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Return period estimates of extreme sea level along the east coast of India from numerical simulations

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  • B. Sindhu
  • A. Unnikrishnan

Abstract

Estimates of return periods of extreme sea level events along the coast are useful for impact assessment. In this study, a vertically integrated 2D model was developed for the simulation of storm surges in the Bay of Bengal. The bathymetry for the model was derived from an improved ETOPO-5 data set, which was prepared in our earlier work. The meteorological forcing for the model was obtained from the cyclone model of Holland using the data available for 136 low-pressure systems that occurred during 1974–2000 in the Bay of Bengal. The simulated total sea level and the surge component were obtained for each event. The simulated peak levels showed good agreement with the observations available at few stations. The annual maxima of sea levels, extracted from the simulations, were fitted with Gumbel distribution using r-largest annual maxima method to estimate the 5- and 50-year return periods of extreme events at 26 stations along the east coast of India. The return periods estimated from simulated sea levels showed good agreement with those obtained from observations. The 5- and 50-year return levels of total sea level along the east coast of India show a considerable increase from south to north, with the 50-year return total sea levels being as high as 6.9 and 8.7 m at stations along the north eastern coast such as Sagar Island and Chandipur, respectively. The high return levels are expected at these stations as the cyclones developed in the Bay of Bengal generally move north or north-west, producing extreme events in the northern part, and moreover, these stations are characterized by high tidal ranges. However, at some regions in the southern part such as Surya Lanka and Machilipatnam, though 50-year return levels of total sea level are not very high (2.98 and 2.97 m, respectively) because of the relatively lower tidal ranges, high return levels of surges (0.84 and 0.57 m, respectively) are found. In addition to the role of shallow depths (5.0 and 6.1 m, respectively) at the two stations, the high return levels of surges are attributed to the effect of geometrical configuration at Surya Lanka and width (100 km) and orientation of continental shelf at Machilipatnam. Copyright Springer Science+Business Media B.V. 2012

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  • B. Sindhu & A. Unnikrishnan, 2012. "Return period estimates of extreme sea level along the east coast of India from numerical simulations," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 61(3), pages 1007-1028, April.
  • Handle: RePEc:spr:nathaz:v:61:y:2012:i:3:p:1007-1028
    DOI: 10.1007/s11069-011-9948-8
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    References listed on IDEAS

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    2. Malay Kumar Pramanik & Sumantra Sarathi Biswas & Biswajit Mondal & Raghunath Pal, 2016. "Coastal vulnerability assessment of the predicted sea level rise in the coastal zone of Krishna–Godavari delta region, Andhra Pradesh, east coast of India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 18(6), pages 1635-1655, December.
    3. S. Saxena & R. Purvaja & G. Mary Divya Suganya & R. Ramesh, 2013. "Coastal hazard mapping in the Cuddalore region, South India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 66(3), pages 1519-1536, April.
    4. Meenu Rani & Sufia Rehman & Haroon Sajjad & B. S. Chaudhary & Jyoti Sharma & Sandeep Bhardwaj & Pavan Kumar, 2018. "Assessing coastal landscape vulnerability using geospatial techniques along Vizianagaram–Srikakulam coast of Andhra Pradesh, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 94(2), pages 711-725, November.

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