Temporal dynamics of catchment transit times from stable isotope data

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dc.contributor.authorKlaus, Julianen
dc.contributor.authorChun, K. P.en
dc.contributor.authorMcGuire, Kevin J.en
dc.contributor.authorMcDonnell, J. J.en
dc.contributor.departmentForest Resources and Environmental Conservationen
dc.contributor.departmentVirginia Water Resources Research Centeren
dc.date.accessioned2017-01-12T01:39:24Zen
dc.date.available2017-01-12T01:39:24Zen
dc.date.issued2015-06-01en
dc.description.abstractTime variant catchment transit time distributions are fundamental descriptors of catchment function but yet not fully understood, characterized, and modeled. Here we present a new approach for use with standard runoff and tracer data sets that is based on tracking of tracer and age information and time variant catchment mixing. Our new approach is able to deal with nonstationarity of flow paths and catchment mixing, and an irregular shape of the transit time distribution. The approach extracts information on catchment mixing from the stable isotope time series instead of prior assumptions of mixing or the shape of transit time distribution. We first demonstrate proof of concept of the approach with artificial data; the Nash-Sutcliffe efficiencies in tracer and instantaneous transit times were >0.9. The model provides very accurate estimates of time variant transit times when the boundary conditions and fluxes are fully known. We then tested the model with real rainfall-runoff flow and isotope tracer time series from the H.J. Andrews Watershed 10 (WS10) in Oregon. Model efficiencies were 0.37 for the 18O modeling for a 2 year time series; the efficiencies increased to 0.86 for the second year underlying the need of long time tracer time series with a long overlap of tracer input and output. The approach was able to determine time variant transit time of WS10 with field data and showed how it follows the storage dynamics and related changes in flow paths where wet periods with high flows resulted in clearly shorter transit times compared to dry low flow periods.en
dc.description.versionPublished versionen
dc.format.extent4208 - 4223 (16) page(s)en
dc.identifier.doihttps://doi.org/10.1002/2014WR016247en
dc.identifier.issn0043-1397en
dc.identifier.issue6en
dc.identifier.orcidMcGuire, Kevin J. [0000-0001-5751-3956]en
dc.identifier.urihttp://hdl.handle.net/10919/74267en
dc.identifier.volume51en
dc.languageEnglishen
dc.publisherAmerican Geophysical Unionen
dc.relation.urihttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000358301200018&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=930d57c9ac61a043676db62af60056c1en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectEnvironmental Sciencesen
dc.subjectLimnologyen
dc.subjectWater Resourcesen
dc.subjectEnvironmental Sciences & Ecologyen
dc.subjectMarine & Freshwater Biologyen
dc.subjectRESIDENCE TIMEen
dc.subjectHYDROGRAPH SEPARATIONen
dc.subjectDISTRIBUTIONSen
dc.subjectRUNOFFen
dc.subjectGROUNDWATERen
dc.subjectHILLSLOPEen
dc.subjectMODELSen
dc.subjectFUTUREen
dc.subjectFLUXen
dc.subjectFLOWen
dc.titleTemporal dynamics of catchment transit times from stable isotope dataen
dc.title.serialWater Resources Researchen
dc.typeArticle - Refereeden
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Natural Resources & Environmenten
pubs.organisational-group/Virginia Tech/Natural Resources & Environment/CNRE T&R Facultyen
pubs.organisational-group/Virginia Tech/Natural Resources & Environment/Water Resources Research Centeren

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