Integrating GIS and Kernel Density Estimation for Multi-Hazard Risk Assessment of Potential Onshore Pipeline Failures

Abstract

This paper introduces a newly developed risk-assessment framework that combines Kernel Density Estimation (KDE) with Geographic Information System (GIS) technology to analyze multiple hazards, including earthquakes, floods, landslides, mud volcanoes, and soil erosion, for the Baku-Tbilisi-Ceyhan pipeline in Azerbaijan. By integrating hazard-specific parameters into a unified risk matrix, each hazard’s contribution is weighted, refined, and aggregated to produce a spatially explicit, combined risk map. KDE smooths hazard intensities and reveals overlaps among different risk factors. The resulting high-resolution maps enable more targeted prevention and response measures, guiding planners and stakeholders toward effective pipeline protection strategies. Although the model can demand computational power, it remains scalable and flexible, allowing for adaptation to additional hazards or expanded geographical areas. Furthermore, the methodology underscores the importance of cross-validation in setting KDE bandwidth and in calibrating hazard weights to ensure reliable outputs. Preliminary testing indicates that this integrated model improves the clarity of risk data, highlights areas needing immediate attention, and supports resilience planning across the pipeline corridor. This work can be applied more broadly to critical infrastructure projects in regions where multiple hazards coincide, thereby aiding decision-making processes for disaster risk reduction and sustainable development. Future research will focus on refining statistical models for inter-hazard correlations and incorporating machine learning for predictive analytics. The framework stands as a tool to maintain pipeline integrity in the face of evolving environmental threats.