The code is available from the corresponding author upon reasonable request.

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Funding

This study was financially supported by the National Natural Science Foundation of China (No. 51579181, 91547205, and 41971040); the Research Council of Norway (No. 274310), and the Youth Innovation Promotion Association CAS (No. 2017074).

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Authors and Affiliations

Authors

Contributions

Ping Xie developed the main ideas. Lu Wang implemented the algorithms of the methods. Ping Xie collected the data used in the case study. Ping Xie, Chong-Yu Xu and Yan-Fang Sang provided funding for this study. Lu Wang wrote the original draft of the manuscript. Chong-Yu Xu, Yan-Fang Sang and Jie Chen supervised this study, reviewed and edited the original draft. Tao Yu validated the results of this study.

Corresponding authors

Correspondence to Ping Xie or Chong-Yu Xu.

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Conflict of interest

We confirm that this work is original and has not been published elsewhere, nor is it currently under consideration for publication elsewhere. All authors have read and approved the manuscript being submitted, and agree to its submittal to this journal, and have no conflicts of interest to disclose. The work described in this paper was supported financially by the National Natural Science Foundation of China (grant numbers 51579181, 91547205, and 41971040), and the Research Council of Norway (grant number 274310). The hydrological data and information of the study site were provided by the Hydrology Bureau of Guangdong Province, China.

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We confirm that this work is original and has not been published elsewhere, nor is it currently under consideration for publication elsewhere. All authors have read and approved the manuscript being submitted and agree to its publication in this journal.

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Appendices

Appendix 1

Details of the detection for inter-annual water level variability

See Tables 8 and 9.

Table 8 Results of Gaodao station
Table 9 Results of Shijiao station

Appendix 2

Partial process of typical years selection

See Table 10.

Table 10 Partial process of typical years selection

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Wang, L., Xie, P., Xu, CY. et al. A framework for determining lowest navigable water levels with nonstationary characteristics. Stoch Environ Res Risk Assess 36, 583–608 (2022). https://doi.org/10.1007/s00477-021-02058-1

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  • DOI: https://doi.org/10.1007/s00477-021-02058-1

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