Research project NG| Optimal hydrological restoration of Swedish wetlands with deep learning and hydrogeodesy
Wetlands are ecosystems that provide multiple ecosystem services and promote sustainable development. They protect coasts, support biodiversity, regulate groundwater and soil moisture, mitigate floods and sequester carbon.
In the context of Sweden, wetlands have been heavily altered during the last century by modifying their WR for agricultural expansion, forestry, hydropower and road infrastructure. The WR relates to the interannual and seasonal variability in the water surface extent, water levels and hydrologic connectivity of a wetland. The WR can be restored to guarantee optimal water depths for aquatic fauna and vegetation. Restoration can also target climate change mitigation by avoiding critical inundation levels that maximise methane emissions.
Project description
Agricultural expansion, forestry, hydropower and road infrastructure have heavily altered the hydrological regimes of Swedish wetlands. As a result, there is a growing interest in their hydrological restoration. Yet, hydrological restoration should also target climate change mitigation by controlling resulting greenhouse gas emissions. Knowledge of hydrological regimes is compulsory to guide optimal wetland restoration, but a lack of hydrological monitoring limits this understanding.
This project combines artificial intelligence, earth observations, and state-of-the-art techniques tracking water levels from space to define the hydrological regimes in 53 wetlands of international importance. Our main objectives are to quantify comprehensive water surface extent and changes, the spatial and temporal variability of water levels, and define guidelines to prioritise wetland restoration, maximising ecosystem health and climate change mitigation.
Project members
Members
Christoph Humborg
Professor
Peter Hambäck
Professor
Fernando Jaramillo
Associate professor, Docent
