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TitleA comparison of rapid DTM based approaches for on-demand flood inundation mapping
AuthorMcGrath, HORCID logo; Proulx-Bourque, J -S; Bourgon, J -FORCID logo; Nastev, MORCID logo; Abo El Ezz, AORCID logo
SourceIEEE International Geoscience and Remote Sensing Symposium proceedings 2018, 8517772, 2018 p. 1-4,
Alt SeriesNatural Resources Canada, Contribution Series 20190057
MeetingIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium; Valencia; ES; July 22-27, 2018
Mediapaper; on-line; digital
File formatpdf (Adobe® Reader®)
ProvinceNew Brunswick; Quebec
NTS21G/15; 31F/08; 31F/09; 31G/05; 31G/12
AreaGatineau; Gatineau River; Ottawa River; Fredericton; Saint John River
Lat/Long WENS -67.0000 -66.5000 46.0000 45.7500
Lat/Long WENS -76.5000 -75.5000 45.7500 45.2500
Subjectshydrogeology; geophysics; surface waters; rivers; floods; flood plains; hydrodynamics; models; mapping techniques; water levels; meteorology; precipitation; digital terrain modelling; remote sensing; water levels; Risk assessment; Emergency preparedness
Illustrationslocation maps; geoscientific sketch maps; models
ProgramPublic Safety Geoscience Quantitative risk assessment project
Released2018 11 05
AbstractFlood inundation mapping is very useful for both risk assessment and for providing situational awareness during an emergency. Flood modelling is often complex and requires many variables and parameters, which are often unavailable. In this paper, the capability of simplified flood models, relying exclusively on digital terrain models was explored for two study areas. Three simplified conceptual flood models were tested: (i) planar method (ii) inclined plane and (iii) height above nearest drainage network (HAND) model. The accuracy and performance of these models were evaluated using two criteria: inundation extent and computation time. Findings indicate the HAND model is the best predictor of inundation extent. Though the pre-processing time for the HAND model is lengthy, once completed, the time to simulate flood depth at a variety of water levels is rapid, making this model the most suitable choice for on-demand flood inundation mapping.

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