Hybrid approaches for container traffic forecasting in the context of anomalous events: The case of the Yangtze River Delta region in the COVID-19 pandemic.

The COVID-19 pandemic had a significant impact on container transportation. Accurate forecasting of container throughput is critical for policymakers and port authorities, especially in the context of the anomalous events of the COVID-19 pandemic. In this paper, we firstly proposed hybrid models for univariate time series forecasting to enhance prediction accuracy while eliminating the nonlinearity and multivariate limitations. Next, we compared the forecasting accuracy of different models with various training dataset extensions and forecasting horizons. Finally, we analysed the impact of the COVID-19 pandemic on container throughput forecasting and container transportation. An empirical analysis of container throughputs in the Yangtze River Delta region was performed for illustration and verification purposes. Error metrics analysis suggests that SARIMA-LSTM2 and SARIMA-SVR2 (configuration 2) have the best performance compared to other models and they can better predict the container traffic in the context of anomalous events such as the COVID-19 pandemic. The results also reveal that, with an increase in the training dataset extensions, the accuracy of the models is improved, particularly in comparison with standard statistical models (i.e. SARIMA model). An accurate prediction can help strategic management and policymakers to better respond to the negative impact of the COVID-19 pandemic.

Evaluation of the Effectiveness of Active and Passive Safety Measures in Preventing Ship-Bridge Collision.

The risk of ship-bridge collisions should be evaluated using advanced models to consider different anti-collision and bridge-protection measures. This study aimed to propose a method to evaluate the effectiveness of active and passive safety measures in preventing ship-bridge collision. A novel ship-bridge collision probability formulation taking into consideration different safety measures was proposed. The model was applied at Jintang Bridge in China where the surrounding vessel traffic is ultra-crowded. We calculated the collision probability between the bridge and passing traffic using automatic identification system (AIS) data, Monte Carlo simulation, and Bayesian networks. Results under four different safety measures (i.e., active measures, passive measures, both measures and none) were analyzed and compared. The analysis concluded that both active and passive safety measures are effective in reducing the ship-bridge collision probability. Active measures, if deployed properly, can provide protection at an equivalent level than passive measures against collision risks. However, passive measures, such as setting arresting cables, are necessary in cases where the response time of the active measures is long. The proposed method and the results obtained from the case study may be useful for robust and systematic effectiveness evaluation of safety measures in other cases worldwide.

Sea wave propagation from offshore to Maputo's coast. Application to longshore sediment transport assessment.

This study aims to characterize the wave climate near the coastal region of Maputo (Mozambique), and to provide a first assessment of the sediment transport load in this area. A time-series of 13 years' worth of offshore wave data, obtained from reanalysis products, was propagated to the coast. Wave propagation was performed using Linear Wave theory and the numerical model, Simulating WAves Nearshore (SWAN). Propagations with SWAN were carried out considering different scenarios in order to evaluate the influence of parameters such as wind, tidal level, frequency spectrum and numerical mesh resolution on wave characteristics along the coast. The prevalent waves propagated came from between east and southwest directions. Results from linear propagation were used to estimate the potential longshore sediment transport. The Coastal Engineering Research Center formula was applied for a stretch of beach in the Machangulo Peninsula. A net potential rate of longitudinal sediment transport (of the order of 10(5) m(3)/year, along an extension of the coast of 21 km) was directed northwards, and was consistent with the frequent wave directions.

A new risk assessment method for water quality degradation in harbour domains, using hydrodynamic models.

This contribution presents a method for assessing the risk of water degradation in harbour domains. The method describes a normalized Index of Risk, ranging from 0 to 1, which determines the risk of water degradation due to a pollution event. A branch-decision scheme of decision-making theories was implemented in order to obtain this index. This method evaluates the cost of each decision as a function of the vulnerability, proximity and toxicity of the potential contaminant. A novel feature of this method is that the risk is defined by considering the physical behaviour of the harbour (i.e. water circulation patterns). Regions where water residence time is high are considered more vulnerable to pollutant releases. This method could be implemented from an operational perspective, in which case an oceanographic operational system could be used to obtain current forecasts which in turn would be used to forecast risk maps.