To appeal and amend: Changes to recently updated Flood Insurance Rate Maps

Author(s):  
Devin Lea ◽  
Sarah Pralle
Author(s):  
Adam Luke ◽  
Brett F. Sanders ◽  
Kristen Goodrich ◽  
David L. Feldman ◽  
Danielle Boudreau ◽  
...  

Author(s):  
Rebecca Kaiser ◽  
Ibraheem M. Karaye ◽  
Temitope Olokunlade ◽  
Tracy Anne Hammond ◽  
Daniel W. Goldberg ◽  
...  

Abstract Introduction: Hurricane Harvey (2017) forced the closure of hemodialysis centers across Harris County, Texas (USA) disrupting the provision of dialysis services. This study aims to estimate the percentage of hemodialysis clinics flooded after Harvey, to identify the proportion of such clinics located in high-risk flood zones, and to assess the sensitivity of the Federal Emergency Management Agency (FEMA) Flood Insurance Rate Maps (FIRMs) for estimation of flood risk. Methods: Data on 124 hemodialysis clinics in Harris County were extracted from Medicare.gov and geocoded using ArcGIS Online. The FIRMs were overlaid to identify the flood zone designation of each hemodialysis clinic. Results: Twenty-one percent (26 of 124) of hemodialysis clinics in Harris County flooded after Harvey. Of the flooded clinics, 57.7% were in a high-risk flood zone, 30.8% were within 1km of a high-risk flood zone, and 11.5% were not in or near a high-risk flood zone. The FIRMs had a sensitivity of 58%, misidentifying 42% (11 of 26) of the clinics flooded. Conclusion: Hurricanes are associated with severe disruptions of medical services, including hemodialysis. With one-quarter of Harris County in the 100-year floodplain, projected increases in the frequency and severity of disasters, and inadequate updates of flood zone designation maps, the implementation of new regulations that address the development of hemodialysis facilities in high-risk flood areas should be considered.


Author(s):  
J. S. Lee ◽  
I. S. Lee

Recently, the number of natural disaster occurrence is increasing because of abnormal changes of weather in Korea. In Korea the storm and flood insurance system is in effect to prevent these natural disasters. The national storm and flood insurance Premium rate is very low and the risk of adverse selection resides because of choosing by who lives in high risk area. To solve these problems, the storm and flood insurance rate map are required. In this study, the prototype of storm and flood insurance premium rate map of the Ulsan, Korea was made and the method of GIS analysis for the insurance premium rate calculating and the procedure of the Ulsan storm and flood insurance rate map were researched.


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