2015 DHI UK & Ireland Symposium Birds, Bats and Beyond – What’s that got to do with Water? Nick Elderfield (DHI), Tuesday 21 April 2015 at 12:40 - 13:00 Innovation in modelling water environments is what DHI has been about for over 50 years. A detailed understanding of the controlling physical conditions, coupled with a behavioural knowledge of critical species dependant on the water environment, provides a scientifically robust approach to assessing historic and future change spatially and temporally. Our habitat modelling approach has been successfully applied on a number of projects in the UK and the wider North Sea region, combining expertise in water environments with the critical issues for today’s projects. Models always rely on data and, to this end, DHI have developed sensing technologies from low cost, web-ready devices to integrated observation systems for birds and mammals.

1. Birds, Bats and Beyond!
DHI Solutions
Nick Elderfield
Managing Director DHI UK

2. Introduction
© DHI #2

3. © DHI
DHI in the UK
• UK company since 2012 – history since 1990’s
• Improved Software Customer Care
• Local contact for Consultancy business
• Consultancy - Niche focus within Water
• Office in Southampton

4. © DHI
Our areas of expertise
to help solve the world’s toughest challenges in water environments
Aqua- & agriculture Marine structure & energy Climate change
Coast & marine Surface & ground water Urban water
Industry Environment & ecosystems Product safety & environmental risks
#4

6. © DHI
MIKE CustomisedMIKE by DHI

7. The basis for MIKE Customised
© DHI
…manage, organise and
analyse large amounts
of data
…share information and
data to increase
efficiency
…get the full benefit of
real-time monitoring and
early warning systems
…optimise operations
and planning

8. Technology led
Innovative use of sensing technology
Sense and rad
Combining numerical models for marine planning
Feedback Environmental Monitoring &
Mitigation Plans
Vessel motion

9. Birds & bats
© DHI #9

10. Bird collision avoidance study
Objective: To improve the evidence base informing bird collision avoidance rates to
inform consenting decisions
15 Participants: DONG Energy, EDF, Eneco, Fluor, Mainstream Renewable
Power, RWE, Scottish Power Renewables, Siemens, SSE, Statoil, Statkraft,
Vattenfall, DECC, The Crown Estate and Marine Scotland
Approach: Install state of the art monitoring equipment at Vattenfall’s Thanet
Offshore Wind farm to monitor micro, meso and macro bird avoidance
behaviours.
Duration: 2.5 years, starting March 2014
Benefits:
• Start using the outcomes of this study from February 2015
• Bi-annual interim reports to be published
• Study outcomes accepted by SNCBs
• Empirical evidence to improve collision risk models
• Greater certainty on the true risk of bird collisions

11. Project Aim
1 May, 2015© DHI #11
Aims
• Select suitable equipment to measure:
• Macro
• Meso
• Micro avoidance behaviour
• If appropriate, collision impacts
• Location: one or more offshore wind farms
• Outputs:
(1) robust evidence on rates of avoidance and collision for 5 key species
(2) Determine how these data can be applied to support consenting
applications.

12. Traditional approaches for bird surveys
• Observers (Rangefinders)
• Radars
• Cameras
• Aerial surveys etc.
• We want: Good data coverage with species ID
1 May, 2015© DHI #12
We want: Good data coverage with species ID

13. New technology for bird observation
1 May, 2015© DHI #13

14. New technology for bird observation

15. Technology
1 May, 2015© DHI #15
FPGA running
DAPS
PC running
DAPS-Control and
TADSTracker software
Disk array for
tracks- and
video storage

16. How does it work
1 May, 2015© DHI #16
[Movies removed for pdf]

17. Advantages of new technology
• Automation
• Bigger sample sizes (including nights, “rough” weather
conditions etc.)
• Species ID (by viewing of footage by ornithologists)
1 May, 2015© DHI #17

18. Forthcoming developments
• Zooming of camera
• Extend it to different species: e.g. bats
• Wider application for EIA, spatial
planning, scheme specific monitoring
• Use of vertical radars to automate the
height tracking
1 May, 2015© DHI #18
[Movie removed for pdf]

19. Habitat Modelling
1 May, 2015© DHI #19

20. Problem: lack of a comprehensive planning process
Danish Wind Power Research 2013© DHI #20
Shell Flats:
Common Scoter
Docking Shoal:
Sandwich Tern
London Array
(Phase 2):
Red-throated Diver

21. Acceptance criterion: cumulative impact is sustainable at
population level
Danish Wind Power Research 2013© DHI #21
Regional assessments required

22. The Technology Approach
1 May, 2015© DHI #22
- Key Dynamics
resolved by models
Hydrodynamic
Models
- Use of available data
to inform species
understanding
- Statistical
representation
Environmental
Models
- Evaluation of
predictive accuracy
- Assessment of model
fit
- Maps of species
distribution
Integrated
SolutionStratification
(dynamic)
Bottom
slope
Currents
(dynamic)
Bottom
substrates
Distance
to land
Upwelling
(dynamic)
Benthic food
supply
(dynamic)
Hydrographic
fronts
(dynamic)
Water
depth

23. From habitat model to spatial planning tool
1 May, 2015© DHI #23
+
~
Observed
species
Hydrodynamic
models
Static GIS
predictors
Predicted
distribution
2)
1)
Spatial planning of
OWF licenses
Multi-year hindcast of
baseline animal distributions
in development regions
Cumulative impact
assessments
OWF development
scenarios. Calculation of
- Displacement
- Changes in density
- Mortality
3)
Pressure
mapping
+
Spatial Planning of
Marine Licenses
Cumulative Impact
Assessments
Renewables development
scenarios. Calculation of:
• Displacement
• Changes in density
• Mortality
Multi-year hindcast of
baseline animal
distributions in
development zones

24. Challenge to move down in scale
Danish Wind Power Research 2013

25. Downscaling of dynamic habitats
© DHI #25
MIKE3 system for
currents utilizing
flexible mesh – 4
domains: 5000m,
2000m, 300m and
100m
10 zigma layers

26. Thames diver model
Response variable:
P/A of Red-throated Divers
during winter 2004/2005
Environmental variables:
Extracted based on position and
time (linear interpolation
between time steps of 1 h)
• U:tidal stage (interaction
term)
• V:tidal stage (interaction
term)
• Current speed
• Water depth
• Bottom slope
• Current gradient Danish Wind Power Research 2013

27. Horns Rev harbour porpoise model
© DHI #27

28. Ship density and surface sediments
Ship density Surface sediments

29. Mean eddy activity and summer stratification
Eddy activity Summer stratification

30. Beyond
© DHI #30

31. Vessel Motion
1 May, 2015© DHI #31
• WAMSIM
• Wave diffraction force
• Six degrees of freedom
• Time domain
• Panel model of vessels
• Integration with MIKE by DHI
outputs
• Application to realtime – drifting
vessels, underkeel clearance

32. Drifting Vessels
© DHI #32
• Probabilistic assessment of drifting
vessels

33. Feedback EMMP Approach
1 May, 2015© DHI #33
Feedback Loop for Continual Improvement
• Sediment flux and TSS online monitoring
used to validate and update hindcast and
forecast models
• Hindcast modelling used to update spill
budgets
• Habitat monitoring used to update
tolerance limits and spill budgets
• Forecast modelling and spill budgets
used to update production methods/rates
• Continuous improvement cycle
throughout the course of the project
Daily Spill Budget Control

34. Thank you for your attention …
nje@dhigroup.com
© DHI #34