Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Top-down and data-based mechanistic modelling of rainfall-flow dynamics at the catchment scale

Simple item page
dc.contributor.authorYoung, Peter C
dc.date.accessioned2015-12-13T22:37:37Z
dc.date.available2015-12-13T22:37:37Z
dc.date.issued2003
dc.date.updated2015-12-11T09:37:24Z
dc.description.abstractThe 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.
dc.identifier.issn0885-6087
dc.identifier.urihttp://hdl.handle.net/1885/77176
dc.publisherJohn Wiley & Sons Inc
dc.sourceHydrological Processes
dc.subjectKeywords: 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
dc.titleTop-down and data-based mechanistic modelling of rainfall-flow dynamics at the catchment scale
dc.typeJournal article
local.bibliographicCitation.lastpage2217
local.bibliographicCitation.startpage2195
local.contributor.affiliationYoung, Peter C, College of Medicine, Biology and Environment, ANU
local.contributor.authoruidYoung, Peter C, u5092275
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor040608 - Surfacewater Hydrology
local.identifier.ariespublicationMigratedxPub6070
local.identifier.citationvolume17
local.identifier.doi10.1002/hyp.1328
local.identifier.scopusID2-s2.0-0042732130
local.type.statusPublished Version

Downloads

Collections

ANU Research Publications

DSpace software copyright © 2002-2026 LYRASIS