In 2019, the Dutch nitrogen crisis emerged after the Dutch legislation on nitrogen pollution (PAS) was dismissed by the Dutch Raad van State. The crisis resulted in large scale demonstration by farmers and lingering uncertainty in the Dutch business sector. From an ecological perspective the current policy approach is limited as it focusses primarily on reducing the inflow of nitrogen to Natura 2000 areas. Widening the policy approach to better represent the ecological side of the nitrogen crisis provides alternative ecological solution avenues to resolve the crisis. To this end, a System Dynamics model is constructed that encompasses the nutrient cycles of N and P, as well as a level of ecological complexity. To investigate the model’s behaviour under circumstances of deep uncertainty an Exploratory Modelling and Analysis (EMA) approach is used. The results indicate a large potential for cost reduction and increase of ecological performance by aiming policy at ecological compensation instead of emission reduction. The implementation of ecological measures requires scientific substantiation to be accepted into the regulatory framework. The potential economic and societal benefits of an ecological policy approach should be a strong incentive for policy makers and scientists to develop the empirical knowledge for ecological engineering.

Different leader-follower behavior may be observed in models, such as group gathering, backtracking, and flexibility of the group. However, a comparison of these behaviors resulting in possible substantially different estimates of optimal evacuation procedures is lacking. Hence, we developed an Agent-based model in combination with exploratory modeling to compare backtracking, group gathering, and the possibility to change to another leader and investigate their influence on the evacuation and response time to receive a robust result. The results showed that backtracking and flexibility of the group increased the evacuation time. Whereby group gathering impacts the response time. In addition, the combination of behaviors increases the influence on evacuation and response time. Further research needs to test these results with empirical studies. Furthermore, the impact of other leader-follower behavior needs to be investigated.

To provide insight into factors that play a role for DT in the humanitarian sector, a combination of literature and expert interviews was used to identify relevant criteria for the humanitarian sector. In accordance with prevailing literature, these factors have been categorised in people, process and technology factors. People factors include leadership, human resources, culture, organisational structure. Process factors were: alignment operations & IT, long term commitment Management, long term commitment network, long term commitment donor, crisis response, Legal issues. Finally, technology factors included both data and digital. The identified critical DT factors were translated into an assessment framework making use of the CMMi Maturity Model approach. For each factor and maturity level combination, there is an explanation of what a humanitarian organisation has to comply with, before advancing to the next level. This ensures that national societies can generate an overview where they currently are and what steps to take to advance. To adequately deal with the barriers and increase practical applicability of the framework, separate barrier-overcoming-strategies have been formulated.

In 2020, the world was hit by a global pandemic through COVID-19, causing millions of deaths worldwide. The last two years proved that a health-related crisis like COVID-19 strains us as a society and the capacities of health systems worldwide. Severe infections of COVID-19 require higher capacities of hospital beds, ICUs with ventilators and Personal Protective Equipment. For health systems, the question arises of how to secure enough PPE and ventilators before and during a health-related crisis like COVID-19. This research explores how health systems can create responsive and prepared supply strategies to meet the rising demand for critical medical supplies during health-related crises. Concerning the availability of critical medical supplies, preparedness entails stockpiling as a supply strategy. Furthermore, preparedness entails actions decision-makers in health systems can take to increase the effectiveness of responsive supply strategies. Responsiveness refers to supply strategies used at the beginning of a health-related crisis in the short term. Responsive supply strategies include ramping up domestic production, supporting innovations, loaning medical supplies, and purchasing medical supplies from the world market or through direct tender. In this research, a System Dynamics model was developed to explore how health systems can create resilient and responsive supply strategies, a System Dynamics model was developed, focusing on the English health system as an example for the Global North. Given the deep uncertainties surrounding the supply chain of critical medical supplies, Exploratory Modelling and Analysis was conducted to identify candidate policies and explore their performance given the uncertainties. Specifically, uncertainties affecting the success of purchasing supplies through direct tender and from the world market had the most impact on the availability of PPE and ventilators. The results of the analysis and the findings in the literature provide the following recommendations to decision-makers in health systems to create prepared and responsive supply strategies that ensure the availability of critical medical supplies during health-related crises. Decision-makers can implement (i) stockpiles exhibiting higher inventory levels than recommended, and no delays concerning the operation within the warehouse or the delivery of the medical supplies. Furthermore, it is suggested to (ii) implement diverse supplier frameworks and crisis frameworks, (iii) diversify supplier, (iv) implement stocks of raw material for domestic production. It is useful for decision-makers to apply several responsive supply strategies simultaneously. Furthermore, health systems can further investigate additional supply strategies. In this research, it is assumed that collaboration is not relevant nor of interest for the English health system. Hence, it would be interesting to explore the effect that sharing critical medical supplies between national health systems could have on the shortage of PPE and ventilators in the future.

Vehicle automation has the potential to disrupt the status quo of urban transportation, because it adds a new mode of transportation by taking away the task of the driver. The projections of estimations of the impacts of this new technology are based on many uncertainties and are thus largely unknown. A literature review showed that a wide number of effects is possible with automated driving and that no straightforward method to assess future impacts of this new technology exists yet. This thesis developed a method that provides insights into the impacts of vehicle automation in urban areas, without preconceived ideas about the impacts of the different scenarios. Existing knowledge from literature, transportation and land use data, and sociodemographic information were combined in a geographically disaggregated System Dynamic model. This model explored the effects of vehicle automation on the performance of the transportation and spatial system of the case-study city of Copenhagen, Denmark. Different model runs provided insight in the possible range of outcomes. Considerable problems may arise in the transportation network with the introduction of automated driving because, using the car might become very attractive. A city’s land use does, however, not change as much as many could expect. The causes of (un)desirable outcomes were identified with the Patient Rule Induction Method. The ranges of uncertainties in the value of time in an automated vehicle and in the level of adoption of car-sharing were found to influence desirable versus undesirable futures the most. Mitigating measures should focus on these scenarios to prepare for a future with automated driving.

