Volume 16 Issue 3
Sep.  2023
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Yi-ming Hu, Zhong-min Liang, Yi-xin Huang, Jun Wang, Bin-quan Li. 2023: Assessment of first-order-moment-based sample reconstruction method for design flood estimation in changing environment. Water Science and Engineering, 16(3): 226-233. doi: 10.1016/j.wse.2023.05.001
Citation: Yi-ming Hu, Zhong-min Liang, Yi-xin Huang, Jun Wang, Bin-quan Li. 2023: Assessment of first-order-moment-based sample reconstruction method for design flood estimation in changing environment. Water Science and Engineering, 16(3): 226-233. doi: 10.1016/j.wse.2023.05.001

Assessment of first-order-moment-based sample reconstruction method for design flood estimation in changing environment

doi: 10.1016/j.wse.2023.05.001

This work was supported by the National Key Research and Development Program of China (Grant No. 2018YFC1508001), the National Natural Science Foundation of China (Grant No. 51709073), and the Fundamental Research Funds for the Central Universities of China (Grant No. B220202031).

  • Received Date: 2021-12-29
  • Accepted Date: 2023-05-22
  • Rev Recd Date: 2023-04-21
  • Estimating the design flood under nonstationary conditions is challenging. In this study, a sample reconstruction approach was developed to transform a nonstationary series into a stationary one in a future time window (FTW). In this approach, the first-order moment (EFTW) of an extreme flood series in the FTW was used, and two possible methods of estimating EFTW values in terms of point values and confidence intervals were developed. Three schemes were proposed to analyze the uncertainty of design flood estimation in terms of sample representativeness, uncertainty from EFTW estimation, and both factors, respectively. To investigate the performance of the sample reconstruction approach, synthesis experiments were designed based on the annual peak series of the Little Sugar Creek in the United States. The results showed that the sample reconstruction approach performed well when the high-order moment of the series did not change significantly in the specified FTW. Otherwise, its performance deteriorated. In addition, the uncertainty of design flood estimation caused by sample representativeness was greater than that caused by EFTW estimation.


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