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Influence of global change on the water quality
of the Elbe/Labe Einfluss des globalen Wandels
auf die Gewässergüte der Elbe
Helmut Fischer, Volker Kirchesch, Katrin Quiel,
Andreas Schöl Bundesanstalt für Gewässerkunde
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Contents
1. Introduction Position in the model
network Factors influencing water quality The
water quality model QSim 2. Results Longitudin
al development of water quality Model results
(validation) Temporal development of water
quality 3. Conclusions and outlook
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Introduction - position of the project in the
model network

• Einleitung
• Gliederung

Land use and regional water balance
Nutrient load (MONERIS)
Water management (WBALMO)
Hydrological cycle and crop yields (SWIM)
Point source Industry
Inflow
Land use (LAND USE SCANNER)
Point source Sewage plant
Regionalization of global change
Evaporation
Diffuse source Sealed surfaces
Future climate (STAR)
Wetlands
Diffuse source Erosion
Water suppliers
Diffuse source Atmospheric Deposition
Development of agricultural sector (RAUMIS)
Industry
Diffuse source Drainage
Water use
Diffuse source Surface denudation
Mining
Economics and demography (REGE)
Wetlands (MODAM)
Diffuse source Groundwater
Power plants
Diffuse source / Sink Wetlands
Households /business (HAUSHALT WASSER)
Irrigation
Development of energy sector (KASIM)
Industry (INDUSTRIE WASSER)
Nutrient concentr.PhytoplanktonOxygen
Minimal flow for conservation
Energy / Mining (KASIM)
Water quality (QSim)
Transport on inland waterways
Agriculture / Irrigation
Development of water technologies
Transport on inland waterways
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Introduction - position of the project in the
model network
Land use and regional water balance
Nutrient load (MONERIS)
Hydrological cycle and crop yields (SWIM)
Point source dir. ind. discharges
Point discharges WWTP
Regionalization of global change
Land use (LAND USE SCANNER)
Diffuse Source imp. surfaces
Future climate (STAR)
Diffuse Source Erosion
Diffuse Source Atm. Deposition
Development of agricultural sector (WATSIM-RAUMIS)

Diffuse Source Drainage
Water use
Diffuse Source Surface runoff
Economics and demography (REGE)
Wetlands (MODAM)
Diffuse Source Groundwater
Households / business (HAUSHALT WASSER)
Sinks Surface waters/Wetlands
Industry (INDUSTRIE WASSER)
Agriculture / Irrigation
Water quality (QSim)
Development of water technologies
Nutrient concentr.PhytoplanktonOxygen
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Introduction
Factors influencing algal biomass and nutrient
budget and Models providing input data
for QSim
? Climate (temperature, light regime,
precipitation) ? model STAR, PIK
? Discharge (water depth, retention times) ?
model SWIM, PIK
? Nutrients (inputs, concentrations) ? model
MONERIS, IGB
nutrient budget ?? Algal growth and biomass
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Introduction the model QSim
Schöl et al. 1999, 2002
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Results

• Longitudinal (Lagrangian) sampling campaigns
  chlorophyll a

Summer 2000 26.6. 5.7. (9 days) low discharge
Summer 2005 24.7. 1.8. (7 days) medium discharge
Spring 2006 8.5. 15.5. (6 days) high discharge
Chlorophyll a µg/l
Elbe-km
1800
n 3
Elbe
High phytoplankton biomass leads to oxygen
supersaturation in the Middle Elbe (up to 200
in summer) and and heavy loads of organic matter
in the tidal area.
600
1800
tributaries
600
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Results

• Chlorophyll a measured and modelled data

Sommer 2000 26.6. 5.7. low discharge
Chlorophyll a µg/l
1800
Elbe
600
1800
tributaries
600
Elbe-km
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Results

• Longitudinal sampling campaigns dissolved
  phosphorus (ortho-phosphate)

Summer 2000 26.6. 5.7. (9 days) low discharge
Summer 2005 24.7. 1.8. (7 days) medium discharge
Spring 2006 8.5. 15.5. (6 days) high discharge
ortho-PO4-P mg/l
Elbe-km
Elbe
n 6

Tributaries
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Results
Phosphate measured and modelled data
Sommer 2000 26.6. 5.7. low discharge
ortho-PO4-P mg/l
Elbe
tributaries
Elbe-km
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Results

• Longitudinal sampling campaigns silica

Summer 2000 26.6. 5.7. (9 days) low discharge
Summer 2005 24.7. 1.8. (7 days) medium discharge
Spring 2006 8.5. 15.5. (6 days) high discharge
SiO2-Si mg/l
Elbe-km
Elbe
n 6

Tributaries
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Results
Silica measured and modelled data
Sommer 2000 26.6. 5.7. low discharge
SiO2-Si mg/l
Elbe
tributaries
Elbe-km
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Results

• Longitudinal sampling campaigns nitrogen
  (nitrate and total nitrogen)

Summer 2000 26.6. 5.7. (9 days) low discharge
Summer 2005 24.7. 1.8. (7 days) medium discharge
Spring 2006 8.5. 15.5. (6 days) high discharge
NO3-N, total N mg/l
Elbe-km
Total-N
n 6
Elbe
NO3-N
Total-N
Tributaries
NO3-N
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Results
Nitrate measured and modelled data
Sommer 2000 26.6. 5.7. low discharge
NO3-N mg/l
Elbe
tributaries
Elbe-km
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Results
Chlorophyll a (1998)
measured and modelled (Schöl et al. 2006
measured data by ARGE Elbe)
modelled
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Results
Comparison of phytoplankton composition in the
years 1998 and 2003
2003 a warm and dry summer ? development
of cyanobacteria (data by ARGE Elbe)
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Results
2003Measured phytoplankton composition (data
ARGE Elbe)
2003Modelled phytoplankton composition
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Results
In which direction will the system change if
- temperature increases - summer discharges
decrease Model runs with database from years
1998 and 2003

• Model results
• slightly more zooplankton
• only minor change in algal biomass
• change in phytoplankton composition
  (increase of cyanobacteria)

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Conclusions and Outlook

• Current state
• strong phytoplankton growth (factor 4)
• intense turnover of nutrients (biologically
  controlled)
• heavy organic load (secondary pollution)
  impairs the oxygen budget of the Elbe estuary
• high nutrient loads are problematic for coastal
  areas

• Future state
• intensification of biological processes-
  better growth conditions (light, temperature)
• stronger nutrient limitation is possible
• better conditions for cyanobacteria
• open system for invading species (e.g. mussels)

-
Phytoplankton development

-
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Conclusions and Outlook

• Further work within GLOWA-Elbe II
• Modelling nutrient dynamics and phytoplankton
  growth in the Czech Elbe section (below
  Vltava/Moldau).
• Calculation of 5 climate scenarios x 4
  socio-economic scenarios

• Future state
• intensification of biological processes-
  better growth conditions (light, temperature)
• stronger nutrient limitation is possible
• better conditions for cyanobacteria
• open system for invading species (e.g. mussels)

-
Phytoplankton development

-
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Thank You for your attention!
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Results

• Longitudinal sampling campaigns
  (ortho-phosphate) and total phosphorus

Summer 2000 26.6. 5.7. (9 days) low discharge
Summer 2005 24.7. 1.8. (7 days) medium discharge
Spring 2006 8.5. 15.5. (6 days) high discharge
ortho-PO4-P, total P mg/l
Elbe-km
Total-P
n 6
Elbe
ortho-PO4-P

Total-P
Tributaries
ortho-PO4-P