EPA: Multi-Modelling for Complex Challenges With the acknowledgement of international grand challenges, the demand for better and ever more complex models is likely to increase a manifold. Where single models may no longer be able to grasp the complexities of a system, multi-modelling (Nikolic, Warnier, et al., 2019; Vangheluwe, 2000) enables the combination of the strengths of different models whilst enabling the development of multi-perspective insights. In this research, I developed a multi-model to provide policymakers in The Netherlands with insights on how to steer the Urban Energy Transition at both national and municipal level. This is done by combining a System Dynamics (Forrester, 1961) model for evaluating market behaviour at the national scale, and an Agent-Based Model (Epstein & Axtell, 1996) for investigating investment behaviour at the neighbourhood level. The results from experiments with this model show that multi-perspective insights can be very helpful in designing policies and strategies for dealing with Sustainable Urban Development. It is found that challenges concerning the conceptualisation phase of the Model Development Cycle, could turn out to be opportunities for model development. As formalism selection and possible overlapping scales between models requires extra effort and attention, this attention results in model concepts that will be better evaluated, resulting in better concepts to be developed altogether. The main challenge that is currently unresolved, is that of the computational performance of multi-models. Although worsened by the choice for Agent-Based Modelling as one of the formalisms used in the multi-model, the computational requirements for the simulation seriously hamper the opportunities for experimentation and analysis. Although solutions can be found to minimise the computational demand or the effects of it, improvements are required in either computational demand or processing supply, for multi-models to become a suitable method for common modelling and simulation practice. CME: Energy Transition in the Built Environment With the EU goals (European Commission, 2018b) to reduce CO2 emissions to zero tons in 2050, The Netherlands has set up a climate agreement (Klimaatakkoord, 2019) in which municipalities get a leading role in reducing the carbon footprint of the Built Environment. To realise these goals, an energy transition is inevitable and strategies need to be developed for remodelling neighbourhoods into sustainable living environments. Before the end of 2021, municipalities have to come up with a plan in which they decide what neighbourhoods will be transformed and when. A problem in this is that currently, municipalities do not have the resources and tools to do so (RTL, 2019; Schuttenhelm, 2020; Straver, 2019). Currently, existing models, such as the Vesta MAIS model (Planbureau voor de Leefomgeving, 2019c) offered by the national government, are missing two crucial aspects which should help municipalities to set up their strategies: time dynamics and population dynamics. The techno-economic approach does present the ’best’ solution but is missing how to get there. Next to this, uncertainty around national policies makes that it is very difficult to decide on a robust policy. To deal with the aforementioned challenges, I use a multi-modelling approach (Nikolic, Warnier, et al., 2019; Vangheluwe, 2000), using System Dynamics (Forrester, 1961) and Agent-Based modelling (Epstein & Axtell, 1996) in which on the one hand, the time dynamics and population dynamics aspects are incorporated, and on the other hand multi-perspective insights on effects of national policies on national goals as well as insights on the heterogeneous effects at the municipal level are provided. An important finding is the crucial role of a CO2 tax on the realisation of national goals. Without this tax, homeowners and housing corporations will not be motivated sufficiently to significantly invest in insulation measures, making that fewer alternative heating systems will be implemented. Next to this, it is found that major differences can be distinguished between rural and urban areas. Heating grids will be a viable starting point for urban municipalities to start their transition due to the availability of residual heat. For rural municipalities, this will be more difficult due to a dependency on low-temperature systems. There, starting with the neighbourhoods that have the most potential to insulate is advised.

