The Dutch system of waterways, of which the River Waal is the largest, allows for transport of cargo via inland navigation. Inland navigation as a transport mode contributes to the Dutch GDP and is indispensable for the Dutch strategic position in international world trade. Because inland navigation is river-based, it is dependent on natural conditions. Recent periods of drought, such as in 2018, have led to major financial impacts in the Netherlands and Germany. Due to climate change, periods of drought are expected to be more frequent, longer and more extreme in the future. Given the importance of inland navigation, measures are sought after to counteract these effects of climate change. Canalization of the River Waal is a last resort infrastructural measure to gain control over water levels on the river. To date, it is unclear whether climate change will eventually make it necessary to canalize the river for the benefit of inland navigation. In addition, it is unknown on the basis of what considerations such a decision should be made. This research attempts to answer these questions.

To investigate the necessity of canalization due to climate change, first the impact of climate change on inland shipping is determined on three different levels. First the hydrological development including occurrence of (low) discharges and corresponding water depths. Second the impact on individual vessel's loaded draught and loading rate, based on least available water depths on the River Waal in climate scenarios. Third the corridor cargo transport capacity, based on the occurrence of (low) discharges and the cargo transport performance of inland shipping in the past 10 years during similar discharge events. The development of these elements are the considerations in the debate on necessity of canalization of the River Waal from a shipping perspective. Whether these developments support the necessity of canalization is studied by means of limits which, if exceeded, may argue canalization. For the river's navigation function, requirements on navigability were identified based on prevailing international waterway management regulations (CCNR and TEN-T) as well as on previous Dutch canalization projects on the River Meuse and Lower-Rhine. The limits are projected on the analysed future development of the River Waal under climate change, to identify if and when they are met.

The hydrological development of the River Waal is assessed based on future discharge projections at Lobith under climate change. A range in scenario's is described, with a low emission and wet climate scenario 'Ln' on one side and a high emission and dry scenario 'Hd' on the other. In an Ln scenario, the future occurrence of days with low discharges (<1800 m3/s) on average per year is similar to that of the reference scenario (past 30 years, 1990 - 2020). In contrast, an Hd scenario shows a steady increase in the days of low discharges until 2100 after which the trend stabilizes. Extreme low discharges <600 m3/s appear. Furthermore, the lowest annual discharge (generally speaking during summer) lowers to 1000 m3/s by 2150, which is 750 m3/s lower than in the reference scenario.

At Rhine Kilometer 885 near Nijmegen the lowest water depths occur. In an Ln scenario the number of days with low water depth (<2.8 meter) is similar to the reference scenario with 40 days, independent of time. In the Hd scenario the number of days with low water depth increases where <2.8 meter occurs up to 3x more as in the reference scenario and outliers of <1.6 meters appear, up to 10 days. The long term average lowest discharge during the year drops from 3.5 meters in the reference scenario to 3 meters in 2050 and <2.5 meters after 2100.

The analysis of discharges and water depths is used to describe the development of the transport function of the River Waal. The location with the lowest water depth on a route of a vessel determines the loading rate. The combination of loading rate and active fleet determines the total amount of cargo carried on a corridor. In an Ln scenario, there is little deviation from the reference scenario, but nonetheless, a large vessel 135x17.4 meter CEMT Class VI+ has a restricted loading rate for 7 months per year with a minimum of 50% of the maximum vessel loading capacity. In an Hd scenario the loading rate of vessels decreases and the period lasts longer. For a most common vessel 110x11.4 meter CEMT Class Va, an annual average minimum is observed of 60% in 2050 to 40% in 2150. The duration of restricted loading doubles and the steepest decline is observed between 2050 and 2100.

Based on historical performance (2010-2020) of inland navigation, linked to the occurrence of discharges, a first-order indication of the development of transport performance over the River Waal corridor under climate change is made. No absolute numbers can be determined on this basis, but a sense of trends can be obtained.

Assuming no changes in the current fleet, the annual total weight that can be transported will decrease regardless of the climate scenario. The severity does depend on the climate scenario. Zooming in on cargo type does show a varying picture, where for dry bulk cargo there is an annual decrease of -3.0% cargo transport capacity in the most severe 2150 Hd scenario, while for liquid bulk cargo there is a steady decrease to -12.0% cargo transport capacity in 2150. This difference is explained by the number of trips made, where for dry cargo this theoretically rises to +25% in 2150 Hd, while for liquid cargo it can only increase +3%. Redundancy in the fleet can thus partially counteract the effects of climate change.

To reason the necessity of canalization, limits on navigability are identified, based on current navigational requirements and previous canalization practice. For the river's transport function, no clear limits where found, as a result of which no development could be identified that necessitates canalization. There are two regulations that apply to the navigability of the River Waal. TEN-T is a transport policy of the European Union and sets requirements for the quality of its network. On the River Waal, a guaranteed draught of 2.5 meters is required year-round. This is not met in the present (20 days undershoot in an average year) and will not improve in any climate scenario (up to 80 days in 2150 Hd). The CCNR is an association of five countries that is committed to the safety and interests of inland navigation on the Rhine. CCNR guidelines are leading for river management in the Netherlands. On the River Waal, 'OLR' (Agreed Low River Level) conditions require a water depth of 2.8 meters in the fairway, per definition a water depth that is undershot on average 20 days a year. This is not met in the present (40 days undershoot in an average year) and will not improve in any scenario in the future (>100 days in 2150 Hd).

Conditions on the River Meuse (1920) and Lower-Rhine (1960) before canalization were projected onto the present River Waal. If, as on the River Meuse, one want to accommodate a normative vessel CEMT VIc 6-barge push barge, there is at least 180 days of loading rate restrictions, now and in the future under all considered climate scenarios. The Lower-Rhine is canalized for the purpose of navigability of Lower-Rhine and River IJssel and to control freshwater distribution. Both Lower-Rhine and River IJssel did not meet the navigability requirements set at the time. The River Waal also does not meet its current stated navigability requirements (CCNR 2.8m: 40 days), but even in the extreme 2150 Hd scenario this is roughly only half (100) of the days as on the River IJssel and Lower-Rhine (2.7m: 190 and 225). The navigability requirements of that time did fit better with the draught of a most common vessel. The current most common vessel 110x11.4 meter CEMT Va experiences as many days (160) of insufficient water depth as on the River IJssel in all dry climate scenarios between 2033 and 2050. Compared to the Lower-Rhine, this is the case in an Hd scenario between 2050 and 2100 (180 days).

