This paper presents an attempts towards creation of generalized models of ships manoeuvring area determination and ship performance created on the base of real simulation results. Those models are needed for better understanding of the safe navigation process in ports areas and its approaches and for risk analysis when no full information about the ships behaviour is available. The data coming from real time ship simulations that are conducted by experienced pilots and captains are applied in the study. In the first step, general regression models are created to determine manoeuvring areas and major correlations between basic parameters affecting the safe area needed for ships to navigate in restricted areas of ports and its approaches. In the second step, the ship performance models are created to describe the behaviour of the ship including human factors. The ship performance for long-term prediction of the navigation risk regarding the possibility of ships exceeding the channel limits, assumed as grounding or collision with a fixed structure are created by the method which consists of two developed models: (1) an ARMAX (Auto Regressive and Moving Average eXogenous) model is adopted to identify the ship steering dynamic system. With the help of this model, the outputs of the system (course, position, etc.) can be estimated based on the system input conditions (rudder, engine, etc.); (2) the stochastic sequences of the inputs for the first model used are generated using a semi-Markov model. In the paper the implementation of the semi-Markov model for rudder actions has been described. The study used input/output measurements from a ship-handling simulator to estimate the model parameters, so the human factor has been included in the models. The method allows us to extend the results obtained from the simulator to predict future conditions of the system outputs. Since the predicted results and using probabilistic approach, possible ship manoeuvring area margins will be identified and long - term assessment of the navigation risk can be realized.

Flood risk reduction can be provided by interventions such as raising land or constructing flood defences. This paper introduces an approach to optimise the selection of risk reduction strategies. It expands existing economic optimization approaches for flood defences, by introducing (largely) analytical formulations to include the effects of approaches to mitigate flood consequences. The method considers the size of the protected area and associated damages, the costs and dimensioning of interventions and the likelihood of flooding. It is applied in several practical cases. Within the context of this economic model, we conclude that a system of flood defences is more economical than a landfill for larger areas. Fills are preferred for small areas and/or for low costs. A combination of strategies is preferred when the value protected by the flood defence is low compared to the value protected by the fill, or when the high value development is relatively small in size. The sensitivity of outcomes to the choice of the main input parameters is presented, as well as implications of the results and selection of strategies in developing and developed countries. Overall, this approach supports decision makers in developing effective strategies to manage and reduce flood risk.

We review the status of a 1.4 GW, 8 GWh underground pumped hydro storage (U-PHS) project in the southern Netherlands, which has been under development since the 1980s. Its history shows how the prospect of a large-scale U-PHS for The Netherlands (a country whose proverbial flatness prohibits PHS) has been attractive in every decade, based on proven technology in a subsurface location with validated properties, and solid analysis of its economics. Although the ongoing energy transition clearly requires massive electricity storage, (U-)PHS projects are challenging investment propositions, in The Netherlands, as elsewhere. This case study illustrates a point of general relevance, namely that although the project execution risk, related to uncertainty with respect to subsurface integrity, is very low, the transition risk, associated with the intrinsic uncertainties of an electricity system in transition, is significant. We point out mitigation strategies for both risk categories.

Research on phytoplankton dynamics in coastal waters has frequently been proposed, motivated by environmental factors. The present study aims to develop a vertical phytoplankton model to investigate the phytoplankton variability in a case of the Jiangsu coastal waters, driven by physical limitation. The quality of the parameter estimation largely determines the reliability of the model output. Skill assessment results reveal that the vertical phytoplankton model is able to reproduce reliable predictions of phytoplankton biomass in this case. Significant correlations are established between phytoplankton biomass and chlorophyll a. The phytoplankton biomass is significantly correlated with the variables of temperature, light attenuation coefficient, and euphotic depth. A decrease of phytoplankton biomass corresponds to deeper water, excluding the case of Yangkou station. Particular attention has been paid to the depth-averaged phytoplankton biomass. In the presence of uncertainty, the bootstrap method is used to derive a 95% confidence interval of the estimate, as well as mean value, standard deviation, and skewness. The findings of this study contribute to understanding of the coastal ecosystem and coastal management.