Young, Peter C2015-12-132015-12-130885-6087http://hdl.handle.net/1885/77176The 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.Keywords: Catchments; Rain; Rainfall-flow dynamics; Hydrology; catchment; hydrological modeling; rainfall; streamflow; water budget; United Kingdom Catchment scale; Data-based mechanistic; Deterministic; Hypothetico-deductive; Inductive; Parsimonious; Rainfall-flow; Reductionist; Stochastic; Top-down200310.1002/hyp.13282015-12-11