Research project ALGOTL: Forecast framework for algae blooms to secure water supply on Gotland
Our project "A new forecast framework for algae bloom hazard to secure future water supply and development of tourism on Gotland" is a collaboration between Stockholm University (MISU and DEEP), the Swedish Meteorological and Hydrological Institute (SMHI) and Region Gotland to develop a novel forecast framework for algae blooms and their impacts on management of water resources, both short term (early warning) and long term (climate scenarios). The project was funded under a call "Securing future water supply through sustainable management" by FORMAS.
Region Gotland experiences limited capacity in groundwater reservoirs combined with increased demand during the warm season when it hosts tourists leading to recurring water stress. Desalination of drinking water from the Baltic Sea is a promising alternative to complement municipal water supply. The operation of the desalination treatment plants becomes however disturbed by intense algae blooms that coincide with summer heatwaves and the increased water demand, all predicted to intensify under the climate change. Developing an apt forecasting system for this "multi-hazard" to inform sustainable management of Gotland's water resources becomes thus a priority and is of broader relevance to other regions in Sweden.
Our project is a collaboration between Stockholm University, the Swedish Meteorological and Hydrological Institute (SMHI) and Region Gotland to develop a novel forecast framework for algae blooms and their impacts on management of water resources, both short term (early warning) and long term (climate scenarios). The project builds upon the fact that the physical processes and parameters (turbulent currents, light, temperature) governs the spreading and growth of algae in the sea. We will develop tailored modelling tools embedded in existing operational services at SMHI. Our stakeholders on Gotland will provide input on adverse impacts, information required for management, and feedback on the forecast framework during the project.
