Performance of automated flood inundation mapping methods in a context of flash floods: a comparison of three methods based either on the Height Above Nearest Drainage (HAND) concept, or on 1D/2D shallow water equations

Abstract

Abstract. Flash floods observed in headwater catchments often cause catastrophic material and human damage worldwide. Considering the large number of small watercourses possibly affected, the use of automated methods for flood inundation mapping at a regional scale can be of great help for the identification of threatened areas and the prediction of potential impacts of these floods. An application of three mapping methods of increasing level of complexity (HAND/MS, caRtino 1D, and Floodos 2D) is presented herein. These methods are used to estimate the flooded areas of three major flash floods observed during the last ten years in South-Eastern France: the 15th of June 2010 flood on the Argens river and its tributaries (585 km of river reaches), the 3rd of October 2015 flood on small coastal rivers of the French Riviera (131 km of river reaches) and the 15th of October 2018 floods on the Aude river and its tributaries (561 km of river reaches). The common features of the three mapping approaches are their high level of automation, their application based on a high-resolution (5 m) DTM, and their reasonable computation times. Hydraulic simulations are run in steady-state regime, based on peak discharges estimated using a rainfall-runoff model preliminary adjusted for each event. The simulation results are compared with the reported flood extent maps and the high water level marks. A clear grading of the tested methods is revealed, illustrating some limits of the HAND/MS approach and an overall better performance of hydraulic models solving the shallow water equations. With these methods, the inundated areas are overall well retrieved, and the errors on water levels remain mostly below 80 cm for the 2D Floodos approach. The most important remaining errors are related to limits of the digital elevation model such as the lack of bathymetric information, uncertainties on embankment elevation and to possible bridge blockages not accounted for in the models.

GIS derived synthetic rating curves and HAND model to support on-the-fly flood mapping

“…This implies that the minimum n SRC flood maps had more significant over-estimations of flood extents than under-estimations. This is most likely a result of the HAND model itself, as it can result in overestimations in flatter geographical regions (Hocini et al 2020) and the Riviere Richelieu site does have a low-moderate river gradient (0.0013 m/m) and flat terrain slopes. Further, it was noticed in the minimum n SRC flood maps (Figs.…”

“…Flat terrains are also a challenge for the HAND model, as the model tends to over-estimate flood extents in these locations; this is a limitation shared with CERC-HAND-D, as the HAND model is required for creating SRCs. Further, the HAND model has been shown to be outperformed by Hydraulic 1D and 2D SWE models, albeit with higher computation times, and the model cannot produce outputs such as velocity and shear stress, which are important for flood hazard assessments (Hocini et al 2020;Rebolho et al 2018). Despite this, results such as those found by McGrath et al (2018) suggest that the HAND model can be a cost-effective, rapid, and accurate flood model that would be suitable for on-the-fly flood mapping.…”

A climate-conditioned catastrophe risk model for UK flooding

“…The metric is also sensitive to the shoreline length to inundated area ratio (Stephens et al, 2014) so that what constitutes a 'good' match varies between sites. CSI values are therefore invariably less than 1 and this results from both model uncertainties (Hocini et al, 2020) and errors in observed data (Hawker et al, 2020;Horritt et al, 2001), both of which can be significant. To put the CSI scores achieved in this paper in context, comparison of modelled flood inundation extent with observations from airborne or satellite sources for individual river reaches typically results in CSI values in the range 0.65-0.9 (Aronica et al, 2002;Horritt & Bates, 2001a, with the higher value only ever achieved for sites with very high quality input and validation data Neal et al, 2009).…”

Extending Height Above Nearest Drainage to Model Multiple Fluvial Sources in Flood Inundation Mapping Applications for the U.S. National Water Model

“…(2018) developed a methodology for determining stage‐discharge relationships known as SRCs by sampling reach‐averaged parameters from HAND data sets and inputting into the Manning's equation (Gauckler, 1867; Manning et al., 1890). This collection of methods, coupling HAND with SRCs, have been experimented with and compared to other sources of FIM including engineering scale models, in‐situ observation, and remote sensing based observation with solid results in large spatial scale applications (Afshari et al., 2018; Godbout et al., 2019; Garousi‐Nejad et al., 2019; Hocini et al., 2020; Johnson et al., 2019; Nobre et al., 2016; Teng et al., 2015, 2017; J. Zhang et al., 2018; Zheng, Maidment, et al., 2018).…”

“…HAND, to our knowledge, has only been applied to natural, inland, and riverine inundation applications thus it is also missing pluvial, coastal, ground water, and dam break components among other possible sources of flooding. Additionally, in order to flood an area, HAND assumes all areas eligible for inundation must drain to some nearest flowpath which is used for catchment allocation and relative elevation calculation (Garousi‐Nejad et al., 2019; Hocini et al., 2020; Johnson et al., 2019; Y. Y. Liu et al., 2016; Y. Liu et al., 2020; Maidment, 2017; Nobre et al., 2011, 2016; Rennó et al., 2008; Zheng, Maidment, et al., 2018; Zheng, Tarboton, et al., 2018). Stream thalweg networks must also collectively drain to a singular outlet point for a given processing region (Nobre et al., 2016; Rennó et al., 2008; Zheng, Maidment, et al., 2018).…”