Celsius or 1085 GtC. This thesis explores this significance and points toward prioritizing ecosystem conservation as a highly effective strategy for mitigating climate change. Initiatives such as carbon offsetting, performed by organizations like ‘8 billion trees’ and ‘cool earth’, could provide feasible solutions to enhance carbon sequestration. The EU's Nature Restoration Law is a step in the right direction, advocating for the conservation of existing ecosystems and restoring deteriorated systems, specifically increasing organic stocks in forests and restoring and rewetting drained peatlands of agricultural use and peat extraction sites seem to be compelling aspects in terms of improving the carbon system proposed in this law. I encourage the exploration of similar policy changes globally, underscoring the importance of taking immediate action and ensuring no further deterioration of existing terrestrial carbon systems. Following the importance of terrestrial carbon storage, the debate remains about who should sacrifice their land. This research has displayed a high sensitivity in land allocation for terrestrial carbon storage when comparing ethical perspectives of justness, also defined as climate justice principles. This sensitivity can be seen as normative uncertainties and represent potential tensions in developing a coherent global policy. In my research, certain countries are more sensitive to these normative uncertainties than others. The Netherlands, Pakistan, China, and Yemen are highly sensitive to terrestrial carbon storage obligations if islands and smaller states are not considered. In the case of the Netherlands, this sensitivity is caused by a high GDP and, therefore, ability-to-pay. Still, when following efficiency prioritized, Dutch agricultural land should be kept for its high agricultural productivity. China is expected to reach a high level of domestic food security. Therefore, they would have to sacrifice their land for terrestrial carbon storage according to a different interpretation of ability-to-pay. Also, the efficiency prioritized principle for China would be ideal because, with their economic growth and innovation, they are expected to reach a high level of agricultural productivity. In the case of Yemen, it is different, Yemen has low agricultural productivity, and efficiency-prioritized will lead to them converting agricultural land to forests. The best interpretation of ability-to-pay for Yemen is the available land that could be converted for terrestrial carbon storage. In my analysis, I showed proof of principle to include these normative uncertainties in policy analysis to explore areas of consensus. Through this approach, I found countries that should convert or conserve their land for terrestrial carbon storage and countries that arguably could still replace their forests and wetlands for other land covers such as urban- and agricultural land. I propose that climate justice principles should be included as uncertainties in policy-analysis, thus arguing for – additional – simplified models to allow for easy implementation of these uncertainties in the analysis. To come to these findings, I performed an extensive analysis of the global food-, land cover-, and carbon system, simulating a wide range of scenarios up to the year 2100. The model I have developed operates at a national-detail level and includes 173 countries worldwide. The model considers several factors for each country, such as socioeconomic development, current land cover, agricultural productivity, and food demand. The national systems interact globally to represent global systems such as food change and the carbon cycle. I tested a wide range of distribution methods on this system for terrestrial carbon storage burden, represented by five policy levers. Additionally, I considered 21 uncertainties in the model and performed 10.000 experiments to ensure the robustness of the proposed policies. In the last phase of the analysis, I created world maps that display the land countries should convert for terrestrial carbon storage according to climate justice principles and the sensitivity per country. These maps allow for an easy understanding and interpretation of the climate justice principles. I started the research by exploring frequently used climate change policy evaluation in ethics. Ethics literature discusses two main social justice types: distributive and procedural justice. In this study, I focus on distributive justice for its applicability in modelling solutions. I utilize pre-defined climate justice principles and introduce a new principle – efficiency prioritized, based on the utilitarian principle. The ‘principle efficiency prioritized’ allocates agricultural land to countries with the highest agricultural productivity and terrestrial carbon storage burden to the less-productive countries. Selected principles are Ability to Pay (based on available land for terrestrial carbon storage, domestic food supply, and GDP per capita), You-Broke-It-You-Fix-It (based on historical emissions), and Efficiency Prioritized, with different interpretation methods considered for Ability to Pay. I modeled the system using Vensim, a System Dynamics modeling software. System Dynamics is a quantitative modeling formalism suitable for dealing with complex systems, allowing for exploring relations between system structure and behavior. It helps to understand the complex land use, land-use change, and forestry, food, and carbon system. It also enables the incorporation of parametric and structural uncertainties, testing a wide range of scenarios in systems with deep uncertainty. The model consists of several sub-systems, leveraging existing models from prior research by Auping (2018), and takes data from sources such as the World Bank, FAOSTAT, OECD, and IPCC as input. To find robust policies in the face of deep uncertainty, I adopted an Exploratory Modelling and Analysis (EMA) approach using the open-source EMA workbench for Python. This approach involves performing a broad range of computational experiments, analyzing the results, and identifying robust policies based on these findings. EMA workbench has a special connection built-in to run experiments with Vensim efficiently. It includes built-in functions for sampling, such as Latin Hypercube Sampling, and scenario discovery, such as PRIM, used in my analysis to find the scenarios of interest. I visualized the results with Basemap, NumPy, Pandas, and the EMA workbench, among other tools. Creating maps allows for a simple data representation, enhancing understanding and communicating the findings. This approach enables a thorough exploration of climate justice principles, modeling, and experimentation, providing valuable insights for decision-makers facing complex and uncertain climate change challenges. To summarize, I applied System Dynamics modeling and scenario discovery to explore the global food and carbon system. I proved the importance of terrestrial carbon storage, especially conserving existing forests and wetlands. Terrestrial carbon storage policy also faces policy challenges in implementation, mainly the distribution of the terrestrial carbon storage burden. Because land for terrestrial carbon storage goes at the cost of agricultural and urban land that could provide economic prosperity and food security, there is a trade-off between different Sustainable Development Goals. Several distribution conventions have been evaluated following climate justice principles to find overlapping policies between the principles. I found a significant difference in the distribution of terrestrial carbon storage obligations between the principles, displaying potential complexities and tensions in policy-making. I also found consensus between the principles, defined as non-discriminatory policies. Policy-makers should start with non-discriminatory policies to ensure swift implementation. I recommend that other policy modelers also include ethical perspectives as uncertainties in their models to find non-discriminatory policies and, if necessary, develop simplified models to enable this.

In this thesis, the System Dynamics (SD) model of the Full Reserve Banking (FRB) system built by Van Egmond and De Vries (2016) has been reviewed and improved. The improved model is used to see the effect of FRB system in preventing a long-lasting recession as one occurred in 2008. FRB system is a monetary reform which attempts to separate private banks’ monetary and credit functions. Under FRB system, central bank creates money depending on the price level. Therefore, theoretically, FRB system can prevent recessions by maintaining the price level constant. Van Egmond and De Vries have modeled FRB system using System Dynamics (SD) modeling technique. However, their model has a few model problems which reduce reliability of the model; Ⅰ) the model crashes in different conditions, Ⅱ) the model is based on some assumptions that are less realistic or logical Ⅲ) the measurement units of the model are not specified. In this thesis the solutions for these model problems were sought through a model review and desk research. In the original model, high house prices and debt level are a direct and definite reason why the recession begins. Households default because house prices went up too fast and they could not afford the debt repayment. However, in the improved model, households default because their wages are stagnated. Households default when wages are stagnated while debt level grows high. In both original model and improved model, FRB system successfully protects the price and wage level. Under FRB system, the probability of recession decreases significantly. However FRB system is found to be not effective in stabilizing the price level when the firms’ dividend payout ratio is high. Furthermore, FRB system was not necessary as households do not default when the firms’ dividend payout ratio is low. The reason that FRB system’s effectiveness is decided by dividend payout ratio is because the model was calibrated originally with dividend payout ratio of 100% which is unrealistic in the real world. Therefore, the model is expected to be calibrated properly especially focusing on dividend payout ratio in a future work. Furthermore, it is recommended to include trades with other countries in the model in further work.