This research concludes is that from the inland shipping perspective there are two overarching considerations in the decision on canalization of the River Waal, the perspective of the navigability of the river and the perspective of its capacity to allow cargo transport. The navigability, described in (low) discharges and water depth, deteriorates due to climate change. Clear thresholds as TEN-T and CCNR requirements are not met and there is not sufficient water depth to accommodate the normative vessel CEMT VI+ year round. Taking action in the form of canalization would guarantee these requirements to be met now and in the future. Uncertainty in climate conditions causes that no clear predictions can be given on how severe the impact on the transport function is. Furthermore the transport function is more complex, since it describes a spread of individual vessels, different cargo types and a corridor. It is not inconceivable that adjustments within the 'transport function', like alterations in the logistical chain or improvement of the fleet, could (partially) counteract the negative impacts of climate change, which subvert the necessity of canalization. Apart from that, this research concluded that for the transport function there are no uniform quantified goals. Goals mentioned are the added value to Dutch GDP, the role in other sectors, the model shift and (military) strategic. Since these goals are broadly formulated, but not well quantified, it is difficult to identify limits in the performance of the system under climate change which could argue the necessity of canalization. To make a deliberate decision on canalization based on its capacity to allow cargo transport, it should first be defined and quantified what achievements should be made with the River Waal.

To stay on track for the 1.5°C pathway of the Paris Agreement, an accelerated energy transition is essential. Efficient offshore energy infrastructure planning, incorporating novel methods, is crucial and requires transparent, industry-wide discussion. However, two main challenges emerge: (i) the often-overlooked integration of energy islands in literature and (ii) the lack of a standardized techno-economic comparison method. A comprehensive review of offshore wind supply chain feasibility studies highlighted the need for explicit implementation of standardization, syntax and semantics in model development. Detailed assessment of international and industry standards revealed that no single standard fully covers the study's scope. Nevertheless, one ISO standard showed significant similarities in component definitions, with which this study's component definition is maximally aligned. The developed open-source model enables automated supply chain configuration generation, eventually calculating economic metrics such as the Levelized Cost of Hydrogen (LCOH). Applying the developed techno-economic model to the 19.5GW case study hub North in the North Sea Energy programme demonstrated its applicability and the techno-economic advantages of integrating an offshore energy island. The key finding is that island-based configurations are economically more efficient for hydrogen production compared to platform or onshore setups. Comparison with other studies on hydrogen import indicates that the calculated LCOH range of 8.54 - 10.40 €/kg has the potential to compete with hydrogen imports, which often have overly optimistic estimates ranging from 4 to 9 €/kg. Ultimately, in this way, a standardized, transparent method for industry-wide collaboration is presented.

On Saba, an island located in the Caribbean, a new harbour will be constructed. To protect coral reefs in the vicinity from light attenuation and sedimentation, it is important to monitor and predict the turbidity stresses caused by the dredging operation. In the early stages of such projects involving dredging operations, a common approach is to estimate the turbidity stresses in a simplified way using stationary source terms and the exclusion of important physical processes as tidal and wind-forcing. This research focused on the development of a representative approach to simulate the turbidity effects from dredging activities by backhoe dredgers in the vicinity of Caribbean islands, by building on existing methods by Becker et al. (2015) and Tuinhof (2014). The Black Rocks harbour project on Saba was used as a case study to test the effectiveness of the new method approach.

First, the local physical processes were identified and their influence on the turbidity stresses and dispersion of the sediment plumes were discussed. Insight in the wave heights and wave period should be obtained to aid in the decision for the dredging equipment to use and their workability. Key processes to include for a representative simulation for the dispersion of the plumes were identified to be the tidal and wind driven currents over the depth. Another local phenomenon to consider was the run-off from peak precipitation events, as this results in high background turbidity levels. Analysis of local sediment samples is required to obtain insight in the fines content, required for the estimation of the sediment flux, and the distribution of particle sizes and the particle density to determine the settling velocity.

Insight in the work method and duration of the dredging cycle provides information to determine the temporal distribution of the source terms to suitably simulate the loss of fines over time, making a distinction for the presence of the source between day and night cycles and during relocation. The primary source term contributing to the release of fines, identified to be the bucket drip, was spatially distributed to simulate the relocation of the backhoe. An additional method step was introduced by estimating the local fines content for each source term over the dredging volume, resulting in a more representative approach for dredging volumes exhibiting a heterogeneous distribution of the fines content compared to using a single value for the fines content. The source terms were estimated using an existing method by Becker et al. (2015) and distributed over multiple sediment fractions, to include the representation of the smaller particles, affecting the
far-field SSC in the model.

The effects of tidal and wind-forcing were incorporated using a 3D model, while running different hydrodynamic scenarios to test the effects for a variety of flow conditions. The grid resolution was chosen to ensure an accurate representation of the spatial distribution of the sediment concentration resulting from the bucket drip. The source terms were equally distributed over the depth to simulate the gradual loss of the fines over the depth by the bucket drip. The selection of an appropriate formulation for the settling velocity, to account for the local hydrodynamic conditions and sediment characteristics, increases the representation of the distribution of fines over time.

The model results indicated that for both a stationary and relocating source term, an accurate
depiction of the average SSC values over longer time periods as days and weeks is simulated, while the relocating source tends to estimate peak concentrations more accurately, as the source location and quantity is represented more precisely. Turbidity thresholds, set for the Black Rocks project, were only exceeded on one occasion during the occurrence of a current reversal for the relocating source, but not for a stationary source. This indicates the added value of applying a more detailed approach to simulate the turbidity stresses. Following the suggested additions to the methods an updated approach to simulate the turbidity stresses by a backhoe dredger was proposed. Further research into refinement of the method, focusing on the spatial distribution of the source and appropriate spatial and vertical grid resolution, can increase the suitability of the suggested method for simulating turbidity stresses induced by a backhoe dredger.

The lock of Hansweert, located in the province of Zeeland in the Netherlands, serves as a crucial inland shipping node between the Western Scheldt estuary and the Rhine Delta. The outer harbour of the lock complex provides the connection to the Western Scheldt and accommodates waiting facilities for inland ships. The Western Scheldt is a vital gateway for maritime traffic, linking the Port of Antwerp to the North Sea. As the navigation channel of the Western Scheldt is located close to the outer harbour of Hansweert, multiple ship incidents at this location are attributed to the water motions generated by passing seagoing vessels on the Western Scheldt. This research investigates how the water motions induced by passing vessels in the Western Scheldt contribute to unsafe situations in the outer harbour and locks of Hansweert, and what preventative measures can be identified to effectively minimize incidents and mitigate risks.

Investigating the incident records reveals that the key contributors are the primary water motions generated by the passing vessels in the Western Scheldt. The phenomenon, experienced as a sudden lowering of the water level and suction forces, can lead to the breakage of mooring lines and uncontrolled movements of inland ships, resulting in a range of safety hazards and operational disruptions. Several documented incidents, field studies and interviews highlight the urgency for effective measures to mitigate the potentially harmful effects of passing vessels on the ships in the Hansweert outer harbour and locks.

