Wave run-up prediction and observation in a micro-tidal beach
-
Published:2018-11-02
Issue:11
Volume:18
Page:2841-2857
-
ISSN:1684-9981
-
Container-title:Natural Hazards and Earth System Sciences
-
language:en
-
Short-container-title:Nat. Hazards Earth Syst. Sci.
Author:
Di Luccio DianaORCID, Benassai GuidoORCID, Budillon GiorgioORCID, Mucerino LuigiORCID, Montella Raffaele, Pugliese Carratelli Eugenio
Abstract
Abstract. Extreme weather events bear a significant impact on coastal
human activities and on the related economy. Forecasting and hindcasting the
action of sea storms on piers, coastal structures and beaches is an important
tool to mitigate their effects. To this end, with particular regard to low
coasts and beaches, we have developed a computational model chain
based partly on open-access models and partly on an ad-hoc-developed
numerical calculator to evaluate beach wave run-up levels and flooding. The
offshore wave simulations are carried out with a version of the WaveWatch III
model, implemented by CCMMMA (Campania Centre for Marine and Atmospheric
Monitoring and Modelling – University of Naples Parthenope), validated
with remote-sensing data. The waves thus computed are in turn used as initial
conditions for the run-up calculations, carried out with various empirical
formulations; the results were finally validated by a set of specially
conceived video-camera-based experiments on a micro-tidal beach located on
the Ligurian Sea. Statistical parameters are provided on the agreement
between the computed and observed values. It appears that, while the system
is a useful tool to properly simulate beach flooding during a storm,
empirical run-up formulas, when used in a coastal vulnerability context, have
to be carefully chosen, applied and managed, particularly on gravel beaches.
Publisher
Copernicus GmbH
Subject
General Earth and Planetary Sciences
Reference79 articles.
1. Aagaard, T. and Holm, J.: Digitization of wave run-up using video records,
J. Coastal Res., 5, 547–551, 1989. a, b 2. Airy, G. B.: Tides and waves, Encyclopaedia Metropolitana, 3, 1817–1845,
1841. a 3. Ascione, I., Giunta, G., Mariani, P., Montella, R., and Riccio, A.: A grid
computing based virtual laboratory for environmental simulations, Euro-Par
2006 Parallel Processing, 1085–1094, 2006. a 4. Aucelli, P. P. C., Di Paola, G., Incontri, P., Rizzo, A., Vilardo, G.,
Benassai, G., Buonocore, B., and Pappone, G.: Coastal inundation risk
assessment due to subsidence and sea level rise in a Mediterranean alluvial
plain (Volturno coastal plain–southern Italy), Estuar. Coast. Shelf
S., 198, 597–609, https://doi.org/10.1016/j.ecss.2016.06.017, 2016. a 5. Aulicino, G., Cotroneo, Y., Ruiz, S., Román, A. S., Pascual, A., Fusco,
G.,
Tintoré, J., and Budillon, G.: Monitoring the Algerian Basin through
glider observations, satellite altimetry and numerical simulations along a
SARAL/AltiKa track, J. Marine Syst., 179, 55–71, 2018. a
Cited by
31 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|