Symposium Water Quality and Ecological modelling

1. DSD-INT 2014: 3 November 2014
Optimisation of the nutrient reduction strategy for the North Sea
IenM/RWS WVL : Ronald van Dokkum Deltares: Tineke Troost , Hans Los, Jan v. Beek, Christophe Thiange, Marc Weeber, Joost v.d Roovaart, Sibren Loos

2. Contents
1.Introduction
2.Approach
3.Results
4.Conclusions
2

3. 3
Eutrophication in the North Sea
Nuisance blooms
•scum layers, bad odour, foam on beaches
Oxygen depletion
•mortality of benthic fauna
Phaeocystis

4. 4
Assessment of ecological status
2008

5. Nitrogen targets (winterconc DIN mg/l)
In case of overlapping targets the most strict of the two is considered
5
Offshore targets (OSPAR)
Coastal targets (WFD)

6. 6
Project objective
• Starting point: Several areas with present nutrient concentrations
• Desired end point: target nutrient concentrations
• Potential Measures: River load reductions
Objective: To find the optimal set of river load reductions to meet all targets

7. Contents
1.Introduction
2.Approach
3.Results
4.Conclusions
7

8. 8
Modeling approach
due to:
-Transboundary transport of nutrients
-Biogeochemical processes
-Limiting factors may vary (e.g. nitrate, phosphate, light)
Relative reduction (%) in chlorophyll concentration following 50% river loads reduction
Non-linear response of the ecosystem to reduced river loads

9. Integrated catchment and coastal model
9
Hydrology: SOBEK-RR Hydrodynamics: Delft3D-FLOW

10. 10
biogeochemical processes: Delft3D-WAQ
•N, P, Si, plankton, detritus , O2
•4 functional groups: diatoms, flagellates, dinoflagelates, Phaeocystis
•3 phenotypes adapted to environmental conditions (light, N, P limitation)
•Nutrient uptake, respiration, mortality + ‘grazing’
•Decay in water & sediments, nitrification, denitrification: parameterised
•O2 production, consumption, reareation
•Light extinction (CDOM, SPM, algae, detritus)
(see e.g. Los & Wijsman, JMS, 2007)
AlgaePNCNNH4-NNO3-NPPO4-PDetritus PNCsettlingsettlingrespirationphotosynthesisNutrientmineralisationmineralisationmetabolismmortalityDOproductionconsumptionreaerationDetritus in SedimentC N P SiSiSiN2 denitrificationmineralisation& nitrificationautolysisSiconsumptionnitrificationGrazersgrazinggrazingoxygen consumptionbiodepositionAIPadsorptionMicrophytobenthosC N P SiAIP in sedimentsettlingmortalityphotosynthesis

11. How to determine required nutrient reductions
Traditional approach (source oriented)
•Change some forcings (river loads)
•Rerun several times (scenarios)
•Look at difference between scenarios and base case
11
?
Current situation
Desired end point

12. How to determine required nutrient reductions
12
Alternative approach (target oriented)
1. Labelling: follow fate and transport of all nutrients
2. Set up composition matrix
3. Apply optimization technique
Current situation
Desired end point

13. Step 1. Labelling nutrients
13
• Labeling the nutrients when they enter the system and following
them throughout time and space
FR
BE
NL2
NL1
GM
UK1
UK2
Atlantic
Channel
Atm
Dep
NH4
NH4r
flux
shadow flux
NH4r / NH4 x flux

