Within the project CONNECT we are establishing a collaborative network between experts in remote sensing (RS) and freshwater ecology to study connectivity and coherence of lake ecosystems in a regional context at unprecedented temporal and spatial resolution. The overall aim is to understand the yet unexplained variation in phytoplankton dynamics among river-connected German lowland lakes, many of which are presently classified as in poor to bad ecological status. These lakes often face a high risk of eutrophication, mass development of harmful algal blooms, and high production of greenhouse gases. We suggest if measured on adequate temporal and spatial scales much of the among-lake variation in phytoplankton dynamics to be explained by the strength of hydrological lake-to-lake and lake-to-catchment connectivity as modulated by lake depth and mixing regime. This may have profound implications for the maximum intensity, spatial range and regional-scale magnitude of eutrophication impacts. We will use (i) a large-scale experimental manipulation of lake connectivity, and (ii) an observational field campaign contrasting deep and shallow river-connected lakes, to challenge this research frontier by an innovative combination of automatic high- frequency in situ measurements with state of the art near-to-far RS technology. Climate change is expected to alter the hydrology, and thus the connectivity of lake-river systems. However, it is also predicted to increase extreme weather events leading to an increased input of nutrients as well as colored dissolved organic matter (cDOM). By providing data of high spatio-temporal coverage, CONNECT will provide basic high quality data to better understand mechanisms of eutrophication at the local and regional scale. Our data, thus, provide a valuable basis to improve current management of such river-connected lake ecosystems under future climate scenarios. To reach this ambitious goal, the project will (i) build a cross- disciplinary collaborative network of excellence, (ii) develop a mechanistic understanding of lake ecosystem functioning at local and regional scale, (iii) improve future environmental monitoring and interpretation of available data from inland waters, and (iv) support more effective integrated management of river-connected lakes to mitigate eutrophication impacts.