Presentation by Luca van Duren, Deltares, The Netherlands, at the Delft3D - User Days (Day 3: Water quality and ecology), during Delft Software Days - Edition 2017. Wednesday, 1 November 2017, Delft.

1. 1 November 2017
Coupled physical – ecological models to
assist assessment of effects of sand mining
along the Dutch coast
Luca van Duren, Tineke Troost, Anouk Blauw, Lilith Kramer, Jeroen
Wijsman, Johan Craeymeersch, Peter Herman, Theo van der Kaaij
and Nicki Villars

2. 2 Sand mining initiatives 2018 - 2027
 RWS – 140 (120) 106 m3 for coastal nourishments
 LaMER Foundation – 165 (135) 106 m3 commercial sand mining (construction)
1 November 2017Coupled physical-ecological models to support EIAs 2
 What are the effects of increasing the fine sediment load on the North
Sea and Wadden Sea?
 Analogous to EIA – 2012
 Support for EIA, carried out by SWECO

3. Effect chain approach
1 November 2017Coupled physical-ecological models to support EIAs 3
HABITAT rule-based
MOSSEL Modules
Delft3D-WAQ (DELWAQ)
Silt - light
Delft3D-FLOW
Ecosystemmodels
sand mining dischargesclimate fisheries conservationshipping
Externalfactors/
humanpressures
nutrients
waves
flow light
temp.
silt
algae
sea bed
plankton fish
benthic fish
birds
Ecosystem
benthos
seagrass

4. Coupled models
1. Hydrodynamics
2. Waves
3. Fine sediment

5. Coupled models
1. Hydrodynamics
2. Waves
3. Fine sediment
4. Ecological modelling
 Water quality
 Primary production
 Shellfish growth (DEB models
dynamically integrated in
DELWAQ-ECO)

6. Dynamic Energy Budget models
1 November 2017Coupled physical-ecological models to support EIAs 6
DEB assumes:
- Foraging scales with surface area
- Maintenance scales with biovolume
Isomorph organism:
- Surface area ~ L2
- Volume ~ L3
 Growth changes with size (age)
Energy reserves don’t require maintenance
 Scale relations body size
food faecesgut
blood
biovolume
maturity
reproductive
stage
eggs
somatic
maintenance
storage
maturity
maintenance

1 2
3
4
5
6
7
8 9
10
11

pseudo-
faeces
food faecesgut
blood
biovolume
maturity
reproductive
stage
eggs
somatic
maintenance
storage
maturity
maintenance

1 2
3
4
5
6
7
8 9
10
11

pseudo-
faeces

7. The trouble with shellfish
1 November 2017Coupled physical-ecological models to support EIAs 7
Recruitment poorly understood
 Habitat suitability important – is
influenced presence of shellfish beds
 Timing of spring bloom crucial
 Probably strong top-down control through
predation
 Often hardly any relationship between
larval production and recruitment
 Bottleneck for deterministic modelling
 Use models as tools to gain insight in
system dynamics – not as predictive tools

8. STEPS AND CHOICES

9. Fine sediment - adjustments
1 November 2017Coupled physical-ecological models to support EIAs 9
 Fine sediment module developed and calibrated
near the coast. The boundaries have no
seasonal dynamics; open sea has little
seasonal dynamics
• Major effect on ecology.
 Near the coast: direct forcing from
sediment model, open sea forcing with
cosine function

10. Fine sediment - adjustments
1 November 2017Coupled physical-ecological models to support EIAs 10
 Fine sediment module developed and calibrated
near the coast. The boundaries have no
seasonal dynamics; open sea has little
seasonal dynamics
• Major effect on ecology.
 Near the coast: direct forcing from
sediment model, open sea forcing with
cosine function
 Concentrations Wadden Sea far too low due to
low resolution
• Would have major impact on ecology
• Fine-scaled PACE model available
 Concentrations scaled with PACE model

11. DEB choices
1 November 2017Coupled physical-ecological models to support EIAs 11
Start simple: fewer variables = easier to parameterise and initialise
1. DEB kiss: assumes no reserves
2. Steady state: assumes – reserves in balance with environment (OK for
small organisms, e.g. plankton)
3. V1-morph: assumes constant surface – volume ratio (i.e. constant
size distribution within a population)
V1morph: population is calculated as ‘total biomass’ with an average
length (weighted with structural volume). I.e. this does not take changing
surface-volume ratio throughout development.
A population can be modelled as a collection of V1 morphs

12. DEB choices (2)
1 November 2017Coupled physical-ecological models to support EIAs 12
Ideal: model all populations as iso-morph, with calibrated recruitment, species
specific predation and species specific habitat preference

13. DEB choices (2)
1 November 2017Coupled physical-ecological models to support EIAs 13
 2 species V1 morphs, with
location preference determined
on observations
Ideal: model all populations as iso-morph, with calibrated recruitment, species
specific predation and species specific habitat preference

14. DEB choices (2)
1 November 2017Coupled physical-ecological models to support EIAs 14
 2 species V1 morphs, with
location preference determined
on observations
 Ensis grows in North Sea coast
Ideal: model all populations as iso-morph, with calibrated recruitment, species
specific predation and species specific habitat preference

