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Management Unit of the North Sea Mathematical Models (MUMM),

3 rd OSPAR Workshop on Eutrophication Modelling (ICG-EMO) “Transboundary nutrient fluxes” MUMM, Brussels, 07-09 Sep 2009. Belgium contribution Geneviève Lacroix 1 , Kevin Ruddick 1 , Christiane Lancelot 2. Management Unit of the North Sea Mathematical Models (MUMM),

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Management Unit of the North Sea Mathematical Models (MUMM),

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  1. 3rd OSPAR Workshop on Eutrophication Modelling (ICG-EMO) “Transboundary nutrient fluxes” MUMM, Brussels, 07-09 Sep 2009 Belgium contribution Geneviève Lacroix1, Kevin Ruddick1, Christiane Lancelot2 • Management Unit of the North Sea Mathematical Models (MUMM), • Royal Belgian Institute for Natural Sciences (RBINS), • 2. Ecologie des Systèmes Aquatiques (ESA), Université Libre de Bruxelles (ULB) AMORE 3 Advanced Modeling and Research on Eutrophication) Belgian Science Policy

  2. MIRO&CO-3D model: setup • Standard run: validation Time series (NL, UK, BE) / surface distribution (BE) • Standard run: TBNT • Water mass origin: passive tracer • Nutrient origin: sensitivity analysis (-1% river input) • Conclusions - ?  Discussion

  3. MIRO&CO-3D model: setup • Standard run: validation Time series (NL, UK, BE) / surface distribution (BE) • Standard run: TBNT • Water mass origin: passive tracer • Nutrient origin: sensitivity analysis (-1% river input) • Conclusions - ?  Discussion

  4. Forcing: • 6h meteo RF (UKMO/ECMWF) • 01/02 • - Real river input (daily flow) +NL/UK rivers • - small BE/FR • - Weekly SST (BSH) Rivers: Nutrient loads (bi-)monthly Some diff., + NL/UK rivers - small BE/FR MIRO&CO-3D model:setup Configurations “STD” “ICG-EMO” (Lacroix et al. 2007. JMS) PAR attenuation (kPARv1): KPAR=f(chl, TSM, CDOM) model estimated from salinity SeaWiFS seasonal climatology Ecosystem model MIRO-0D (ESA) Hydrodynamic model COHERENS-3D (MUMM) • Open BC • Current, elevation • from CSM 2D • - S, nutrients • imposed (ICES data) • T, biological state var. • gradient 0 • Grid: • 5.8 km long. x 4.6 km lat • 5  layers • Period: • 1991-2006 1993-2002 coupling (Lacroix et al. 2004. JSR) (Lancelot et al. 2005. MEPS)

  5. MIRO model MIRO biogeochemical model (C, N, P, Si cycles) Nutrients: - Nitrate [NO3] - Ammonia [NH4] - Phosphapte [PO4] - Dissolved silica [DSi] Phytoplankton (3 groups): - Diatoms [DA, 3 forms*], - Nanophytoflagellates [NF, 3 forms*], - Phaeocystis colonies [OP, 3 forms*] and mucus [OPM] * 3 forms (Reserve [xR], Functional [xF], Monomeric Substrates [xS]) Zooplankton: - Microzooplankton [MZ] - Copepeods [CP] Bacteria [BC] DOM: - Bacteria-available carbon monomeric substrates [BSC] - Bacteria-available nitrogen monomeric substrates [BSN] - Dissolved organic C, N & P of high (1) and low(2) biodegradability [DC1], [DC2], [DN1], [DN2], [DP1], [DP2] POM: - Particulate organic C, N & P of high (1) and low(2) biodegradability [PC1], [PC2], [PN1], [PN2], [PP1], [PP2] Biogenic Silica [BSi] Benthic diagenesis (C, N, P) (Lancelot et al. 2005. MEPS)

  6. MIRO&CO-3D model: setup • Standard run: validation Time series (NL, UK, BE) / surface distribution (BE) • Standard run: TBNT • Water mass origin: passive tracer • Nutrient origin: sensitivity analysis (-1% river input) • Conclusions - ?  Discussion

  7. Underestimation? River input? TBNT simulation without small BE rivers (Leie, Ijser) Model validation: surface distribution (BE) Model : mean February Data: 4-6 February 2002 (BELGICA campaign BE2002/02A) - BMDC mmolP/m³ mmolN/m³