14. 14
Step 2: From labelling to Composition Matrix
Labelling Technique
Area/River BE FR GM NL1 NL2 UK1 UK2 CH NA ATM PO4
UKC6 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000288 0.000012 0.022190 0.000000 0.02249
UKO5 0.000000 0.000002 0.000004 0.000002 0.000000 0.000003 0.000025 0.000244 0.022566 0.000000 0.022846
NO2 0.000003 0.000017 0.000025 0.000024 0.000001 0.000030 0.000236 0.002374 0.020817 0.000000 0.023527
DO1 0.000085 0.000215 0.000263 0.000612 0.000043 0.000435 0.001901 0.017441 0.014486 0.000000 0.035481
DC1 0.000252 0.000558 0.001977 0.002379 0.000222 0.000635 0.001018 0.030624 0.008692 0.000000 0.046357
UKC5 0.000000 0.000001 0.000001 0.000001 0.000000 0.000001 0.000657 0.000046 0.023142 0.000000 0.023849
UKC4 0.000000 0.000002 0.000001 0.000001 0.000000 0.000002 0.000378 0.000060 0.022880 0.000000 0.023324
DO2 0.000002 0.000016 0.000014 0.000016 0.000001 0.000027 0.000242 0.002743 0.020642 0.000000 0.023703
UKC3 0.000000 0.000001 0.000001 0.000001 0.000000 0.000002 0.003233 0.000048 0.022592 0.000000 0.025878
UKO4 0.000001 0.000004 0.000001 0.000003 0.000000 0.000005 0.000084 0.000107 0.021042 0.000000 0.021247
NLO3 0.000001 0.000012 0.000001 0.000008 0.000001 0.000022 0.000416 0.000890 0.020350 0.000000 0.021701
GO3 0.000002 0.000013 0.000002 0.000010 0.000001 0.000023 0.000372 0.001708 0.020178 0.000000 0.022309
DWD1 0.000237 0.000467 0.001962 0.002312 0.000248 0.000378 0.000117 0.008755 0.000984 0.000000 0.01546
UKO3 0.000001 0.000005 0.000001 0.000003 0.000000 0.000006 0.000197 0.000127 0.021148 0.000000 0.021488
GO2 0.000059 0.000172 0.000008 0.000253 0.000013 0.000524 0.002121 0.013181 0.014801 0.000000 0.031132
NLO2 0.000020 0.000084 0.000000 0.000065 0.000002 0.000198 0.001332 0.003989 0.018964 0.000000 0.024654
DWD2 0.000334 0.000651 0.003289 0.003239 0.000345 0.000558 0.000216 0.013368 0.001074 0.000000 0.023074
UKC2 0.000011 0.000090 0.000000 0.000019 0.000000 0.000206 0.003137 0.007305 0.015703 0.000000 0.026471
UKO2 0.000038 0.000271 0.000000 0.000060 0.000000 0.000436 0.001268 0.010237 0.012667 0.000000 0.024977
GO1 0.000458 0.000858 0.000415 0.002850 0.000232 0.001867 0.001296 0.044914 0.002917 0.000000 0.055807
GC1 0.000571 0.001017 0.003236 0.005270 0.000587 0.001169 0.000514 0.039424 0.001860 0.000000 0.053648
UKC1 0.000089 0.000793 0.000000 0.000132 0.000000 0.007237 0.000615 0.019530 0.001030 0.000000 0.029426
GWD1 0.000413 0.000764 0.020616 0.004109 0.000474 0.000637 0.000188 0.013233 0.000616 0.000000 0.04105
UKO1 0.000126 0.001022 0.000000 0.000201 0.000000 0.001455 0.000088 0.024638 0.000210 0.000000 0.02774
NLO1a 0.000432 0.001254 0.000000 0.000852 0.000000 0.001217 0.000008 0.024627 0.000013 0.000000 0.028403
NLO1b 0.000168 0.000701 0.000000 0.000481 0.000010 0.001295 0.001498 0.019549 0.004623 0.000000 0.028325
UKC7 0.000002 0.000455 0.000000 0.000003 0.000000 0.000248 0.000001 0.027388 0.000001 0.000000 0.028098
BO1 0.000184 0.001055 0.000000 0.000360 0.000000 0.000990 0.000007 0.025638 0.000002 0.000000 0.028236
FO1 0.000006 0.001187 0.000000 0.000010 0.000000 0.000152 0.000001 0.026008 0.000001 0.000000 0.027365
UKC8 0.000000 0.000219 0.000000 0.000000 0.000000 0.000422 0.000000 0.022732 0.000000 0.000000 0.023373
BC1 0.001958 0.001340 0.000000 0.004015 0.000000 0.000665 0.000003 0.019743 0.000005 0.000000 0.027729
NLC1 0.006215 0.001217 0.000000 0.008665 0.000000 0.000982 0.000004 0.019279 0.000023 0.000000 0.036385
NLC2a 0.001144 0.001249 0.000000 0.011720 0.000000 0.001231 0.000005 0.023109 0.000027 0.000000 0.038485
NLC2b 0.000858 0.001238 0.000000 0.009147 0.000039 0.001896 0.000071 0.028759 0.000070 0.000000 0.042078
NLC3 0.000683 0.001126 0.000003 0.004097 0.000238 0.002140 0.000445 0.030589 0.000534 0.000000 0.039855
UKC9 0.000000 0.000054 0.000000 0.000000 0.000000 0.000071 0.000000 0.022430 0.000000 0.000000 0.022555
FC2 0.000004 0.003012 0.000000 0.000008 0.000000 0.000030 0.000000 0.023247 0.000000 0.000000 0.026301
FC1 0.000000 0.000105 0.000000 0.000000 0.000000 0.000000 0.000000 0.022364 0.000000 0.000000 0.022469
GWD2 0.000416 0.000762 0.002443 0.004235 0.000541 0.000744 0.000288 0.030153 0.001288 0.000000 0.04087
NLWD 0.000522 0.000667 0.000408 0.004005 0.005824 0.001097 0.000170 0.021453 0.000289 0.000000 0.034435
…leads to…
Composition Matrix

