UK scientists to revolutionise lake research in 2.5 million pound global project
Published: 10 September 2012
A consortium of scientists from six UK universities and Research Institutes has been awarded a prestigious £2.5 million grant to create the world’s first satellite-based global lake surveillance system, to monitor how lakes and reservoirs are being affected by environmental change.
A consortium of scientists from six UK universities and Research Institutes has been awarded a prestigious £2.5 million grant to create the world’s first satellite-based global lake surveillance system, to monitor how lakes and reservoirs are being affected by environmental change.
Funded by the Natural Environment Research Council (NERC), the consortium project, entitled Globolakes, will be led by Dr Andrew Tyler, Head of Biological & Environmental Sciences at the University of Stirling.
Dr Claire Miller (PI) and Prof. Marian Scott from the Environmental Statistics group in the School of Mathematics and Statistics have been awarded a £400,000 grant from the Natural Environment Research Council as part of the Globolakes consortium.
Dr Miller and Prof Scott are to lead the statistical analysis for the Globolakes consortium to detect spatial and temporal patterns in lake water quality. They will jointly supervise a postdoctoral researcher who will develop models to assess the present state and evidence for long-term change in lakes globally, identifying, in particular, clusters of lakes which possess common patterns over time and similar phenological changes.
This work will be a valuable tool to enable them to extrapolate from measured to unmeasured lakes. Processed remote sensing data from The University of Stirling, University of Edinburgh and Plymouth Marine Laboratory will be used for this work and the outputs will directly contribute (along with work from The University of Dundee) to work on attributing the causes of lake response, which will be undertaken by the Centre for Ecology & Hydrology. Dr Miller and Prof. Scott will also contribute to modelling the uncertainty identified for measurements recorded by a variety of methods at different temporal and spatial scales.
First published: 10 September 2012
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