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20.04.23| Folie 1
Assessment of diffuse sources for pollution
Meeting of the Working Group
"Statistics of the Environment“
Sub-Group "Water“
9 - 10 October 2007
Luxembourg
Katharina Lenz
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Contents
• Relevance of diffuse sources
• The EUROHARP-project
• Overview of different models
• Modeling of diffuse sources of heavy metals
• Summary & conclusion
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Diffuse sources /point sources
mio m³/y
mio m³/y* Mining and quarrying (10-14) mio m³/y* Total manufacturing industries (15-37) mio m³/y of which: foodprocessing industry (15) mio m³/y basic metals (27) mio m³/y transport equipment (35) mio m³/y textiles etc. (17-19) mio m³/y paper & paper products (21) mio m³/y chemical products & refined petroleum (23-24) mio m³/y* Production & distribution of electricity (401) mio m³/y* Construction (45) mio m³/y* All industrial activities (10-45) mio m³/y
mio m³/y of which: Other activities (50-93) mio m³/y
mio m³/ymio m³/ymio m³/y
(1) mio m³/y(2) mio m³/y(3) mio m³/y(4) mio m³/y(5) mio m³/y(6) mio m³/y(7) mio m³/y(8) mio m³/y
mio m³/ymio m³/ymio m³/y
(9) mio m³/ymio m³/y
(10) mio m³/ymio m³/ymio m³/y
mio m³/y
of which: connected to urban waste water collecting system (41) not connected and discharged, total of which discharged after independent treatment
of which: re-used
Total waste water connected to urban waste water collecting system (f) (41)
Total waste water generated by industry (e) (40) of which: connected to urban waste water collecting system (41) not connected and discharged, Total of which: discharged after treatment in IWWP (j)
Total discharges to Inland waters (h) (62)
Total discharges to the sea (i) (62)
connected to IWWTP discharged without treatmentEffluents of UWWTP (g) (59) of which: discharged
of which: connected to UWWTP
Of which: * Agriculture, forestry, fishing (b)
ALL SOURCES
VOLUME WASTE WATER GENERATED (58) BY SOURCE AND BY SECTOR - POINT SOURCES (Total) (a)
* Domestic sector (c)
of which: householdsNON POINT SOURCES (d)
WASTE WATER DISCHARGED BY TYPE OF COLLECTING SYSTEMWaste water generated by domestic sector (c) (38)
Point sources
Diffuse sources
Diffuse sources are of high relevance !
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Diffuse sources /point sources in the Danube River Basin
Danubs - project:
http://danubs.tuwien.ac.at/
Nutrient Fluxes in the Danube Basin
Insitute for Water Quality and Waste management, Vienna University of Technology (2005). Nutrient Management in the Danube and ist Impact on the Black Sea, Final Report
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Relevance of diffuse sources
EEA (2005). Source apportionment of nitrogen and phosphorus inputs into the aquatic environment, EEA-Report No7/2005
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Diffuse sources - Background
• Diffuse pollution cannot be measured, it has to be modeled!
• Validation of model with measured values at monitoring sites (monitoring networks)
• Water Framework Directive (WFD): harmonised tools/ methodologies to quantify nutrient losses from diffuse sources
Project EUROHARP (www.euroharp.org)
• Objective: Comparison of different catchment scale modeling approaches for characterisation of the relative importance of point and diffuse pollution in surface freshwater systems
• Performance of 9 quantification tools in 17 European-wide river catchments
• Coordination: NIVA (Norvegian Institute for Water Research)
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EUROHARP
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EUROHARP
QT no. Name of the QT Modelling institute Nutrients
1 NL - CAT ALTERRA(NL) [N, P]2 Irish method-REALTA KMM (IRL) [P]3 N-LESS NERI (DK) [N]4 MONERIS FV-IGB (D) [N, P]5 TRK (SOILN/HBV) SLU / SMHI (S) [N, P]6 SWAT EC-JRC/NTUA (GR)/IRSA-CNR (I) [N, P]7 EVENFLOW ADAS (UK) [N]8 NOPOLU IFEN / BETURE-CEREC (F) [N, P]9 Source apportionment NERI (DK) [N, P]
Process oriented, dynamic models: QT 1, 5, 6: dynamics of the fate of nutrient inputs in the soil are modelled in a two or three-dimensional way, often on a daily basis. Comprehensive representation of all individual system processes
Semi-empiric models: QT 3, 4, 7: using a series of simpler, conceptual (semi-) empirical or statistical functions
QT 2, 8, 9: do not consider soil processes, but can serve as “broad brush” tools to assess pollutant loads at catchment level.
