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Abstract This paper presents an overview of the ‘downward approach’ to hydrologic prediction and attempts to provide a context for the papers appearing in this special issue. The downward approach is seen as a necessary counterpoint to the mechanistic ‘reductionist’ approach that dominates current hydrological model development. It provides a systematic framework to learning from data, including the testing of hypotheses at every step of analysis. It can also be applied in a hierarchical manner: starting from exploring first‐order controls in the modelling of catchment response, the model complexity can then be increased in response to deficiencies in reproducing observations at different levels. The remaining contributions of this special issue present a number of applications of the downward approach, including development of parsimonious water balance models with changing time scales by learning from signatures extracted from observed streamflow data at different time scales, regionalization of model parameters, parameterization of effects of sub‐grid variability, and standardized statistical approaches to analyse data and to develop model structures. This review demonstrates that the downward approach is not a rigid methodology, but represents a generic framework. It needs to play an increasing role in the future in the development of hydrological models at the catchment scale. Copyright © 2003 John Wiley & Sons, Ltd.
Sivapalan et al. (Thu,) studied this question.