Assessment of runup predictions by empirical models on non-truncated beaches on the south-east Australian coast

Abstract

This paper assesses the accuracy of 11 existing runup models against field data collected under moderate wave conditions from 11 non-truncated beaches in New South Wales and Queensland, Australia. Beach types spanned the full range of intermediate beach types from low tide terrace to longshore bar and trough. Model predictions for both the 2% runup exceedance (R2%) and maximum runup (Rmax) were highly variable between models, with predictions shown to vary by a factor of 1.5 for the same incident wave conditions. No single model provided the best predictions on all beaches in the dataset. Overall model root mean square errors are of the order of 25% of the R2% value. Models for R2% derived from field data were shown to be more accurate for predicting runup in the field than those developed from laboratory data, which overestimate the field data significantly The most accurate existing models for predicting R2% were those developed by Holman (1986) and Vousdoukas et al. (2012), with mean RMSE errors of 0.30m or 25%. A new "model of models" for R2% was developed from a best fit to the predictions from six existing field and one large scale laboratory R2% data-derived models. It uses the Hunt (1958) scaling parameter � and incorporates a setup parameterisation. This model is shown to be as accurate as the Holman and Vousdoukas et al. models across all tidal stages. It also yielded the smallest maximum error across the dataset. The most accurate predictions for Rmax was given by Hunt (1958) but this still tended to under predict the observed maximum runup obtained for 15-minute records. Mase's (1989) model has larger errors but yields more conservative estimates. Greater observed values of Rmax are expected with increased record length, leading to greater differences with predicted values. Given the large variation in predictions across all models, 2 however, it is clear that predictions by uncalibrated runup models on a given beach may be prone to significant error and this should be considered when using such models for coastal management purposes. It should be noted that in extreme events, which are lacking in the dataset, runup may truncated by beach scarps, cliffs, and dunes, or by overtopping, and, as a result, the probability density functions will have different tail shapes. The uncertainty already present in current models is likely to increase in such conditions.

The use of genetic programming to develop a predictor of swash excursion on sandy beaches

“…Because of the importance of accurate predictions of swash excursion, the predictors provided by Stockdon et al (2006) have been tested by various authors on beaches ranging from reflective to dissipative (e.g. Vousdoukas et al, 2012;Cohn and Ruggiero, 2016;Atkinson et al, 2017). Predictions using Stockdon et al (2006) are certainly sound (especially considering the task of generating a universal formula for vertical swash excursion), even though differences between measurements and predictions, possibly associated with local conditions, are inevitably found.…”

Automated Sensing of Wave Inundation across a Rocky Shore Platform Using a Low-Cost Camera System

“…The potential for lateral overwash at transect N2 may vary with different hydrodynamic conditions, and this may contribute some of the variability in inundation frequency observed in Figures 10 and 11. It should be noted, however, that the variability observed here due to wave overtopping driving inundation is comparable to that observed by other studies that have investigated other nearshore, wave-related parameters such as wave driven run-up and overwash (e.g., [26,27]), wave driven setup (e.g., [30,31]), and the nearshore wave breaker criterion (e.g., [32,33]). …”

“…The influence of wave period (through wavelength) on platform inundation was assessed by the use of √ H s L m01 , which is commonly used in wave runup investigations on sandy beaches (e.g., [26,27] (Figure 10c,d). Figure 10c,d).…”

“…Four hydrodynamic parameters were investigated to assess correlations between offshore conditions and platform inundation frequency: (1) significant wave height (Hs), (2) The influence of wave period (through wavelength) on platform inundation was assessed by the use of , which is commonly used in wave runup investigations on sandy beaches (e.g., [26,27]), as well as a modified version that incorporates SWL, (1.8 + SWL)…”

The use of genetic programming to develop a predictor of swash excursion on sandy beaches

“…Because of the importance of accurate predictions of swash excursion, the predictors provided by Stockdon et al, (2006) have been tested by various authors on beaches ranging from reflective to dissipative (e.g., Vousdoukas et al, 2012;80 Cohn and Ruggiero, 2016;Atkinson et al, 2017). Predictions using Stockdon et al (2006) are certainly sound (especially considering the task of generating a universal formula for vertical swash excursion) even though differences between measurements and predictions, possibly associated to local conditions, are inevitably found.…”