HOW WE COMMUNICATED WITH LOCAL, STATE AND FEDERAL AGENCIES WITH RESPECT TO HURRICANE STORM SURGE: THE PROCESS

2016 ◽  
Author(s):  
Alan I. Benimoff ◽  
◽  
William J. Fritz ◽  
Michael Kress
2016 ◽  
Vol 66 (8) ◽  
pp. 1005-1024 ◽  
Author(s):  
Alyssa Pampell-Manis ◽  
Juan Horrillo ◽  
Jens Figlus

2008 ◽  
Vol 136 (3) ◽  
pp. 833-864 ◽  
Author(s):  
Joannes J. Westerink ◽  
Richard A. Luettich ◽  
Jesse C. Feyen ◽  
John H. Atkinson ◽  
Clint Dawson ◽  
...  

Abstract Southern Louisiana is characterized by low-lying topography and an extensive network of sounds, bays, marshes, lakes, rivers, and inlets that permit widespread inundation during hurricanes. A basin- to channel-scale implementation of the Advanced Circulation (ADCIRC) unstructured grid hydrodynamic model has been developed that accurately simulates hurricane storm surge, tides, and river flow in this complex region. This is accomplished by defining a domain and computational resolution appropriate for the relevant processes, specifying realistic boundary conditions, and implementing accurate, robust, and highly parallel unstructured grid numerical algorithms. The model domain incorporates the western North Atlantic, the Gulf of Mexico, and the Caribbean Sea so that interactions between basins and the shelf are explicitly modeled and the boundary condition specification of tidal and hurricane processes can be readily defined at the deep water open boundary. The unstructured grid enables highly refined resolution of the complex overland region for modeling localized scales of flow while minimizing computational cost. Kinematic data assimilative or validated dynamic-modeled wind fields provide the hurricane wind and pressure field forcing. Wind fields are modified to incorporate directional boundary layer changes due to overland increases in surface roughness, reduction in effective land roughness due to inundation, and sheltering due to forested canopies. Validation of the model is achieved through hindcasts of Hurricanes Betsy and Andrew. A model skill assessment indicates that the computed peak storm surge height has a mean absolute error of 0.30 m.


2006 ◽  
Vol 26 (1) ◽  
pp. 18-25 ◽  
Author(s):  
K. Zhang ◽  
S.-C. Chen ◽  
P. Singh ◽  
K. Saleem ◽  
N. Zhao

2012 ◽  
Vol 66 (2) ◽  
pp. 955-983 ◽  
Author(s):  
Alexandros A. Taflanidis ◽  
Gaofeng Jia ◽  
Andrew B. Kennedy ◽  
Jane M. Smith

2018 ◽  
Vol 149 (3-4) ◽  
pp. 413-425 ◽  
Author(s):  
Davina L. Passeri ◽  
Matthew V. Bilskie ◽  
Nathaniel G. Plant ◽  
Joseph W. Long ◽  
Scott C. Hagen

Author(s):  
David F. Rico

This chapter illustrates how to optimize the return on investment (ROI) of enterprise architecture. Enterprise architecture is a blueprint for defining the structure and operation of organizations such as local, state, and federal agencies. Done well, enterprise architecture results in leaner and more effective information systems that satisfy organizational goals and objectives. This chapter introduces a suite of simple metrics and models for measuring the ROI of enterprise architecture. This chapter also introduces real options, which is a contemporary approach to measuring ROI. Whereas typical measures tend to underestimate ROI, real options have the ability to unearth business value hidden deep within the economics of investments in enterprise architecture.


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