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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/113150
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dc.contributor.authorWright, D.-
dc.contributor.authorThyer, M.-
dc.contributor.authorWestra, S.-
dc.contributor.authorMcInerney, D.-
dc.date.issued2018-
dc.identifier.citationJournal of Hydrology, 2018; 561:211-222-
dc.identifier.issn0022-1694-
dc.identifier.issn1879-2707-
dc.identifier.urihttp://hdl.handle.net/2440/113150-
dc.description.abstractAbstract not available-
dc.description.statementofresponsibilityDavid P. Wright, Mark Thyer, Seth Westra, David McInerney-
dc.language.isoen-
dc.publisherElsevier-
dc.rights© 2018 Published by Elsevier B.V-
dc.source.urihttp://dx.doi.org/10.1016/j.jhydrol.2018.01.036-
dc.subjectHydrologic model calibration; influence diagnostics; influence analysis; leverage; generalized leverage; Cook’s distance-
dc.titleA hybrid framework for quantifying the influence of data in hydrological model calibration-
dc.typeJournal article-
dc.identifier.doi10.1016/j.jhydrol.2018.01.036-
pubs.publication-statusPublished-
dc.identifier.orcidWestra, S. [0000-0003-4023-6061]-
dc.identifier.orcidMcInerney, D. [0000-0003-4876-8281]-
Appears in Collections:Aurora harvest 3
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