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The Floodwater Depth Estimation Tool (FwDET v2.0) for improved remote sensing analysis of coastal flooding

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
prioritizing of 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 of 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 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.