A seven-week measurement campaign, involving 1281 passages of so-called oversized vessels, reveals distinct patterns of water level fluctuations during a vessel’s passage. A vessel is considered oversized if its length exceeds 210 metres or if its draught is larger than 10 metres. These patterns are described as a translatory drawdown wave travelling into the harbour, reflecting against the lock complex and oscillating back and forth in the outer harbour until dampened. The key parameter characterizing this wave is the lowering of the water level, referred to as the drawdown height. The average measured drawdown height approximates 6 centimetres, with maximum observations up to 40 centimetres. The main factors influencing the drawdown height are the vessel’s passing distance to the outer harbour, its speed relative to the currents and its dimensions, shown by a correlation analysis between the parameters describing the passing vessel and the generated drawdown height. Extreme drawdown events were exclusively observed during a combination of a relatively high speed through the water of the seagoing vessel and small passing distances relative to the harbour’s entrance.

The impact of the drawdown effects on the inland ships is determined by the forces generated by the pressure difference along the ships, caused by the inclination of the water level. A critical drawdown height of 12 centimetres is set, based on existing force criteria and the linear relation between the drawdown height and water level slope. To improve on the existing drawdown height prediction methods, a site-specific drawdown height prediction equation has been derived. Validation of this equation using the observations made during the measurement campaign yields a Pearson correlation coefficient of 0.81 and an Mean Absolute Error score of 2.2 centimetres.

Preventative measures are identified, aiming to minimize incidents and mitigate the risks related to the water motions induced by passing vessels. The predicted drawdown, generated by the passing vessel, is kept below the critical level by recommending a maximum speed related to the passing distance and dimensions of the vessel. Practically, this measure could be applied as a calculation tool or as an overlay on the pilot’s electronic sea chart. Coupling this information with awareness campaigns for pilots will contribute to minimizing the adverse effects on the ships in the outer harbour. The resilience against drawdown-induced risks could be strengthened by restricting the maximum combined width of ships moored alongside. Furthermore, by limiting the excessive slack in the lines of the moored ships, through signage and floating bollards, the movements of the ships will be restricted, reducing the risk of line breakage. Notifications of anticipated critical drawdowns would allow traffic controllers or lock operators to caution the inland ships and delay the lock chamber door openings, whilst alerting the passing vessel. Incorporating the mitigation measures recommended in this research could positively impact the safety of navigation in the Hansweert outer harbour and locks.

In the early project phase, decisions are made when considering a port basin berth layout that affects the outcome and the success of the project. In order to make a decision regarding the berth layout, port planners create a set of variants for comparison and assessment in order to pick the basin berth layout that suits the project goals the best. The selected basin berth layout is the preferred variant that will be used to eventually be realised. However, since the decision in the early project phase has a great influence on the entire project, port planners want to improve the decision-making for selecting the best berth layout. This research aims to improve the decision-making process for selecting the berth layout of preference by developing a design generation method for berth layouts and its respective pathway. This method might give insights into optimal berth layout configurations and its pathway in order for decision-makers to assess their preferred variant resulting from the set of variants developed by experts and the generated layout. After the method is developed, the method is tested on conceptual benchmark cases and a real case in order to assess whether such method can add value, or improve, design solutions of port basin layouts during the early project phase. Although limited studies and methods exist that have resemblance or commonalities with berth layout optimisation, the idea is in its infancy. Methods for berth layout optimization have been developed to generate berth layouts and its re spective pathway through the basin in this report. The optimization is separated into two steps: firstly, berth location optimization using a pre-defined central basin pathway, and secondly, optimization of the pathway belonging to the respective berth layout. The separation of the berth location and pathway optimisation reduces computational time. The heuristic berth location optimization optimizes the locations of the berths to minimize the central pathway dredging, while satisfying constraints prescribing a minimal distance between the berths. After the berth locations are optimized, the pathways can either be optimized by means of a heuristic pathway approach, or by means of an exact mathematical pro gramming approach, both of which are developed in this research. The heuristic pathway optimization approach models required dredging by translating the dredging for a berth into a graph with weighted edges and then sequentially defining the route that requires the least dredging per berth, eventually forming the complete basin pathway. The exact pathway approach uses a mathematical programming setup. The methods are applied to conceptual benchmark cases a real-life case. The benchmarks differ in basin dimensions, basin bottom profile, and fleet characteristics. The real-life case concerned the Scheurhaven, which is a small port basin for mainly tugboats. The layout of the Scheurhaven had to be adapted to fit more tugboats in the basin. The Scheurhaven case was optimised with the heuristic approach, due to the potentially large computational time of the exact approach. As the berth locations were limited and the method lacked features to make the design comparable, such as structures and berth geometry, only heuristic pathway optimisation was done.

