Improving forecasts of phytoplankton blooms using high frequency satellite observations

Host institution

The University of Stirling, UK.

Project description

It is widely accepted that increases in the frequency of extreme climatic events are likely to promote potentially toxic phytoplankton blooms increasing risks to water quality. Mitigation of these risks will rely on accurate forecasting of blooms to inform early management interventions.

This challenge is now being overcome through the increased use of data from Earth-observing satellites which now provide wellvalidated data on key water quality parameters at high spatial and temporal resolutions at local to global scales (Fig. 1). The objective of this project is to develop an improved 1-D model for forecasting phytoplankton blooms in lakes and reservoirs through the use of satellite data for model calibration and validation. 1-D models will initially be developed and applied at a local-scale for 1-2 UK lakes and reservoirs managed by AW where high quality insitu and satellite data (Sentinel-2 MSI/-3 OLCI) are available.

These models will then be extended to a larger set of lakes with a more global distribution representing different physical, chemical and climatic conditions to predict how lake phytoplankton blooms will respond over longer timescales to changes in climate


Helmholtz Centre for Environmental Research, Germany. 4 months.
Anglian Water, UK. 2 months.
EAWAG, Switzerland. 3 months.


Maud Siebers

high frequency satellite observations
phytoplankton blooms