TY - CHAP
T1 - Producing and Communicating Flood Risk
T2 - A Knowledge System Analysis of FEMA Flood Maps in New York City
AU - Hobbins, Robert
AU - Muñoz-Erickson, Tischa A.
AU - Miller, Clark
N1 - Funding Information:
Acknowledgements This material is based upon work supported by the National Science Foundation-funded Urban Resilience to Extreme Weather-Related Events Sustainability Research Network (UREx SRN; NSF grant no. SES 1444755), as well as dissertation research grants provided to Robert Hobbins from the Graduate Professional Student Association at Arizona State University and the American Association of Geographers. The authors are also very grateful for the time and information provided by practitioners in our case study cities and from the two anonymous reviewers who provided valuable feedback on earlier versions of this chapter.
Publisher Copyright:
© 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.
PY - 2021
Y1 - 2021
N2 - The burgeoning development of coastal cities coupled with increasing exposure to sea level rise and extreme weather events has exacerbated the vulnerability of coastal communities and infrastructure to floods. In order to make good flood risk reduction and resilience decisions, cities are interested in gaining better insights into what are perceived to be the “real” risks of floods. However, what counts as a good estimate of such risks is constructed through the design of a knowledge system that ratifies certain ideas and methods over others. We refer to knowledge systems as the organizational practices and routines that produce, validate and review, communicate, and use knowledge relevant to policy and decision-making. In this chapter, we conduct a knowledge system analysis of FEMA’s Flood Insurance Rate Maps in New York City. In 2012, Superstorm Sandy exposed in the national spotlight the shortcomings of how we calculate, map, and use knowledge about flood risk. Through this case study, we hope to demonstrate the value of knowledge systems analysis as a method to stress-test and identify the weaknesses of a knowledge system that warrant attention, as well as to inform potential methods ofupgrading or redesigning that system in support of building resilient cities.
AB - The burgeoning development of coastal cities coupled with increasing exposure to sea level rise and extreme weather events has exacerbated the vulnerability of coastal communities and infrastructure to floods. In order to make good flood risk reduction and resilience decisions, cities are interested in gaining better insights into what are perceived to be the “real” risks of floods. However, what counts as a good estimate of such risks is constructed through the design of a knowledge system that ratifies certain ideas and methods over others. We refer to knowledge systems as the organizational practices and routines that produce, validate and review, communicate, and use knowledge relevant to policy and decision-making. In this chapter, we conduct a knowledge system analysis of FEMA’s Flood Insurance Rate Maps in New York City. In 2012, Superstorm Sandy exposed in the national spotlight the shortcomings of how we calculate, map, and use knowledge about flood risk. Through this case study, we hope to demonstrate the value of knowledge systems analysis as a method to stress-test and identify the weaknesses of a knowledge system that warrant attention, as well as to inform potential methods ofupgrading or redesigning that system in support of building resilient cities.
KW - Climate resilience
KW - Knowledge systems analysis
KW - National flood insurance program
KW - Risk communication
UR - http://www.scopus.com/inward/record.url?scp=85103940212&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85103940212&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-63131-4_5
DO - 10.1007/978-3-030-63131-4_5
M3 - Chapter
AN - SCOPUS:85103940212
T3 - Urban Book Series
SP - 67
EP - 84
BT - Urban Book Series
PB - Springer Science and Business Media Deutschland GmbH
ER -