Inland shipping is widely acknowledged as a sustainable mode of transportation due to its low energy consumption and emissions in comparison to road and rail transport. However, with growing concerns around reducing emissions in the transportation sector, there is pressure to address environmental issues associated with inland shipping. In the Netherlands, a Green Deal has been formulated to outline the goals for reducing CO2 emissions by 2030 and other environmental pollutants by 2035 in inland navigation, to enable us to take the next step towards a climate-neutral society by 2050. This increasing pressure raises the question of how to get insight of the energy consumption and the associated emissions from inland shipping. To date, an accurate method is lacking that is able to estimate the total resistance, the propulsive power and in turn the energy consumption in shallow water and thus to quantify the CO2 emissions. Over the years, several power estimation methods have been developed for inland vessels, with the Rijkswaterstaat power estimation method being one of the most widely recognized. Recently, Backer van Ommeren (2019) investigated the Rijkswaterstaat power estimation method and found that certain assumptions and parameters used in the method were not well-founded, and that some approximations were unnecessary.
The main objective of this study to conduct a comprehensive literature analysis on Backer van Ommeren (2019) comments and recommendations regarding the Rijkswaterstaat (RWS) or Bolt (2003) method in order to clarify to what extent these recommendations will indeed improve the Bolt (2003) method or if an alternative power method should be proposed instead. This will be accomplished through a comparison process of the power results as a function of sailing speed, water depth, and channel dimensions for various types of inland vessels, utilizing the selected methods that will be derived from the literature study along with Backer van Ommeren (2019) recommendations applied to the original method. After coding these methods in Python and analyzing their results, the best practice(s) that will be derived from the test cases, will be implemented on two classes of motor vessels an M6 and an M8 to estimate the resistance and the power and then they will suggest to Rijkswaterstaat for potential future use.
To achieve the main research objectives, the following research was conducted. Initially, a literature analysis on the available resistance methods, how they consider and divide the several resistance components, and which are the shallow water effects that affect them, was done in order to evaluate their performance in terms of power estimations. Secondly, the comments made by Backer van Ommeren were presented and analyzed. Specifically, he investigated various formulations for calculating the return flow, water level depression, and characterizing the waterway as normal, narrow, wide, or very wide. This study was accomplished through the use of specific power efficiency and resistance coefficients. Based on his study, he derived a method, the Backer method (Backer van Ommeren, 2019) and suggested a number of formulas to be further tested. After completing the literature review, the findings lead to the selection of the power methods that will be treated in this thesis and the kind of improvements that will be applied to the original Bolt (2003) method.
Subsequently, from the literature study and Backer van Ommeren (2019) review, four methods were derived to be simulated and tested in this thesis. These methods include the TU Delft method, Bolt method with speed correction, Bolt method modified by Backer, and Backer method. The simulation was achieved with two rounds of tests that are conducted, firstly the “Academic test case” and secondly the “Real-world test case”. In the “Academic test case” five methods were simulated and the most promising that met specific criteria are selected. Then, in the “Real-world test case” the selected methods as they were derived from the “Academic test case”, were further evaluated for the selection of the best practice(s). The first round of tests is applied to two classes of motor vessels in narrow and wide waterways with shallow, intermediate and deep water depth conditions and the results include the total resistance and the brake power while the second round simulates only one motor vessel of class six in wide waterways for the same depth conditions as previously and the outcome includes the delivered power. The “Real-world test case” is divided in two parts. The first part includes the comparison between the estimated and the measured delivered power in order to assess the performance of the methods with the real data. The second part evaluates the performance of the methods in the presence of a current flow, by comparing the fuel consumption in upstream, downstream and round trips.
The evaluation of the methods in a real-world test case led to a number of conclusions, and the best practices were recommended accordingly. It should be noted that the comparison process was based solely on a single real-world case, utilizing a singular set of real data. It is important to be conducted additional comparisons across multiple real cases in order to increase the understanding of the accuracy of the various methods being compared. In the context of power estimation in shallow water, both the Bolt (2003) method and TU Delft method(Jiang, Baart & van Koningsveld, 2022) have demonstrated remarkable accuracy in their predictions while Backer method and Bolt method modified by Backer are not recommended for power predictions. Notably, Bolt (2003) method has proven to be effective in estimating power within a speed range of 2.5m/s to 3.5m/s while TU Delft method (Jiang, Baart & van Koningsveld, 2022) showed accurate predictions within a speed range of 2.5m/s-4m/s (accurate as defined within 20% of the observed value). Regarding the intermediate and deep water conditions, only TU Delft method (Jiang, Baart & van Koningsveld, 2022) showed acceptable performance in power estimation again for sailing speeds varying 2.5 m/s – 5 m/s. The power demand at very low speeds for all the three methods display a considerable deviation between the estimated power output and the actual values, surpassing the acceptable rate of 20%. This can be attributed to two reasons. At low speeds, the interaction between a sailing vessel and the boundary layer becomes more pronounced, causing the ship to experience turbulent effects that dominate the boundary layer more intensively. As a result, the vessel experiences increased resistance, requiring more power. Secondly, in actual operating conditions, a ship has a minimum power engine setting that is dependent on the engine characteristics. So, when the ship is moored and the "hotel mode" is on, as the ship not having a separate auxiliary power unit, a propeller brake is used to allow the turbine to continue running and generate power without the propeller spinning. This effect does not consider by the power estimation methods that rely on parameters such as sailing speed and water depth. The Backer (2019) method demonstrated satisfactory performance in predicting resistance and power for both types of motor cargo vessels within narrow waterways. This method effectively accounted for the variations in depth by accurately estimating lower resistance and power demand as the depth increased. However, Its accuracy in wide waterways diminished due to the equations' unsuitability for such conditions, by generating nearly identical resistance and power estimations for the three different water depths. Based on the aforementioned restriction, it is not recommended to employ this particular approach for subsequent power estimations. As regards the Bolt method modified by Backer performs poorly in estimating resistance and power across narrow and wide waterways with varying depths. It consistently yields similar results for shallow, intermediate, and deep depths at a specific sailing speed. Therefore, it is not recommended as an improvement to the Bolt method. In the presence of current flow, three methods have shown promising results. Specifically, the TU Delft method (Jiang, Baart & van Koningsveld, 2022) is recommended for motor vessel, as it produces deviations from real measurements of 0.93% for upstream, 1.36% for downstream, and 0.45% for round trips. Also, TU Delft method (Jiang, Baart & van Koningsveld, 2022) is recommended in case of pushed and coupled convoys as it has been found to produce the smallest deviations in upstream sailing, with a maximum of 3.9% while the deviations observed for downstream sailing and round trips are around 1.9%. Bolt (2003 )method and Bolt method with speed correction, were found to produce acceptable deviation rates of around 7% for upstream trips, with the benefit that these methods require less detailed input data. Nevertheless, for downstream and round trips, the deviations were much higher, reaching up to 80% and 30%, respectively and event that requires additional investigation and validation.

This study integrates strategic decisions and operational control systems in autonomous shipping. By providing ships with situational information and adding a virtual operator, we show that vessels can make informed choices regarding their route and engine settings. To demonstrate this integration, we developed new components that were tested in three lab experiments.
The 'green routing' experiment showed the bridge between the control system of the autonomous vessel, operated via Robot Operating System (ROS), to the simulation environment of OpenCLSim. We developed a real-time variant of OpenCLSim and a communication component that could expose the state of the OpenCLSim simulation with the ROS system. This experiment showed that the path provided by the simulation was followed by an autonomous vessel.
The 'green steaming' experiment showed that the ship could also adapt its speed based on information from the simulations. We developed an additional communication component capable of advising the vessel about its velocity. Together with the green routing capability, this forms the basis for more complex experiments.
The 'port call' experiment showed a potential use case of the green routing and green steaming capabilities. We created a waypoint layout similar to the port. While a ship is sailing, every five seconds, twelve simulations are computed. The scenarios vary in engine order, route choices, resulting in varying emissions, fuel, and cost. We evaluated the impact of different tactics such as green routing, green steaming, and full-speed sailing on operational behavior like steering and engine order. Our approach, using a real-time version of a Vessel in the OpenCLSim simulation software, enabled predictive simulations to facilitate the chosen tactic based on a given strategy. Integrating simulations to evaluate the options with the control systems can develop into a valuable tool for optimizing vessel performance and reducing environmental impact in autonomous shipping operations.

The increasing severity of river drought poses a potential threat to the operations of ports using rivers as hinterland connections. River droughts have impacted navigation in various rivers worldwide, including the Rhine river where instances of low water levels in 2018 and 2022 caused disruptions in navigation. As a consequence, inland vessels were forced to reduce their cargo loads. Seaport terminals that serve as crucial links between sea vessels and inland vessels may be impacted by changes in fleet composition, thereby affecting a terminal's cargo handling operations and storage. However, there is a lack of research quantifying the effects of low river levels on seaport processes and determining suitable methods to assess this impact using vessel movement data.

To address this research gap, this study aims to quantify the impact of low river levels on seaport processes by focusing on the EMO dry bulk terminal within the Port of Rotterdam as a case study. Given the connection between this port and the Rhine, which is known for its vulnerability to drought and serves as a vital route for inland navigation, the analysis begins by examining the impact of reduced river discharge on the dry bulk fleet sailing from Rotterdam to Germany utilising Information and Tracking System for Shipping (IVS) data. Additionally, Automatic Identification System (AIS) data is employed to assess the service time, the number of vessels and the berth occupancy within the terminal to quantify the impact of low river discharge on the cargo handling process within the terminal. Specifically investigating the effects on vessels being loaded and bound to the hinterland and those being unloaded after arriving from the sea. Finally, the study analyses the impact on the storage capacity of the EMO terminal using monthly cargo data provided by the terminal, by studying the balance between the amount of cargo being unloaded and loaded.

