Enhanced assessment of the eReefs biogeochemical model for the Great Barrier Reef using the Concept/State/Process/System model evaluation framework
The Great Barrier Reef is a UNESCO World Heritage Area that has been assessed as having a very poor outlook and needing urgent intervention. The eReefs hydrodynamic-biogeochemical models are used to complement monitoring, facilitate data interpretation and support policy decisions. Management and po...
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Published in | Environmental modelling & software : with environment data news Vol. 129; p. 104707 |
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Main Authors | , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Oxford
Elsevier Ltd
01.07.2020
Elsevier Science Ltd |
Subjects | |
Online Access | Get full text |
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Summary: | The Great Barrier Reef is a UNESCO World Heritage Area that has been assessed as having a very poor outlook and needing urgent intervention. The eReefs hydrodynamic-biogeochemical models are used to complement monitoring, facilitate data interpretation and support policy decisions. Management and policy for the Great Barrier Reef are politically contentious, so a high standard of model evaluation is required. We report the application of a recently-developed four-level “CSPS” (Concept/State/Process/System) model evaluation framework to the eReefs biogeochemical model. The framework considers: Level 0, conceptual evaluation; Level 1, simulated state variables; Level 2, process rates; and Level 3, system-level patterns and emergent properties. This paper is the first complete application of this model assessment framework. It highlights both strengths and weaknesses of the eReefs biogeochemical model that might not have been apparent from a traditional model evaluation. The framework can be applied to evaluation of any complex, process-based numerical model.
•In politically-contentious contexts, models require a high standard of assessment.•We demonstrate the four-level (Concept/State/Process/System) assessment framework.•The performance of the eReefs marine models is assessed.•The approach highlights strengths and weaknesses of the models.•Emergent properties are particularly useful to enhance model assessment. |
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ISSN: | 1364-8152 1873-6726 |
DOI: | 10.1016/j.envsoft.2020.104707 |