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Insights into Phytoplankton Dynamics and Water Quality Monitoring with the BIOFISH at the Elbe River, Germany

Wilhelms, Andre 1; Börsig, Nicolas 1; Yang, Jingwei; Holbach, Andreas; Norra, Stefan 1
1 Institut für Angewandte Geowissenschaften (AGW), Karlsruher Institut für Technologie (KIT)


Understanding the key factors influencing the water quality of large river systems forms an important basis for the assessment and protection of cross-regional ecosystems and the implementation of adapted water management concepts. However, identifying these factors requires in-depth comprehension of the unique environmental systems, which can only be achieved by detailed water quality monitoring. Within the scope of the joint science and sports event “Elbschwimmstaffel” (swimming relay on the river Elbe) in June/July 2017 organized by the German Ministry of Education and Research, water quality data were acquired along a 550 km long stretch of the Elbe River in Germany. During the survey, eight physiochemical water quality parameters were recorded in high spatial and temporal resolution with the BIOFISH multisensor system. Multivariate statistical methods were applied to identify and delineate processes influencing the water quality. The BIOFISH dataset revealed that phytoplankton activity has a major impact on the water quality of the Elbe River in the summer months. The results suggest that phytoplankton biomass constitutes a substantial proportion of the suspended particles and that photosynthetic activity of phytoplankton is closely related to significant temporal changes in pH and oxygen saturation. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000149053
Veröffentlicht am 27.07.2022
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Geowissenschaften (AGW)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 2073-4441
KITopen-ID: 1000149053
Erschienen in Water (Switzerland)
Verlag MDPI
Band 14
Heft 13
Seiten Art.-Nr.: 2078
Bemerkung zur Veröffentlichung Gefördert durch den KIT-Publikationsfonds
Vorab online veröffentlicht am 29.06.2022
Schlagwörter water quality; phytoplankton; river dynamics; multisensor system; online monitoring; high spatial resolution; multivariate statistics
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