Numerical Simulation of the Beach Response Mechanism under Typhoon Lekima: A Case Study of the Southern Beach of Chudao
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area and Data
2.2. Numerical Model Method
2.2.1. Overview of the XBeach Model
2.2.2. Model Grid Setup
2.2.3. Model Parameters Setup
- (1)
- Constructing the likelihood function:
- (2)
- Setting the threshold: Choosing a threshold that is too low is not conducive to determining the parameter tuning range, while a high threshold may result in fewer occurrences in which the threshold is exceeded. In this paper, a BSS threshold of 0.3 is selected.
- (3)
- Parameter sensitivity ranking: Assuming the numerical ranges of the base parameters follow a uniform distribution of likelihood functions, the simulated cumulative likelihood functions of each parameter are compared and analyzed against the assumed cumulative uniform functions.
Parameter | Description | Default | Recommended Range |
---|---|---|---|
facua | The extent to which wave skewness and asymmetry impact the directional movement of sediment. | 0.1 | 0–1 |
eps | Depth threshold for distinguishing between wet and dry cells. | 0.005 | 0.001–0.1 |
gamma | The wave dissipation model’s breaker index. | 0.55 | 0.4–0.9 |
gammax | The maximum permissible ratio of wave height to water depth. | 2 | 0.4–5 |
2.2.4. Model Validation
3. Results
3.1. Beach Dynamic Response Status
3.2. Dynamic Changes of Beach Profile
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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BSS Value Range | Prediction Effect |
---|---|
1~0.8 | Good |
0.8~0.6 | Preferable |
0.6~0.3 | Reasonable |
0.3~0 | Not good |
<0 | Difference |
Height-Value Relation | Beach Response State |
---|---|
< | scouring |
< | erosion |
> , < | overwash |
> , > | breaching |
Time | P1 | P2 | P3 | P4 | P5 |
---|---|---|---|---|---|
UED (m3) | UED (m3) | UED (m3) | UED (m3) | UED (m3) | |
9 h | 1.03 | 0.61 | −0.42 | −1.65 | 0.82 |
24 h | −5.11 | −3.83 | −6.95 | −9.34 | −9.32 |
48 h | −12.57 | −8.80 | −19.25 | −14.93 | −19.21 |
Simulation 72 h | −14.50 | −8.71 | −21.62 | −16.79 | −20.75 |
Measured 72 h | −12.46 | −13.40 | −18.71 | −15.47 | −18.45 |
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Xing, H.; Li, P.; Zhang, L.; Xue, H.; Shi, H.; You, Z. Numerical Simulation of the Beach Response Mechanism under Typhoon Lekima: A Case Study of the Southern Beach of Chudao. J. Mar. Sci. Eng. 2023, 11, 1156. https://doi.org/10.3390/jmse11061156
Xing H, Li P, Zhang L, Xue H, Shi H, You Z. Numerical Simulation of the Beach Response Mechanism under Typhoon Lekima: A Case Study of the Southern Beach of Chudao. Journal of Marine Science and Engineering. 2023; 11(6):1156. https://doi.org/10.3390/jmse11061156
Chicago/Turabian StyleXing, Hao, Pingping Li, Lili Zhang, Huaiyuan Xue, Hongyuan Shi, and Zaijin You. 2023. "Numerical Simulation of the Beach Response Mechanism under Typhoon Lekima: A Case Study of the Southern Beach of Chudao" Journal of Marine Science and Engineering 11, no. 6: 1156. https://doi.org/10.3390/jmse11061156
APA StyleXing, H., Li, P., Zhang, L., Xue, H., Shi, H., & You, Z. (2023). Numerical Simulation of the Beach Response Mechanism under Typhoon Lekima: A Case Study of the Southern Beach of Chudao. Journal of Marine Science and Engineering, 11(6), 1156. https://doi.org/10.3390/jmse11061156