In the military field, detailed simulation models are often used to get insight in the consequences of choices regarding the composition of a force and the extent to which it can be kept deployable. With detailed models, the main idea is to capture all real-world complexity relevant for decision-making processes. However, detailed models tend to be ‘bad’ in the evaluation of uncertainty in a system. This can be problematic, as the outcomes of detailed models usually depend on numerous dubious assumptions that are too buried to be understood by hand. As simplified models can better cope with uncertainty, this study examined the combined use of a detailed model and a simplified model (this approach is also known as ‘multi-resolution modelling’) to improve the robustness of a naval force support system. In order to work with models with different levels of detail, an existing detailed model that reflects certain elements of the force support system of the Dutch Royal Navy is used to develop a new simpler model. The key takeaway of this study is that multi-resolution modelling can be considered useful as the detailed model and the simplified model were found to be mutually dependent in their design, validity, and use to improve the robustness of a naval force support system. As the detailed model contains a more accurate depiction of the system of interest, it formed together with a set of aggregation functions and cross-validation tests the basis for the design and validity of the aggregated model. The detailed model also remains important for the evaluation of the real-world effectiveness of promising ‘high-level’ actions discovered by the simplified model. Vice versa, by means of exploratory analysis, the simplified model revealed some potentially problematic assumptions in the detailed model which has implications for its design and validity. Also, the simplified model gave insight into (a) problematic scenarios that lead to a low sailing availability, (b) patterns in the robustness of policies across different usage profiles, and (c) potential leverage points to increase the robustness of the naval force support system. This study concludes with a number of scientific research recommendations involving challenges in strong consistency and the composability of models at different levels of detail.

Since the conception of the euro, it has often been suggested that the eurozone start a programme of jointly issuing government debt. There are many arguments for these so-called Eurobonds, and temporary issuance of them has already taken place in response to the economic impact of the recent COVID-19 pandemic. However, a permanent Eurobond programme remains a controversial topic within the EU. Advocates claim that a Eurobond programme can facilitate economic growth and stability for the entire eurozone. It could offer much-needed fiscal space to some of the eurozone’s most heavily indebted southern economies, by decreasing borrowing costs. It is assumed that the extra growth facilitated in these countries will spill over to the rest (mostly the less indebted north) of the eurozone, through increased cross-country trade and investment. Criticism mostly originates from the more financially sound eurozone member states, which fear a situation of moral hazard that leads to uncontrolled spending, and a possible deterioration of their own creditworthiness. This research attempts to explore the economic effects of the introduction of Eurobonds on the eurozone economies. For this effort, two distinct types of Eurobonds are identified and analysed: unlimited Eurobonds and Blue Bond Eurobonds, with the former allowing unlimited issuance of mutualised debt, and the latter restricting this to 60% of a country’s GDP. The economic sub systems that are crucial for explaining the dynamics relevant to this study show a high degree of complexity and uncertainty; whether it is the dynamics of debt management (including stocks, flows, delays and feedback mechanisms), the different ways of determining bond yields (these are structural uncertainties), or the magnitude of economic elasticities/sensitivities (these are parametric uncertainties). These system characteristics stress the need for a simulation modelling approach. Because the interactions between the system’s components and the relative importance of certain elements are of interest, and because the results should be insightful to non-technical policy-makers, a transparent, ‘white-box’ model can provide the most meaningful results. For these reasons, a system dynamics model has been developed for this study. Specifically, an exploratory system dynamics modelling and analysis approach is used, due to the inherent structural and parametric uncertainties related to the system that have to be accounted for. Through exploratory experimentation with this model, the effectiveness of both Eurobond policies has been assessed based on how they affect eurozone and country-specific GDP, interest rates, and debt levels. All experimental results are robust for the different structural and parametric uncertainties identified in the system; multiple methods of determining bond yields taken have been into account, just as a large number of configurations of the parametric uncertainties. As for the economic growth facilitated by both Eurobond policies, the country-level results are mostly insignificant (i.e., not more than 0.50% additional GDP growth after 10 years). Only slight increases in GDP are observed for both policies, with the benefits not evenly distributed amongst member states. Southern, more heavily indebted economies have more to gain, due to the larger relative decrease in their borrowing costs, assuming that the additional funding is spent productively. Furthermore, the anticipated positive economic spill-over effects caused by increased cross-country trade and investment (and not attributed decreases in interest rates) are shown to be insignificant as well. ii However, the results of the analysis do indicate that both unlimited and Blue Bond Eurobonds have the potential to offer significant benefits to the eurozone’s economic stability, by reducing borrowing costs for all participating countries. As anticipated, it is again mostly the heavily indebted southern economies that benefit from this. Unlimited Eurobonds offer slightly more benefits to these countries, when compared to Blue Bond Eurobonds. However, the latter is the preferred option for the less indebted north, since it restricts debt issuance and subsequently prevents Eurobond yields from surpassing their current borrowing costs; something will eventually be the case with unlimited Eurobonds. Based on this study’s results, a recommendation is made to start the implementation of (a variant of) the Blue Bond Eurobond policy. It has the potential to significantly increase the eurozone’s public debt sustainability, while also offering minor (mostly insignificant) growth benefits to the heavily indebted southern member states, without deteriorating the creditworthiness and the fiscal position of the other, northern member states. Furthermore, the existing market pressure for prudent fiscal behaviour is maintained in the Blue Bond Eurobond proposal, mitigating the risks of moral hazard feared by critics of debt mutualisation. Additionally, it is necessary to set up an adequate legal and political framework that incentivises fiscal discipline and does not allow for free-riding behaviour. A transfer of fiscal sovereignty to the EU level is to be a requirement for participation in the Eurobond programme. This is necessary to build confidence in the system, both for the eurozone member states, as for the capital markets and the general public. It is further deemed sensible to include a legal clause in the Eurobond programme that allows for the suspension of individual member states’ participation. The (budgetary) conditions for such a clause to be invoked, and the potential (financial) penalties associated with this remain to be decided upon by the eurozone member states and the EU’s (to-be erected) fiscal and monetary institutions. Keywords: Eurobonds, Bond yield determination, Debt sustainability, Macroeconomic analysis, Policy analysis, Exploratory Modelling and Analysis

