Hydrological-ecological processes

Effects of land use, transport and in-stream processing on nutrients

Research interests

We investigate the relationships of carbon, nitrogen, and phosphorus input and processing and their effects on ecosystem functioning and services of inland waters to develop new approaches for integrative ecosystem management. We use experimental and data science approaches, and combine concepts from ecological stoichiometry, biogeochemistry, aquatic ecology, and catchment science.

Our research is closely connected to the work of other researchers from different disciplines. In addition to the highly interlinked research within our department, we cooperate with researchers from the departments River ecology, Hydrogeology and Lake research, as well as research from the research units  Chemicals in the Environment und Smart Models/ Monitoring. The research of this group is also linked to the work on natural attenuation of nutrients in the Helmholtz International Research School TRACER. Outside UFZ we also cooperate with different researchers, for example colleagues from the Wassercluster Lunz (Dr. Gabriele Weigelhofer) in Austria, the James-Hutton-Institute in Scotland (Prof. Marc Stutter) und the Aarhus University (Prof. Brian Kronvang, Dr. Thomas A. Davidson) in Denmark.


  • We study land-use effects on ecosystem state variables, ecological functions, and biogeochemical cycling of inland waters.
  • We focus on the sources, stoichiometry and processes of dissolved organic matter, as well as dissolved nitrogen and phosphorus fractions.
  • Here we use experimental studies at different scales to develop new approaches for integrative ecosystem management of inland waters.
  • Our experimental work combines in-situ measurements by sensors, stable isotope approaches, biological process measurements, spectroscopy & chemometrics, and wet chemistry laboratory measurements.
  • We combine our experimental work with data analytical work to test findings from our experimental work using measurements from various monitoring data sets, and to generate hypotheses for further experiments.




Alexander Bartusch
Katharina Hohensee