The findings show that vessels sailing along the Rhine are required to reduce their load as discharge decreases, leading to an increased number of vessels. However, this compensation by more vessels does not fully offset the load losses, resulting in a decrease in the total load carried per day when discharge decreases. Consequently, more vessels arrive at the EMO loading berths during low discharge periods to compensate for the reduced load and therefore loading time for vessels at these berths is shortened. Due to the increased vessel arrivals, the berth occupancy at the loading berths increases to a maximum of 65%. On the contrary, the berth occupancy at the unloading berths remains unaffected. Cargo flow analysis shows that the lowest cargo loading into inland vessels occurs during months without low discharge, rather than during the months with the lowest discharge. Additionally, the share of rail transport increases during low discharge months but remains below maximum capacity, indicating sufficient slack to handle all cargo. The stockpile analysis reveals a small surplus during low discharge months, although not as significant as in months with normal discharge levels.

Overall, the findings indicate that the large size of the EMO terminal allows it to withstand the impacts of past periods of low river discharge. As the loading berth's occupancy is not at its maximum capacity and the unloading berths remain unaffected, there is sufficient slack to accommodate additional vessels. Accordingly, adequate vessels are loaded to transport cargo to the hinterland, ensuring no impact on the stockpile and thus maintaining the storage operations at the EMO terminal without disruption.

While this research provides valuable insights, it is important to acknowledge that terminals of varying sizes or handling different cargo types may experience different impacts and should be subject to further investigation. Additionally, the limited availability of AIS and cargo data, with only one year of extreme drought (2022) for analysis, prevents drawing definitive trends and making long-term assumptions for future scenarios. Nevertheless, this study's methodology can be adopted in related studies to analyse more terminals and gain further insights.

To facilitate the energy transition, effective collaboration among all stakeholders is necessary. However, there is currently a lack of understanding regarding the impact of different components in the value chain on the energy system's overall structure and the final energy price. This knowledge gap poses a significant obstacle to cooperation and progress in the energy transition. It creates the risk that effort goes into developing certain partial solutions when they may not be feasible from a larger system perspective. By focusing on their own component, stakeholders do not fully take into account the needs and interests of others involved. As the development of green hydrogen projects is in its early stages, it is important to think in terms of systems. Stakeholders should establish an ecosystem where players operating in different parts of the value chain are collaborating together. This helps to de-risk projects, share lessons and promote the development of innovative, first-mover initiatives.

This study aims to develop a standardised method to evaluate offshore wind to hydrogen concepts through a techno-economic analysis. This analysis method combines technical analysis with economic evaluation of projects and concepts to determine the potential economic outcomes and impacts of implementing a particular technology or project.

Through stakeholder interviews, the study found that stakeholders in the offshore wind and hydrogen market have distinct objectives and concerns. Key factors influencing their willingness to contribute include confidentiality, competition, and reputation.

To increase the transparency of the model, it was developed in Python. A standard notation system was developed, which was presented alongside the model's results. This should aid in the understanding of the underlying assumptions.

The dredging industry is a contributor to the greenhouse gas (GHG) emissions due to the energy-intensive process of dredging and transporting sediment. This industry has to reduce the GHG emissions due to future possible restricting regulations on GHG emissions. The dredging industry is shifting towards more environmentally friendly fuels, but designing new vessels which can run on these fuels will be a time consuming transformation. Though, the demand of dredging activities is growing, think of construction of offshore wind farms and creating flood defences against sea level rise. To minimize the costs due to the high GHG footprint in the short term, Van Oord should be able to estimate the energy consumption (GHG emissions) based on different dredging strategies.

Van Oord uses a model to estimate energy consumption that accurately describes the majority of dredging projects, based on the power installed, dredging time, and a power coefficient term. This power coefficient term is based on empirical data and may result in a less accurate estimation of more complex (new) projects such as offshore wind farms and cable dredging, which are the new opportunities arising for dredging companies. To better estimate energy consumption during these complex dredging operations, a physics-based and semi-empirical method is developed that can more accurately estimate energy consumption based on certain dredging strategies. Previous research already looked at the sailing phases of the dredging cycle, therefore the main objective of this thesis is:

To quantify the energy consumption of different TSHD dredging strategies based on physics for the loading phase.

To achieve this research objective, first a literature study is conducted to list the different physics-based methods available to estimate the energy consumption. The energy consumption of a TSHD is divided into five main energy consumers (propulsion system, dredge pumps, jet pumps, bow thrusters and board net) in which the energy of the individual components is described by a power and a time term. The time component is represented by the duration of the loading cycle, which in this study is limited to the filling process of the hopper until overflow. The power term of the jet- and dredge pumps have been estimated by the (adjusted) in-house physics-based methods of Van Oord. The board net and the bow thrusters have been estimated by data analysis of a case study. The goal of this research is to develop a method to estimate the required propulsion power and a tool to bring all methods together to simulate the total energy consumption during the loading phase based on different dredging strategies.

A model is developed to estimate the required propulsion power during loading. The model development is divided into three phases; The first phase describes the development of a semi-empirical physics based model. In this, the various resistance forces acting on the vessel, suction pipe, and draghead are calculated based on stationary parameters such as vessel dimensions, and project parameters. The project parameters, including water depth, trailing speed, and visor angle, are extracted by filtering the actual data from the case study. In this way the estimation model is set equal to a reference case. Finally, the output of the estimation model is calibrated by comparison with the actual data of the case study. This calibration phase is an iterative process in which the accuracy of the model is described and increased.

The model shows that it is possible to calculate the required propulsion power based on operational parameters, such as trailing speed. Furthermore, the model provides insight into the amount of resistance on the three components (draghead, suction pipe and vessel). The power curve follows a quadratic pattern for increasing trailing speed, which appears to be a reasonable estimate. When comparing the model to the actual data it can be seen that the model underestimates at lower trailing speed and over estimates at higher trailing speed. By finding correlations between visor angle and trailing speed the model is calibrated and seems to better fit the dataset, however the slope of the curve still has a large deviation compared to the regression line based on the actual dataset. Therefore, the model needs to be further developed before it can be included as an addition to the existing models within Van Oord. The static friction term is not included, which could compensate the underestimation of the model and the high cutting forces are the potential reason for the overestimation at high Van Oord Marine Ingenuity iii Delft University of Technology trailing speed. For now, the current developed model falls within the reference dataset for the trailing speed between 1.6 [kn] and 1.9 [kn], thus making it a reasonable first estimate of the required propulsion power.