For centuries humanity has been engineering the second largest river system in the Netherlands, the river Meuse system. This resulted in improvements for the shipping and water safety functions, but simultaneously has had a negative impact on other functions of the river Meuse system. Nature and water quality, for example, degraded due to the construction of dikes, weirs, locks, bend cut-offs, summer bed mining and floodplain reduction. Additionally, climate change is affecting the fresh water availability due to low river discharges in combination with little precipitation in dry periods. On top of that, weir leakage and levelling of ships lead to water loss, which amplifies the fresh water availability problems even more. What the future might bring is deeply uncertain, however, the current problems are expected to grow larger due to influence of climate change and socio-economic developments.With the upcoming task to replace the hydraulic structures (weirs and locks) in the Meuse river, a unique opportunity arises to improve the problems that the river Meuse system experiences and prepare it for future developments. Replacement strategies need to be developed and tested on the system. Traditionally separate models will be constructed to simulate shipping, nature, water quality and hydraulics. They tend to be complex and computationally heavy and more often than not, these models make predictions based on a small set of the most probable scenarios. However, in the rapidly changing times of today, these scenarios are often not sufficient enough to account for the highly uncertain future. Therefore, in this thesis, one model is constructed containing the multi-functionality of the river Meuse system which is tested on a broad range of future scenarios to test replacement strategies for the hydraulic structures. MethodologyRobust Decision Making (RDM) is used to explore replacement strategies from a multifunctional perspective and evaluate them based on their robustness. RDM is a method which helps making decisions that lead to the construction of a robust system without making predictions and a system is robust if the applied strategy performs satisfactory under a wide variety of future conditions. RDM works with four steps, first the river Meuse system is modelled in the system dynamics software Vensim. This Meuse Model consists of submodels that simulate: the flow of water, the flow of shipping and the performance of the functions water quality, fresh water availability and the shipping load on the locks. All functions are therefore assessed in one model. The second step explores the behaviour of the current system by analysing the performance of the functions under future scenarios (i.e., combinations of future uncertainties). To cope with the deep uncertainty of the future, the probability of occurrence for each scenario is assumed to be uniformly distributed. Thirdly, design options are developed based on the vulnerabilities of the current system and combinations of design options form replacement strategies. In the fourth and last step, the replacement strategies are applied to the system in a policy analysis, after which the design options are evaluated based on their robustness. Exploration of the current systemExploring the current system behaviour over a variability of plausible futures demonstrates that in some scenarios problems arise for the functioning of the system. The performance of the fresh water availability is in general robust. The river Meuse system is designed to maintain a specific water level to provide for shipping. However, especially in weir section Grave, which contains outflow to the river Waal and a relatively large leakage of the weir at Grave, fresh water availability problems occurred during extreme drought events. In approximately 18% of the runs, the fresh water availability was smaller than full capacity. A scenario discovery revealed that several uncertainties have crucial impact on the undesired performance of the fresh water availability. It is found that leakage of the weirs and certain dry discharge years are influential uncertain input variables that cause problems for the fresh water availability.The water quality in the weir sections of the river Meuse reaches for most of the runs risky or undesired behaviour. The weir sections Linne, Grave and Lith are the most vulnerable because the weirs in these weir sections maintain relatively large water depths. This results in low flow velocities and therefore high risk for algal and cyanobacterial blooms and low diffusivity of toxic substances. For the intensity of shipping, two future scenarios are composed under socio-economic developments. The first leads to a slight increase of ship intensity and the second one leads to a slight decrease of ship intensity in the coming decades. Most of the locks seem to be able to cope with this change. Only the lock at Grave might experience issues as it contains the smallest and least amount of lock chambers in the corridor. For approximately 30% of the runs, the intensity to capacity ratio of the lock at Grave took either risky or undesired levels (>0.5). Formulating replacement strategies Based on these findings, a number of design options are formulated with the main goal to improve the robustness of the fresh water availability. Robustness performance of other functions, however, should not deteriorate, and preferably improve by applying the design options. Weir section Grave is used as main focus for improvement as this weir section is most vulnerable for future scenarios, and improvements will therefore have the largest impact. The design options are: •Installation of pumps (all weir sections): limit the outflow of water in dry periods•Heightening crest levels of the weirs at Grave or Lith: increase buffer capacity•Relocating the weir at Grave in upstream direction: increase the average water depth •Dynamic crest level (all weir sections): temporarily increase buffer capacity in drought periods•Efficient locking (all locks): limit the daily outflow of water in dry periods by imposing a minimum amount of ships that need to enter the lock chamber before starting the locking cycle Analysing the replacement strategies Combinations of design options are made to form replacement strategies, which are now applied to the system. All design options lead to improvement of the fresh water availability for weir section Grave. By introducing efficient locking, however, the intensity/capacity value of the lock at Grave increases compared to the current system for more than 80% of the runs. Raising the crest level of the weir at Grave leads to a decrease of flow velocity, and therefore water quality, for approximately 80% of the runs. Changing this to a dynamic crest level results in a decrease in flow velocity for approximately 25% of the runs, which is significantly less. By relocating the weir at Grave, the robustness of the fresh water availability in weir section Lith is slightly reduced and the ship draught downstream of the weir at Grave is at risk. To increase the water depth and remove the risk of insufficient ship draught, the crest level of the weir at Lith is raised. However, an increase in water depth leads to a decrease in flow velocity and therefore water quality. Installing pumps creates the largest robustness for freshwater availability, does not induce any deterioration for the other functions and is therefore seen as best performing replacement strategy. ConclusionThe research implemented a general robust decision making method to analyse complex systems and applied it to the replacement of hydraulic structures in rivers. Thereby it has shown how various design options can be evaluated for multiple functions and under uncertain future scenarios. This approach can be used to select design strategies that perform well under a broad scope of future uncertainties and thus make the system more robust. However, the model and tools used in this thesis also know many limitations. Costs, for example, are left outside of the scope of this thesis but is expected to have a large impact on the decision making process. Furthermore, potentially better fitting methods such as Many Objective Robust Decision Making or Dynamic Pathways are available to analyse replacement strategies. Because of these limitations, the results from this study can be seen as a first interpretation and setup for further research.

