TY - JOUR
T1 - Global distribution of nearshore slopes with implications for coastal retreat
AU - Athanasiou, Panagiotis
AU - Van Dongeren, Ap
AU - Giardino, Alessio
AU - Vousdoukas, Michalis
AU - Gaytan-aguilar, Sandra
AU - Ranasinghe, Roshanka
PY - 2019/10/2
Y1 - 2019/10/2
N2 - 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).
AB - 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).
UR - http://www.scopus.com/inward/record.url?scp=85073257743&partnerID=8YFLogxK
U2 - 10.5194/essd-11-1515-2019
DO - 10.5194/essd-11-1515-2019
M3 - Article
VL - 11
SP - 1515
EP - 1529
JO - Earth system science data
JF - Earth system science data
SN - 1866-3508
IS - 4
ER -