| Title | A comparison of rapid DTM based approaches for on-demand flood inundation mapping |
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| Author | McGrath, H ;
Proulx-Bourque, J -S; Bourgon, J -F; Nastev, M; Abo El Ezz, A |
| Source | IEEE International Geoscience and Remote Sensing Symposium proceedings 2018, 8517772, 2018 p. 1-4, https://doi.org/10.1109/IGARSS.2018.8517772 |
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| Year | 2018 |
| Alt Series | Natural Resources Canada, Contribution Series 20190057 |
| Publisher | IEEE |
| Meeting | IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium; Valencia; ES; July 22-27, 2018 |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf (Adobe® Reader®) |
| Province | New Brunswick; Quebec |
| NTS | 21G/15; 31F/08; 31F/09; 31G/05; 31G/12 |
| Area | Gatineau; 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 |
| Subjects | hydrogeology; 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 |
| Illustrations | location maps; geoscientific sketch maps; models |
| Program | Public Safety Geoscience Quantitative risk assessment project |
| Released | 2018 11 05 |
| Abstract | Flood 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. |
| GEOSCAN ID | 314676 |
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