Publications (2)2.49 Total impact
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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.Hydrological Processes 07/2003; 17(11):2101 - 2111. · 2.49 Impact Factor
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ABSTRACT: Current approaches to constructing catchment intensity-duration-frequency (IDF) curves are dominated by the use of empirically-derived areal reduction factors (ARFs). In this paper we present an alternative methodology which is based on the spatial correlation structure of rainfall. It represents an attempt to link current scientific theories of space-time rainfall fields with design methods. The starting point is to derive the parent distribution of catchment average rainfall intensity from that of point rainfall intensity. The parameters of the two parent distributions are related through a variance reduction factor which is a function of the spatial correlation structure of rainfall and catchment area. Assuming that the parent distribution is of the “exponential type”, it is then transformed to an extreme value distribution of the Gumbel type. The crucial step is to match the parameters of the extreme rainfall distribution derived above, for the particular case of zero catchment area, with those of empirical point IDF curves which have also been fitted to the Gumbel distribution. With this match, the proposed theory then naturally generalises to yield catchment IDF curves for catchments of any size, and for rainfall of any spatial correlation structure. The new catchment IDF curves have the attractive property that, with a minimum number of assumptions, they can reproduce a range of observed properties of catchment rainfall. For example, not only the mean and the standard deviation of extreme rainfall, but also its coefficient of variation, decrease with increasing catchment area. We also find that computed ARFs using the new approach depend not only on catchment area and storm duration, but also on the return period. We estimate ARFs using the new methodology for two major observed storms in Austria, and find that these estimates compare favourably with our understanding of the rainfall generating mechanisms associated with these two particular storm types.Journal of Hydrology.