  8. +15d Mean April Underestimation? Timing? River input? Nutrient underestimation Model validation: surface distribution (BE) Model : 27 March Data: 26-27 March 2002 (campaign BE2002/08A) - BMDC mgChl/m³ 27 March

  9. Model validation:time series (BE) Station 330 1993-2002 Data from BMDC

  10. Model validation:time series (NL) Model: mean 1993-2002 RIKZ data: 1991-2004 Noordwijk 2km Noordwijk 10km Noordwijk 20km

  11. Model validation:time series (NL) Station Noordwijk 10km 1993-2002 Data from RIKZ

  12. Improvements with RECOLOUR (2003-2006) ! Model validation:time series (UK) Dec 2000-2002 Data from CEFAS Western Gabbard (>08/2002) Gabbard (<08/2002) Warp

  13. Model validation:time series (UK) Western Gabbard (>08/2002) • TSM • In ‘Standard’ (ICG-EMO), TSM used for kPAR from seasonal SeaWiFS climatology (97-03) • IMPROVEMENT with ‘RECOLOUR’ TSM • EOFs used to fill the gaps between RS data (clouds,...) • high spatio-temporal resolution (ex. daily) ‘RECOLOUR’ daily TSM 2003-2006 from MODIS Warp Gabbard (<08/2002) Improvements with RECOLOUR (2003-2006) !

  14. MIRO&CO-3D model: setup • Standard run: validation Time series (NL, UK, BE) / surface distribution (BE) • Standard run: TBNT • Water mass origin: passive tracer • Nutrient origin: sensitivity analysis (-1% river input) • Conclusions - ?  Discussion

  15. NLO1 NLC2 UKO1 NLC1 BO1 UKC1 BC1 UKC7 FC2 FO1 TBNT setup:Target areas

  16. RNL1 RUK1 NLO1 NLC2 UKO1 NLC1 BO1 UKC1 Not ‘tagged’ BC1 RBE UKC7 FC2 FO1 RFR1 TBNT setup:Rivers

  17. NBC1 NBC2 0,05 sv 0,005 sv NLO1 NLC2 UKO1 0,0005 sv NLC1 BO1 UKC1 BC1 UKC7 WBC3 FC2 FO1 WBC2 WBC1 TBNT results:transport across transects (2002)

  18. TBNT results:nutrient fluxes computation For all target areas (2002) • Monthly mean (29.5 days) • Fluxes across transects & national boundaries • DIN, DON, PON  Ntot • DIP, DOP, POP  Ptot • Fluxes between water column & benthos • Ntot, Ptot • Daily • River loads (DIN, DIP, Norg, Porg  Ntot, Ptot) • RBE  NLC1 • RNL1  NLC2 • RFR1  FR2 • RUK1  UKC1, UKC7, UKC9 • Temporal average: • Growing season (Mar-Sep) • Winter (Oct-Feb) • - Annual

  19. TBNT results:nutrient ‘transport’ fluxes BC1 Seasonal differences (magnitude & direction for Ntot) ‘transport’ across transects 4.9 kTN/y 5.7 kTP/y

  20. TBNT results:nutrient budget BC1 Seasonal differences (magnitude & direction) ‘transport’ across transects river input (not in all areas) ‘transport’ across transects

  21. ~ denitrification << ‘Transects’ winter > growing seasonal var. winter: - < ‘Transects TBNT results:nutrient budget all target areas + import - export TOTAL ~// transects

  22. (NL –> UK) 4894 m³/s 16 kTN/y 9.19 kTP/y NOOS transects 0,05 sv NOOS 12 UK –> BE 234 m³/s -0.49 kTN/y 0.65 kTP/y National boundaries 0,05 sv 0,0005 sv NOOS 14 NOOS 13 BE –> NL 49623 m³/s 197 kTN/y 100.60 kTP/y FR –> BE 49324 m³/s 193 kTN/y 99.68 kTP/y FR –> UK 13300 m³/s 48 kTN/y 27.05 kTP/y NOOS14 NOOS13 NOOS12 Volume (m3/s) 93219 94751 97919 Ntot (kTN/y) 235 353 637 Ptot (kTP/y) 187.74 193.20 209.35 TBNT results: transport across national bound. + NOOS transects Annual mean (2002) NLO1 NLC2 UKO1 NLC1 BO1 UKC1 BC1 UKC7 FC2 FO1