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EUROHARP: 17 catchments
Austria: Gurk catchment
• MONERIS• SWAT• NOPOLU
• Source apportionment
Catchment area: 2.602km2
Elevation Range: 393- 1820 m Rainfall: 905 mm Arable land: 59.442 ha Grassland: 30.641 ha Forest: 143.037 ha (55%) Lakes: 17 (>2 ha) Inhabitants: 235.500 River Course Length: 150 km
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EUROHARP: N Balance for the Gurk Catchment per year
t N/a SWAT MONERIS SA
N-Input:
Point sources 325 387 276
Atmospheric deposition on water bodies
10 45 22
Loss from woodland and other non-agricultural land
368 983 617
Loss from agricultural land 995 1.061 2.847
Total N-Input 1.698 2.476 3.762
N-Output:
Load 1.703 2.132 1.902
Retention 20 345 1.859
Total N-Output 1.723 2.477 3.761
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EUROHARP: P Balance for the Gurk Catchment per year
t P/a SWAT MONERIS SA
P-Input:
Point Sources 41 48 19
Atmospheric deposition on water bodies
2 0,4
Loss from woodland and other non-agricultural land
4 35 13
Loss from agricultural land 210 25 55
Total P-Input 255 110 87
P-Output:
Load 216 85 73
Retention 18 24 14
Total P-Output 234 109 87
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EUROHARP-Catchment Gurk: Results
Model SWAT MONERIS NOPOLU SA measured values
Total area (ha) 252.070 256.400 255.864 260.200 260.286
Agricultural land (ha)
85.877 75.800 93.800 90.080 90.083
Period: 1995–1999
1995–1999 1991–1999 1995–1999 1991–1999
Flow (Mio m3/y) 954 893 902 902 886–902
Load (t N/y) 1.703 2.132 2.230 1.902 1.810–2.165
Load (t P/y) 216 85 124 73 54–82
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MONERIS
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MONERIS: MOdeling Nutrient Emissions in RIver Systems
7 pathways: atmospheric deposition groundwater tile drainage paved urban areas erosion surface runoff (dissolved nutrients) discharges from point sources
(municipal waste water treatment plants and industrial discharges)
Basic input into the model: Data on river flow water quality ( GIS integrating digital maps (e.g. hydrogeo-
logical maps, soil maps) statistical information (inhabitants, land use)
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Phosphorus Einwohner FlächeAtmosphär
-ische Deposition
Abschwem-mung
Dränagen ErosionGrund-wasser
Punkt-quellen
versiegelte urbane Flächen
GesamtLandwirt-
schaftliche Aktivitäten
PLR Nr.
