Download - Amber Kickoff Catchment Modelling - IOW
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Baltic Sea Catchment Modelling
• BNI•Catchment characteristics and threads
• CSIM model• Modelling eutrophication issues and N and
P fluxes•Isotope studies in AMBER
•Christoph Humborg, Carl-Magnus Mörth, Erik Smedberg, Dennis P. Swaney
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BNI History• MArine Research on Eutrophication (MARE)• Funded 1999-2006• Aim: Define “critical loads” for Baltic
eutrophication and illustrate “cost-efficient”ways to reach these loads
• Product: Decision Support System NEST• “Institutionalized” in 2007 as Baltic NEST
Institute (Swedish and Danish branch)
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Drainage basin modeling
Marine modeling
Marine and runoff data
Atmospheric emissions and load
Food web model
Cost minimization model
NEST can be used freelywith any computer with Internet
access fromhttp://www.Balticnest.org
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• 87 major catchments and 21 costal strips
• Hydrological data and nutrient fluxes for 1970-2006
• Landscape types, Population Agricultural dataAtmospheric deposition
• PLC 5 based on national inconsistent approaches
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Legendglc250mClass_Names
Artificial surfaces and associated areas
Bare areas
Cultivated and managed terrestrial areas
Herbaceous, closed - pastures, natural grassl
Herbaceous, open with shrubs
Lichens and mosses
Mosaic: crop/ tree cover
Regularly f looded shrub and/or herbaceous
Snow and ice
Sparse herbaceous or sparse shrubs
Tree cover, broadleaved, deciduous, closed
Tree cover, broadleaved, deciduous, open
Tree cover, mixed phrenology, closed
Tree cover, mixed phrenology, open
Tree cover, needleleaved, evergreen, closed
Tree cover, needleleaved, evergreen, open
Water
•Changes sewage cleaning and livestock densities affecting N and P fluxes
•Hydrological alterations and global warming affecting Si and C fluxes
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Graham 2004
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Changes in lifestyles translates into N emissions
0 10000 20000 30000 40000GNP [$ cap-1]
40
45
50
55
60
65
70
75
Ani
mal
Pro
tein
Con
sum
ptio
n [g
cap
-1 d
ay-1]
Belarus
Denmark
Estonia
Finland
Germany
Latvia
Lithuania
Poland
Sweden
Y = 6.9 * ln(X) - 4.10548635R2 = 0.71
Economic Growth
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CSIM (Catchment Simulation)
Forest
Herbacous
Lake and streams
Cultivated areas
Ground water compartment 1
Ground water compartment 2
Precipitation
Runoff
Evapotranspiration
Point sources:Manure
Rural sewageUrban sewage:
a) from WWTPsb) no treatment
ErosionCalculated
foreach land
class
Loadings in mg l-1
Water
Forest
Herbacous
Lake and streams
Cultivated areas
Ground water compartment 1
Ground water compartment 2
Precipitation
Runoff
Evapotranspiration
Point sources:Manure
Rural sewageUrban sewage:
a) from WWTPsb) no treatment
ErosionCalculated
foreach land
class
Loadings in mg l-1
WaterLoadings in mg l-1
Water
Mörth et al. 2007Now: fixed type concentrationsFuture: Type concentrations =f(land use)
Future: dynamicRiverine retention
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Emission numbers and informations on MWWTPS, rural vs urban poulation, livestock densities, various retention coefficients in soils and river were used for Scenario
AnalysesCountry Milk cows Other cattle Slaughter pigs Sows Humans
N P N P N P N P N P Belarus 47.4 9.8 34.0 4.5 8.8 3.6 22.0 9.0 3.9 1.1 Czech republic 63.0 11.8 34.0 4.5 8.8 3.6 22.0 9.0 3.9 1.1 Germany 96.1 16.1 34.0 4.5 8.8 3.6 22.0 9.0 3.9 1.1 Denmark 74.2 13.3 34.0 4.5 8.8 3.6 22.0 9.0 3.9 1.1 Estonia 94.3 15.9 34.0 4.5 8.8 3.6 22.0 9.0 3.9 1.1 Finland 84.8 14.6 34.0 4.5 8.8 3.6 22.0 9.0 3.9 1.1 Lithuania 63.5 11.9 34.0 4.5 8.8 3.6 22.0 9.0 3.9 1.1 Latvia 62.2 11.7 34.0 4.5 8.8 3.6 22.0 9.0 3.9 1.1 Norway 101.6 16.8 34.0 4.5 8.8 3.6 22.0 9.0 3.9 1.1 Poland 63.0 11.8 34.0 4.5 8.8 3.6 22.0 9.0 3.9 1.1 Russia 47.4 9.8 34.0 4.5 8.8 3.6 22.0 9.0 3.9 1.1 Sweden 101.6 16.8 34.0 4.5 8.8 3.6 22.0 9.0 3.9 1.1
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Simulated (validation period vs. measured) streamflow, TN and TP loads
Mörth et al. 2007
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Seasonalsimulationsof an eutrophied(Oder)and unperturbedsystem (Råne)
Mörth et al. 2007
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Future plans
• Forcing data update• Type concentrations = f(soil types,
specific runoff, crop type, livetsock density, manure handling etc.)
