Shallow water modeling for automated constraint on headwater hydrographic modelling

Authors: Ethan Shavers*, U.S. Geological Survey, Center of Excellence for Geospatial Information Science, Lawrence Stanislawski, U.S. Geological Survey, Center of Excellence for Geospatial Information Science
Topics: Water Resources and Hydrology, Earth Science, Natural Resources
Keywords: Lidar, DEM, Hydrography, Hydrology, Stream, Headwater
Session Type: Virtual Paper
Day: 4/8/2021
Start / End Time: 11:10 AM / 12:25 PM
Room: Virtual 3
Presentation File: No File Uploaded


The challenge of automated headwater stream mapping is well established, as is the importance of cataloging these features. Headwater streams make up greater than half the streams by length in the conterminous United States, and they are highly mutable and diverse. Here we present a strategy for automated constraint of drainage networks for headwater hydrographic delineation. A water depth raster, representing surface water depth given simulated rain inundation, is derived from a two-dimensional shallow water model and used to map surface flow patterns. The second derivative of an inundated area over water depth curve (ADC) is calculated for a given basin. It is found that on the resulting curve, the water depth at which the slope approaches zero, corresponding with the flattening of the ADC with decreasing depth, is a good approximation of the depth at which the surface transitions from channel to hill slope. The resulting channel extent network regions can be used to constrain flow accumulation lines or other line generation methods. The method presented here is developed and tested in diverse areas that have proven difficult to model using traditional strategies. The process shows promise for contributing to automated surface water mapping over broad areas. Further testing is needed to determine the optimal basin size and spatial resolution for the shallow water model.

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