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

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          Abstract

          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 a ~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 simulation with XBeach outperforms bathtub flood mapping.

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          Is Open Access

          Future Coastal Population Growth and Exposure to Sea-Level Rise and Coastal Flooding - A Global Assessment

          Coastal zones are exposed to a range of coastal hazards including sea-level rise with its related effects. At the same time, they are more densely populated than the hinterland and exhibit higher rates of population growth and urbanisation. As this trend is expected to continue into the future, we investigate how coastal populations will be affected by such impacts at global and regional scales by the years 2030 and 2060. Starting from baseline population estimates for the year 2000, we assess future population change in the low-elevation coastal zone and trends in exposure to 100-year coastal floods based on four different sea-level and socio-economic scenarios. Our method accounts for differential growth of coastal areas against the land-locked hinterland and for trends of urbanisation and expansive urban growth, as currently observed, but does not explicitly consider possible displacement or out-migration due to factors such as sea-level rise. We combine spatially explicit estimates of the baseline population with demographic data in order to derive scenario-driven projections of coastal population development. Our scenarios show that the number of people living in the low-elevation coastal zone, as well as the number of people exposed to flooding from 1-in-100 year storm surge events, is highest in Asia. China, India, Bangladesh, Indonesia and Viet Nam are estimated to have the highest total coastal population exposure in the baseline year and this ranking is expected to remain largely unchanged in the future. However, Africa is expected to experience the highest rates of population growth and urbanisation in the coastal zone, particularly in Egypt and sub-Saharan countries in Western and Eastern Africa. The results highlight countries and regions with a high degree of exposure to coastal flooding and help identifying regions where policies and adaptive planning for building resilient coastal communities are not only desirable but essential. Furthermore, we identify needs for further research and scope for improvement in this kind of scenario-based exposure analysis.
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            A simple raster-based model for flood inundation simulation

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              A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling

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                Author and article information

                Contributors
                Journal
                Journal of Flood Risk Management
                J Flood Risk Management
                Wiley
                1753-318X
                1753-318X
                October 2019
                November 28 2018
                October 2019
                : 12
                : S1
                Affiliations
                [1 ] Chaire de recherche en géoscience côtière Université du Québec à Rimouski, Québec‐Océan, Centre d'études nordiques Rimouski Quebec Canada
                [2 ] Institut des sciences de la mer de Rimouski Université du Québec à Rimouski, Québec‐Océan, Physique des Océans – Laboratoire de Rimouski Rimouski Quebec Canada
                [3 ] Department of Civil Engineering Boise State University Boise Idaho
                Article
                10.1111/jfr3.12505
                b7c4a3a8-54ed-4300-a8ea-95387889a7ff
                © 2019

                http://onlinelibrary.wiley.com/termsAndConditions#vor

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