• Riverine Retention =f (TI, HL)
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HELCOM MunicipalHot Spot List
HELCOM data on hot spots and sewage
PLC-4 MWWTP
List
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Watershed Nutrient Budgets as a solid base for the scientific and
economic analyses
NANI=Net Anthropogenic Nutrient Input
Howarth et al. 1996; Boyer et al. 2002
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Waste water treatment plants
ImportFodder
Export Animal productsExport
Plant products
FertilizersAtmospheric
depositionN-fixatinglegumes
Fodder
NH3
NH3
Manure on pastures
Manure stables
Food
N-leakageN-leakage
N-emissionsto water & air
NH3 from fertilizers
DenitrificationN -leakage
NH3 from plant
residues
Food spoilage
Human sludge
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NANI = Food and Feed budgets + N-fixation + Fertilizer Use+ Atmospheric Deposition
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Dynamic description of retention
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Modelling of the Baltic Sea catchment
2520
Terres
trial D
OMMari
ne D
OMMari
ne se
dimen
tMari
ne al
gae
151050-5
-10
δ34 S
-DO
M
12 14 16 18 20 22load weighted δ18O-NO3 [‰]
0
20
40
60
80
culti
vate
d la
nd in
cat
chm
ent [
%]
KeKo
Ne
Vi Od
Pa
Per²=0.67n=7p<0.05
-2 0 2 4 6 8 10load weighted δ15N-NO3 [‰]
0
20
40
60
80
LuKaToKeKo
DaAn
Ne
Vi Od
Pa
Per² = 0.769n=11p<0.001
Validation by multiple stable isotopes
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Tundra and Taiga (Podzol Zone) C-Budgets as linked to Hydrology
• Polar amplification of global warming• 450 Pg C stored • ~ 70 annual anthropogenic emissions• Boreal/subarctic Baltic unperturbed rivers as model systems
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Graham 2004
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DOC increases up to mid lattitudes in Sweden
Trend analysis30 yearsMonitoring dataWith monthlyResolution
Longitude
-0.2
0
0.2
0.4
0.6
0.8TO
C in
crea
se [m
g yr
-1]
56 58 60 62 64 66 68 Humborg et al., 2007HESS
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RV Maria S. Merian28 28 febfeb 2006 2006 –– 17 mars 200617 mars 2006
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Conservative mixing of TOC in the Baltic?
Wedborg et al. 1997 Fonselius 1995
TOC Humic Substances
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Conservative mixing of TOC in the Baltic?
Fonselius, 1995
Degradation patterns can not be seen by just comparing TOC/Salinity
Discrimination between terrestrial and marine TOC has to be made
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Terrestrial source (end member)
δ13C = -28 ‰‰
How to use isotopic signatures
δ13C:(‰‰))
-21-28
δ13C = -25 ‰ 57 % terrestrial DOC 43 % marine
Marine source (end member)
δ13C = -21 ‰
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Methods
• Ultra filtration (cross flow filtration) used to up-concentrate DOM
• Natural stable isotopes, specific value of each source –each end member
DOM-concentrates from Bothnian Sea and Bothnian Bay
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Results of Results of δδ1313C analysis of the DOM C analysis of the DOM
Normal terrestrial signal
Too little difference from the total terrestrial sample to make a quantification of terrestrial input.
Terrestrial signature:-28‰‰
Marine signature: -21‰‰
Estuarine production: about -24‰‰
-27.8‰
-26.7‰
-25.4‰
-25.5‰
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Still not a total marine signature
Terrestrial end member
Terrestrial signature:6.9‰‰
Marine signature:18.1‰‰
7.0‰
10.3‰
12.5‰
13.7‰
Results of Results of δδ3434SS analysis of the DOM analysis of the DOM
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δ34S vs. δ13C
End points of the two isotope signatures correspond well
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TTerrestrialerrestrial fractionfraction of DOCof DOC
100%87%
75%
67%
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Bothnian BayRiver
input: 760
DOC= 75% terrestrial440 700
DOC= 87% terrestrial
- 420- 410
Bothnian Sea
N. Baltic proper
~50% to sediments and/or respired
Simple box modelSimple box model --fluxes of terrestrial DOCfluxes of terrestrial DOC
DOC= 67% terrestrial
- 420
DOC= 75% terrestrial
- 420
DOC= 67% terrestrial
DOC= 75% terrestrial
- 420
36 50 River input: 550
74 50 Kton C/yr
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