Coastline evolution based on statistical analysis and modeling

<p>Wind, waves, tides, sediment supply, changes in relative sea level and human activities strongly affect shorelines, which constantly move in response to these processes, over a variety of timescales. Thus, the implementation of sound coastal zone management strategies needs reliable informa...

Full description

Bibliographic Details
Main Authors: E. Armenio, F. De Serio, M. Mossa, A. F. Petrillo
Format: Article
Language:English
Published: Copernicus Publications 2019-09-01
Series:Natural Hazards and Earth System Sciences
Online Access:https://www.nat-hazards-earth-syst-sci.net/19/1937/2019/nhess-19-1937-2019.pdf
id doaj-32191510c4e34203993a2a686983b669
record_format Article
spelling doaj-32191510c4e34203993a2a686983b6692020-11-25T00:50:12ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812019-09-01191937195310.5194/nhess-19-1937-2019Coastline evolution based on statistical analysis and modelingE. ArmenioF. De SerioM. MossaA. F. Petrillo<p>Wind, waves, tides, sediment supply, changes in relative sea level and human activities strongly affect shorelines, which constantly move in response to these processes, over a variety of timescales. Thus, the implementation of sound coastal zone management strategies needs reliable information on erosion and/or deposition processes. To suggest a feasible way to provide this information is the main reason for this work. A chain approach is proposed here, tested on a vulnerable coastal site located along southern Italy, and based on the joint analysis of field data, statistical tools and numerical modeling. Firstly, the coastline morphology has been examined through interannual field data, such as aerial photographs, plane-bathymetric surveys and seabed characterization. After this, rates of shoreline changes have been quantified with a specific GIS tool. The correlations among the historical positions of the shoreline have been detected by statistical analysis and have been satisfactorily confirmed by numerical modeling, in terms of recurrent erosion–accretion area and beach rotation trends. Finally, based on field topographic, sediment, wave and wind data, the response of the beach through numerical simulation has been investigated in a forecasting perspective. The purpose of this study is to provide a feasible, general and replicable chain approach, which could help to thoroughly understand the dynamics of a coastal system, identify typical and recurrent erosion–accretion processes, and predict possible future trends, useful for planning of coastal activities.</p>https://www.nat-hazards-earth-syst-sci.net/19/1937/2019/nhess-19-1937-2019.pdf
collection DOAJ
language English
format Article
sources DOAJ
author E. Armenio
F. De Serio
M. Mossa
A. F. Petrillo
spellingShingle E. Armenio
F. De Serio
M. Mossa
A. F. Petrillo
Coastline evolution based on statistical analysis and modeling
Natural Hazards and Earth System Sciences
author_facet E. Armenio
F. De Serio
M. Mossa
A. F. Petrillo
author_sort E. Armenio
title Coastline evolution based on statistical analysis and modeling
title_short Coastline evolution based on statistical analysis and modeling
title_full Coastline evolution based on statistical analysis and modeling
title_fullStr Coastline evolution based on statistical analysis and modeling
title_full_unstemmed Coastline evolution based on statistical analysis and modeling
title_sort coastline evolution based on statistical analysis and modeling
publisher Copernicus Publications
series Natural Hazards and Earth System Sciences
issn 1561-8633
1684-9981
publishDate 2019-09-01
description <p>Wind, waves, tides, sediment supply, changes in relative sea level and human activities strongly affect shorelines, which constantly move in response to these processes, over a variety of timescales. Thus, the implementation of sound coastal zone management strategies needs reliable information on erosion and/or deposition processes. To suggest a feasible way to provide this information is the main reason for this work. A chain approach is proposed here, tested on a vulnerable coastal site located along southern Italy, and based on the joint analysis of field data, statistical tools and numerical modeling. Firstly, the coastline morphology has been examined through interannual field data, such as aerial photographs, plane-bathymetric surveys and seabed characterization. After this, rates of shoreline changes have been quantified with a specific GIS tool. The correlations among the historical positions of the shoreline have been detected by statistical analysis and have been satisfactorily confirmed by numerical modeling, in terms of recurrent erosion–accretion area and beach rotation trends. Finally, based on field topographic, sediment, wave and wind data, the response of the beach through numerical simulation has been investigated in a forecasting perspective. The purpose of this study is to provide a feasible, general and replicable chain approach, which could help to thoroughly understand the dynamics of a coastal system, identify typical and recurrent erosion–accretion processes, and predict possible future trends, useful for planning of coastal activities.</p>
url https://www.nat-hazards-earth-syst-sci.net/19/1937/2019/nhess-19-1937-2019.pdf
work_keys_str_mv AT earmenio coastlineevolutionbasedonstatisticalanalysisandmodeling
AT fdeserio coastlineevolutionbasedonstatisticalanalysisandmodeling
AT mmossa coastlineevolutionbasedonstatisticalanalysisandmodeling
AT afpetrillo coastlineevolutionbasedonstatisticalanalysisandmodeling
_version_ 1725248703772491776