Costas Gómez, RaquelCarro Fidalgo, HumbertoFiguero, A.Peña González, EnriqueSande, José2023-04-262023-04-262023Costas, R.; Carro, H.; Figuero, A.; Peña, E.; Sande, J. A Decision-Making Tool for Port Operations Based on Downtime Risk and Met-Ocean Conditions including Infragravity Wave Forecast. J. Mar. Sci. Eng. 2023, 11, 536. https://doi.org/10.3390/jmse11030536http://hdl.handle.net/2183/32947[Abstract:] Port downtime leads to economic losses and reductions in safety levels. This problem is generally assessed in terms of uni-variable thresholds, despite its multidimensional nature. The aim of the present study is to develop a downtime probability forecasting tool, based on real problems at the Outer Port of Punta Langosteira (Spain), and including infragravity wave prediction. The combination of measurements from three pressure sensors and a tide gauge, together with machine-learning techniques, made it possible to generate long wave prognostication at different frequencies. A fitting correlation of 0.95 and 0.9 and a root mean squared error (RMSE) of 0.022 m and 0.012 m were achieved for gravity and infragravity waves, respectively. A wave hindcast in the berthing areas, met-ocean forecast data, and information on 15 real operational problems between 2017 and 2022, were all used to build a classification model for downtime probability estimation. The proposed use of this tool addresses the problems that arise when two consecutive sea states have thresholds above 3.97%. This is the limit for guaranteeing the safety of port operations and has a cost of just 0.6 unnecessary interruptions of operations per year. The methodology is easily exportable to other facilities for an adequate assessment of downtime risks.engAtribución 3.0 Españahttp://creativecommons.org/licenses/by/3.0/es/Long waves predictionPort operabilityMultidimensional operational thresholdMachine learningPort managementjournal articleopen access10.3390/jmse11030536