- Department:(Dept. 1) Ecohydrology and Biogeochemistry
One-Hundred Fundamental, Open Questions to Integrate Methodological Approaches in Lake Ice Research
Microbial communities and fatty acid markers across acidification and eutrophication extremes in a river influenced by mining activities
Length Scales, Rates, and Variability of Mixing Downstream of River Confluences
The Unexploited Treasures of Hydrological Observations Beyond Streamflow for Catchment Modeling
Other hydrological data than streamflow have the potential to improve process consistency in hydrological modeling and consequently for predictions under change. The authors review how storage and flux variables are used for model evaluation and calibration; improving process representation.
Biogenic polyphosphate as relevant regulator of seasonal phosphate storage in surface sediments of stratified eutrophic lakes
Using nuclear magnetic resonance spectroscopy, the authors studied the polyphosphate seasonality in the topmost sediment layer of three stratified lakes with prolonged anoxic periods during summer stratification. Polyphosphate acted as a temporary phosphorus storage, formed at the beginning of the summer stratification under oxic conditions and released time delayed under anoxic conditions.
Environmental effects of the Kakhovka Dam destruction by warfare in Ukraine
Recent Developments and Emerging Challenges in Tracer-Aided Modeling
The authors reviewed recent advances and remaining challenges of tracer-aided modelling which offers insights into internal storages, water sources, flow pathways, mixing processes, and water ages, which cannot be derived from hydrometric data alone. Tracer data have the capability to falsify hydrological models and test hypotheses, and thus increase understanding of hydrological processes.
Diversification of macrophytes within aquatic nature-based solutions (NBS) developing under urban environmental conditions across European cities
DREAM(LoAX): Simultaneous Calibration and Diagnosis for Tracer-Aided Ecohydrological Models Under the Equifinality Thesis
The authors developed a new algorithm DREAM(LoAX) as an effective conditioning tool to consider epistemic uncertainty in process-based models. It provides real-time diagnostic information of model failures for identification of uncertainty in data or flaws in model structure, and hence is a learning tool for limitations in current monitoring networks and development of future models.