The OpenCLSim python package, which can be used to simulate discrete events, is used to simulate the dredging processes of the loading phase. A plugin for this python package is developed to calculate the total energy consumption during these processes. The propulsion model is integrated (with the set limitations) in this plugin together with the four other power estimation methods (dredge pumps, jet pumps, bow thrusters and board net). The simulation tool runs based on four input characteristics: vessel parameters (TSHD), site characteristics, dredging strategy, and data describing the bow thrusters and board net. The output of the simulation includes required power, duration, and consumed energy. Additionally, the simulation estimates the fuel usage,
emissions, and project costs associated with energy consumption.

The main ability of the simulation tool is that it can visualize the energy consumption (and emissions) based on dredging strategies and location. This enables the prediction and potential reduction of emissions in sensitive areas, such as fine dust emissions near cities. By using this simulation tool, a dredging plan can be created based on dredging strategies (trailing speed) to reduce emissions in these sensitive areas. To better demonstrate the other capabilities of the developed plugin within the OpenCLSim Python package, the simulation tool is applied to an imaginary project called Barachi. This project has strict regulations that prohibit overflow and apply emission taxes. Two dredging strategies are compared based on the limitations of the developed propulsion model: trailing speeds of 1.6 [kn] and 1.9 [kn]. The results show that, first of all, the project duration will decrease with an increasing trail speed. Secondly, the increase in power has a greater effect on energy consumption than the decrease in project duration, meaning that energy consumption will increase. Since fuel use and corresponding emissions are linked to energy consumption, they will also increase. However, the cost analysis provides a different view. In this case, because the ship’s operating costs are governing, faster trailing is the most cost-efficient, even if an emission tax of 200 euros/ton CO2e is applied.

To conclude, by creating a model to estimate the propulsion power and by integrating this model in a simulation tool, it is possible to quantify the energy consumption of different TSHD dredging strategies based on physics for the loading phase. Subsequently, the simulation also provides insight into the fuel usage, carbon emissions, and costs of the project. Further development and validation of the propulsion model is needed to give a more accurate estimation of the required power. Firstly, the static friction component should be included in the estimation model which could potentially solve the underestimation at lower trailing speed. Secondly, a maximum trail speed limit should be set based on the available propulsion power with respect to the total power distribution of the vessel. This limit should be included in the simulation tool, since it is linked to the other power consumers and the operational parameters. Thirdly, the propulsion model can only be used in saturated sand projects. Other cutting models based on cutting of silt, clay and rock should be added in the propulsion model to be able to apply the model in these soil conditions. Finally, the use of the tool is limited to dredging projects where overflow is not allowed. The suction production and the settling process within the hopper should be added to expand the capabilities of the tool to projects where overflow is possible.

Currently, inland waterway safety assessments rely heavily on historic accident data and expert opinions, often lacking comprehensive qualitative and quantitative information. Addressing this gap, this thesis introduces a method based on Automatic Identification System (AIS) data to identify anomalous vessel behaviour for enhancing safety assessments.

The proposed methodology establishes definitions of normal vessel behaviour and identifies deviations from these norms as anomalies. Analysing vessel trips recorded in AIS data logs, various features—including speed, acceleration, direction, manoeuvrability, and positional attributes—are extracted to define vessel behaviour.

The Uniform Manifold Approximation and Projection (UMAP) algorithm reduces the multidimensional features into a two-dimensional embedding to condense the vessel behaviour into a manageable form. This reduction technique preserves the inherent behaviour while representing similarities within a 2-dimensional space. Subsequently, the K-means clustering algorithm is applied to group vessels displaying similar behavioural patterns. The hyperparameters for clustering are determined using the elbow method and multiple scoring metrics.

Application of this methodology to the Moerdijkbrug at the Hollands Diep and Schellingwouderbrug at the IJ reveals clusters with similarities in vessel direction and paths. Several atypical patterns were observed and further investigated, analysing less than 1% of the data set in both cases, revealing two distinct patterns classified as probable accidents in the IJ case. These findings demonstrate the potential of the proposed method in identifying specific vessel behavioural anomalies with implications for safety assessment on inland waterways.

Increased complexity on the waterway asks for more insight into distances between vessels. A method is created to determine the ship domain in a port area based on AIS data analysis. The method includes location, encounter types, relative position and ship-specific parameters.

Lock passage can potentially make up a third of a vessel’s travel time for inland waterway transport and therefore has a large impact on inland waterway and multimodal transport networks.
To reduce the overall environmental and economical impact of transport, there is an increasing interest in inland waterway transport relative to road and rail transport. To keep up with this shift towards inland waterway transport, models are created for the optimal arrangement of multimodal transport and transport on inland waterway networks. Hence, lock operations need to be carefully modelled.
The modelling of lock passage is often based on historical data and generalised for all the locks on the network. However, there are uncertainties in historical data, especially with the prospect of an increasing fleet size and more extreme seasonal changes. Additionally, locks can vary in functionality (e.g. recreational or professional use), operability and strategy (e.g. filling and emptying), structural design (e.g. capacity of lock chamber), and environmental conditions (e.g. water level differences).
These variations impact the passage time of phases in the locking cycle. An overgeneralised validation for a simulation model can result in inaccurate simulations for a specific lock.
Therefore, it is desired to use more lock specific data, which can be achieved by applying vessel specific data in the form of AIS (Automatic Identification Systems). AIS, live location data of professional vessels, is used in waterway traffic management, but is also collected for research purposes. The data is easily accessible for a desired period of time and area.
Literature studies show that analyses and validations of simulation models is a common practice with the combination of GPS based data. Some studies use AIS data around locks, only to find the total passage time of the vessel. A lock passage can be divided in more phases that impact the total passage and waiting time of a vessel, examples are the entering and exiting of the vessel and the
operating time of the lock itself.
The objective of this study is to find a generic method to derive validation parameters for simulation models of locks. Data derived from this study can further be used in the optimisation of lock passages in simulation models. In this way, any desired lock and for any circumstances (e.g. seasonal changes or periods of maintenance) a validation can be performed.
A method was created to translate AIS data to information that is relevant for a lock. This method enabled us to analyse the total passage time and the phases of a lock passage that impact this passage time. Based on the AIS data over a certain time period and considering the geometry of the lock, trajectories of passing vessels were derived. These movements were combined into lock cycles
and therefore the corresponding validation parameters could be identified. One example of these validation parameters was the lock operating time, which is estimated based on the principle that all vessels in the lock chamber stopped moving.
The lock specific data can be used to compare the data with the performance of a simulation model of a lock and period in time. This applies for models that only use the total passage time of a vessel, which in some situations might be sufficient. This also applies to models that consider more detailed lock passage. Since the method is based on positional data, the boundaries of the lock sections can be adjusted to the definitions used in the model.
The method is applied on a cases study of the Volkerak and Kreekrak locks. Firstly, the AIS data translation is performed for a lock to create data sets of the lock passages. Also, data of the water level at the lock is linked to each locking cycle. Secondly, this data is compared to a lock simulation in the same situation. The arrival rates, arrival speed, vessel dimensions and water level difference
are used as input to create a base simulation for various configurations. The lock simulation module of OpenTNSim is used because this is an open-source transport network simulation model developed at TU Delft.
The simulations are compared to the collected data, for a total of 18 segments on the trajectory passing the lock. The segments correspond to the phases of a locking cycle. The average passage time of each segment is compared between the vessels of the simulated and the collected data. Because of the large sample sizes, these comparisons created a view on the overall performance of the simulation for each segment.
The information found in the base simulations was further used to calibrate the OpenTNSim package. The vessel speed was adjusted on the approach and leaving of the lock chamber to match the trajectory of the arriving vessels. Also, the filling time of the the lock chamber was optimised for the simulation.
The Volkerak had a total of 24,446 vessels passing over the time period, this is comparable to the 24,570 vessels that were counted by Rijkswaterstaat in the same period. Three cases were selected to compare the simulation model, one vessel passing without waiting, one vessel passing with waiting and two vessels passing. These resulted in sample sizes of 943, 89 and 561 lock cycles respectively. The case study shows that, with a small sample size of 89 locking cycles, there can be large variability in passage times.
The largest deviations of the simulations relative to the collected data were found in the passage time of the segments between the waiting area and the lock chamber. Another deviation was found in the lock operating time for the case of two vessels passing.
The method used can give a large and useful data set of vessels passing a certain lock. The lock data can be used for statistical analyses. An example includes the number of vessels per locking cycle or the entering time or speed. Also, each locking cycle can be assessed and visualised individually or for a desired time span.
When the data is used for the validation of a simulation model, a large data set is needed to give reliable results. After all there can be large outliers and the performance of the lock is dependent on human interaction, the lock operator and the vessel’s captain. A combination of the AIS based data with other additional data can expand the method.
In conclusion, a highly suitable method was found that enables to use AIS data for the validation of a simulation model of a lock. The method is sufficient for most applications of a lock simulation model, despite being limited to just the movement of the vessels. However, when an accurate simulation of a lock phase like the closing of the gate is desired, other data sources might be more suitable. While this research has a focus on the comparison of the collected data to a lock simulation, the data can also be used for a statistical analysis of the lock when looking at fleet composition, arrival rates and stopping distances.