15. DEB choices (2)
1 November 2017Coupled physical-ecological models to support EIAs 15
 2 species V1 morphs, with
location preference determined
on observations
 Ensis grows in North Sea coast
 Wadden Sea: mussels as
model shellfish
Ideal: model all populations as iso-morph, with calibrated recruitment, species
specific predation and species specific habitat preference

16. DEB choices (2)
1 November 2017Coupled physical-ecological models to support EIAs 16
 2 species V1 morphs, with
location preference determined
on observations
 Ensis grows in North Sea coast
 Wadden Sea: mussels as
model shellfish
 All model grid cells are seeded
with 1 isomorph larva as
indicator for vulnerability
Ideal: model all populations as iso-morph, with calibrated recruitment, species
specific predation and species specific habitat preference

17. RESULTS

18. Monitoring areas
1 November 2017Coupled physical-ecological models to support EIAs 18
Model results in terms of fine
sediment increase and ecological
effects (primary production and
shellfish growth) Averaged over 26
monitoring areas

19. Wadden Sea (mussels)
1 November 2017Coupled physical-ecological models to support EIAs 19
Shellfish biomass
 Results right order of magnitude
 Visual match on locations of high
concentrations

20. Wadden Sea - shellfish
1 November 2017Coupled physical-ecological models to support EIAs 20
• Mussel plots (purple / pink)
• Mussels and oysters (blue, red, and green,
yellow and orange dots)
• Top benthos location from SIBES (orange,
red, purple)

21. Wadden Sea: corrections benthic primary production
1 November 2017Coupled physical-ecological models to support EIAs 21
 Total primary production in line with
measurements (≈150 g C/m2/yr in Western
Wadden Sea)
 Proportion benthic algae too low in model
 They can resuspend and become food for
mussels
 Benthic algae grow fixed in shallow areas; get
little effect from turbidity
 Based on literature values for benthic primary
production and morphological data a correction
has been calculated for primary production

22. Wadden Sea: corrections benthic primary production
1 November 2017Coupled physical-ecological models to support EIAs 22
 Total primary production in line with
measurements (≈150 g C/m2/yr in Western
Wadden Sea)
 Proportion benthic algae too low in model
 They can resuspend and become food for
mussels
 Benthic algae grow fixed in shallow areas; get
little effect from turbidity
 Based on literature values for benthic primary
production and morphological data a correction
has been calculated for primary production
 Based on literature data on availability of MPB
for shellfish in relation to wind the reduced effect
on shellfish was calculated

23. North Sea (Ensis)
1 November 2017Coupled physical-ecological models to support EIAs 23
Modelled shellfish biomass in correct order of magnitude
500 g/m2
0 g/m2
250 g/m2

24. Ensis
1 November 2017Coupled physical-ecological models to support EIAs 24
 Ensis not everywhere in
equilibrium
 Sometimes very
disproportional reactions to
changes in fine sediment and
primary production

25. Effect size V1 morph
1 November 2017Coupled physical-ecological models to support EIAs 25
VanderVeer
Schellekens/DELWAQ
 Simplified 1D model with 2
parameter sets
 Large animals are slower in
reaching equilibrium than smaller
ones and may not survive in areas
with low productivity.
 This is sensitive to parameter set:
In left set, individuals of 7 cm3 can
still grow but not with the
DELWAQ set

26. Overall results Ensis
1 November 2017Coupled physical-ecological models to support EIAs 26
Increase[mud]
High Ensis biomass
(shallow)
Average Ensis biomass
(9-21 m depth)
Low Ensis biomass
(deep)
Biomass
(V1-morf)
Length growth
(isomorph,
juvenile)
Biomass
(V1-morf)
Biomass
(V1-morf)
Length growth
(isomorph,
juvenile)
Length growth
(isomorph,
juvenile)
Increase[mud]
Increase[mud]

27. What we think will happen
1 November 2017Coupled physical-ecological models to support EIAs 27
biomass
Length (cm)
Biomass distribution in
reference scenario
Expert judgement model
interpretation of biomass
distribution in sand mining
scenario
0 104 62 8 12 14 16 18
Model prediction of biomass
distribution in sand mining
scenario

28. Results summary
1 November 2017Coupled physical-ecological models to support EIAs 28
 Overall increase in SPM, leads to proportional reduction in primary production and shellfish
biomass
 Usually effects of sand mining are small (few %), with some local extremes particularly in
the North Sea
 Wadden Sea
• Some disproportional reduction in very small edges along gullies – does not affect the
total and is possibly a grid artefact
• Compensation for benthic primary production order of magnitude 10% reduction in
effects
 North Sea:
• Disproportional reduction in marginal areas. This may partially be realistic, but
partially a result of over-estimation due to the use of large V1-morphs.
• Marginal areas are large in comparison to shellfish beds. Averaging over whole
compartments may result in large decrease → not ecologically relevant!
 Primary driver for large-scale distribution of organisms is food

29. Conclusions regarding model use
1 November 2017Coupled physical-ecological models to support EIAs 29
 Complex set of problems requires
multidisciplinary team
 Quite a few corrections were required – need
to be fixed for next time.
 Lack of fundamental knowledge (recruitment /
habitat) and DEB simplification requires a lot
of communication on model results and how to
use model results –
Results can’t be used at face value

30. QUESTIONS?