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

TitleA multi-lake comparative analysis of the General Lake Model (GLM): Stress-testing across a global observatory network
Publication TypeJournal Article
Year of Publication2018
AuthorsBruce LC, Frassl MA, Arhonditsis GB, Gal G, Hamilton DP, Hanson P, Hetherington AL, Melack JM, Read JS, Rinke K, Rigosi A, Trolle D, Winslow L, Adrian R, Ayala AI, Bocaniov SA, Boehrer B, Boon C, Brookes JD, Bueche T, Busch BD, Copetti D, Cortés A, de Eyto E, J. Elliott A, Gallina N, Gilboa Y, Guyennon N, Huang L, Kerimoglu O, Lenters JD, MacIntyre S, Makler-Pick V, McBride CG, Moreira S, Özkundakci D, Pilotti M, Rueda FJ, Rusak JAnthony, Samal NR, Schmid M, Shatwell T, Snorthheim C, Soulignac F, Valerio G, van der Linden L, Vetter M, Vinçon-Leite B, Wang J, Weber M, Wickramaratne C, R. Woolway I, Yao H, Hipsey MR
JournalEnvironmental Modelling & Software
Volume102
Pagination274 - 291
ISSN1364-8152
KeywordsGLM, Global observatory data, Lake model, Model assessment, Network science, Stratification
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.

URLhttp://www.sciencedirect.com/science/article/pii/S1364815216311562
DOI10.1016/j.envsoft.2017.11.016
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