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This Special Issue explores how big data and deep learning can bolster hydrological modelling, flood prediction and drought tracking. It bridges the gap between conventional hydrological modelling and emerging data-driven approaches, and offers a platform for researchers to exchange insights on sustainable water management, disaster resilience and climate adaptation. Contributions to this compilation will advance our understanding of how the synergy of big data and deep learning can reshape hydrology, benefiting both scientific progress and practical flood/drought management.