The Netherlands is subject to labour scarcity across a variety of industries. While labour scarcity has occurred in the past, only now the consequences of higher educational attainment have become prevalent in the Netherlands. Due to a shortage of vocational workers and a population that is getting older, circumstances ask for adequate policy-making. Although policies like increasing the formal retirement age are put in place to negate labour scarcity, it remains difficult to understand the long-term outcomes of policy implications made in the present. Understanding this long-term behaviour of the dutch labour system is deemed useful to develop strategies that result in a well-functioning labour market. Since the labour market is intertwined with other systems (e.g. population, educational system and the economy) and is subject to uncertain future developments it results in increased complexity of understanding long-term dynamics. This research aims to develop a better understanding of the long-term behaviour of these systems in deeply uncertain futures.

Acceleration of the energy transition requires increased mining of materials. An important material for the energy transition is nickel, used in the stainless steel required for all energy infrastructure and an important component for both stationary batteries and batteries used in electric vehicles. Previous research has been done on the global nickel requirements for the energy transition at a high level of aggregation. In this thesis, exploratory system dynamics modelling and analysis was used to assess the resilience of the nickel supply chain and its nexus with the energy system at the level of individual mines. The development of the global nickel supply chain, and its energy requirements and greenhouse gas emissions, was modelled and explored between 2015 and 2060 under different disruption scenarios, sustainability policies and uncertainties. A nickel demand of 6 - 18 million tonnes per year is projected by 2060 for the BAU scenario, with projections up to 38 million tonnes per year in the scenarios that aim to limit global temperature increase to 1.5 °C. The main contributors to this large demand are electric vehicle batteries. The nickel system is conditionally resilient to the energy transition, given sufficient exploration and annual capacity increase. To increase the resilience of the nickel system, policies that support innovation in battery material composition and lifetime and good end of life waste management of batteries can play an important role. Modelling the nickel supply chain at mine level leads to different behaviour compared to previous research where mines were aggregated. Insights obtained from the detailed modelling in this thesis include a higher demand than previously projected; the possibility of the average ore grade increasing over time as mines with lower ore grades are decommissioned; average final energy requirements that can decrease, increase or increase rapidly depending on a varying average ore grade, a varying composition of processing methods and a varying composition of by-products; average energy costs that differ depending on the projected electricity mix in the countries containing deposits; and a reduction in end of life nickel recycling rate for most scenarios due to an increasing share of batteries. The most important contribution of this thesis is not in the data and assumptions, but in the model itself, which can be adapted and refined in further research, where more stakeholder input is included, to make the outcomes more robust and useful for decision making. Other important avenues for further research include determining how much exploration is possible and how quickly mining capacity can be increased.

These days, technological progress and automation are widespread, but productivity growth and thus overall economic growth lags behind. There is a strong conviction that the declining growth rates are caused by a shortfall in aggregate demand. This shortfall in aggregate demand might be due to the development of a ‘dual economy’. A dual economy is an economy in which a limited number of economic activities experience high productivity growth rates due to automation and technological progress (progressive sector), meanwhile the remaining economic activities experience almost no productivity growth because automation is barely present (stagnant sector). A dual economy develops due to unbalanced economic growth between the progressive and stagnant sector. To assure stable economic growth, it is important to slow down unbalanced growth. However, until today it is not known how to effectively target unbalanced growth, because the driving factors are not well known. This research tries to improve the understanding of unbalanced growth by finding the driving factors behind unbalanced growth. A macroeconomic modelling methodology is used to achieve this objective. Conclusions that provide information about which factors drive unbalanced growth, and how these factors should be influenced by policy makers to slow down unbalanced growth and stimulate stable growth are provided.

The COVID-19 pandemic has changed travel behaviour and mobility in the Netherlands. It is questioned if the mobility system is subject to long-lasting change in the near and distant future. This study aims to observe the development of mobility impacts over time with a quantitative approach. Current traditional transport models have difficulties implementing uncertainties such as the mobility disruptions of COVID-19. These models lack the exploratory nature to cope with quickly arising events and changes. Using system dynamics, a model is developed to observe the mobility impacts of disruption and trends in transportation. The developed model and alternative transport modelling approach are tested and validated by applying the case of the COVID-19 mobility disruptions in the Netherlands. By including a tele-activity alternative in the mode choice component of the model, an option not to travel is modelled as a contender to the traditional modes of transport using choice models. Subsequently, applying the model to the COVID-19 situation provided insight into new relations and understandings of the development of the mobility impacts over time in the near and distant future. It was found that the future attractiveness of modes of transport changes as a result. Travellers' preference for private modes of transport will remain high in the forthcoming years, causing public transportation to recover slowly. It can be concluded that the system dynamics modelling approach is beneficial and has accomplished the design of a model widely applicable to COVID-19 and other mobility disruptions.

