Ikpoto Udoh

03 August 2012

Regional attributes of hurricane surge response functions for hazard assessment

  • Youn Kyung Song
  • , Jennifer L. Irish 
  • , Ikpoto E. Udoh         2012


Accurate quantification of hurricane surge probabilities is critically important for coastal planning and design. Recently, the joint probability method has been shown to yield statistically reliable surge probabilities and has quickly become the method of choice for extreme-value surge analysis in the United States. A main disadvantage of the joint probability method is the requirement to have accurate computational surge simulations for a large array of hurricane conditions. Recently, this shortcoming has been overcome by using a variety of interpolation schemes to reduce the number of surge simulations required to an optimal sample for joint probability analysis. One interpolation scheme uses response functions, or physically based dimensionless scaling laws, that consider the relative impact of hurricane landfall position, central pressure, and storm size on surge magnitude at the location of interest. Here, the influence of regional changes in bathymetry on the physically based response function form is investigated. It will be shown that the influence of continental shelf width on surge generation along a continuous coast is coupled with the influence of storm size and that this coupled physical effect can be treated within the response functions via dimensionless scaling. The surge response function model presented here has an algebraic form for rapid calculation. This model performs well for the entire 600-km Texas coast, yielding accurate surge estimates (root-mean-square errors less than 0.22 m and R 2 correlations better than 0.97) with virtually no bias (mean error magnitudes less than 0.03 m).


Storm surge Coastal flooding Tropical cyclones Hurricanes Risk assessment




Development and uncertainty quantification of hurricane surge response functions for hazard assessment in coastal bays

  • Nick R. Taylor
  • , Jennifer L. Irish 
  • , Ikpoto E. Udoh                     2015
  • , Matthew V. Bilskie
  • , Scott C. Hagen


Reliable and robust methods of extreme value-based hurricane surge prediction, such as the joint probability method (JPM), are critical in the coastal engineering profession. The JPM has become the preferred surge hazard assessment method in the USA; however, it has a high computational cost: One location can require hundreds of simulated storms and more than ten thousand computational hours to complete. Optimal sampling methods that use physics-based surge response functions (SRFs) can reduce the required number of simulations. This study extends the development of SRFs to bay interior locations at Panama City, Florida. Mean SRF root-mean-square errors for open coast and bay interior locations were 0.34 and 0.37 m, respectively, comparable with ADCIRC errors. Average uncertainty increases from open coast, and bay SRFs were 10 and 12 %, respectively. Long-term climate trends, such as rising sea levels, introduce nonstationarity into the simulated and historical surge datasets. A common approach to estimating total flood elevations is to take the sum of projected sea-level rise (SLR) and present day surge (static approach); however, this does not account for dynamic SLR effects on surge generation. This study demonstrates that SLR has a significant dynamic effect on surge in the Panama City area, and that total flood elevations, with respect to changes in SLR, are poorly characterized as static increases. A simple adjustment relating total flood elevation to present day conditions is proposed. Uncertainty contributions from these SLR adjustments are shown to be reasonable for surge hazard assessments.


Storm surge Hazard assessment Coastal flooding Uncertainty Hurricanes




A Concise Methodology for the Design of Statically-Equivalent Deep-Offshore Mooring Systems

Ikpoto E. Udoh

·  ISBN: 978-0-7918-4537-0

·  Copyright © 2014


Model testing of deepwater offshore structures often requires the use of statically-equivalent deepwater mooring systems. The need for such equivalent systems arises due to the spatial limitations of wave basins in accommodating the dimensions of the direct-scaled mooring system. With the equivalent mooring system in place and connected to the model floater, the static global restoring forces and global stiffness of the prototype floating structure can be matched (to within some tolerance) by those of the model for specified offsets in the required degrees of freedom. A match in relevant static properties of the system provides the basis for comparisons of dynamic responses of the model and prototype floaters. Although some commercial programs are capable of designing equivalent mooring systems, the physics applied in these programs are protected by intellectual property, and their methodologies are generally inflexible. This paper illustrates a concise approach to the design of statically-equivalent deepwater mooring systems. With this approach, either manual or advanced optimization techniques can be applied as needed based on the complexity of the equivalent system to be designed. A simple iterative scheme is applied in solving the elastic catenary equations for the optimal static configuration of each mooring line. Discussions cover the approach as applied in developing a fit-for-purpose tool called STAMOORSYS, its validation, and its application to the design of an equivalent mooring system for a spar platform in deepwater. The spar model parameters are representative of a structure which could be tested in the Offshore Technology Research Center, College Station, Texas, USA. Results show that the method is capable of producing good design solutions using manual optimization and a genetic algorithm.

Copyright © 2014 by ASME

Topics: Ocean engineering , Design , Mooring






Jennifer Linnea Irish, Celso Ferreira, Francisco Olivera, Ikpoto Udoh, Youn Kyung Song, Kunag-An Chang




In this paper, a joint probability approach is used with scaling laws for hurricane surge to rapidly develop probabilistic based hurricane surge and damage forecasts. The method presented is demonstrated along the Texas, USA coastline for Hurricane Ike, which made landfall in September of 2008. The probabilistic approach presented here is both accurate and fast, with a single surge and percent damage forecast taking less than one minute while representing more than 170,000 distinct hurricane possibilities.




hurricane surge; surge forecasting; flooding damages


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