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In catchment hydrology, it is in practice impossible to measure everything we would like to know about the hydrological system, mainly due to high catchment heterogeneity and the limitations of measurement techniques. These limitations and the need to extrapolate information from the available measurements in both space and time initiated the application of hydrological models. However, hydrological models suffer from uncertainty in their predictions, which reduces applicability of and confidence in such models. In this review, we summarise the different classifications of hydrological model types, and discuss relative advantages and disadvantages of each type of model. In addition, we summarise established model calibration processes and discuss the sources of uncertainty that affect model predictions. We summarise different methods to quantify uncertainty in the model predictions that could sit well within a model evaluation framework. And, finally, some recent developments in hydrological modelling are reviewed.

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Catchment scale hydrological modelling: A review of model types, calibration approaches and uncertainty analysis methods in the context of recent developments in technology and applications