Abstract

Waves overtop berms and seawalls along the shoreline of Imperial Beach (IB), CA when energetic winter swell and high tide coincide. These intermittent, few-hour long events flood low-lying areas and pose a growing inundation risk as sea levels rise. To support city flood response and management, an IB flood warning system was developed. Total water level (TWL) forecasts combine predictions of tides and sea-level anomalies with wave runup estimates based on incident wave forecasts and the nonlinear wave model SWASH. In contrast to widely used empirical runup formulas that rely on significant wave height and peak period, and use only a foreshore slope for bathymetry, the SWASH model incorporates spectral incident wave forcing and uses the cross-shore depth profile. TWL forecasts using a SWASH emulator demonstrate skill several days in advance. Observations set TWL thresholds for minor and moderate flooding. The specific wave and water level conditions that lead to flooding, and key contributors to TWL uncertainty, are identified. TWL forecast skill is reduced by errors in the incident wave forecast and the one-dimensional runup model, and lack of information of variable beach morphology (e.g., protective sand berms can erode during storms). Model errors are largest for the most extreme events. Without mitigation, projected sea-level rise will substantially increase the duration and severity of street flooding. Application of the warning system approach to other locations requires incident wave hindcasts and forecasts, numerical simulation of the runup associated with local storms and beach morphology, and model calibration with flood observations.

Highlights

  • Serafin et al (2017) estimate that wave runup contributes about half of the maximum total water levels (TWLs) for a study site in California, with the remainder from tides and mean sea-level anomalies

  • In addition to regional models that span hundreds of km of shoreline and include a range of beach types and shoreline infrastructure, site specific forecast systems have been developed for wave runup (e.g., Atkinson et al 2017, Luccio et al 2018) and TWL (Coastal Data Information Program, https://cdip.ucsd.edu/themes/cdip?pb=​1&d2=p112; PacIOOS, https://www.pacioos.hawaii.edu/shoreline-category/highsea/, Guiles et al 2019)

  • The wave runup contribution to TWL, R2, is defined as the elevation exceeded by 2% of uprushing waves

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Summary

Introduction

Along the U.S West Coast, high ocean water levels and coastal flooding can occur when energetic winter swell events coincide with high tides. Serafin et al (2017) estimate that wave runup contributes about half of the maximum total water levels (TWLs) for a study site in California, with the remainder from tides and mean sea-level anomalies. In addition to regional models that span hundreds of km of shoreline and include a range of beach types and shoreline infrastructure, site specific forecast systems have been developed for wave runup (e.g., Atkinson et al 2017, Luccio et al 2018) and TWL (Coastal Data Information Program, https://cdip.ucsd.edu/themes/cdip?pb=​1&d2=p112; PacIOOS, https://www.pacioos.hawaii.edu/shoreline-category/highsea/, Guiles et al 2019). Estimates of the impact to Imperial Beach’s Gross Domestic Product (GDP) range from $9.4 M for a 2-m rise in sea level accompanied by a single 1-yr return period storm event, Fig. 1 Imperial Beach map showing offshore isobaths relative to MSL, names of often flooded streets, and sensor locations during the Resilient Futures observations. As part of the Resilient Futures project, additional wave, water level, and beach elevation observations have been collected to test runup models, quantify forecast uncertainties, and examine TWL variation along the IB shoreline.

Study area and data
Components of a flood forecast
Ocean water level
Runup model
Incident waves
Foreshore beach slope
Hindcasts and flood thresholds
TWL uncertainties
Flood predictions and probabilities
Findings
Discussion
Conclusions
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