Open AccessCollaborative Modeling With Fine‐Resolution Data Enhances Flood Awareness, Minimizes Differences in Flood Perception, and Produces Actionable Flood Maps
Author(s) -
Sanders Brett F.,
Schubert Jochen E.,
Goodrich Kristen A.,
Houston Douglas,
Feldman David L.,
Basolo Victoria,
Luke Adam,
Boudreau Dani,
Karlin Beth,
Cheung Wing,
Contreras Santina,
Reyes Abigail,
Eguiarte Ana,
Serrano Kimberly,
Allaire Maura,
Moftakhari Hamed,
AghaKouchak Amir,
Matthew Richard A.
Publication year - 2020
Publication title -
earth's future
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.641
H-Index - 39
ISSN - 2328-4277
DOI - 10.1029/2019ef001391
Subject(s) - flood myth , flooding (psychology) , flood insurance , emergency management , environmental resource management , computer science , vulnerability (computing) , hazard , flood mitigation , geography , flood stage , environmental planning , environmental science , 100 year flood , computer security , political science , ecology , psychology , archaeology , law , psychotherapist , biology
Existing needs to manage flood risk in the United States are underserved by available flood hazard information. This contributes to an alarming escalation of flood impacts amounting to hundreds of billions of dollars per year and countless disrupted lives and affected communities. Making information about flood hazards useful for the range of decisions that dictate the consequences of flooding poses many challenges. Here, we describe collaborative flood modeling, whereby researchers and end‐users at two coastal sites co‐develop fine‐resolution flood hazard models and maps responsive to decision‐making needs. We find, first of all, that resident perception and awareness of flooding are enhanced more by fine‐resolution depth contour maps than Federal Emergency Management Agency (FEMA) flood hazard classification maps and that viewing fine‐resolution depth contour maps helps to minimize differences in flood perception across subgroups within the community, generating a shared understanding. We also find that collaborative flood modeling supports the engagement of a wide range of end‐users in contemplating the risks of flooding and provides strong evidence that the co‐produced knowledge can be readily adopted and applied for Flood Risk Management (FRM). Overall, collaborative flood modeling advances FRM by providing multiple points of entry for diverse groups of end‐users to contemplate the spatial extent, intensity, timing, chance, and consequences of flooding, thus enabling the web of decision‐making related to flooding to be better informed with the best available science. This transdisciplinary approach emphasizes vulnerability reduction and is complementary to FEMA Flood Insurance Rate Maps used for flood insurance administration.