Combining remote sensing data and an inundation model to map tidal mudflat regions and improve flood predictions: A proof of concept demonstration in Cook Inlet, Alaska

Details Combining remote sensing data and an inundation model to map tidal mudflat regions and improve flood predictions: A proof of concept demonstration in Cook Inlet, Alaska Combining remote sensing data and an inundation model to map tidal mudflat regions and improve flood predictions: A proof of concept demonstration in Cook Inlet, Alaska

Feb 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009georl..3604605e&link_type=abstract

Geophysical Research Letters, Volume 36, Issue 4, CiteID L04605

Physics

Geophysics

2

History Of Geophysics: Ocean Sciences, Oceanography: General: Coastal Processes, Oceanography: General: Remote Sensing And Electromagnetic Processes (0689, 2487, 3285, 4455, 6934), Oceanography: General: Numerical Modeling (0545, 0560), Oceanography: Physical: Topographic/Bathymetric Interactions

Scientific paper

Accurate flood predictions require high resolution inundation numerical models and detailed coastal and land topography data. However, such data are not always available. A new method to obtain topographic information of flood zones from remote sensing data is demonstrated here for Cook Inlet, Alaska, where tidal range reaches 8-10 m. The moving shoreline is detected from analysis of water coverage in satellite images taken at different tidal stages, and then the shoreline data from different times are combined with water level data from observations and models to produce new topographic maps of previously unobserved mudflats. The remote sensing-based analysis provides for the first time a way to evaluate the flood predictions of the inundation model of the inlet. The new flood-zone topography obtained from the remote sensing data will help to construct a more accurate inundation model in the future.

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