15. Step 3: Optimisation
15
1. We replace present concentrations by desired reductions
2. Apply an optimisation technique (e.g. Linear Programming)
Area/River BE FR GM NL1 NL2 UK1 UK2 CH NA ATM PO4 PO4Reduction
UKC6 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000288 0.000012 0.022190 0.000000 0.02249 0
UKO5 0.000000 0.000002 0.000004 0.000002 0.000000 0.000003 0.000025 0.000244 0.022566 0.000000 0.022846 0
NO2 0.000003 0.000017 0.000025 0.000024 0.000001 0.000030 0.000236 0.002374 0.020817 0.000000 0.023527 0
DO1 0.000085 0.000215 0.000263 0.000612 0.000043 0.000435 0.001901 0.017441 0.014486 0.000000 0.035481 0
DC1 0.000252 0.000558 0.001977 0.002379 0.000222 0.000635 0.001018 0.030624 0.008692 0.000000 0.046357 0
UKC5 0.000000 0.000001 0.000001 0.000001 0.000000 0.000001 0.000657 0.000046 0.023142 0.000000 0.023849 0
UKC4 0.000000 0.000002 0.000001 0.000001 0.000000 0.000002 0.000378 0.000060 0.022880 0.000000 0.023324 0
DO2 0.000002 0.000016 0.000014 0.000016 0.000001 0.000027 0.000242 0.002743 0.020642 0.000000 0.023703 0
UKC3 0.000000 0.000001 0.000001 0.000001 0.000000 0.000002 0.003233 0.000048 0.022592 0.000000 0.025878 0
UKO4 0.000001 0.000004 0.000001 0.000003 0.000000 0.000005 0.000084 0.000107 0.021042 0.000000 0.021247 0
NLO3 0.000001 0.000012 0.000001 0.000008 0.000001 0.000022 0.000416 0.000890 0.020350 0.000000 0.021701 0
GO3 0.000002 0.000013 0.000002 0.000010 0.000001 0.000023 0.000372 0.001708 0.020178 0.000000 0.022309 0
DWD1 0.000237 0.000467 0.001962 0.002312 0.000248 0.000378 0.000117 0.008755 0.000984 0.000000 0.01546 0
UKO3 0.000001 0.000005 0.000001 0.000003 0.000000 0.000006 0.000197 0.000127 0.021148 0.000000 0.021488 0
GO2 0.000059 0.000172 0.000008 0.000253 0.000013 0.000524 0.002121 0.013181 0.014801 0.000000 0.031132 0
NLO2 0.000020 0.000084 0.000000 0.000065 0.000002 0.000198 0.001332 0.003989 0.018964 0.000000 0.024654 0
DWD2 0.000334 0.000651 0.003289 0.003239 0.000345 0.000558 0.000216 0.013368 0.001074 0.000000 0.023074 0
UKC2 0.000011 0.000090 0.000000 0.000019 0.000000 0.000206 0.003137 0.007305 0.015703 0.000000 0.026471 0
UKO2 0.000038 0.000271 0.000000 0.000060 0.000000 0.000436 0.001268 0.010237 0.012667 0.000000 0.024977 0
GO1 0.000458 0.000858 0.000415 0.002850 0.000232 0.001867 0.001296 0.044914 0.002917 0.000000 0.055807 0
GC1 0.000571 0.001017 0.003236 0.005270 0.000587 0.001169 0.000514 0.039424 0.001860 0.000000 0.053648 0.0080472
UKC1 0.000089 0.000793 0.000000 0.000132 0.000000 0.007237 0.000615 0.019530 0.001030 0.000000 0.029426 0.0058852
GWD1 0.000413 0.000764 0.020616 0.004109 0.000474 0.000637 0.000188 0.013233 0.000616 0.000000 0.04105 0
UKO1 0.000126 0.001022 0.000000 0.000201 0.000000 0.001455 0.000088 0.024638 0.000210 0.000000 0.02774 0
NLO1a 0.000432 0.001254 0.000000 0.000852 0.000000 0.001217 0.000008 0.024627 0.000013 0.000000 0.028403 0
NLO1b 0.000168 0.000701 0.000000 0.000481 0.000010 0.001295 0.001498 0.019549 0.004623 0.000000 0.028325 0
UKC7 0.000002 0.000455 0.000000 0.000003 0.000000 0.000248 0.000001 0.027388 0.000001 0.000000 0.028098 0
BO1 0.000184 0.001055 0.000000 0.000360 0.000000 0.000990 0.000007 0.025638 0.000002 0.000000 0.028236 0.0014118
FO1 0.000006 0.001187 0.000000 0.000010 0.000000 0.000152 0.000001 0.026008 0.000001 0.000000 0.027365 0
UKC8 0.000000 0.000219 0.000000 0.000000 0.000000 0.000422 0.000000 0.022732 0.000000 0.000000 0.023373 0
BC1 0.001958 0.001340 0.000000 0.004015 0.000000 0.000665 0.000003 0.019743 0.000005 0.000000 0.027729 0.0055458
NLC1 0.006215 0.001217 0.000000 0.008665 0.000000 0.000982 0.000004 0.019279 0.000023 0.000000 0.036385 0.007277
NLC2a 0.001144 0.001249 0.000000 0.011720 0.000000 0.001231 0.000005 0.023109 0.000027 0.000000 0.038485 0.01270005
NLC2b 0.000858 0.001238 0.000000 0.009147 0.000039 0.001896 0.000071 0.028759 0.000070 0.000000 0.042078 0.0105195
NLC3 0.000683 0.001126 0.000003 0.004097 0.000238 0.002140 0.000445 0.030589 0.000534 0.000000 0.039855 0.0039855
UKC9 0.000000 0.000054 0.000000 0.000000 0.000000 0.000071 0.000000 0.022430 0.000000 0.000000 0.022555 0
FC2 0.000004 0.003012 0.000000 0.000008 0.000000 0.000030 0.000000 0.023247 0.000000 0.000000 0.026301 0
FC1 0.000000 0.000105 0.000000 0.000000 0.000000 0.000000 0.000000 0.022364 0.000000 0.000000 0.022469 0
GWD2 0.000416 0.000762 0.002443 0.004235 0.000541 0.000744 0.000288 0.030153 0.001288 0.000000 0.04087 0
NLWD 0.000522 0.000667 0.000408 0.004005 0.005824 0.001097 0.000170 0.021453 0.000289 0.000000 0.034435 0

