Key Drivers in Flood and Drought Risk Assessment: Unveiling Risk Factors Through a Multi-Metric Network Approach

Flood and drought risks in river basins are driven by a complex interplay of natural and anthropogenic factors, making their assessment and management particularly challenging. This paper presents a novel approach to systematically identify and evaluate the most influential parameters contributing to these risks. We employed Interpretive Structural Modelling (ISM) and Causal Loop Diagrams (CLD) to construct a comprehensive framework of 116 interconnected parameters. By applying 11 network metrics, including betweenness centrality, PageRank, and closeness centrality, we identified the key parameters that act as critical influencers within the system [4]. The Cross-Entropy method was then utilized to refine this set, pinpointing the most significant 30 percent of parameters across all metrics. This analysis led to the development of causal networks for flood and drought risks, highlighting the dynamic relationships and critical drivers in each context. The findings provide a robust foundation for decision-makers to prioritize resources, optimize risk management strategies, and predict future risks. This work offers valuable insights for policymakers and river basin managers to converge socio-environmental planning and transboundary water management, while also supporting the proactive mitigation of flood and drought impacts.