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dc.contributor.authorKuppel, Sylvain
dc.contributor.authorTetzlaff, Doerthe
dc.contributor.authorManeta, Marco
dc.contributor.authorSoulsby, Chris
dc.date.accessioned2019-01-12T00:05:49Z
dc.date.available2019-01-12T00:05:49Z
dc.date.issued2018-03
dc.identifier.citationKuppel , S , Tetzlaff , D , Maneta , M & Soulsby , C 2018 , ' What can we learn from multi-data calibration of a process-based ecohydrological model? ' , Environmental Modelling and Software , vol. 101 , pp. 301-316 . https://doi.org/10.1016/j.envsoft.2018.01.001en
dc.identifier.issn1364-8152
dc.identifier.otherPURE: 114729596
dc.identifier.otherPURE UUID: 1075baa6-5087-4840-b711-6c6d7ec2c916
dc.identifier.otherScopus: 85040362093
dc.identifier.urihttp://hdl.handle.net/2164/11771
dc.descriptionThis work was funded by the European Research Council (project GA 335910 VeWa). M. Maneta acknowledges support from the U.S National Science Foundation (project GSS 1461576) and U.S National Science Foundation EPSCoR Cooperative Agreement #EPS1101342. All model runs were performed using the High Performance Computing (HPC) cluster of the University of Aberdeen, and the IT Service is thanked for its help in installing PCRaster and other libraries necessary to run EcH2O and post-processing Python routines on the HPC cluster. Finally, the authors are grateful to the many people who have been involved in establishing and continuing data collection at the Bruntland Burn, particularly Christian Birkel, Maria Blumstock, Jon Dick, Josie Geris, Konrad Piegat, Claire Tunaley, and Hailong Wang.en
dc.format.extent16
dc.language.isoeng
dc.relation.ispartofEnvironmental Modelling and Softwareen
dc.rights© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectcatchment hydrologyen
dc.subjectecohydrologyen
dc.subjectprocess-based modellingen
dc.subjectmulti-objective calibrationen
dc.subjectinformation contenten
dc.subjectEcH2Oen
dc.subjectGE Environmental Sciencesen
dc.subjectQE Geologyen
dc.subjectEuropean Research Councilen
dc.subjectGA 335910 VeWaen
dc.subject.lccGEen
dc.subject.lccQEen
dc.titleWhat can we learn from multi-data calibration of a process-based ecohydrological model?en
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Geography & Environmenten
dc.contributor.institutionUniversity of Aberdeen.Northern Rivers Institute (NRI)en
dc.contributor.institutionUniversity of Aberdeen.Energyen
dc.contributor.institutionUniversity of Aberdeen.Environment and Food Securityen
dc.description.statusPeer revieweden
dc.description.versionPostprinten
dc.description.versionPostprinten
dc.identifier.doihttps://doi.org/10.1016/j.envsoft.2018.01.001
dc.date.embargoedUntil2019-01-12


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