Planungs-raum
[E] [km²] [t/a] [t/a] [t/a] [t/a] [t/a] [t/a] [t/a] [t/a] [t/a]
1 Rhein 325013 2327 1 47 0 107 41 25 21 242 38
2 Elbe 48567 931 0 9 0 30 5 2 2 48 37
3Donau bis Jochenstein
1221205 18535 6 552 1 815 276 262 71 1984 398
4Donau unterhalb Jochenstein
3870443 27453 14 682 8 948 252 438 117 2459 1213
5 March 175813 3683 1 19 1 152 6 19 5 204 168
8 Mur 878381 10316 3 138 1 287 67 268 41 805 228
9 Drau 704220 11809 6 275 1 418 122 60 44 925 267
10Leitha, Raab und Rabnitz
728245 8835 14 46 4 275 18 192 21 571 302
Gesamt
Österreich7951887 83889
45 1769 17 3033 787 1266 320 7236 2652
0,6% 24,4% 0,2% 41,9% 10,9% 17,5% 4,4% 100,0% 36,6%
MONERIS: Austrian example Phosphorus
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MONERIS model
+: No model calibration needed Good applicability for
catchments size ≥ 500 km2
Representation of full N- and P-cycle
Identification of emission pathways
Consideration of retention processes in groundwater and surface water
Scenario calculations possible
-: Empirical approaches limited in
their applicability (particularly for semi-arid regions)
limited spatial distribution Uncertainty increases with
decreasing catchment size limited temporal variations (5
years annual values) GIS data needed to parameterise
the model
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SWAT
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SWAT
SWAT: 3 dimensional/continous time watershed model that operates on a daily time step at basin scale. management & timing of agricultural practises rivers
Nitrogen processes in the soil described in SWAT
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SWAT
Precipitation
Irrigation
Rain Snow
Snow melt
Surface Runoff
Transmission Losses
Infiltration
Snow cover
Soil Storage
Soil EvaporationPlant Uptake
and Transpiration
Lateral Flow
Percolation
Soil Water routing (10
layers)
Sreamflow
Irrigation Diversion
Transmission Losses
Route to next Reach or Reservoir
Shallow Aquifer
Irrigation
Revap Seepage
Return Flow
Pond/ Reservoir Water Balance
P/R Evaporation
Irrigation
P/R Outflow
P/R Seepage
Deep Aquifer
Irrigation
SWAT: hydrological processes
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SWAT model
+: good representation of
hydrological conditions (3 runoff components, ETR, snow melt…)
spatial distribution of hydrologic characteristics
diverse options for land management
river chemistry comprehensive definition of soil
characteristics calculation of components of N-
and P-cycle, distinction between land and water phase
Calculation on daily timestep
-: model calibration in general Number of parameters to be calibrated
on HRU-, subbasin- or basin-level definition of some hydrologic parameter
not on same level (snow melt-basin level, soil-HRU, GW-subbasin)
no connection between GW-recharge and baseflow for N-cycle (no scenario calcuations)
Limitation in applicability regarding catchment area
Erosion (P-emissions) decisively dependent on well calibrated surface runoff components
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NOPOLU
NOPOLU: N-balance; N-surplus + transfer model dep. on soil characteristics part of it to surface waters
Nitrogen input balance used within NOPOLU
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SOURCE APPORTIONMENT
Source apportionment (SA): based on the assumption: Total nitrogen and phosphorus loads at the selected river measurement site (Lriver) represent the sum of the nitrogen and phosphorus discharges from point sources (DP), the nitrogen and phosphorus losses from diffuse sources (LOD) and the natural background losses of nitrogen and phosphorus (LOB). Furthermore retention of nitrogen and phosphorus in the rivers is taken into account (R).
LOD = Lriver - DP - LOB + R
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Applicability of models
Main questions:
- is the model valid for use under the specific catchment conditions being considered?
- what is the temporal and spatial scale at which model output is required, and which chemical species need to be modelled?
- what are the resource limitations (time and data costs) on a particular study (the models vary widely in their high or low data input requirements and time needed for model applications)
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Diffuse sources: Heavy metals
Fuchs, S.; Scherer, U.; Hillenbrand, T.; Marscheider-Weidemann, F.; Behrendt, H.; Opitz, D. (2002): Emissions of Heavy Metals and Lindane into River Basins of Germany. UBA-Texte 55/02, Berlin, Germany
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Diffuse sources: Heavy metals
• Upgrade of nutrient models for application on heavy metal emissions
• MONERIS (Oltmann et al., 2003): addition of heavy metal typical transport processes and specific pathways to the basic module:
• historic mining activities
• shipping
• Update of input data concerning heavy metals
•Data inquiries to improve the input data are needed
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Summary & Conclusion
Diffuse sources represent an important source for nutrients and heavy metals into the aquatic environment
Calculation/ modeling of diffuse source pollution is an issue for water experts ask at universities, ministries, water associations
Diffuse sources issue of WFD contact administrative bodies responsible for WFD - implementation
Different models vary considerably as regards input data, complexity, resources needed and level of process representation
Choice of methodology/ model used individually based on requirements in a country
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Thank you for your attention!