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<p>The scouring phenomenon can pose a serious threaten to bridge serviceability and users' safety, as well. In extreme circumstances, it can lead to the bridge's structural collapse. Despite efforts to reduce the scour's unfavorable effects in the vicinity of bridge foundations, this issue remains a significant challenge. Many uncertainties affect the design process of bridge foundations, namely the associated hydrological and hydraulic parameters. Past and recent flood records strengthen bridges' vulnerability by reducing scouring estimation uncertainties. Therefore, the present study applies a semi-quantitative methodology of scour risk assessmentto a Portuguese bridge case study, accounting for those uncertainties. The risk-based methodology comprises three main steps towards the assignment of the bridge's scour risk rating. The methodology constitutes a potential key tool for risk management activities, assisting bridge's owners and managers in decision-making.</p>

The present work aims to provide reliable estimates of extreme discharge flows and their probability of occurrence. Such estimates are important for the assessment of the associated hydrological risk of hydraulic infrastructures, such as bridges and dams, in the design process as well as during their operations. The hydrological modeling herein developed was applied to estimate the design floods approaching the new Hintze Ribeiro bridge, in the north of Portugal. It proposes a statistical analysis of the maximum annual streamflow data by using a flood frequency analysis technique. The data series were subject to a reliability analysis and the specific modeling assumptions, required for the study, were appropriately given and tested. An extrapolation technique of the missing instantaneous discharge data was herein derived. Such technique was validated by two distinct methods. The estimations are accurate with a mean deviation of 7.2% relative to the observed data. A set of probabilistic models were considered and the models' performance verified by the goodness-of-fit tests and Q-Q plots. The model and the parameter uncertainties were taken into account. Model uncertainties were addressed by comparing the estimated design floods through selecting the best fitting probability model (MS) with the approach that considered the distribution functions which fit well the data (MM). On the other hand, the computed flow rates were estimated with 95% of confidence to reduce the inherent parameter uncertainties. An additional accuracy assessment of the parametric approaches was performed through a comparative analysis of such design floods with the ones retrieved by application of the non-parametric Kernel density estimate (KDE). The MM approach showed a lower discrepancy (18.5%) to KDE estimates, when compared with the MS results. A sensitivity analysis of the associated hydrological risks was also undertaken.

SAFEPORT safety system aims at forecasting and alerting, on a regular basis, emergency situations regarding ships operation in port areas caused by extreme weather-oceanographic conditions. It uses forecasts provided offshore of the area under study of sea agitation, wind and tide. The characterization of the response of the free and moored ships at a berth is performed using the numerical package SWAMS. The system issue alerts, through danger levels associated with risk levels of exceedance of recommended values for movements and forces imposed on ship mooring systems. SAFEPORT can be adapted to any port. So far, it has been developed and adapted to three terminals of the port of Sines, where three different ships were simulated. This paper presents the developments made to date of the safety system, which includes tests performed in storm situations. The numerical models run every day, in real-time mode, in a computer cluster and the system provide forecast results for the next 72 hours. The results are disseminated on a web page and a mobile application in a variety of formats. It was concluded that the SAFEPORT safety system issued alerts according to the observed reality during the storm Dora. It has also been shown to be a computer tool for the optimization of ship mooring systems. The system is currently in testing and validation phase therefore, forecasts should be interpreted as indicative.