TY - JOUR

T1 - Statistical analysis of beach profiles – A spatiotemporal functional approach

AU - Otto, Philipp

AU - Piter, Andreas

AU - Gijsman, Rik

N1 - Funding Information: The authors gratefully acknowledge the Coastal Authority of Schleswig-Holstein (LKN.SH) for the provision of the coastal profile and wave buoy data. Rik Gijsman was funded through project STENCIL (Contract No. 03F0761) of the German Ministry of Education and Research (Bundesministerium für Bildung und Forschung or BMBF) . We acknowledge Torsten Schlurmann (Leibniz University Hannover) for his role in the initial setup of this research and Alessandro Fassó and Francesco Finazzi (University of Bergamo) for the fruitful discussions and their inspiring comments and suggestions. Moreover, we thank two anonymous referees for their valuable comments and suggestions.

PY - 2021/12

Y1 - 2021/12

N2 - Beach profile data sets provide valuable insight into the morphological evolution of sandy shorelines. However, beach monitoring schemes often show large variability in temporal and spatial intervals between beach profiles. Moreover, beach profiles are often incomplete (i.e. only a part of the profile is measured) and data gaps are unavoidable. The resulting irregular sets of beach profiles complicate statistical analysis and previous studies on the morphological evolution and the effects of external influences have often omitted incomplete beach profiles. In this perspective, a statistical model is suggested to study beach profiles and to identify the effects of external influences. To be precise, the statistical model can be used (1) to determine the temporal and spatial variability of beach profiles while accounting for autoregressive dependencies in space and time, (2) to identify effects of external influences, (3) to predict complete beach profiles at unknown locations (i.e., interpolation between beach profiles), and (4) to forecast complete beach profiles accounting for external influences, such as storm events or nourishments. To illustrate the applicability of this model to irregular beach profile data, this state-of-the-art functional, spatiotemporal model was applied to beach profiles of the island of Sylt, Germany. In a first case study on submerged beach profiles, a decreasing temporal dependency between the profiles in the offshore direction was revealed, highlighting that less frequent measurements of offshore areas would suffice. A second analysis of the emerged beach profiles revealed the general effect of storm conditions (wave heights > 5 m) on subsequently measured beach profiles, which was statistically significant, and the profiles eroded with approximately 0.2–0.7 m in height. In summary, this study proposes and explores the application of a state-of-the-art statistical model to investigate beach profile changes from increasingly diverse and large profile data in coastal engineering and management.

AB - Beach profile data sets provide valuable insight into the morphological evolution of sandy shorelines. However, beach monitoring schemes often show large variability in temporal and spatial intervals between beach profiles. Moreover, beach profiles are often incomplete (i.e. only a part of the profile is measured) and data gaps are unavoidable. The resulting irregular sets of beach profiles complicate statistical analysis and previous studies on the morphological evolution and the effects of external influences have often omitted incomplete beach profiles. In this perspective, a statistical model is suggested to study beach profiles and to identify the effects of external influences. To be precise, the statistical model can be used (1) to determine the temporal and spatial variability of beach profiles while accounting for autoregressive dependencies in space and time, (2) to identify effects of external influences, (3) to predict complete beach profiles at unknown locations (i.e., interpolation between beach profiles), and (4) to forecast complete beach profiles accounting for external influences, such as storm events or nourishments. To illustrate the applicability of this model to irregular beach profile data, this state-of-the-art functional, spatiotemporal model was applied to beach profiles of the island of Sylt, Germany. In a first case study on submerged beach profiles, a decreasing temporal dependency between the profiles in the offshore direction was revealed, highlighting that less frequent measurements of offshore areas would suffice. A second analysis of the emerged beach profiles revealed the general effect of storm conditions (wave heights > 5 m) on subsequently measured beach profiles, which was statistically significant, and the profiles eroded with approximately 0.2–0.7 m in height. In summary, this study proposes and explores the application of a state-of-the-art statistical model to investigate beach profile changes from increasingly diverse and large profile data in coastal engineering and management.

KW - Beach nourishment

KW - Beach profiles

KW - Coastal erosion

KW - Functional data-driven model

KW - Spatiotemporal statistics

UR - http://www.scopus.com/inward/record.url?scp=85114775038&partnerID=8YFLogxK

U2 - 10.1016/j.coastaleng.2021.103999

DO - 10.1016/j.coastaleng.2021.103999

M3 - Article

AN - SCOPUS:85114775038

VL - 170

JO - Coastal engineering

JF - Coastal engineering

SN - 0378-3839

M1 - 103999

ER -