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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/nhess-2019-78
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2019-78
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 26 Mar 2019

Research article | 26 Mar 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

The Floodwater Depth Estimation Tool (FwDET v2.0) for Improved Remote Sensing Analysis of Coastal Flooding

Sagy Cohen1, Austin Raney1, Dinuke Munasinghe1, Derek Loftis2, Andrew Molthan3, Jordan Bell3, Laura Rogers4, John Galantowicz5, G. Robert Brakenridge6, Albert J. Kettner6, Yu-Fen Huang7, and Yin-Phan Tsang7 Sagy Cohen et al.
  • 1Department of Geography, Univeristy of Alabama, Tuscaloosa, 35487, USA
  • 2Virginia Institute of Marine Science, College of William and Mary, Gloucester Pt, 23062, USA
  • 3SPoRT Center, NASA Marshall Space Flight Center, Huntsville, 35808, USA
  • 4Disasters Program, NASA Langley Research Center, Hampton, 23666, USA
  • 5Atmospheric and Environmental Research, Inc. (AER), Lexington, 02421, USA
  • 6Dartmouth Flood Observatory, University of Colorado, Boulder, 80309, USA
  • 7Natural Resources and Environmental Management, University of Hawaii, Manoa, 96822, USA

Abstract. Remote sensing analysis is routinely used to map flooding extent either retrospectively or in near-real-time. For flood emergency response, remote sensing-based flood mapping is highly valuable as it can offer continued observational information about the flood extent over large geographical domains. Information about the floodwater depth across the inundated domain is important for damage assessment, rescue, and to prioritize relief resource allocation, but cannot be readily estimated from remote sensing analysis. The Floodwater Depth Estimation Tool (FwDET) was developed to augment remote sensing analysis by calculating water depth based solely on an inundation map with an associated Digital Elevation Model (DEM). The tool was shown to be accurate and was used in flood response activations by the Global Flood Partnership. Here we present a new version of the tool, FwDET v2.0, which enables water depth estimation for coastal flooding. FwDET v2.0 features a new flood boundary identification scheme which accounts for the lack of confinement of coastal flood domains at the shoreline. A new algorithm is used to calculate the local floodwater elevation for each cell, which improves the tool's runtime by a factor 15 and alleviates inaccurate local boundary assignment across permanent water bodies. FwDET v2.0 is evaluated against physically-based hydrodynamic simulations in both riverine and coastal case studies. The results show good correspondence, with an average difference of 0.18 m and 0.31 m for the coastal (using a 1-m DEM) and riverine (using a 10-m DEM) case studies respectively. A FwDET v2.0 application of using remote sensing derived flood maps is presented for three case studies. These case studies showcase FwDET v2.0 ability to efficiently provide a synoptic assessment of floodwater. Limitations include challenges in obtaining high-resolution DEMs and increases in uncertainty when applied for highly fragmented flood inundation domains.

Sagy Cohen et al.
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Sagy Cohen et al.
Model code and software

FwDET v1.0 Code S. Cohen https://doi.org/10.5281/zenodo.1119066

Sagy Cohen et al.
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Short summary
Flooding is the most destructive natural disaster on Earth. Satellite and airborne imagery are commonly used for flood monitoring and response. While these remote sensing techniques are effective at providing the extent of flooding these cannot be used to infer the depth of flood water. This paper describes and analyzes version 2.0 of the Floodwater Depth Estimation Tool (FwDET). FwDET 2.0 offer enhanced calculation algorithm for coastal regions and much-improved run time.
Flooding is the most destructive natural disaster on Earth. Satellite and airborne imagery are...
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