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Journal Articles Environmental Modelling and Software Year : 2018

A multi-lake comparative analysis of the General Lake Model (GLM): Stress-testing across a global observatory network

Louise Bruce
  • Function : Author
Marieke Frassl
  • Function : Author
George Arhonditsis
  • Function : Author
Gideon Gal
  • Function : Author
David Hamilton
Paul Hanson
  • Function : Author
Amy Hetherington
  • Function : Author
Jordan Read
  • Function : Author
Anna Rigosi
  • Function : Author
Dennis Trolle
  • Function : Author
Luke Winslow
  • Function : Author
Rita Adrian
Ana Ayala
  • Function : Author
Serghei Bocaniov
  • Function : Author
Bertram Boehrer
  • Function : Author
Casper Boon
  • Function : Author
Justin Brookes
  • Function : Author
Thomas Bueche
  • Function : Author
Brendan Busch
  • Function : Author
Diego Copetti
  • Function : Author
Alicia Cortés
  • Function : Author
Elvira de Eyto
  • Function : Author
J. Alex Elliott
  • Function : Author
Nicole Gal
  • Function : Author
Yael Gilboa
  • Function : Author
Lei Huang
  • Function : Author
  • PersonId : 954959
John Lenters
  • Function : Author
Vardit Makler-Pick
  • Function : Author
Chris Mcbride
  • Function : Author
Marco Pilotti
  • Function : Author
Francisco Rueda
  • Function : Author
James Rusak
Nihar Samal
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Martin Schmid
  • Function : Author
Tom Shatwell
  • Function : Author
Craig Snorthheim
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Frédéric Soulignac
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Giulia Valerio
  • Function : Author
Leon van Der Linden
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  • PersonId : 903004
Mark Vetter
  • Function : Author
Lei Vinçon-Leite
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Junbo Wang
  • Function : Author
Chaturangi Wickramaratne
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R. Iestyn Woolway
  • Function : Author
Huaxia Yao
  • Function : Author
Matthew Hipsey
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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.

Dates and versions

hal-02070282 , version 1 (17-03-2019)

Identifiers

Cite

Louise Bruce, Marieke Frassl, George Arhonditsis, Gideon Gal, David Hamilton, et al.. A multi-lake comparative analysis of the General Lake Model (GLM): Stress-testing across a global observatory network. Environmental Modelling and Software, 2018, 102, pp.274-291. ⟨10.1016/j.envsoft.2017.11.016⟩. ⟨hal-02070282⟩
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