Multihazard simulation for coastal flood mapping: Bathtub versus numerical modelling in an open estuary, Eastern Canada

Abstract

Funding informationFonds Québécois de la recherche sur la nature et les technologies; Québec Ministry of Public Security Coastlines along the St. Lawrence Estuary and Gulf, Eastern Canada, are under increasing risk of flooding due to sea level rise and sea ice shrinking. Efficient and validated regional-scale coastal flood mapping approaches that include storm surges and waves are hence required to better prepare for the increased hazard. This paper compares and validates two different flood mapping methods: numerical flood simulations using XBeach and bathtub mapping based on total water levels, forced with multihazard scenarios of compound wave and water level events. XBeach is validated with hydrodynamic measurements. Simulations of a historical storm event are performed and validated against observed flood data over ã 25 km long coastline using multiple fit metrics. XBeach and the bathtub method correctly predict flooded areas (66 and 78%, respectively), but the latter overpredicts the flood extent by 36%. XBeach is a slightly more robust flood mapping approach with a fit of 51% against 48% for the bathtub maps. Deeper floodwater by~0.5 m is expected with the bathtub approach, and more buildings are vulnerable to a 100-year flood level. For coastal management at regional-scale, despite similar flood extents with both flood mapping approaches, results suggest that numerical simulati on with XBeach outperforms bathtub flood mapping.

Modelling Coastal Flood Propagation under Sea Level Rise: A Case Study in Maria, Eastern Canada

“…Validation results for the mean water level (not included in Table 2) are virtually within a centimeter-scale deviation from the observations (r 2 = 0.99). indicators are under 0.07 cm, which is consistent with other studies (e.g., [33,71]). Overall, there is no tendency to over-or under-estimate wave heights in the nearshore zone (MBE close to 1 on both sensors) and regression lines have a nearly null intercept (a2 = ±0.01).…”

“…Hourly wave boundary conditions for the 2010 flood simulation were extracted from WAVEWATCH III (see a description in Appendix A) with a 1 km grid resolution. The reader is referred to Didier et al [33] and Bernatchez et al [76] for a detailed explanation of the WW3 implementation in the EGSL. Based on the comparison between wave observations at the AWAC location and WW3 between 9-30 November 2015, Bernatchez et al [76] observed a negative bias of −0.253 m (RMSE = 0.297 m) attributed to (1) the insufficient resolution of the CFSR wind forcing model in coastal environments and (2) bathymetric effects, which are not resolved in the 1 km grid simulations.…”

“…With the same model, Bates et al [82] and Vousdoukas et al [25] respectively obtained F values of the order of 54-91% and 49%. Recently, using XBeach in surfbeat mode, Didier et al [33] The use of XBeach as a 2D coastal inundation model is still developing. Its validation is typically done with field measurements of simulated water levels and waves.…”

“…Based on the assumption of hydraulic conductivity, a conservative approach can also be used, where all elevation cell values under the design scenario are considered as flooded [30]. Bathtub flood mapping is known to overestimate flood extent because it excludes the effects of landscape roughness [31] and flow velocity, leading to exaggerated overland flow distances [25,26,32,33]. Considering flood propagation parameters, such as velocity, U, and direction, can improve the effectiveness of coastal flood maps.…”

“…With the recent development of regional sea level rise models [62][63][64], local-scale relative sea level rise forecasts are increasingly used to map future flood-prone areas [57] or to evaluate future wave runup levels [56], but their effects on the coastal flood propagation are still limited [65]. Recently, XBeach [66] has been increasingly used to simulate the propagation of water levels and waves in a context of risk management [32,33,[67][68][69][70]. Its ability to seamlessly simulate wave propagation, overwash and flooding in complex nearshore environments under sea level rise has also been demonstrated [71,72].…”