The consequences of climate change are happening now, and will increase in the years to come. Understanding the energy consumption of dredging operations is becoming increasingly important for dredging contractors such as Van Oord. With the emergence of more complex dredging situations, including dredging at limited depths and short sailing distances, it has become more difficult to provide an accurate estimate. This research was conducted to evaluate Van Oord's current estimation method, called VOHOP, and to provide an improved estimate of the energy consumption for dredging activities based on historical data. Therefore, the main objective of the study is as follows:

"To improve the estimation of energy consumption for dredging activities based on actual data."

To achieve this goal, the method that is selected for creating improvement is comparing estimation methods with actual data where the difference gives insight in how to improve the estimation method, explained more briefly: EST vs ACT = DIFF. A literature review is first conducted to indicate what a dredging cycle looks like. After analyzing the different phases, consisting of sailing empty, loading, sailing full and disposing, the parameters that play a role in the consumption of energy during the dredging process are stated. For example for the sailing stages parameters that play a role are: sailing distance and sailing speed. Due to the relatively less elaborate calculation of energy consumption for the sailing stages, an improvement of estimation accuracy for these phases is considered to be valuable. Next, existing alternative methods for estimating energy consumption for the sailing phases are explored and the method proposed by Holtrop & Mennen (HM), including modifications created for limited depth estimations, is selected as the most appropriate because it takes into account a larger number of parameters (such as depth, draught and distance), which is expected to increase the accuracy. After comparing the current estimation method VOHOP, with the method proposed by HM including modifications, one of the main findings is that the modified HM approach has a lower outcome of energy consumption compared to VOHOP especially for larger depths. After comparing, the starting point of the selected estimation method (EST) is created. The comparison of the modified HM method and VOHOP is done by means of the simulation software OpenCLSim in Python.

To validate the accuracy of either VOHOP or modified HM, comparative material consisting of actual data provided by Van Oord is used. Multiple projects (20+) that have been performed by a trailing suction hopper dredger (TSHD) of Van Oord are analyzed after which three are selected. The selection is based on the amount of data available for a project and the difference in depth and distance, to use data that is suitable for comparison. After filtering out non-representative data (missing data points or too large time steps), the actual data is analyzed where a distinction is made between acceleration, free sailing and deceleration. Using the suitable data for comparison contributes to the actual data (ACT) part of this research.
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The selected actual data is compared with the modified HM approach for estimating energy consumption, which contributes to the DIFF part. For the free sailing part, a main finding when comparing the modified HM with the actual data is the deviation (lower estimation compared to actual data) for increasing depth estimations (analyzed for depths up to 60 m). A possible reason for this is due to the applied modifications for the modified HM approach that are observed to have less impact on the estimation for increasing depths with respect to the draught. However, estimates for limited depth also show a deviation as the results are more sensitive and show an asymptotic behaviour for which a correction is recommended. It is therefore concluded that the modified HM approach needs corrections for both estimating deeper situations as for situations with more limited depths. After analyzing the resistance components of the modified HM approach in different situations, consisting of different ratios of depth and draught, the reason for the large deviation in the modified HM method for deeper situations and the greater sensitivity for more limited depths is found in the contribution of the wave resistance term $R_w$. This is found out after comparing and determining the contribution of all resistance terms for multiple situations gathered from real time projects of actual data containing increasing depths and draughts. A correction to the wave resistance calculation is made using actual data, finding a fitting between increasing wave resistance for increasing vessel draught with respect to water depth. The result is a proposed HM method containing a less sensitive estimation method that takes into account the draught of the vessel related to the water depth for both deeper situations and shallower situations.

The acceleration and deceleration phases of the actual data are considered inappropriate for comparison with the modified HM approach, since the used power in the actual data contains the effect of slip, causing the vessel to use more power for reaching a certain velocity than actually required according to modified HM. Therefore, to improve the estimation of the acceleration and deceleration, a generalized fit is found in the actual data for the power in relation to time. This fit is generated for different ranges of depth and is coupled with the sailed distance to quantify whether the distance has any effect on the results. It is found that at a short sailing distance a significantly lower velocity is achieved, which in turn affects the power used. By taking into account depth and distance, an estimation fit results that takes into account a larger number of parameters (velocity, distance, depth and draught) than the VOHOP method, and is therefore expected to produce more accurate results. With the estimation fits created for acceleration and deceleration and the corrected estimation method, HM proposed, for free sailing, the outcome is a newly created estimation tool that is based on historical data.