16. Step 3: Optimisation (2 x 2 example)
Ems
Rhine
Reduction
goal
GC1
0.10 * f1
0.12 * f2
≥
0.08
NLC2
0.00 * f1
0.33 * f2
≥
0.13
1.00 * f1
0.00 * f2
≤
0.85
0.00 * f1
1.00 * f2
≤
0.85
16
Goal: Find set of reduction factors f1 and f2 which will achieve the targets and be as cheap as possible
Cost function
10 * f1
100 * f2
Optimal reduction f1 = 0.33, f2 = 0.4

17. Contents
1.Introduction
2.Approach
3.Results
4.Conclusions
17

18. Nitrogen targets (winterconc DIN mg/l)
In case of overlapping targets the most strict of the two is considered
18
Offshore targets (OSPAR)
Coastal targets (WFD)

19. Target concentrations
0
0.5
1
1.5
2
2.5
3
Current
Target
Winterconcentrations of DIN (mg/l)
• only the most strict targets per area are shown;
• the WFD-target for the Ems-Dollard estuary is 1.33 mg/l
19

20. Composition Matrix
20

21. Optimal reduction strategy for uniform costs
Uniform costs (= equal reduction costs for all sectors and countries)  constant costs per water volume
21
Required river load reduction
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1
Scheldt
Ems
Rhine
IJssel
Minimum foreign
reduction
Maximum Dutch
reduction

22. Nutrient loads per sector and country
22

23. Economic costs
23
Economic costs  Reduction costs per sector and increase with reduction percentage.
Agriculture
Sewage water treatment
23

24. Optimal reduction strategy for economic costs – NL reductions only
None of the targets can be achieved!
24

25. Still some targets cannot be achieved!
Optimal reduction strategy for economic costs – NL + foreign reductions
25

26. Replacing infeasible thresholds by minimum attainable concentrations
26
Very costly!
26

27. Replacing infeasible thresholds by alternative concentrations
27
Reasonable targets, and less costly!

28. Consequences for chlorophyll
28

29. Contents
1.Introduction
2.Approach
3.Results
4.Conclusions
29

30. Conclusions
Optimisation method is a quick and powerful tool to:
•optimise nutrient reductions
•check consistency and attainability of targets
•facilitate discussions between stakeholders
30