A model integrating longshore and cross‐shore processes for predicting long‐term shoreline response to climate change

Abstract

We present a shoreline change model for coastal hazard assessment and management planning. The model, CoSMoS‐COAST (Coastal One‐line Assimilated Simulation Tool), is a transect‐based, one‐line model that predicts short‐term and long‐term shoreline response to climate change in the 21st century. The proposed model represents a novel, modular synthesis of process‐based models of coastline evolution due to longshore and cross‐shore transport by waves and sea level rise. Additionally, the model uses an extended Kalman filter for data assimilation of historical shoreline positions to improve estimates of model parameters and thereby improve confidence in long‐term predictions. We apply CoSMoS‐COAST to simulate sandy shoreline evolution along 500 km of coastline in Southern California, which hosts complex mixtures of beach settings variably backed by dunes, bluffs, cliffs, estuaries, river mouths, and urban infrastructure, providing applicability of the model to virtually any coastal setting. Aided by data assimilation, the model is able to reproduce the observed signal of seasonal shoreline change for the hindcast period of 1995–2010, showing excellent agreement between modeled and observed beach states. The skill of the model during the hindcast period improves confidence in the model's predictive capability when applied to the forecast period (2010–2100) driven by GCM‐projected wave and sea level conditions. Predictions of shoreline change with limited human intervention indicate that 31% to 67% of Southern California beaches may become completely eroded by 2100 under sea level rise scenarios of 0.93 to 2.0 m.

Predicting Climate‐Driven Coastlines With a Simple and Efficient Multiscale Model

“…The models of Hanson et al (), Larson et al (), and Palalane et al () are an exception as they incorporate several physical processes trying to include beach and foredune change in response to cross‐shore processes of foredune growth by wind and foredune erosion (FDE) by storms, and by gradients in longshore sand transport that will alter shoreline position. Vitousek, Barnard, Limber, Erikson, et al () have introduced a hybrid transect‐based model composed of a one‐line longshore transport model, a cross‐shore equilibrium shoreline model, and a sea level‐driven shoreline recession model. The model of Vitousek, Barnard, Limber, Erikson, et al () covers a wide range of important processes for understanding coastal behavior, and the implemented data assimilation technique has improved the model's accuracy in comparison with measurements.…”

“…Vitousek, Barnard, Limber, Erikson, et al () have introduced a hybrid transect‐based model composed of a one‐line longshore transport model, a cross‐shore equilibrium shoreline model, and a sea level‐driven shoreline recession model. The model of Vitousek, Barnard, Limber, Erikson, et al () covers a wide range of important processes for understanding coastal behavior, and the implemented data assimilation technique has improved the model's accuracy in comparison with measurements. However, in this model water level variations other than SLR do not affect computed shoreline erosion rates and during conditions of very low wave energy (or no energy) and SLR, the profile still readjusts at a constant rate given by the “Bruun Rule” (Bruun, ).…”

Correlation Between Shoreline Change and Planform Curvature on Wave‐Dominated, Sandy Coasts

“…Despite their vulnerability to storms and sea‐level rise—event‐driven and chronic natural hazards—these environments tend to be intensively developed (Wong et al, ), motivating efforts to quantify present and historical rates of shoreline change and assess erosion risk, in the United States (Armstrong & Lazarus, ; Fletcher et al, ; Gibbs & Richmond, ; Gornitz et al, ; Hapke et al, ; Hapke et al, ; Hapke et al, ; Hapke & Reid, ; Morton et al, ; Morton et al, ; Morton & Miller, ; Ruggiero et al, ) and internationally (e.g., Coelho et al, ; Nicholls & Vega‐Leinert, ; Shaw et al, ). Related to this empirical work are efforts to explain past and predict future trends in shoreline behavior with numerical models of coastal processes and environmental conditions (Ruggiero et al, ; Gutierrez et al, ; Hapke et al, ; Plant et al, ; Vitousek et al, ; Yates & Le Cozannet, ). However, modeled and observed shoreline changes on sandy coastlines still tend to show poor agreement over larger‐spatial (>10 1 km) and longer‐temporal (>10 1 years) scales (e.g., Gutierrez et al, ; French et al, ; Yates & Le Cozannet, ).…”

LX-Shore : Un nouveau modèle d’évolution du trait de côte pour les littoraux sableux dominés par l'action des vagues

“…Pour le cas des littoraux sableux dominés par l'action des vagues, ces modèles complexes échouent encore à simuler les évolutions du trait de côte sur le moyen (année/décennie) et long-terme (siècle) du fait de limitations physiques et numériques (cascade d'erreurs au travers des échelles et temps de calcul très longs). Pour ces échelles, l'utilisation de modèles numériques de trait de côte à complexité réduite représente une alternative pour simuler des évolutions de manière fiable et avec des temps de calcul raisonnables (VITOUSEK et al, 2017). Dans le cas des littoraux sableux dominés par l'action des vagues, les évolutions du trait de côte sont généralement dominées sur le moyen et long-terme par les gradients longshore spatiaux de transport sédimentaire longshore, et sur le plus court-terme par les processus cross-shore liés à la variabilité temporelle des caractéristiques des vagues incidentes.…”