A Comprehensive Assessment of Floodwater Depth Estimation Models in Semiarid Regions

Abstract

Simple models continue to be important for continental‐scale floodwater depth mapping due to the prohibitively expensive cost of calibrating and applying hydrodynamic models. This paper investigates the accuracy of three simple models for floodwater depth estimation from remote sensing derived water extent and/or Digital Elevation Models (DEMs) in semiarid regions. The three models are Height Above Nearest Drainage (HAND; Nobre et al., 2011, https://doi.org/10.1016/j.jhydrol.2011.03.051), Teng Vaze Dutta (TVD; Teng et al., 2013, http://hdl.handle.net/102.100.100/97033?index=1), and Floodwater Depth Estimation Tool (FwDET; Cohen, Brakenridge, et al., 2018, https://doi.org/10.1111/1752-1688.12609). The model accuracy and nature of errors are established using industry's best practice hydrodynamic models as benchmarks in three regions in eastern Australia. The overall results show that FwDET tends to underestimate (by 0.32 m at 50th percentile) while HAND and TVD overestimate floodwater depth for almost all floods (by 0.97 and 0.98 m, respectively). We quantify how switching DEM from 5 m LiDAR to national or global data sets DEM‐H (Gallant et al., 2011, https://ecat.ga.gov.au/geonetwork/srv/eng/catalog.search%23/metadata/72759), MERIT (Yamazaki et al., 2019, https://doi.org/10.1029/2019WR024873), or FABDEM (Hawker et al., 2022, https://doi.org/10.1088/1748-9326/ac4d4f) can affect different models differently; and we evaluate model performance against reach geomorphology and magnitude of flood events. The findings emphasize the importance of choosing a model that is fit for the intended application. By describing the applicability, advantages, and limitations of these models, this paper assists practitioners to choose the most appropriate model based on characteristics of their study area, type of problems they try to solve, and data availability.

The floodplain inundation history of the Murray-Darling Basin through two-monthly maximum water depth maps

“…FwDET calculates water depth by first extracting boundary elevation of the flood extent from a DEM, interpolating water surface elevation using the boundary elevation, then subtracting the ground elevation from the interpolated surface elevation. The interpolation method used in this version was the Thin Plate Spline, which provided a smoother surface and overcome some of the known caveats of linear interpolation used in the previous version of FwDET 16 . Input data borders and the boundaries of areas without data (fully cloud covered through the two-month period) were not included as points in the interpolation.…”

“…Teng et al . 16 conducted a comprehensive assessment of floodwater depth estimation models in semi-arid regions and found that the Floodwater Depth Estimation Tool (FwDET), first developed by Cohen et al . 17 was the most suitable approach for this region.…”

“…After we had conducted a thorough review of 13 hydrodynamic models for the MDB 16 , we carefully selected three representative hydrodynamic models 38 – 40 that covered different parts of the MDB, as illustrated in Fig. 3 .…”

“…Following the same technique as Teng et al . 16 , the two-monthly maximum depth outputs were translated into surface water elevation (by adding the DEM) and compared at 5 m spatial resolution for each flood event. With the combination of flood events (up to three events per model) and regions, there were 13 model outputs that were part of the comparison.…”

Two-monthly maximum water depth for the Murray�Darling Basin: Usage guidance

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The recently released two monthly maximum water depth maps by Teng et al, (2023) provide opportunities for scientists to examine the relationship between hydrological and ecological processes. The depth maps provide a consistent spatial estimate of flood water depth across the Murray-Darling Basin (MDB) over the past 35 years.

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