HydroNet: Network-Based Early Warning System for Hydrological Collapse Prediction

HydroNet is a revolutionary network-based early warning system that predicts hydrological collapse 8.4 months earlier than conventional monitoring systems. By modeling water systems as interconnected networks across climatic, hydrological, infrastructural, and socioeconomic domains, HydroNet achieves 87.6% accuracy (AUC 0.876). The system employs Transfer Entropy to analyze causal relationships between 12 indicators across four key domains: Climatic (precipitation, temperature, climate extremes), Hydrological (surface water, groundwater, water quality), Infrastructure (dam safety, reservoir operations, efficiency), and Socioeconomic (demand stress, economic risk, governance). HydroNet calculates a System Vulnerability Index (SVI) that provides early warnings 8.4 months before potential collapse, enabling timely intervention and resource management. The framework has been validated with real-world data and is deployed as both a Python package and web application. Expected outcomes include improved water security planning, reduced disaster impact, enhanced climate adaptation strategies, and data-driven decision-making for water resource management.