The Optimization of Four Key Parameters in the XBeach Model by GLUE Method: Taking Chudao South Beach as an Example
When the XBeach model is used to simulate beach profiles, the selection of four sensitive parameters—facua, gammax, eps, and gamma—is crucial. Among these, the two key parameters, facua and gamma, are particularly sensitive. However, the XBeach model does not specify the exact choice of these four k...
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2025-03-01
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| author | Yunyun Gai Longsheng Li Zikang Li Hongyuan Shi |
| author_facet | Yunyun Gai Longsheng Li Zikang Li Hongyuan Shi |
| author_sort | Yunyun Gai |
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| description | When the XBeach model is used to simulate beach profiles, the selection of four sensitive parameters—facua, gammax, eps, and gamma—is crucial. Among these, the two key parameters, facua and gamma, are particularly sensitive. However, the XBeach model does not specify the exact choice of these four key parameters, offering only a broad range for each one. In this paper, we investigate the applicability of tuning these four parameters within the XBeach model. We employ Generalized Likelihood Uncertainty Estimation (GLUE) to optimize the model settings. The Brier Skill Score (<i>BSS</i>) for each parameter combination is calculated to quantify the likelihood probability distribution of each parameter. The optimal parameter set (facua = 0.20, gamma = 0.50) was ultimately determined. Here, the facua parameter represents the degree of influence of wave skewness and asymmetry on the direction of sediment transport, while the gamma parameter represents the equivalent random wave in the wave dissipation model and is used to calculate the probability of wave breaking. Six profiles of the southern beach on Chudao Island are selected to validate the results, establishing the XBeach model based on profile measurement data before and after Typhoon “Lekima”. The results indicate that after parameter optimization, the simulation accuracy of XBeach is significantly improved, with the <i>BSS</i> increasing from 0.3 and 0.17 to 0.68 and 0.79 in P1 and P6 profiles, respectively. This paper provides a recommended range for parameter values for future research. |
| format | Article |
| id | doaj-art-0052d4204bdd45ca9fe6bcf6e7e2b8f3 |
| institution | Kabale University |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-03-01 |
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| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-0052d4204bdd45ca9fe6bcf6e7e2b8f32025-08-20T03:43:36ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-03-0113355510.3390/jmse13030555The Optimization of Four Key Parameters in the XBeach Model by GLUE Method: Taking Chudao South Beach as an ExampleYunyun Gai0Longsheng Li1Zikang Li2Hongyuan Shi3The Department of Food and Biochemical Engineering, Yantai Vocational College, Yantai 264670, ChinaCollege of Water Conservancy and Civil Engineering, Ludong University, Yantai 264025, ChinaCollege of Water Conservancy and Civil Engineering, Ludong University, Yantai 264025, ChinaCoastal Research Institute, Ludong University, Yantai 264025, ChinaWhen the XBeach model is used to simulate beach profiles, the selection of four sensitive parameters—facua, gammax, eps, and gamma—is crucial. Among these, the two key parameters, facua and gamma, are particularly sensitive. However, the XBeach model does not specify the exact choice of these four key parameters, offering only a broad range for each one. In this paper, we investigate the applicability of tuning these four parameters within the XBeach model. We employ Generalized Likelihood Uncertainty Estimation (GLUE) to optimize the model settings. The Brier Skill Score (<i>BSS</i>) for each parameter combination is calculated to quantify the likelihood probability distribution of each parameter. The optimal parameter set (facua = 0.20, gamma = 0.50) was ultimately determined. Here, the facua parameter represents the degree of influence of wave skewness and asymmetry on the direction of sediment transport, while the gamma parameter represents the equivalent random wave in the wave dissipation model and is used to calculate the probability of wave breaking. Six profiles of the southern beach on Chudao Island are selected to validate the results, establishing the XBeach model based on profile measurement data before and after Typhoon “Lekima”. The results indicate that after parameter optimization, the simulation accuracy of XBeach is significantly improved, with the <i>BSS</i> increasing from 0.3 and 0.17 to 0.68 and 0.79 in P1 and P6 profiles, respectively. This paper provides a recommended range for parameter values for future research.https://www.mdpi.com/2077-1312/13/3/555XBeachGLUE methodbeach morphological evolutionoptimal parameter set |
| spellingShingle | Yunyun Gai Longsheng Li Zikang Li Hongyuan Shi The Optimization of Four Key Parameters in the XBeach Model by GLUE Method: Taking Chudao South Beach as an Example Journal of Marine Science and Engineering XBeach GLUE method beach morphological evolution optimal parameter set |
| title | The Optimization of Four Key Parameters in the XBeach Model by GLUE Method: Taking Chudao South Beach as an Example |
| title_full | The Optimization of Four Key Parameters in the XBeach Model by GLUE Method: Taking Chudao South Beach as an Example |
| title_fullStr | The Optimization of Four Key Parameters in the XBeach Model by GLUE Method: Taking Chudao South Beach as an Example |
| title_full_unstemmed | The Optimization of Four Key Parameters in the XBeach Model by GLUE Method: Taking Chudao South Beach as an Example |
| title_short | The Optimization of Four Key Parameters in the XBeach Model by GLUE Method: Taking Chudao South Beach as an Example |
| title_sort | optimization of four key parameters in the xbeach model by glue method taking chudao south beach as an example |
| topic | XBeach GLUE method beach morphological evolution optimal parameter set |
| url | https://www.mdpi.com/2077-1312/13/3/555 |
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