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Keywords:

  • reductionist;
  • top-down;
  • deterministic;
  • data-based mechanistic;
  • inductive;
  • hypothetico-deductive;
  • stochastic;
  • parsimonious;
  • rainfall–flow;
  • catchment scale

Abstract

The data-based mechanistic (DBM) approach to modelling has developed as a stochastic, ‘top-down’ response to the problems associated with the deterministic, ‘bottom-up’ approach. As such, it can be compared with the deterministic, top-down modelling methods that have been attracting attention recently in the hydrological literature. Using catchment-scale rainfall–flow modelling as an example, this paper compares the inductive DBM approach with its hypothetico-deductive, deterministic alternative and shows how they can be used to identify and estimate low-order, nonlinear models of the rainfall–flow dynamics in the River Hodder catchment of northwest England based on a limited set of rainfall–flow data. Copyright © 2003 John Wiley & Sons, Ltd.