Constraining uncertainty and process-representation in an algal community lake model using high frequency in-lake observations
| Autor: | Mitzi M. De Ville, Paul Smith, Stephen C. Maberly, Keith Beven, Eleanor B. Mackay, Trevor Page, Heidrun Feuchtmayr, Ian D. Jones, J. Alex Elliott |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0106 biological sciences
010504 meteorology & atmospheric sciences Ecology 010604 marine biology & hydrobiology Ecological Modeling Process representation Climate change Nutrient flux 01 natural sciences Algal bloom Algal community Ecology and Environment Data assimilation Nutrient Economic cost Environmental science Water resource management 0105 earth and related environmental sciences |
| DOI: | 10.1016/j.ecolmodel.2017.04.011 |
| Popis: | Excessive algal blooms, some of which can be toxic, are the most obvious symptoms of nutrient enrichment and can be exacerbated by climate change. They cause numerous ecological problems and also economic costs to water companies. The process-representation of the algal community model PROTECH was tested within the extended Generalised Likelihood Uncertainty Estimation framework which includes pre-defined Limits of Acceptability for simulations. Testing was a precursor to modification of the model for real-time forecasting of algal communities that will place different demands on the model in terms of a) the simulation accuracy required, b) the computational burden associated with the inclusion of forecast uncertainties and c) data assimilation. We found that the systematic differences between the model’s representation of underwater light compared to the real lake systems studied and the uncertainties associated with nutrient fluxes will be the greatest challenges when forecasting algal blooms. |
| Databáze: | OpenAIRE |
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