Extreme rainfall and flooding are intensifying worldwide, reshaping risks to agriculture, rural livelihoods, and watershed systems in ways that demand both scientific insight and practical responses. This chapter brings together advances in observing, understanding, and modelling these hazards, linking rainfall extremes, flood dynamics, and risk assessment into a unified framework. It reviews key climate data and tools used to study these changes, including ground observations, satellite products, reanalysis datasets, and high-resolution convection-permitting models, alongside statistical methods for identifying extremes and vulnerability hotspots. The chapter also highlights progress in hydrological and hydraulic modelling, from machine learning and physics-informed approaches that improve predictions across diverse catchments to efficient two-dimensional models for large-scale flood mapping. In addition, it discusses techniques such as statistical downscaling and weather generators that translate climate-scale information into local impacts. Together, these developments show how observations and models can generate actionable insights for flood risk management and climate adaptation.