A multi-lake comparative analysis of the General Lake Model (GLM): Stress-testing across a global observatory network. (April 2018)
- Record Type:
- Journal Article
- Title:
- A multi-lake comparative analysis of the General Lake Model (GLM): Stress-testing across a global observatory network. (April 2018)
- Main Title:
- A multi-lake comparative analysis of the General Lake Model (GLM): Stress-testing across a global observatory network
- Authors:
- Bruce, Louise C.
Frassl, Marieke A.
Arhonditsis, George B.
Gal, Gideon
Hamilton, David P.
Hanson, Paul C.
Hetherington, Amy L.
Melack, John M.
Read, Jordan S.
Rinke, Karsten
Rigosi, Anna
Trolle, Dennis
Winslow, Luke
Adrian, Rita
Ayala, Ana I.
Bocaniov, Serghei A.
Boehrer, Bertram
Boon, Casper
Brookes, Justin D.
Bueche, Thomas
Busch, Brendan D.
Copetti, Diego
Cortés, Alicia
de Eyto, Elvira
Elliott, J. Alex
Gallina, Nicole
Gilboa, Yael
Guyennon, Nicolas
Huang, Lei
Kerimoglu, Onur
Lenters, John D.
MacIntyre, Sally
Makler-Pick, Vardit
McBride, Chris G.
Moreira, Santiago
Özkundakci, Deniz
Pilotti, Marco
Rueda, Francisco J.
Rusak, James A.
Samal, Nihar R.
Schmid, Martin
Shatwell, Tom
Snorthheim, Craig
Soulignac, Frédéric
Valerio, Giulia
van der Linden, Leon
Vetter, Mark
Vinçon-Leite, Brigitte
Wang, Junbo
Weber, Michael
Wickramaratne, Chaturangi
Woolway, R. Iestyn
Yao, Huaxia
Hipsey, Matthew R.
… (more) - Abstract:
- Abstract: The modelling community has identified challenges for the integration and assessment of lake models due to the diversity of modelling approaches and lakes. In this study, we develop and assess a one-dimensional lake model and apply it to 32 lakes from a global observatory network. The data set included lakes over broad ranges in latitude, climatic zones, size, residence time, mixing regime and trophic level. Model performance was evaluated using several error assessment metrics, and a sensitivity analysis was conducted for nine parameters that governed the surface heat exchange and mixing efficiency. There was low correlation between input data uncertainty and model performance and predictions of temperature were less sensitive to model parameters than prediction of thermocline depth and Schmidt stability. The study provides guidance to where the general model approach and associated assumptions work, and cases where adjustments to model parameterisations and/or structure are required. Highlights: The General Lake Model (GLM) is stress tested against 32 globally distributed lakes. There was low correlation between input data uncertainty and model performance. Model performance related to lake-morphometry, light extinction and flow regime; deep, clear lakes had the lowest model error. Predictions of temperature were less sensitive to model parameters than thermocline depth and Schmidt stability.
- Is Part Of:
- Environmental modelling & software. Volume 102(2018)
- Journal:
- Environmental modelling & software
- Issue:
- Volume 102(2018)
- Issue Display:
- Volume 102, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 102
- Issue:
- 2018
- Issue Sort Value:
- 2018-0102-2018-0000
- Page Start:
- 274
- Page End:
- 291
- Publication Date:
- 2018-04
- Subjects:
- Lake model -- Stratification -- GLM -- Model assessment -- Global observatory data -- Network science
Environmental monitoring -- Computer programs -- Periodicals
Ecology -- Computer simulation -- Periodicals
Digital computer simulation -- Periodicals
Computer software -- Periodicals
Environmental Monitoring -- Periodicals
Computer Simulation -- Periodicals
Environnement -- Surveillance -- Logiciels -- Périodiques
Écologie -- Simulation, Méthodes de -- Périodiques
Simulation par ordinateur -- Périodiques
Logiciels -- Périodiques
Computer software
Digital computer simulation
Ecology -- Computer simulation
Environmental monitoring -- Computer programs
Periodicals
Electronic journals
363.70015118 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13648152 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.envsoft.2017.11.016 ↗
- Languages:
- English
- ISSNs:
- 1364-8152
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3791.522800
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British Library HMNTS - ELD Digital store - Ingest File:
- 11763.xml