Abstract for: Improving Coastal Infrastructure Resilience by Bridging Risk Perception of Engineers and Maintenance Decision-Making

Dam safety is not just about engineering, it also depends on how people perceive risk, make decisions, and allocate resources. While engineers usually analyze dam failures based on technical and physical factors, human and behavioral dynamics play a major role in infrastructure resilience. This study explores how risk perception and maintenance decisions interact by using a system dynamics approach to examine the relationships between dam owners, engineers, and policymakers. Based on interviews and a survey conducted among U.S based engineers, this study identifies key challenges in dam upgrade. Using information and physical flows, this work employs a system dynamics method and presents a stock-flow model for strengthening dam resilience. In order to evaluate dam resilience and the engineering community's perception of risk, causal linkages are established for the physical, financial, climate policy, and regulatory layers. Findings show that dam owners, as the main decision-makers, often focus on short-term financial priorities rather than long-term resilience. Engineers’ risk perception influences their recommendations for maintenance budgets, but financial constraints, political shifts, and regulatory instability frequently delay necessary investments. Using causal loop modeling and a stock-flow framework, this research shows how risk perception can fluctuates over time, affecting funding decisions that will result in cycles of neglect and urgent upgrade. This study focuses on the need for proactive maintenance strategies instead of reactive fixes after disasters. Policy recommendations include regular risk awareness training for engineers, long-term funding structures for maintenance, and reducing political influence in infrastructure investment decisions. Understanding how human factors shape dam safety can help develop better policies to ensure long-term infrastructure resilience. AI used for grammar checking.