Natural disasters pose increasing risks to human life and infrastructure, demanding faster and more accurate predictive systems. This chapter explores the integration of Quantum Artificial Intelligence (Quantum AI) with High-Performance Computing (HPC) for environmental data analysis and disaster prediction. The proposed hybrid framework leverages HPC for large-scale simulations, artificial intelligence (AI) for data-driven learning and quantum algorithms for accelerated pattern recognition and optimization. Case studies on flood forecasting and hurricane intensification demonstrate that Quantum AI enhances predictive accuracy by 2–5% and extends forecast lead times by up to 6 h compared to conventional approaches. While current quantum hardware constraints limit full-scale deployment, simulated experiments show clear potential for hybrid quantum-classical architectures in improving disaster forecasting efficiency and scalability. The chapter concludes that Quantum AI, when embedded in HPC infrastructures, can significantly advance the next generation of resilient and intelligent environmental modelling systems.