Numerical study of storm surge-induced coastal inundation in Laizhou Bay, China

Abstract

Storm surge inundation can induce great disasters in coastal regions, and Laizhou Bay (LZB), located in the Bohai Sea, is a bay that frequently experiences coastal storm flooding. In this study, we perform a numerical study of the effects of wind and waves on the storm surge-induced coastal inundation in the LZB using the coupled model ADCIRC+SWAN. Two historical typhoons (No. 9216 Typhoon Polly (TY9216) and No. 1909 Typhoon Lekima (TY1909)) are considered, wave effects in terms of wind-wave-induced surface stress and radiation stress are included, and two widely used wind data sources (CFS and ERA5) are used. The results indicate that the total inundation area and average inundation depth in the LZB during TY1909 are 10.70%-19.16% larger than during TY9216, and the CFS wind field reproduces a 14.31%-23.05% more intense inundation simulation than does the ERA5 wind field. The wave-induced surface stress plays the primary role in increasing the inundation area and average depth by up to 11.42%-18.50% and 5.82%-8.75%, respectively, and the wave-induced radiation stress also increases the inundation area and average depth by 3.80%-6.60% and 3.70%-4.57%, respectively. The results highlight the importance of considering wave effects in storm surge-induced coastal inundation simulations, and we demonstrate that the wave effects on the inundation area can be quite sensitive to the choice of wind field source.

Mapping Compound Flooding Risks for Urban Resilience in Coastal Zones: A Comprehensive Methodological Review

“…Similarly, Tang (2013) implemented a domain decomposition method, facilitating tight coupling between the Godunov-type shallow-water model (SWM) and the ocean model FVCOM [179]. Moreover, Shi (2022) amalgamated the one-dimensional SWMM model into the two-dimensional ADCIRC model, achieving tight coupling to examine various flood factors [122], while Li (2022) employed the tightly coupled ADCIRC-SWAN model to study storm-surge-induced coastal inundation in Laizhou Bay [180]. Nonetheless, merely amplifying the coupling intensity may not suffice for accurate simulations.…”

A Review of Application of Machine Learning in Storm Surge Problems

“…Prediction of the inundation depth hydrograph is crucial for emergency managers to understand how flooding will develop and recede and enable timely decisions on mitigations and evacuations as the storm passes [67]. A quantity of storm surge models has been applied to accurately simulate hurricane inundation depths, for example, Delft 3D [68], ADCIRC [69], and FVCOM [70]. Despite the advanced understanding of the physics of coastal inundations, such simulation requires huge computational resources, and fitting ML models with complex spatio-temporal high-dimensional variables constitutes a major challenge [51].…”

Kết quả bước đầu thử nghiệm thuật toán XGBoost dự báo nước dâng do bão tại trạm Hòn Dáu

“…Thông thường, các mô hình số như POM [1][2], ROMS [3][4], ADCIRC [5][6], SuWAT [7][8][9][10], Delft3D [11][12] được sử dụng để dự báo nước dâng do bão có độ tin cậy cao do sử dụng các phương trình vật lý chính xác, nhưng thường đi kèm với đó là cần tài nguyên tính toán lớn, thời gian vận hành khá đáng kể. Với ưu điểm là linh hoạt và mạnh mẻ, có khả năng xác định các mối quan hệ phức tạp trong dung lượng lớn dữ liệu đầu vào nên trí tuệ nhân tạo (AI: Artificial Intelligence) sẽ phù hợp khi áp dụng để triển khai học máy chuyên sâu, phân tích dữ liệu đa yếu tố nhanh và chính xác.…”