Climate change poses a growing threat to critical infrastructure systems, particularly road networks, which are vulnerable to flooding, heat waves, and extreme weather events. Despite the increasing urgency to adapt infrastructure to these risks, assessing suitable adaptation measures remains a complex challenge due to competing priorities, including effectiveness, cost, and social impact. This thesis aims to help decision-makers assess suitable climate change adaptation measures for road infrastructure. The research employs Multi-Criteria Decision Analysis (MCDA) tools, namely the Best-Worst Method (BWM), to derive weights for the evaluation criteria based on stakeholder preferences, and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to rank the adaptation alternatives accordingly. A survey was conducted and received 129 responses from academic, governmental, and practitioner backgrounds across the Global North and South.

This study found that respondents assign higher importance weight to adaptation strategies that effectively reduce disaster risk (28%), have minimal unintended consequences (27%), and have low adverse societal impact (27%), placing less emphasis on project cost (18%). As a consequence, Improved Drainage, Vegetation Plans, and Monitoring Systems emerged as the most suitable adaptation measures. In contrast, Alternative Roads, Road Reallocation, and Road Height adjustments were seen as less favorable. Subgroup and sensitivity analyses confirmed the robustness of these findings, showing only minor variations across respondent backgrounds and regions. Despite limitations such as a modest sample size and limited regional specificity, this study can be a reference for policymakers in assessing suitable climate change adaptation strategies in road infrastructure through criteria-based evaluation. The assessment approach is universally applicable and can be extended to other public infrastructure sectors such as energy, transportation, and buildings.

This master's thesis investigates the complex interdependencies between mobility and electricity sectors in the Dutch energy transition (2016-2050). Through comprehensive system dynamics modeling and scenario analysis, the research examines how Battery Electric Vehicle (BEV) adoption patterns interact with renewable energy integration. The study develops three major scenario analyses: exploring various BEV adoption rates combined with energy sector transitions, investigating different renewable energy generation capacities (120-180 TWh), and evaluating the feasibility of the Netherlands' 2030 zero-emission vehicle sales mandate. The findings demonstrate that while renewable energy capacity can accommodate increased electric vehicle demand, successful transition requires careful cross-sectoral coordination. The research contributes to understanding critical infrastructure challenges and provides valuable insights for policymakers and stakeholders involved in sustainable infrastructure development, particularly in the Dutch context.