Hydrological modelling is a valuable tool for studying the processes governing impacts of climate change and urban development on water resources and for projecting potential ranges of impacts from scenarios of future change. To improve understanding of processes involved and to project potential future conditions, hydrologists rely on models to simulate system behaviour. Hydrological modelling is a useful methodology for experimenting with the dynamics that govern complex environmental and social systems and for projecting possible ranges of impacts. Hydrologic models are simplified, conceptual representations of a part of the hydrologic cycle. Hydrological models can range from sand-filled boxes to complicated computer program. They are primarily used for hydrologic prediction and for understanding hydrologic processes. Recent research in hydrologic modelling tries to have a more global approach to the understanding of the behaviour of hydrologic systems to make better predictions and to face the major challenges in water resources management. Two major types of hydrologic models can be distinguished: Stochastic Models and Process-Based Models. Stochastic Models also known as stochastic hydrology models are black box systems, based on data and using mathematical and statistical concepts to link a certain input (for instance rainfall) to the model output. Process-Based Models try to represent the physical processes observed in the real world, containing representations of surface runoff, subsurface flow, evapotranspiration, and channel flow. These models are known as deterministic hydrology models. Deterministic hydrology models can be subdivided into single-event models and continuous simulation models.