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Hypothetico-inductive data-based mechanistic modeling of hydrological systems

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dc.contributor.authorYoung, Peter C
dc.date.accessioned2015-12-13T22:23:00Z
dc.date.issued2013
dc.date.updated2016-02-24T09:09:00Z
dc.description.abstractThe paper introduces a logical extension to data-based mechanistic (DBM) modeling, which provides hypothetico-inductive (HI-DBM) bridge between conceptual models, derived in a hypothetico-deductive manner, and the DBM model identified inductively from the
dc.identifier.issn0043-1397
dc.identifier.urihttp://hdl.handle.net/1885/72552
dc.publisherAmerican Geophysical Union
dc.sourceWater Resources Research
dc.subjectKeywords: Diagnostic tests; Distributed models; Effective rainfall; Hydrological system; Mechanistic modeling; State-dependent parameters; Stochastic simulation model; Time-series data; Mathematical models; Water resources; Parameter estimation; conceptual framewor
dc.titleHypothetico-inductive data-based mechanistic modeling of hydrological systems
dc.typeJournal article
local.bibliographicCitation.issue2
local.bibliographicCitation.lastpage935
local.bibliographicCitation.startpage915
local.contributor.affiliationYoung, Peter C, College of Medicine, Biology and Environment, ANU
local.contributor.authoruidYoung, Peter C, u5092275
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor040608 - Surfacewater Hydrology
local.identifier.absfor010204 - Dynamical Systems in Applications
local.identifier.absseo960608 - Rural Water Evaluation (incl. Water Quality)
local.identifier.ariespublicationf5625xPUB3303
local.identifier.citationvolume49
local.identifier.doi10.1002/wrcr.20068
local.identifier.scopusID2-s2.0-84876567143
local.type.statusPublished Version

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