The improvement of the newly developed estimation method is validated by comparing VOHOP and the new estimation tool with eight cases from historical data. The cases are selected at different depths and different distances and are found in the selected projects for this research. The results show an increase in accuracy for the acceleration phase, while the other two phases, free sailing and deceleration, show fluctuating results. The reason for the fluctuation in the free sailing phase is the difference in duration of the phase caused by the definition of acceleration and free sailing, where the new estimation tool considers part of the free sailing as acceleration. The results indicate that the power usage is more accurately estimated by the new estimation tool, which indicates that the fluctuations of energy estimates are caused by a miss-estimation of duration instead of power usage. For deceleration, the fluctuating results can be attributed to the fluctuating pattern of deceleration, which may be caused by external factors such as traffic or currents, making it difficult to predict the energy consumption for this part of the sailing phase. All in all, the new estimation tool exhibits greater accuracy for the overall energy consumption estimation compared to the current estimation method VOHOP. In addition, the estimation of power consumption during free sailing shows improvement, indicating that incorrect estimates of energy during free sailing are more likely to be caused by inaccurate estimations of the duration instead of inaccurate estimations of power.

In conclusion, the results show that when considering depth, distance and draught as input parameters and applying a data based correction, the accuracy of the estimation method increases. Where the results do show an improvement, it is recommended that further research be conducted on the estimation of energy consumption and sailing duration for acceleration and deceleration. Several assumptions were made in this study to simplify the analysis such as constant wave climate, where a follow-up study could verify these assumptions or even improve the results of the study by implementing additional consequences for these assumptions. Moreover, this study took into account a certain number of parameters and observed only one vessel type, where adding more parameters or considering more vessel types would give a clear picture of the reliability of the estimation method and energy consumption. A further study is needed to perform the same procedure of improving the estimation also for the other phases of a dredging cycle, since these phases do contribute to a large extent of the total energy consumption of a dredging cycle. Finally, using a larger amount of data for this study could reduce the uncertainty of the results and increase the reliability. In addition, an increase in the quality of the data further increases the reliability of the results.

Hydrogen is expected to be a significant force in this transition. Hydrogen can be produced using technologies that do not emit CO2 or other greenhouse gasses (“green H2”). Hydrogen can be transported in big quantities and long distances unlike electricity and can play the role of a clean fuel. The emerging hydrogen economy, which will be accompanied by the gradual phase-out of fossil fuels, will significantly impact ports around the world. Ports can and should play a pivotal role in this “energy revolution”. Apart from import and export services, ports often include industrial clusters, they provide servicing and refuelling to visiting vessels and connect major trade routes.

This study aims at understanding and providing insights on challenges that the above-explained transition will create in a port environment focusing on hydrogen. Firstly, a favourable policy environment for hydrogen projects in the ports and maritime sector is a key topic that this study will address. This is included as a conclusion in many reports and port conferences. Secondly, the questions related to terminal planning and area requirements of hydrogen terminals remain unanswered as large scale hydrogen projects do not exist yet -with many being under development-, and thus this research will try to shed light on area calculations of hydrogen terminals. Thirdly, and lastly, terminals operators, investors and policy makers will need to make decisions on the preferred hydrogen carrier and location for various hydrogen projects that will be developed in the near future. Therefore, a method of comparison of different alternatives is required, especially when terminals are planned next to existing liquid bulk terminals.

Ecosystems are under pressure worldwide, due to both natural and anthropogenic stresses. Stresses on ecosystems can cause a decline in biodiversity, a loss of habitat and a deterioration in ecosystem services. To avoid further pressure on ecosystems caused by advancing economic development, new infrastructure projects should be integrated into the ecosystem. Environmental Impact Assessments (EIAs) are now mandatory for projects that are likely to have significant environmental effects. EIAs have primarily focused on mitigating negative impacts. However, recently new design philosophies have emerged such as ‘Engineering with Nature’, ‘Working with Nature’ and ‘Building with Nature’ which also focus on promoting positive impacts.
Constructively realizing nature-inclusive projects is complicated due to involving stakeholders with dif-fering perspectives. Therefore, in an integrated approach towards new marine infrastructure devel-opment, the next step is to promote constructive collaboration between stakeholders to systematically investigate the nature-inclusive potential of infrastructure. This thesis describes a proposed strategy for doing so, within the context of nearshore infrastructure development located in or nearby coral ecosys¬tems. The focus is on how nature-inclusive potential of new marine infrastructure might be maximised, taking into account the local ecosystem.
The aim of this research is to find an optimal approach to develop coral-inclusive infrastructure. This is done by structuring the required discussions between stakeholders considering socio-economic, ecolo¬gical and engineering perspectives regarding the nature-inclusive design potential of new marine infra¬structure. For this purpose, a method was developed that proposes a step-by-step strategy to promote constructive collaboration between relevant stakeholders, consisting of the following five steps:

1. project description, outlining the basic challenge at hand

2. project location analysis, involving a systematic assessment of the relevant ’natural system’ as well as the ’anthropogenic system’

3. Development of marine infrastructure design applications, involving an inventory of project ele­ments that can have negative or positive effects on the overall ecosystem

4. inventory and ranking of potential measures, objectively outlining feasibility and potential effect­iveness of measures and design modifications

5. summary of sustainable design recommendations, leading to a systematic ranking of potential measures proposed to support further decision making.

We have investigated the effectiveness of the systematic method, by applying it to a case study in Sint Eustatius that investigates whether the intended extension of a breakwater in Sint Eustatius can be designed as a coral-inclusive project. Sint Eustatius was chosen because Rijkswaterstaat offered research opportunities on location. In an ideal case, the use of long-term consistent data maps the nat¬ural factors over a longer period of time. This provides greater certainty of results and recommended actions. However, the values that were reported for the Sint Eustatius case were not derived from long term systematic data collection. Furthermore, the substrate from the existing breakwater looks to be promising for coral recruitment. However, there is not a lot of coral development evident on the existing breakwater. Possible negative factors hindering coral development on the existing breakwater are: 1) poor water quality; 2) high hydrodynamic circumstances with high wave action in shallow waters which limits the type of coral species; 3) inconsistent larval supply through ocean currents.
Coral reef connectivity seems sufficient and potential substrate is already present in the existing break¬water. Extension of the breakwater will lead to substrate increase which could improve the chance for coral recruitment in a hurricane-risk area as Sint Eustatius. A valid next step that could be proposed to aid a better understanding of this habitat is to invest in an extensive and dedicated data gathering campaign.

In conclusion, the main improvements derived from the application of the systematic approach for nature-inclusive potential for infrastructure projects are:

·  providing an overview of the steps required to create coral-inclusive infrastructure,

·  instigating the investigation of the status or the possibilities for coral development,

·  assisting ecologists and engineers to structure the discussion on coral-inclusiveness,

·  lowering the barrier to use (new) design philosophies,

·  and stimulating coral development and decreasing negative effects by providing design recom­mendations.

Bringing stakeholders with different perspectives together in one nature-inclusive project plan remains challenging. Environmental data can play a role in arriving at a realistic approach supported by ecolo­gists and civil engineers to realize nature-inclusivity for infrastructure. This requires knowledge, money and time and could provide insight into the threats and opportunities. The systematic approach, derived in this thesis, has been proven to support stakeholders in assessing the nature-inclusive potential of marine infrastructure.