Coastal Hazard Risk Assessment in a Changing Climate: A Review of Predictive Models and Emerging Technologies

Abstract

Climate change is one of the most significant problems facing the coastal regions throughout the entire world, exposing communities, infrastructure, and ecosystems to the risks of erosion, storm surges, floods, and sea level rise. Traditional risk assessment of coastal hazards using statistics-based techniques and deterministic models has been found useful, but is typically insufficient to capture a non-stationary climate regime and compound events. The paper establishes a coherent system to apply predictive analytics and new technologies to evaluate the risks associated with climate-induced events in the United States' coastal communities. Probability hazard maps from sea level rise, regional climate model, socioeconomics, and environmental features are developed using GIS and Random Forest, Extreme Gradient Boosting, and K-Nearest Neighbour. Due to the development of early warning systems, digital twins, the Internet of Things, next-generation monitoring satellite systems, and big data analytics, coastal management can become more proactive.  In addition to providing a decision-making tool for resource distribution, treatment prioritization, and long-term adaptation planning, the resulting projection was more accurate with the system. In bringing together machine learning, geospatial analysis, and technology advances, the study provides a compelling window for resilience-building, adaptive management, and sustainable coastal risk management under accelerated climate change.