Geomechanics and Engineering

  • 제35권5호
  • /
  • Pages.499-509
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  • 2023
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  • 2005-307X(pISSN)
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  • 2092-6219(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Application of deterministic models for obtaining groundwater level distributions through outlier analysis

  • Dae-Hong Min (Department of Construction and Disaster Prevention Engineering, Daejeon University) ;
  • Saheed Mayowa Taiwo (Infrastructure Group, Manawatu District Council) ;
  • Junghee Park (Department of Civil, Environmental Engineering, Incheon national University) ;
  • Sewon Kim (Department of Geotechnical Engineering Research, Korea Institute of Civil Engineering and Building Technology) ;
  • Hyung-Koo Yoon (Department of Construction and Disaster Prevention Engineering, Daejeon University)
  • 투고 : 2023.03.03
  • 심사 : 2023.11.16
  • 발행 : 2023.12.10
⟨ 이전 논문 다음 논문 ⟩

초록

The objective of this study is to perform outlier analysis to obtain the distribution of groundwater levels through the best model. The groundwater levels are measured in 10, 25 and 30 piezometers in Seoul, Daejeon and Suncheon in South Korea. Fifty-eight empirical distribution functions were applied to determine a suitable fit for the measured groundwater levels. The best fitted models based on the measured values are determined as the Generalized Pareto distribution, the Johnson SB distribution and the Normal distribution for Seoul, Daejeon and Suncheon, respectively; the reliability is estimated through the Anderson-Darling method. In this study, to choose the appropriate confidence interval, the relationship between the amount of outlier data and the confidence level is demonstrated, and then the 95% is selected at a reasonable confidence level. The best model shows a smaller error ratio than the GEV while the Mahalanobis distance and outlier labelling methods results are compared and validated. The outlier labelling and Mahalanobis distance based on median shown higher validated error ratios compared to their mean equivalent suggesting, the methods sensitivity to data structure.

키워드

과제정보

This research was supported by the Daejeon University Research Grants (2022).

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