Top-down and data-based mechanistic modelling of rainfall-flow dynamics at the catchment scale
Date
2003
Authors
Young, Peter C
Journal Title
Journal ISSN
Volume Title
Publisher
John Wiley & Sons Inc
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.
Description
Keywords
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-down
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Source
Hydrological Processes
Type
Journal article