Lough Feeagh monitoring station
Lough Feeagh monitoring station

What is PROGNOS?

The PROGNOS project aims to integrate high-frequency monitoring of lakes with dynamic water quality models in order to provide short-term water quality forecasts that support decision making for water management.

Improved forecasting

Based on high frequency monitoring, near real time modelling of lake conditions can be used to forecast short-term (7-10 days) changes in algal blooms and levels of dissolved organic carbon. Longer-term predictions (weeks-months) can also be improved by combining historical conditions with the short-term forecasts.

Benefits for Water Management

The short-term forecasts should provide a greater window of opportunity for making water quality management decisions, potentially reducing water treatment costs. The short-term and long-term forecasts should enable water managers to better adapt to climate-change risks.


The PROGNOS project will also carry out a cost-benefit analysis, weighing-up the cost of establishing high frequency monitoring and forecasting systems with the benefits for drinking water provision and recreational activities. The cost-benefit analysis should thus help water managers determine if high-frequency monitoring and forecast systems will improve the cost-effectiveness of their operations.


Useful material

Factsheets on setting up automatic, high-frequency monitoring stations are available through the NETLAKE COST Action.

An open access article in Environmental Science and Technology on using automatic monitoring to manage lakes and reservoirs is available, published within the NETLAKE COST Action.

Additional material that will be produced during the PROGNOS project includes reports and publications that will help mangers better understand the principles behind the PROGNOS-developed forecast system, and provide guidance needed to develop such a system at their site. These include:

  • Determining the optimal data input frequency to drive model simulations for a range of sites and models (Autumn 2017)
  • A description of the auto-calibration routine for model parametrisation (Winter 2017-2018)
  • How the use of near real-time data can improve water quality model performance (Summer 2018)
  • How to transfer cost-benefit estimates made by PROGNOS to other sites (Winter 2018-2019)
  • How to use automated near real time data to drive short-term model forecasts (Summer 2019)
  • A cost-benefit assessment of HF monitoring and short-term forecast models (Summer 2019)
  • A set of policy briefs describing PRONGOS outputs (Summer 2019)

As the PROGNOS project concludes, a workshop will be organised for European water resource managers (Summer 2019).