Over the last decades, the world population has grown vastly and the percentage of people living in cities has increased. This process of urbanization has had a lot of implications for both safety management and research on evacuations. Due to this growth in urbanization, more high density gatherings are taking place, potentially resulting in more casualties during emergencies. A common method used to conduct research on evacuations is simulation models. Simulation models have already improved our understanding of human behaviour during evacuations, but researchers argue that most current models are still not able to accurately describe human behaviour during evacuations since they do not take into account the effect of groups. Empirical research has shown that social groups in crowds influence the dynamics of evacuations. For instance, when an emergency happens and groups have to decide where to go, groups sometimes just follow other groups. However, accurately modelling such notions is often complex and contains uncertainty. One of the ways to deal with uncertainty systematically is by applying exploratory modelling. This, however, has yet to be applied to evacuations. This study aims to address the need for models which include the notion of groups by analysing the effect of two decision-making schemes on the evacuation time; leader-follower decision-making and consensus decision-making. Furthermore, this study aims to provide a stepping stone for exploratory modelling in the realm of evacuation modelling. In order to do so, this study uses three methods; a literature study, agent-based modelling, and exploratory modelling. The literature study was conducted to lay the foundation of the agent based model, while exploratory modelling was used to explore the uncertainty space of the agent-based model. After the development of the model, it was verified and validated using multiple tests, and data from a previous study. Through extensive validation and verification, it was concluded that this model is fit for purpose. It is both able to generate behaviour in the same magnitude as previous empirical research, and show valid behaviour on the lower abstraction levels of the model. Results show that groups have a significant impact on evacuation time. The more groups are present, and the bigger they are, the higher the evacuation time will be. Furthermore, results show that there is almost no difference in leader-follower decision-making and consensus decision-making. These two only differ when no one is familiar in a building. When there is 0% familiarity, leader-follower behaviour will lead to lower evacuations times compared to consensus decision-making. Lastly, results show that the combination of groups being present and all people being familiar with a building may actually have adverse effects on the evacuation time in crowd densities between 0.07 and 0.36. In case of crowd densities up to 0.36, a high percentage of familiarity may actually lead to higher evacuation times. All in all, this study provides a stepping stone for modelling group behaviour using an exploratory agent-based modelling approach. This study was the first to lay focus on the effect of group decision-making schemes by incorporating it in an agent-based model and exploring its behaviour by running it numerous times under different parameter settings. Furthermore, this research has important implications. First, evacuations inside buildings should not only be evaluated by crowd density or familiarity, but also by exit capacity. Secondly, different crowd compositions have different effects on the evacuations time. Policymakers should, therefore, take into account what types of groups will most likely be present. As regards future research, future research should mainly focus on the effect of modelling leader-follower behaviour in different ways, modelling consensus groups in general, analysing the effect of groups on different segments of evacuation time, and adding more (social) factors to the model which influence evacuation behaviour.

Evacuation strategies are critical in preventing casualties during emergency evacuations in buildings. As large-scale gatherings and high crowd densities in buildings occur more often, the need of relevant and effective evacuation strategies emerges. However, the domain of research that tries to identify possible ways to improve evacuation, i.e. prescriptive domain, is underlooked. Several studies successfully improve evacuation by optimizing existing evacuation scenarios in buildings. A shortcoming of these studies is that they often focus on one strategy and scenario in particular. Therefore, one should opt for a more generic approach to evaluate the effectiveness of evacuation strategies under different circumstances. A way to mitigate uncertainties in evacuation is by using data. Recent studies use a data-driven approach, in which data is used as an input to calibrate and enhance the evacuation strategy. A promising source of data is WiFi data. WiFi data captures movement patterns of building occupants and can be translated to population and building characteristics. Therefore, WiFi data offers the creation of evacuation scenarios in which evacuation strategies can be practically tested. This study aims to (1) evaluate the efficiency of evacuation strategies in buildings under different circumstances, and (2) determine effective evacuation strategies given WiFi data as an input. Therefore, this study presents a new exploratory agent-based approach to evaluate evacuation strategies, and moreover, presents an approach to incorporate input data to practically test evacuation strategies in a given building. To do so, this study used three methodological approaches, namely ExploratoryModeling and Analysis (EMA), Agent- Based Modeling (ABM) and Data Mining. EMA is used to experiment with the created agent-based evacuation model. EMA addresses the effect of uncertainties on the evacuation time, and if evacuation strategies are effective and robust in different circumstances. This study showed that in the created model of the TU Delft TPM faculty building, guiding evacuation strategies, such as dynamic signs and using evacuee staff members turned out to be an effective option if the familiarity in the building is low. However, as the familiarity increases the relative effectiveness of these strategies becomes negligible. In case of increasing familiarity, bottleneck improvement strategies, such as wider exits or stairs and obstacle placement, decrease the total evacuation time consequently. Moreover, this study concluded that an exploratory approach for evacuation models is promising, as the effectiveness of evacuation strategies is very dependent on the evacuation scenario. As a result, this study is able to evaluate these scenarios beforehand and to determine the effect on the total evacuation time. In this study the uncertainties crowd density, familiarity with the building, compliance with given instructions, and the exit capacity are leading in influencing the total evacuation time. The latter was found as a newly modelled uncertainty for evacuation scenarios.

