Predicting site-specific storm wave run-up
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Predicting site‑specific storm wave run‑up Julia W. Fiedler1 · Adam P. Young1 · Bonnie C. Ludka1 · William C. O’Reilly1 · Cassandra Henderson1 · Mark A. Merrifield1 · R. T. Guza1 Received: 4 March 2020 / Accepted: 9 July 2020 © The Author(s) 2020
Abstract Storm wave run-up causes beach erosion, wave overtopping, and street flooding. Extreme runup estimates may be improved, relative to predictions from general empirical formulae with default parameter values, by using historical storm waves and eroded profiles in numerical runup simulations. A climatology of storm wave run-up at Imperial Beach, California is developed using the numerical model SWASH, and over a decade of hindcast spectral waves and observed depth profiles. For use in a local flood warning system, the relationship between incident wave energy spectra E(f) and SWASH-modeled shoreline water levels is approximated with the numerically simple integrated power law approximation (IPA). Broad and multi-peaked E(f) are accommodated by characterizing wave forcing with frequency-weighted integrals of E(f). This integral approach improves runup estimates compared to the more commonly used bulk parameterization using deep water wave height H0 and deep water wavelength L0 Hunt (Trans Am Soc Civ Eng 126(4):542–570, 1961) and Stockdon et al. (Coast Eng 53(7):573–588, 2006. https://doi.org/10.1016/j.coast aleng.2005.12.005). Scaling of energy and frequency contributions in IPA, determined by searching parameter space for the best fit to SWASH, show an H0 L0 scaling is near optimal. IPA performance is tested with LiDAR observations of storm run-up, which reached 2.5 m above the offshore water level, overtopped backshore riprap, and eroded the foreshore beach slope. Driven with estimates from a regional wave model and observed 𝛽f , the IPA reproduced observed run-up with < 30% error. However, errors in model physics, depth profile, and incoming wave predictions partially cancelled. IPA (or alternative empirical forms) can be calibrated (using SWASH or similar) for sites where historical waves and eroded bathymetry are available. Keywords Wave run-up · Numerical modeling · Boundary conditions · SWASH · LiDAR · Extreme events
* Julia W. Fiedler [email protected] 1
Scripps Institution of Oceanography, La Jolla, CA, USA
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Natural Hazards
1 Introduction As sea level rises, high shoreline water levels will increase in frequency and severity. Total shoreline water level (TWL) contains components with wide ranges of time and space scales, including sea-level rise, climatic and seasonal cycles, tides, oceanic eddies, storm surge, and local waves (e.g., Idier et al. 2019; Woodworth et al. 2019). When several components co-occur, high TWL threatens coastal infrastructure. In northern hemisphere mid-latitudes, continental west coast TWL hazards largely come from high waves combined with high tides, rather than from tropical and extratropical storm surges important on east coasts (Rueda et al. 2017). On US West Coast beaches, wave run-up an
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