PhD student (Earth Observation data to investigate water quality and upscaling the ecological processes in aquatic ecosystems with different trophic status and pollution gradients) Lithuania, EU

The increasing human population, industrialization, intensive a land use and climate change enhanced pressure on water ecosystem functioning and therefore requires a sustainable water management. Knowledge about the state of inland and coastal water bodies are therefore of great interest and it is being monitored. A number of European legislations aiming to protect and/or to improve the water quality have been constructed: the EU Directives (WFD, MSFD). In respect to the implementation of the directives, many indicators are being tested and selected as powerful markers of healthy ecosystem, pollution sources that need to be monitored. Algal blooming is one of the factors with the greatest impact on the quality and accessibility of bodies of water in aquatic ecosystems, and on the preservation of existing ecological balances. New and sustainable and operational methods are of great demand. Satellite remote sensing has become a valuable asset for monitoring water bodies and assessment of ecological status in a broad spatial and temporal scale. However, the applicability of data derived from optical remote sensing is limited to areas that are prone to cloud covers as northern latitudes, therefore to enhance the availability of information about ecological processes the use of other sources of information, like radar remote sensing and hydrodynamic modelling, is of great interest.
The work will focus on:
a) the use of Earth Observation data to investigate water quality and upscaling the ecological processes in aquatic ecosystems with different trophic status and pollution gradients;
b) the calibration/validation of the EO data of Sentinel sensors from Copernicus programme;
c) special attention will be given to the algal blooms – the EO-based investigation of status, development, intensity, fate and effect on the aquatic ecosystem (like light conditions).
d) in collaboration with Modelling group of Marine Research Institute, a synergistic use of hydrodynamic modelling and EO data for short-term fine scale (spatially and temporally) forecasting and/or hindcasting of cyanobacteria bloom will be tested.
e) as final outcome of this research, the recommendations for the ecological monitoring to integrate EO-based information is planned.