Predicting Longshore Sediment Transport and Coastline Dynamics using Satellite-derived Shoreline data

Abstract

Coastal regions, particularly beaches, are vital and dynamic areas for human activities. They serve various functions and are crucial barriers safeguarding coastal cities. However, the beach faces an increase in population and natural hazards caused by climate change are creating new challenges that coastal engineers are working to address.

This study introduces a new technique, SHORECAST (Satellite-derived Historical and future Orientation-based Relation for Estimating Coastline Adjustments and Sediment Transport), to enhance the Satellite-derived Shorelines (SDS). This technique is designed to estimate the shoreline dynamics in front of the shoreline and predict shoreline positions globally, offering a quick and accessible alternative to the existing models. The primary objective of this study is to employ shoreline position data obtained from SDS to estimate Longshore Sediment Transport (LST) and predict shoreline position quickly and effortlessly.

To achieve the study's objective, SHORECAST is developed and adapted into a multi-step framework using the annual dataset from the Shoreline Monitor of Luijendijk et al. (2018). The dataset assesses sandy and non-sandy beaches and their historical shoreline position at transects every 500 meters along the coast for the last 37 years. Only sandy shoreline evolutions are considered for the development of this new tool. First, a routine is developed to find coastal cells to which the research's aim could be applied. Secondly, multiple algorithms were deployed on the coastal cells to obtain the historical shoreline orientation and the LST. Combining these values leads to a correlation for predicting shorelines.

Out of all the coastal cells studies, three have been chosen: Nouakchott (Mauritania), Aveiro (Portugal) and Delfland (the Netherlands). The Nouakchott cell was split into a north and south side. These cells have in common that they all have a littoral barrier at one of the boundaries of the coastal cell with the assumption that there is no sediment transport. Due to this assumption, the LST could be calculated for each coastal cell. Nouakchott North experienced an annual sediment transport of 0.66 million m3 between 1985 and 2020, a volume increase of 23.01 million m3. Conversely, Nouakchott South experienced an erosion rate of 0.92 million m3 per year, resulting in a total loss of 32.36 million m3 over 35 years. In this same period, the Aveiro shoreline has accumulated a volume of 17.83 million m3 of sediment. In addition, the Aveiro shoreline displayed significant fluctuations compared to Nouakchott.

The Delfland coastal cell is the most complex coastal area among the three selected cases due to two littoral barriers at the boundaries and the anthropogenic measures in the past 37 years. This results in a volume increase of 45.55 million m3, similar to the beach nourishment volume of 46.51 million m3. As a result, it can be concluded that only the beach nourishment is visible in the SDS data, even though shoreface and dune nourishments have also been carried out during this period.

The findings indicate that the SHORECAST model, which incorporates the "Single-line theory" and specific boundary conditions, can generate multiple predictions. This makes it a universal tool for estimating sediment transport over time, even with future anthropogenic measures. It is important to note that not all assumed zero boundaries in sediment transport are zero in reality. Apart from SDS data, other shoreline position data can be integrated into the model to achieve similar results. Further research is needed to explore the possibilities of improving the understanding of different boundary conditions, thereby enhancing the obtained outcomes and the practicality of this study. An important suggestion is to explore the feasibility of identifying littoral barriers and other boundary conditions. This would make the developed model more robust and widely applicable.