Bringing the environmental and planning expertise to maximise the value of your investment
Bringing the environmental and planning expertise
to maximise the value of your investment
Modelling bird behaviour to progress wind farm development
Tom HartleyPrincipal GIS Consultant
Atmos Consulting
Our service areas
Renewable energy Sustainable Development Biodiversity Property and Construction Marine and Coastal Water resources Environmental Management
Our specialisms
Environmental Impact Assessment Town Planning Ecology and Ornithology GIS mapping and analysis Noise and Acoustics Hydrology Project Management
Expert technical, environmental and planning support throughout the entire project life-cycle, from feasibility to implementation.
Onshore Wind and GIS
• Historically a good match
• Data has a potentially long shelf life
• Lots of spatial modelling required to assess impacts on sensitive receptors
• Maturing sector and recent changes to subsidies have lead to increased pressure to do more with less
Can’t see the birds?Theoretical modelling of bird activity
Leadhills wind farm• Turbines < 2km from Special
Protection Area
• Lack of activity recorded in Vantage Point surveys
• Uncertainty over potential impacts on key ornithological species – objection from Scottish Natural Heritage
Random Collision Risk Modelling
SNH (2000)
Usually derived from Vantage Point surveys - how to substitute activity levels in the flight risk volume?
• Define the flight risk volume• Calculate how much of this volume is swept by
turbine rotors• Calculate activity levels within this volume for
each species • Calculate the number of bird transits through
the swept rotor volume• