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<p>The tropical cyclones (TCs) in the Bay of Bengal (BoB) have led to severe coastal flooding, causing substantial casualties and property damage. A comprehensive risk assessment for BoB storm surges is thus crucial for developing mitigation and adaptation strategies. However, this is currently hampered by our limited understanding of the complex hydrodynamics and relatively infrequent occurrence of TCs in the BoB. This study addresses these constraints by employing a fully coupled ADCIRC+SWAN modeling system, forced with a large number (2570) of synthetic TCs, physically and statistically representing the present-day observed TCs in the BoB. The model realistically simulates the total water levels influenced by storm surge, tides, and wave setup, revealing significant spatial variability in extreme storm surge levels. The northern BoB is the most vulnerable region, with surge extremes (up to 8&#xa0;m) amplified by shallow bathymetry, a concave coastline, and a broad continental shelf. Intensity-specific composites demonstrate significant nonlinear amplification of water levels with increasing TC intensity, particularly in specific coastal hotspots. A copula-based bivariate joint probability distribution shows the dependence between pre-landfall wind speeds and peak storm surges across the BoB. Regional differences are notable: northern BoB shows weaker dependence due to complex coastal features, while central east coast exhibits the strongest correlation. Southern east coast displays moderate extremes. High-impact events, though rare, pose serious threats, with 50-year return events exceeds 8&#xa0;m in surge and 55&#xa0;m/s pre-landfall wind speed. The study offers a complete picture of TC-induced coastal hazards by incorporating joint extremes analysis and synthetic TC datasets. It enables a robust estimation of low probability and high impact events, addressing historical data gaps and offering valuable insights for regional coastal planning and compound TC hazard assessment in data-sparse regions.</p>

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Probabilistic assessment of tropical cyclone-induced storm surge hazards along the Bay of Bengal coast

  • 期刊论文

  • 发表日期：

    2026年5月21日

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  • V. Adithyan,
  • S. Neetu,
  • Athira Krishnan

摘要

The tropical cyclones (TCs) in the Bay of Bengal (BoB) have led to severe coastal flooding, causing substantial casualties and property damage. A comprehensive risk assessment for BoB storm surges is thus crucial for developing mitigation and adaptation strategies. However, this is currently hampered by our limited understanding of the complex hydrodynamics and relatively infrequent occurrence of TCs in the BoB. This study addresses these constraints by employing a fully coupled ADCIRC+SWAN modeling system, forced with a large number (2570) of synthetic TCs, physically and statistically representing the present-day observed TCs in the BoB. The model realistically simulates the total water levels influenced by storm surge, tides, and wave setup, revealing significant spatial variability in extreme storm surge levels. The northern BoB is the most vulnerable region, with surge extremes (up to 8 m) amplified by shallow bathymetry, a concave coastline, and a broad continental shelf. Intensity-specific composites demonstrate significant nonlinear amplification of water levels with increasing TC intensity, particularly in specific coastal hotspots. A copula-based bivariate joint probability distribution shows the dependence between pre-landfall wind speeds and peak storm surges across the BoB. Regional differences are notable: northern BoB shows weaker dependence due to complex coastal features, while central east coast exhibits the strongest correlation. Southern east coast displays moderate extremes. High-impact events, though rare, pose serious threats, with 50-year return events exceeds 8 m in surge and 55 m/s pre-landfall wind speed. The study offers a complete picture of TC-induced coastal hazards by incorporating joint extremes analysis and synthetic TC datasets. It enables a robust estimation of low probability and high impact events, addressing historical data gaps and offering valuable insights for regional coastal planning and compound TC hazard assessment in data-sparse regions.