With growing tensions in today's world, new powers rising and contesting old powers, two nations risk ending up in a so called security dilemma: One nation's increase in security threatens its opposing nation. The consequence could be the escalation of military buildups into arms races. With ongoing technological advancements, militaries around the world are expanding on autonomous capabilities that need less and less human control. In this research, I investigate under which conditions arms races for these systems between two fictitious nations may occur and how the nations can influence these. For this, I construct a system dynamics model based on literature and expert consultations and conduct experiments to generate a wide range of possible scenarios. The model results suggest that different types of arms races for autonomous military capabilities occur under specific conditions: the inferior nation lacks behind the superior nation and fills this initial gap not with a greater number of autonomous systems, but with higher quality autonomous systems, leading to an arms race in quality. Bilateral disarmament in the form of regulations on the level of autonomy seem not to be the answer for the superior nation: some of the arms racing is reduced, but the superior nation now loses both racing and non-racing scenarios. Restrict an opponent in their technological development is more effective for the superior nation. Still, the inferior nation is able to win in the specific case, where the superior nation requires "too much" human control. Generally, arms races can further be reduced when both nations avoid to be too "reactive" to each other's arming actions. This suggests, that a third party could step in and aim at relaxing the tensions between the two nations. Further, this third party could also aim at encouraging the inferior nation to raise its ethical standards. To conclude, the model can give insight into which decisions a nation or a third party can take with different goals in mind. These include, for the nations involved in a competition as a result from tensions, to either win the race towards autonomy or to prevent its opponent from winning it. A third party, interested in a peaceful world without having nations piling up autonomous military capabilities, might aim at preventing arms races whatsoever.

The transition to a low-carbon economy depends on several critical materials, among which is cobalt. This metal is a main component in batteries, and therefore, demand for cobalt is expected to increase in the coming years. This paper explores future scenarios for the cobalt system, in light of its role in the low-carbon transition. The future of cobalt is characterized by deep uncertainty: it involves uncertainty on how the system is structured, on the values of variables influencing the system, and on the desirability of outcomes of interest. Therefore, this research uses Exploratory system dynamics modelling and analysis as the method, since it allows to explore an ensemble of models, each with different values for the input variables. The results show that cobalt is likely to remain a critical material for the electric vehicle transition, although the demand for the metal could vary greatly, depending on the size of future batteries and how fast the average oregrade of cobalt will decline. The demand scenarios in turn influence the development of industrial and artisanal mining, and recycling in the cobalt system. Depending on the collection rate of batteries and other cobalt-containing goods at the end of their life, recycled cobalt could account for a significant part of the demand. The by-product nature of cobalt makes future industrial mining dependent on developments in the nickel and copper markets. If the demand for cobalt increases sufficiently and its price levels go up, cobalt could become a co-product for nickel and copper. With regards to scarcity and sustainability of the cobalt system, this research examines the influence of the assumptions of the two opposing paradigms in the literature on these two concepts: the Fixed stock paradigm and the Opportunity cost paradigm. While the Fixed stock paradigm warns for eminent physical scarcity, the Opportunity cost paradigm places its trust in the regulating capabilities of the price of metals, the signal for economic scarcity. This paper argues that the continued discussion on the paradigms, divert the attention from the externalities of mining. Cobalt resources are not likely to soon be depleted, but externalities of mining could continue to increase. More cooperation between scientists of both paradigms could help to increase understanding of metal systems, and to produce better advice on policies for decision makers to cope with the externalities. Increased research into understanding how externalities of mining could be mitigated is therefore recommended.

Accidents in buildings happen frequently and if people are not evacuated in time, this can have major consequences. The behaviour of building occupants is one of the most critical determinants herein. Evacuation behaviour consists of two phases: the response phase and the evacuation movement phase. During the response phase, a building occupant is notified of an incident and performs a series of information and action tasks. When the response phase is finished, a building occupant will initiate movement towards an exit or safe place during the evacuation movement phase. In this thesis, the focus is on response-phase behaviour. There are many factors influencing response-phase behaviour, four of these are: culture, cues, affiliation and setting. Culture is defined as "the collective programming of the mind distinguishing the members of one group or category of people from others". For this research, national cultures have been considered. Cues are any kind of changes in the environment, which indicate that something is not normal. Affiliation encompasses the tendency for people to seek friends or colleagues. Lastly, setting limits the knowledge obtained and the type of actions which can be performed based on the location of the building occupant. The following research question has been answered: " How does culture, in combination with cues, settings and affiliation, influence response-phase behaviour and time and total evacuation time ? ”. To answer the research question, a case study was introduced. In this case study library evacuations have been considered in Czech Republic, Poland, Turkey and the UK. Within the context of this case study a questionnaire and an agent-based model have been developed. The results show that that there are significant differences in the number of response tasks being performed. Turkey performs the highest number of response tasks, followed in a decreasing order by Poland, Czech Republic and the UK. Furthermore, it has been found that response behaviour in all countries is influenced by cues, setting and affiliation, which results in significant differences between the countries for their response and evacuation time. It has been found that, as with the number of response tasks, Turkey has the highest evacuation and response times, followed in a decreasing order by Poland, Czech Republic and the UK. Lastly, it has been found that affiliation and being informed by a staff member highly affect response and evacuation times, while the setting and seeing fire do not. The degrees to which these factors influence response and evacuation times differ per country. Overall, this research acknowledges the importance of performing cross-cultural research for evacuation behaviour. It has shown the need for policy makers and emergency planners to discuss effects of culture on evacuations. Additionally, it provides a new approach to study the effect of cultures, in combination with cues, setting and affiliation, on response-phase behaviour and response and evacuation times.