Abstract
Coastal flooding is driven by the combination of (high) tide and storm surge, the latter being caused by strong winds and low pressure in tropical and extratropical cyclones. The combination of storm surge and the astronomical tide is defined as the storm tide. To gain an understanding of the threat posed by coastal flooding and to identify areas that are especially at risk, now and in the future, it is crucial to accurately model coastal inundation. Most models used to simulate the coastal inundation scale follow a simple planar approach, referred to as bathtub models. The main limitations of this type of models are that they implicitly assume an infinite flood duration, and they do not capture relevant physical processes. In this study we develop a method to generate hydrographs called HGRAPHER, and we provide a global dataset of storm tide hydrographs based on time series of storm surges and tides derived from the Global Tide and Surge Model (GTSM) forced with the ERA5 reanalysis wind and pressure fields. These hydrographs represent the typical shape of an extreme storm tide at a certain location along the global coastline. We test the sensitivity of the HGRAPHER method with respect to two main assumptions that determine the shape of the hydrograph, namely the surge event sampling threshold and coincidence in the time of the surge and tide maxima. The hydrograph dataset can be used to move away from planar inundation modelling techniques towards dynamic inundation modelling techniques across different spatial scales.
Original language | English |
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Pages (from-to) | 1847-1862 |
Number of pages | 16 |
Journal | Natural Hazards and Earth System Sciences |
Volume | 23 |
Issue number | 5 |
Early online date | 22 May 2023 |
DOIs | |
Publication status | Published - May 2023 |
Bibliographical note
Funding Information:We would like to thank Nathalie van Veen for her active involvement in the interpretation of the model outcomes and her critical review of the methodology. Job C. M. Dullaart and Jeroen C. J. H. Aerts received funding from the COASTRISK project financed by the SCOR Corporate Foundation for Science (grant no. R/003316.01). Jeroen C. J. H. Aerts is also funded by the ERC Advanced Grant COASTMOVE (grant no. 884442). Sanne Muis received funding from the research programme MOSAIC with project number ASDI.2018.036, which is financed by the Netherlands Organization for Scientific Research (NWO). Dirk Eilander and Philip J. Ward received funding from the NWO in the form of a VIDI grant (grant no. 016.161.324). This work was sponsored by NWO Exact and Natural Sciences for the use of supercomputer facilities (grant no. 2020.007).
Funding Information:
This research has been supported by the SCOR Corporate Foundation for Science (grant no. R/003316.01), the European Research Council, the H2020 European Research Council, the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (grant no. MOSAIC ASDI.2018.036), and the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (grant no. VIDI 016.161.324).
Publisher Copyright:
© 2023 Job C. M. Dullaart et al.
Funding
We would like to thank Nathalie van Veen for her active involvement in the interpretation of the model outcomes and her critical review of the methodology. Job C. M. Dullaart and Jeroen C. J. H. Aerts received funding from the COASTRISK project financed by the SCOR Corporate Foundation for Science (grant no. R/003316.01). Jeroen C. J. H. Aerts is also funded by the ERC Advanced Grant COASTMOVE (grant no. 884442). Sanne Muis received funding from the research programme MOSAIC with project number ASDI.2018.036, which is financed by the Netherlands Organization for Scientific Research (NWO). Dirk Eilander and Philip J. Ward received funding from the NWO in the form of a VIDI grant (grant no. 016.161.324). This work was sponsored by NWO Exact and Natural Sciences for the use of supercomputer facilities (grant no. 2020.007). This research has been supported by the SCOR Corporate Foundation for Science (grant no. R/003316.01), the European Research Council, the H2020 European Research Council, the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (grant no. MOSAIC ASDI.2018.036), and the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (grant no. VIDI 016.161.324).
Funders | Funder number |
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H2020 European Research Council | |
SCOR Corporate Foundation for Science | R/003316.01 |
SCOR Corporate Foundation for Science | |
European Research Council | 884442 |
European Research Council | |
Nederlandse Organisatie voor Wetenschappelijk Onderzoek | VIDI 016.161.324, 2020.007, 016.161.324 |
Nederlandse Organisatie voor Wetenschappelijk Onderzoek |