A Global Statistical View of Lake Water Quality: The GloboLakes Project

• Activity Number: 50
• Type: Invited
• Date/Time: Sunday, August 3, 2014 : 4:00 PM to 5:50 PM
• Sponsor: The International Environmetrics Society
• Author(s): Claire Miller*+ and Marian Scott and Ruth Haggarty and Francesco Finazzi
• Companies: University of Glasgow and University of Glasgow and University of Glasgow and University of Bergamo
• Keywords: Functional clustering ; state-space modelling ; lake water quality

Abstract

Traditional monitoring of lake water quality has focused on in-depth studies of individual lakes, without considering the global context of environmental change. GloboLakes is a 5-year consortium project funded by the Natural Environment Research Council, UK, to investigate the state of lakes and their response to environmental drivers at a global scale. The project involves: the production of a 20-year time series of observed ecological parameters for approximately 1000 lakes globally from archive satellite data, collation of associated catchment and meteorological data, and in-situ monitoring of selected lakes.

Lakes are sensitive to large-scale environmental pressures and hence different lakes within a region can be expected to behave similarly through time (temporal coherence). Functional clustering and state space modelling provide efficient and informative statistical approaches to investigate coherence of water quality parameters from earth observation data. Understanding the spatial extent of this coherence enables validation, extrapolation from measured to unmeasured lakes, and hence investigation of the environmental factors controlling lake structure and function.