  23. Mean NPP ~ proportional to nutrient conc. exepted BC1 & UKC1 Stronger light limitation? TBNT results:mean nutrient & NPP

  24. MIRO&CO-3D model: setup • Standard run: validation Time series (NL, UK, BE) / surface distribution (BE) • Standard run: TBNT • Water mass origin: passive tracer • Nutrient origin: sensitivity analysis (-1% river input) • Conclusions - ?  Discussion

  25. 52.5 52 51.5 51 Latitude (°N) 50.5 50 49.5 49 48.5 -4 -3.5 -3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Longitude (°E) depth (m) Water mass contribution:setup To determine the origin of the waters and the relative contribution of the rivers  1°) passive tracers NBC water RUK1 Thames + 16 rivers RNL1 North Sea Canal Rhine Meuse Initial water RBE Scheldt RFR1 Canche Authie Somme Seine Initial water WBC water

  26. WBC: 77 %  98 % Water mass contribution:results (2002) NBC: 1 %  20 % (UKC1) River contribution 1 %  6 % (C) NLC1 UKO1 UKC1 BC1 UKC7 BO1 FC2 FO1

  27. WBC: 77 %  98 % Water mass contribution:results (2002) NBC: 1 %  20 % (UKC1) River contribution 1 %  6 % (C) NLC1 UKO1 UKC1 BC1: 50 % from RBE & RNL1 45 % from RFR1 5 % from RUK1 BC1 UKC7 BO1: 17 % from RBE & RNL1 69 % from RFR1 14 % from RUK1 BO1 FC2 FO1

  28. MIRO&CO-3D model: setup • Standard run: validation Time series (NL, UK, BE) / surface distribution (BE) • Standard run: TBNT • Water mass origin: passive tracer • Nutrient origin: sensitivity analysis (-1% river input) • Conclusions - ?  Discussion

  29. -1% N & P NBC  Run TNB 52.5 52 -1% N & P RUK1  Run TUK 51.5 51 -1% N & P WBC  Run TWB -1% N & P RNL1  Run TNL Latitude (°N) 50.5 50 -1% N & P RBE  Run TBE 49.5 49 -1% N & P RFR1  Run TFR 48.5 -4 -3.5 -3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Longitude (°E) depth (m) Nutrient origin:setup To determine the origin of the nutrients and the relative contribution of the rivers  2°) sensitivity analysis NBC water RUK1 Thames + 16 rivers RNL1 North Sea Canal Rhine Meuse Initial water RBE Scheldt RFR1 Canche Authie Somme Seine Initial water WBC water 1997-2002 -1 %  linearity

  30. Nutrient origin:preliminary results SENSITIVITY ANALYSIS BC1 impact NPP: RBE >> RNL1~RFR1 impact nutrients: RBE ~ RFR1 > RNL1 BO1 impact RFR1 >> TBE TNL TFR TUK No TWB TNB 2000 When all results  % of variability due to each ‘contributor’

  31. MIRO&CO-3D model: setup • Standard run: validation Time series (NL, UK, BE) / surface distribution (BE) • Standard run: TBNT • Water mass origin: passive tracer • Nutrient origin: sensitivity analysis (-1% river input) • Conclusions - ? Discussion

  32. Validation:Bloom timing (importance TSM)Underestimation ChlMax Conclusions • TBNT: • Water transport: FR  BE, BE NL, UK BE (<<<), FR UK(<) • Nutrient transport: // except N (BE UK) • N & P budget: Seasonal differences (magnitude & direction) • Total annual budget // fluxes across transects • River contribution to total annual budget <<< transport across transects • Benthos fluxes of N ~= transport across transects • Benthos fluxes of P << transport across transects • Water mass contribution: • Significant contribution of ‘Atlantic water’ (river contribution: 1% - 6%) • As ‘expected’ contribution of national rivers  national target areas • Origin nutrients: • Previous study: Atlantic water contribution  BE waters (~60% PO4, ~50 % DIN) • - Preliminary results: Significant contribution of RBE & RNL1 (C), RFR1 (O)  BE waters

  33. Questions for discussion • Comparison between models - Objective validation (Taylor diagram?) - If they are differences between model results (TBNT)  how to determine origin of differences • Sensibility to BC? • Interannual variability?

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