The Floodwater Depth Estimation Tool (FwDET v2.0) for Improved Remote; Sensing Analysis of Coastal Flooding Conference Proceeding uri icon



  • 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.;

publication date

  • December 11, 2019

Full Author List

  • Cohen S; Raney A; Munasinghe D; Loftis D; Molthan A; Bell J; Rogers L; Galantowicz J; Brakenridge GR; Kettner AJ

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