Browsing by Author "Arhonditsis, George B."

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    A multi-lake comparative analysis of the General Lake Model (GLM): Stress-testing across a global observatory network
    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 A.; Adrian, Rita; Ayala, Ana I.; Bocaniov, Serghei A.; Boehrer, Bertram; Boon, Casper; Brookes, Justin D.; Bueche, Thomas; Busch, Brendan D.; Copetti, Diego; Cortes, 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; Oezkundakci, Deniz; Pilotti, Marco; Rueda, Francisco J.; Rusak, James A.; Samal, Nihar R.; Schmid, Martin; Shatwell, Tom; Snorthheim, Craig; Soulignac, Frederic; Valerio, Giulia; van der Linden, Leon; Vetter, Mark; Vincon-Leite, Brigitte; Wang, Junbo; Weber, Michael; Wickramaratne, Chaturangi; Woolway, R. Iestyn; Yao, Huaxia; Hipsey, Matthew R. (2018-04)
    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. (c) 2017 Published by Elsevier Ltd.
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    A system of metrics for the assessment and improvement of aquatic ecosystem models
    Hipsey, Matthew R.; Gal, Gideon; Arhonditsis, George B.; Carey, Cayelan C.; Elliott, J. Alex; Frassl, Marieke A.; Janse, Jan H.; de Mora, Lee; Robson, Barbara J. (2020-06)
    In this paper, we introduce the CSPS framework for the hierarchical assessment of aquatic ecosystem models built on a range of metrics and characteristic signatures relevant to aquatic ecosystem condition. The framework is comprised of four levels: 0) conceptual validation; 1) comparison of simulated state variables with observations ('state validation'); 2) comparison of fluxes with measured process rates ('process validation'); and 3) assessment of system-level emergent properties, patterns and relationships ('system validation'). Of these, only levels 0 and 1 are routinely undertaken at present. To highlight a diverse range of contexts relevant to the aquatic ecosystem modelling community, we present several case studies of improved validation approaches using the level 0-3 assessment hierarchy. We envision that the community-driven adoption of these metrics will lead to more rigorously assessed models, ultimately accelerating advances in model structure and function, and improved confidence in model predictions.