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Reducing Horton-Strahler Stream Order Can Enhance Flood Inundation Mapping Skill with Applications for the U.S. National Water Model
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  • Fernando Aristizabal,
  • Fernando Renzo Salas,
  • Gregory Petrochenkov,
  • Trevor Grout,
  • Brian Avant,
  • Bradford Bates,
  • Ryan Spies,
  • Nick Chadwick,
  • Zachary Wills,
  • Jasmeet Judge
Fernando Aristizabal
Lynker, Lynker

Corresponding Author:fernando.aristizabal@noaa.gov

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Fernando Renzo Salas
Office of Water Prediction (NOAA/NWS), Office of Water Prediction (NOAA/NWS)
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Gregory Petrochenkov
United States Geological Survey, United States Geological Survey
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Trevor Grout
National Oceanic and Atmospheric Administration, National Oceanic and Atmospheric Administration
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Brian Avant
Lynker, Lynker
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Bradford Bates
Lynker, Lynker
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Ryan Spies
Lynker Technologies, Lynker Technologies
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Nick Chadwick
National Oceanic and Atmospheric Administration Office of Water Prediction, National Oceanic and Atmospheric Administration Office of Water Prediction
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Zachary Wills
Cooperative Institute for Satellite Earth System Studies, Cooperative Institute for Satellite Earth System Studies
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Jasmeet Judge
University of Florida, University of Florida
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Abstract

The National Water Model (NWM) currently requires the post-processing of forecast discharges to produce forecast flood inundation maps (FIM) for protecting life and property. Height Above Nearest Drainage (HAND), a drainage normalizing terrain index, is worthy of producing high-resolution FIMs at large spatial scales and frequent time steps using reach-averaged synthetic rating curves. However, HAND based FIMs suffer from a known limitation caused by independent catchments that lack the ability to cross catchment boundaries and ridgelines. To counter this constraint, a version of HAND known as Generalized Mainstems (GMS) is proposed that reduces the Horton-Strahler stream order of the stream network. GMS contains all segments within the NWM stream network but instead of deriving HAND by accounting for all river segments at once, it is derived independently at the level path (LP) scale. LPs are unique identifiers propagated upstream from a sub-basin’s outlet along the direction of maximum flow distance and repeated recursively until all segments are assigned LP identifiers. These FIMs are then mosaiced together, effectively turning the stream network into discrete groups of homogeneous unit stream order by removing the influence of neighboring tributaries. Improvement in mapping skill is observed when compared to HEC-RAS 1D models by significantly reducing false negatives at river junctions. A more marginal reduction in the false alarm rate is also observed due to a bias introduced in the stage-discharge relationship by increasing the size of the catchments.