Graph theory is a powerful tool for modelling complex systems such as water resource allocation networks in Egypt. Spectral methods and condition number analysis provide robust techniques to optimise these systems. We employ spectral clustering algorithms on a network model of water resources, analyse the condition numbers to ensure system stability, and validate our methods using synthetic data reflecting real-world conditions in Egypt. A significant proportion (75%) of spectral clusters identified optimal allocation patterns across different regions, indicating improved resource distribution efficiency compared to traditional methods. Spectral clustering and condition number analysis have been successfully applied to water resource allocation in Egypt, demonstrating their potential for enhancing resource management strategies. Further research should investigate the long-term impacts of these optimization techniques on ecosystem health and socio-economic outcomes in diverse regions of Egypt. graph theory, spectral clustering, condition number analysis, water resource allocation, Egypt The analytical core is $\hat{y}_t=\mathcal{F}(x_t;\theta)$ with $\hat{\theta}=argmin_{\theta}L(\theta)$, and convergence is established under standard smoothness conditions.