Probabilistic modeling of long-term shoreline changes in response to sea level rise and waves

Abstract

Prediction of long-term shoreline changes plays an important role in planning and management of coastal zones and regional sediment management. Quantifying uncertainties of shoreline evolution and risks of extreme shoreline changes (erosion and accretion) is a key task for practicing best shoreline protection. Due to complex natural features of offshore waves, sediment transport in alongshore and cross-shore directions, and sea level rise, prediction of long-term shoreline changes is a challenge. This paper presents a probabilistic shoreline change prediction model to quantify uncertainties of shoreline changes in response to waves and sea level rise (scenarios) by using Monte Carlo simulations (Fig. 1). A USACE shoreline evolution model, GenCade (Frey et al. 2012), is used to simulate shoreline changes driven by longshore and cross-shore sediment transport due to offshore wave action. A set of probability density functions are developed to represent stochastic features of waves (i.e. heights, periods, and directions) under both fair weather and extreme weather conditions. The newly-developed capabilities of the model are examined by predicting probabilities of shoreline changes in an idealized coast with and without coastal engineering conditions (e.g. installation of hard structures and beach fill/nourishment) (Fig. 2). Applicability of the model is also demonstrated by reproducing shoreline changes in a period in a coast in Duck, NC, USA. It also includes a maximum likelihood estimation to predict long-term extreme shoreline changes (particularly shoreline retreat) in terms of return periods (years) (Fig. 3). Predicted uncertainties of long-term shoreline changes can facilitate the best engineering practice for design and management of shorelines and coasts.