Significance of Fluvial Sediment Supply in Coastline Modelling at Tidal Inlets

Abstract

Abstract:The sediment budget associated with future coastline change in the vicinity of tidal inlets consists of four components; sea level rise-driven landward movement of the coastline (i.e., the Bruun effect), basin infilling effect due to sea level rise-induced increase in accommodation space, basin volume change due to variation in river discharge, and coastline change caused by change in fluvial sediment supply. These four components are affected by climate change and/or anthropogenic impacts. Despite this understanding, holistic modelling techniques that account for all the aforementioned processes under both climate change and anthropogenic influences are lacking. This manuscript presents the applications of a newly-developed reduced complexity modelling approach that accounts for both climate change and anthropogenically-driven impacts on future coastline changes. Modelled results corresponding to the year 2100 indicate considerable coastline recessions at Wilson Inlet (152 m) and the Swan River system (168 m) in Australia and Tu Hien Inlet (305 m) and Thuan An Inlet (148 m) in Vietnam. These results demonstrate that coastline models should incorporate both climate change and anthropogenic impacts to quantify future changes in fluvial sediment supply to coasts to achieve better estimates of total coastline changes at tidal inlets. Omission of these impacts is one of the major drawbacks in all the existing coastline models that simulate future coastline changes at tidal inlets. A comparison of these modelled future coastline changes with the predictions made by a relevant existing modelling technique (Scale Aggregated Model for Inlet-interrupted Coasts (SMIC)) indicates that the latter method overestimates total coastline recessions at the Swan River system, and the Tu Hien and Thuan An Inlets by 7%, 10%, and 30%, respectively, underlining the significance of integrating both climate change and anthropogenic impacts to assess future coastline changes at tidal inlets.

Climate Change, Coasts and Coastal Risk

“…The papers of Watson [1], Helman & Tomlinson [2], Bigalbal et al [3], Bamunawala et al [4] and Kumbier et al [5] aim to improve our understanding of the links between climate change, coastal forcing (SLR, storm surge, waves) and coastline change. Watson [1] and Helman & Tomlinson [2] look backward and discuss observed climate change impacts.…”

“…Watson [1] and Helman & Tomlinson [2] look backward and discuss observed climate change impacts. Bigalbal et al [3], Bamunawala et al [4] and Kumbier et al [5] look forward and discuss methods for modelling the impacts of climate change, presenting applications from around the world.…”

A holistic modelling approach to simulate catchment-estuary-coastal system behaviour at macro-time scales

“…Additionally, previous studies have shown that the inletinterrupted coasts would undergo an additional extent of coastal recession due to sea-level rise driven basin infilling as well Stive, 2004;Stive et al, 1998Stive et al, , 1990. Besides these recessions, future changes in temperature, precipitation and anthropogenic activities at catchment scale would alter the fluvial sediment supply received by the coasts Ranasinghe et al, 2019b;Syvitski and Milliman, 2007), which in turn have significant implications on inlet-interrupted coasts (Bamunawala et al, 2018a). Such long-term coastal recessions will significantly increase the socio-economic risks associated along inlet-interrupted coasts.…”

“…Sediment generation and fluvial sediment throughput at catchment scale are affected by both climate change-driven impacts and anthropogenic activities (Section 1.2). Bamunawala et al (2018a) have illustrated that the empirical BQART model presented by Syvitski and Milliman (2007) can be used to assess the annual fluvial sediment supply to the coast, by considering both climate change-driven impacts and human activities. This empirical model is based on 488 globally-distributed datasets.…”

“…Based on the global dataset used, the optimum range of was suggested as 0.3 to 2.0. Instead of using countrywide estimates of GNP/capita and population density to estimate the humaninduced soil erosion factor ( ), high-resolution spatial information published by the Wildlife Conservation Society -WCS and the Center for International Earth Science Information Network -CIESIN -of Columbia University in 2005 in the form of a human footprint index (HFPI) can be used, so that the anthropogenic influences on sedimentation are better represented (Balthazar et al, 2013;Bamunawala et al, 2018a).…”