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Probabilistic assessment of port operation downtimes under climate change

Abstract: Disruptions in harbor operations have significant implications for local, regional and global economies due to ports strategic role as part of the supply chain. A probabilistic evaluation of port operations considering the influence of climate change is required in order to secure optimal exploitation during their useful life. Here, we propose a hybrid statistic-dynamical framework combining a weather generator and a metamodel. The stochastic generator is based on weather types to project climate variability on hourly multivariate dependent climate drivers outside ports. The metamodel efficiently transforms hourly sea conditions from the entrance of the harbor towards the inside port adding the advantages of a physical process model. Thousands of hourly synthetic time series based on present climate conditions and future ones were transferred inside the port to perform a probabilistic analysis of port operations. Future forcing conditions were defined adding several sea level rise (SLR) scenarios, sampled from their probability distribution, to the synthetic sea level fluctuation time series. Wave amplification due to non-linear interactions between wave and sea level variations and changes in the reflection coefficients inside the port induced by SLR were modelled. Probabilistic future changes of operation downtimes were quantified considering the uncertainty associated with the historical forcing conditions outside the port and likely SLR scenarios. The methodology was applied to a specific case study on a regional port located in the north coast of Spain, were port operability due to wave agitation was assessed.

Otras publicaciones de la misma revista o congreso con autores/as de la Universidad de Cantabria

 Fuente: Coastal Engineering Volume 147, May 2019, Pages 12-24

Editorial: Elsevier

 Fecha de publicación: 01/05/2019

Nº de páginas: 13

Tipo de publicación: Artículo de Revista

 DOI: 10.1016/j.coastaleng.2019.01.007

ISSN: 0378-3839,1872-7379

Proyecto español: BIA2015-70644-R

Url de la publicación: