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dc.contributor.authorHipsey, Matthew R
dc.contributor.authorBruce, Louise C
dc.contributor.authorBoon, Casper
dc.contributor.authorBusch, Brendan
dc.contributor.authorCarey, Cayelan C
dc.contributor.authorHamilton, David P
dc.contributor.authorHanson, Paul C
dc.contributor.authorRead, Jordan S
dc.contributor.authorde Sousa, Eduardo
dc.contributor.authorWeber, Michael
dc.contributor.authorWinslow, Luke A
dc.date.accessioned2019-06-19T13:05:31Z
dc.date.available2019-06-19T13:05:31Z
dc.date.issued2019
dc.identifier.issn1991-959X
dc.identifier.doi10.5194/gmd-12-473-2019
dc.identifier.urihttp://hdl.handle.net/10072/383427
dc.description.abstractThe General Lake Model (GLM) is a one-dimensional open-source code designed to simulate the hydrodynamics of lakes, reservoirs, and wetlands. GLM was developed to support the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of researchers using sensors to understand lake functioning and address questions about how lakes around the world respond to climate and land use change. The scale and diversity of lake types, locations, and sizes, and the expanding observational datasets created the need for a robust community model of lake dynamics with sufficient flexibility to accommodate a range of scientific and management questions relevant to the GLEON community. This paper summarizes the scientific basis and numerical implementation of the model algorithms, including details of sub-models that simulate surface heat exchange and ice cover dynamics, vertical mixing, and inflow–outflow dynamics. We demonstrate the suitability of the model for different lake types that vary substantially in their morphology, hydrology, and climatic conditions. GLM supports a dynamic coupling with biogeochemical and ecological modelling libraries for integrated simulations of water quality and ecosystem health, and options for integration with other environmental models are outlined. Finally, we discuss utilities for the analysis of model outputs and uncertainty assessments, model operation within a distributed cloud-computing environment, and as a tool to support the learning of network participants.
dc.description.peerreviewedYes
dc.description.sponsorshipIan Potter Foundation
dc.description.sponsorshipGriffith University
dc.description.sponsorshipCawthron Institute Trust Board
dc.description.sponsorshipInstitute of Geological & Nuclear Sciences Limited
dc.description.sponsorshipReef and Rainforest Research Centre
dc.description.sponsorshipUniversities Australia
dc.description.sponsorshipDept of Science, Information Technology, Innovation & the Arts (DSITIA)
dc.description.sponsorshipGriffith University
dc.languageEnglish
dc.language.isoeng
dc.publisherCOPERNICUS GESELLSCHAFT MBH
dc.relation.ispartofpagefrom473
dc.relation.ispartofpageto523
dc.relation.ispartofissue1
dc.relation.ispartofjournalGeoscientific Model Development
dc.relation.ispartofvolume12
dc.relation.urihttp://purl.org/au-research/grants/ARC/DP190101848
dc.relation.grantIDDP190101848
dc.relation.fundersARC
dc.subject.fieldofresearchEarth sciences
dc.subject.fieldofresearchcode37
dc.titleA General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON)
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
dc.description.versionVersion of Record (VoR)
gro.rights.copyright© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorHamilton, David P.


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