2nd PhD cohort 

Safae Aala

Safae Aala

Heterogeneous land uses characterize river basins worldwide and result in complex landscape mosaics and mixed natural-rural-urban watersheds. Whereas the assessment of changing land use effects on runoff production is a codified practice, knowledge of the role of landscape patterns in determining water quality along streams is less developed. In particular, high yields of suspended solids triggered by intense anthropogenic land uses constitute an emerging concern worldwide due to, e.g., the environmental peril of sediment bound pollutants and light limitations endangering stream ecosystems. Understanding drivers of pollution caused by suspended solids is a growing research subject that demands robust approaches to describe the behaviours of heterogeneous watersheds, estimate loads in the receiving streams, and predict outcomes of growing urbanization and landscape restoration efforts. In the first step of the PhD project, archetypical patterns of landscape organization and related concentration-discharge relations will be identified. The second step covers the modeling of how landscape organization affects stream particulate loads and the evaluation of mosaics that are most prone to infringe regulatory thresholds. Finally, landscape mosaics that may mitigate water quality stress and buffer climate change effects will be assessed.

Mentor Team

Dr. Soohyun Yang
Dr. Stefano Basso
Prof. Dietrich Borchardt
Prof. Suresh Rao


Helmholtz Cetre for Environmental Research
Purdue University
Anika Große

Anika Große

Nutrient stoichiometry is mainly influencing macronutrient uptake in stream ecosystems. So far, less information is available about how stoichiometry and light effects the long-term storage, release or recycling within the stream and their role within food webs. By adjusting these factors it will be possible to detect how they influence the nutrients pathways beyond the uptake into benthic or hyporheic biofilms and higher trophic levels. This will be implemented by using streamside mobile mesocosms (MOBICOS) and whole stream experiments with the use of stable isotope tracer addition. Another experiment under different climate conditions will provide information about the generalisation of the results beyond temperate regions. This PhD project will help to get a better understanding about predictors of nitrogen and phosphorus uptake and their further paths within the stream ecosystem. This will provide information to improve models describing nutrient cycles in streams. By gaining a better understanding of nutrient cycles, their contributing factors and potential predictors, it will be possible to minimise the risks of eutrophication and conserve ecosystems by giving management options in order to keep the ecosystem services.

Mentor Team

Dr. Daniel Graeber
Dr. Patrick Fink
Dr. Núria Perujo-Buxeda
Prof. Alexander J. Reisinger


Helmholtz Centre of Environmental Research  
University of Florida
Chao Lei

Chao Lei

Stream networks collect loads of water and solutes from the catchment, and patterns of these loadings can be observed at the outlet. However, the situation of losing water from stream to groundwater can exert strong influences on the solute source composition and discharge at the catchment outlet. Long-term exploitation of groundwater and climate change may even exacerbate the losing conditions with the decline of groundwater. The first part of my PhD project will be the case study in the Bode catchment. By the build-up of the data-driven stream network model, we hope to quantify the losing conditions in this catchment and figure out their effects on the solute source composition. Meanwhile, we will simulate the situations of high and severe low flow in the model to better understand the impacts of extreme events. Following the last part, the temporal variability of losing and gaining conditions in the Bode catchment and the Suwannee River in Florida will be investigated then. Based on the research findings from the first two parts, we will work on the upscaling tasks at a larger scale possibly with the help of artificial intelligence (AI), such as in Germany or even Europe. The expected results will be the identification of losing-prone areas of the major European rivers and their trend in the future.

Mentor Team

Dr. Christian Schmidt
Dr. Larisa Tarasova
Dr. Stefano Basso
Dr. Andreas Musolff
Prof. Matthew Cohen


Helmholtz Centre for Environmental Research  

University of Florida