Abstract

Abstract. Nearshore slope, defined as the cross-shore gradient of the subaqueous profile, is an important input parameter which affects hydrodynamic and morphological coastal processes. It is used in both local and large-scale coastal investigations. However, due to unavailability of data, most studies, especially those that focus on continental or global scales, have historically adopted a uniform nearshore slope. This simplifying assumption could however have far-reaching implications for predictions/projections thus obtained. Here, we present the first global dataset of nearshore slopes with a resolution of 1 km at almost 620 000 points along the global coastline. To this end, coastal profiles were constructed using global topo-bathymetric datasets. The results show that the nearshore slopes vary substantially around the world. An assessment of coastline recession driven by sea level rise (SLR) (for an arbitrary 0.5 m SLR) with a globally uniform coastal slope of 1 : 100, as carried out in previous studies, and with the spatially variable coastal slopes computed herein shows that, on average, the former approach would underestimate coastline recession by about 40 %, albeit with significant spatial variation. The final dataset has been made publicly available at https://doi.org/10.4121/uuid:a8297dcd-c34e-4e6d-bf66-9fb8913d983d (Athanasiou, 2019).

Highlights

  • A total of 10 % of the world’s population lives in low-lying coastal areas, i.e., less than 10 m above the current mean sea level (MSL) (McGranahan et al, 2007)

  • The resulting global distribution of dc (Fig. 2) showed that on open-ocean coasts, dc generally increased with latitude because of the wave height, while dc was smaller along the shores of more wave-sheltered seas

  • The west coast of North and South America had on average steeper slopes in comparison to the east, which can be attributed to the swell-dominated wave climate along the former

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Summary

Introduction

A total of 10 % of the world’s population lives in low-lying coastal areas, i.e., less than 10 m above the current mean sea level (MSL) (McGranahan et al, 2007). One of the most vulnerable coastal types is sandy coasts, which are highly dynamic and can change in response to extreme marine events (McCall et al, 2010), long-term trends in MSL (Zhang et al, 2004), natural gradients in alongshore sediment transport (Antolínez et al, 2018), or human interventions (Giardino et al, 2018a; Luijendijk et al, 2018; Mentaschi et al, 2018). Regional, or global studies that seek to quantify natural or human-induced coastal change require high-quality nearshore bathymetry and subaerial topography data. As such data are rarely available, previous studies, especially at the regional or global scale, have had to rely on a number of limiting assumptions, such as globally uniform nearshore or beach slopes (Hinkel et al, 2013; Melet et al, 2018).

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