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

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. An evaluation of the BIOFISH data based on the combination of statistical analysis with weather and discharge data shows that the hydrological and meteorological history of the sampled water body was the main driver of phytoplankton dynamics. This study demonstrates the capacity of longitudinal river surveys with the BIOFISH or similar systems for water quality assessment, the identification of pollution sources and their utilization for online in situ monitoring of rivers.

[1]  C. Stow,et al.  Application of the Beer–Lambert Model to Attenuation of Photosynthetically Active Radiation in a Shallow, Eutrophic Lake , 2018, Water Resources Research.

[2]  David J. Olive Robust Multivariate Analysis , 2017 .

[3]  Frank Dziock,et al.  Lebensräume der Elbe und ihrer Auen , 2015 .

[4]  S. Rolinski,et al.  Contrasting long-term trends and shifts in phytoplankton dynamics in two large rivers , 2014 .

[5]  Lijing Wang,et al.  Three Gorges Reservoir: density pump amplification of pollutant transport into tributaries. , 2014, Environmental science & technology.

[6]  H. Guhr,et al.  Die Wiedergenesung der Elbe nach dem gesellschaftlichen Umbruch in Deutschland und Tschechien , 2014 .

[7]  Lijing Wang,et al.  Water mass interaction in the confluence zone of the Daning River and the Yangtze River—a driving force for algal growth in the Three Gorges Reservoir , 2013, Environmental Science and Pollution Research.

[8]  V. Simeonov,et al.  Assessment of Water Quality in the Elbe River at Flood Water Conditions Based on Cluster Analysis, Principle Components Analysis, and Source Apportionment , 2012 .

[9]  H. Fischer,et al.  Influence of global change on phytoplankton and nutrient cycling in the Elbe River , 2011 .

[10]  J. Einax,et al.  Assessment of Water Quality in the Elbe River at Low Water Conditions Based on Factor Analysis , 2011 .

[11]  J. H. Schuenemeyer,et al.  Statistics for Earth and Environmental Scientists , 2011 .

[12]  B. Qin,et al.  The contribution of phytoplankton degradation to chromophoric dissolved organic matter (CDOM) in eutrophic shallow lakes: field and experimental evidence. , 2009, Water research.

[13]  M. Baborowski,et al.  Consequences of delayed mixing for quality assessment of river water: example Mulde-Saale-Elbe. , 2009 .

[14]  Michael Matthies,et al.  System analysis of water quality management for the Elbe river basin , 2006, Environ. Model. Softw..

[15]  M. Böhme Distribution of water quality parameters in two cross-sections of the river Elbe measured with high local, temporal, and analytic resolution , 2006 .

[16]  K. Friese,et al.  Behaviour of suspended particulate matter (SPM) and selected trace metals during the 2002 summer flood in the River Elbe (Germany) at Magdeburg monitoring station , 2004 .

[17]  B. Karrasch,et al.  The Effects of Nutrient Concentrations in the River Elbe , 2003 .

[18]  Barbara Frank,et al.  ELBIS, an Internet Information System on the Water Quality of the River Elbe , 2003 .

[19]  R. Romanowicz,et al.  Statistical Modeling of Algae Concentrations in the Elbe River in the Years 1985—2001 Using Observations of Daily Dissolved Oxygen, Temperature, and pH , 2003 .

[20]  Online article , 2001, Regulatory Peptides.

[21]  D. G. Smith,et al.  TURBIDITY SUSPENI)ED SEDIMENT, AND WATER CLARITY: A REVIEW 1 , 2001 .

[22]  B. Karrasch,et al.  The dynamics of phytoplankton, bacteria and heterotrophic flagellates at two banks near Magdeburg in the River Elbe (Germany) , 2001 .

[23]  M Rode,et al.  Long-term behaviour and cross-correlation water quality analysis of the River Elbe, Germany. , 2001, Water research.

[24]  Laurent Bertino,et al.  Process identification by principal component analysis of river water-quality data , 2001 .

[25]  B. Karrasch,et al.  Shifts in the Processes of Oxygen and Nutrient Balances in the River Elbe since the Transformation of the Economic Structure , 2000 .

[26]  P. Krause,et al.  Development and application of ICP-MS in Elbe river research , 1997 .

[27]  E. Smith Methods of Multivariate Analysis , 1997 .

[28]  P. J. Wigington,et al.  Use of factor analysis to investigate processes controlling the chemical composition of four streams in the Adirondack Mountains, New York , 1996 .

[29]  T. Reade The River Elbe , 1879, Nature.

[30]  Andreas Holbach Water quality and pollutant dynamics in the Three Gorges Reservoir on the Yangtze River, China = Wasserqualität und Schadstoffdynamik im Drei-Schluchten-Reservoir am Yangtze, China , 2015 .

[31]  Jordi Catalan,et al.  The relationship between phytoplankton biovolume and chlorophyll in a deep oligotrophic lake: decoupling in their spatial and temporal maxima , 2000 .