Flood Risk Governance in Greece in the Aftermath of Storm Daniel

In this study, we assess the impacts of Storm Daniel, which emerged as a low-pressure system on September 4, 2023, and dissipated by September 12. This storm significantly impacted Libya, Greece, Bulgaria, Turkey, Egypt, and Israel, causing widespread flooding. Greece was particularly affected, with 17 deaths and over two billion euros in damages, making it the country's most expensive storm. On September 5, Zagora in Mount Pelion, Greece, recorded an unprecedented 754 mm of rainfall in a single day, leading to extensive flooding in central Greece. A prosecutor's investigation into local authorities' preventive measures followed, aiming to evaluate if further actions could have lessened the storm's effects. This event highlights the need to consider the effects of global warming, which is expected to intensify the hydrological cycle, increasing the likelihood of severe precipitation events and flooding risks. Our paper has two objectives: (a) to analyze the response of the existing Greek Flood Risk Governance (FRG) framework to Storm Daniel, and (b) to recommend improvements of the Greek FRG framework using Multi-Criteria Decision Analysis (MCDA). The initial phase involves analyzing documents related to the flood risk governance cycle, including prevention mapping, emergency response protocols, and national natural disaster insurance frameworks. This analysis uncovers several shortcomings, notably a lack of effective government action in disaster prevention, despite the existence of Flood Risk Management (FRM) plans by the Ministry of the Environment in 2018. Additionally, the Greek natural disaster insurance framework could benefit from strategic improvements. For the second objective, we employ MCDA, specifically Multi-Attribute Utility Theory (MAUT), to evaluate FRG frameworks from various EU countries, identifying the most suitable model for Greece. MAUT is chosen for its ability to incorporate both quantitative and qualitative criteria effectively, ideal for decision-making involving subjective judgments. The feasibility of conducting sensitivity analysis by altering criteria weights, utility scores, and creating best- and worst-case scenarios makes MAUT well-suited for policy decision-making. We assess criteria such as effectiveness, cost, adaptability, resilience, stakeholder engagement, and environmental impact, considering different flood scenarios, including Mediterranean storms and catastrophic flooding. Next, we intend to integrate Machine Learning (ML) techniques to perform a sensitivity analysis on our Multi-Criteria Decision Analysis (MCDA) method for storm disaster management. This approach will enhance our understanding of how different variables impact our decision-making process, thereby improving its accuracy and effectiveness in storm-related scenarios. In summary, this study aims to deliver a thorough and critical evaluation of the Flood Risk Governance (FRG) in Greece. It also seeks to offer well-informed recommendations for enhancing the Greek FRG system, particularly in the context of escalating flood risks driven by climate change. This comprehensive assessment not only scrutinizes the current state of flood risk management but also considers the future challenges posed by environmental changes, aiming to bolster Greece's resilience and adaptive capacity against such natural hazards.