Uncertainties in the Projected Patterns of Wave-Driven Longshore Sediment Transport Along a Non-straight Coastline

Amin Reza Zarifsanayei,Nick Cartwright,José A A Antolínez,Gil Lemos,Amir Etemad-Shahidi,Darrell Strauss

doi:10.3389/fmars.2022.832193

Abstract

This study quantifies the uncertainties in the projected changes in potential longshore sediment transport (LST) rates along a non-straight coastline. Four main sources of uncertainty, including the choice of emission scenarios, Global Circulation Model-driven offshore wave datasets (GCM-Ws), LST models, and their non-linear interactions were addressed through two ensemble modelling frameworks. The first ensemble consisted of the offshore wave forcing conditions without any bias correction (i.e., wave parameters extracted from eight datasets of GCM-Ws for baseline period 1979–2005, and future period 2081–2100 under two emission scenarios), a hybrid wave transformation method, and eight LST models (i.e., four bulk formulae, four process-based models). The differentiating factor of the second ensemble was the application of bias correction to the GCM-Ws, using a hindcast dataset as the reference. All ensemble members were weighted according to their performance to reproduce the reference LST patterns for the baseline period. Additionally, the total uncertainty of the LST projections was decomposed into the main sources and their interactions using the ANOVA method. Finally, the robustness of the LST projections was checked. Comparison of the projected changes in LST rates obtained from two ensembles indicated that the bias correction could relatively reduce the ranges of the uncertainty in the LST projections. On the annual scale, the contribution of emission scenarios, GCM-Ws, LST models and non-linear interactions to the total uncertainty was about 10–20, 35–50, 5–15, and 30–35%, respectively. Overall, the weighted means of the ensembles reported a decrease in net annual mean LST rates (less than 10% under RCP 4.5, a 10–20% under RCP 8.5). However, no robust projected changes in LST rates on annual and seasonal scales were found, questioning any ultimate decision being made using the means of the projected changes.

Highlights

Applying the bias correction methods to the projected forcing conditions and its influence on narrowing or widening uncertainties in the projection of future sediment transport patterns (e.g., Toimil et al, 2021), has not yet been well examined. This manuscript aims to employ an ensemble modelling framework to quantify the uncertainty in the projections of longshore sediment transport (LST) rates using the Gold Coast in southeast Queensland, Australia, as a study site
First, the following tests were conducted to understand the impact of some issues on LST patterns: applying offshore waves uniformly or non-uniformly along the boundary of the wave model and directional standard deviation parameter (DSD)
Means of LST rate was used as the criterion for the comparisons

Summary

INTRODUCTION

Coastal areas are of major importance for the development of cities and infrastructure as they provide economic benefits to their communities. Several studies have shown that the offshore wind and wave patterns around the world are projected to be impacted by global and regional climate change (hereafter CC) by the end of this century (e.g., Hemer and Trenham, 2016; Camus et al, 2017; Lemos et al, 2019, 2021a,b; Morim et al, 2020). Applying the bias correction methods to the projected forcing conditions and its influence on narrowing or widening uncertainties in the projection of future sediment transport patterns (e.g., Toimil et al, 2021), has not yet been well examined This manuscript aims to employ an ensemble modelling framework to quantify the uncertainty in the projections of LST rates using the Gold Coast in southeast Queensland, Australia, as a study site. (site D) and two sites between the middle and north of GC (site E and F), were selected

METHODOLOGY

RESULTS AND DISCUSSION

LIMITATIONS AND THE

CONCLUSION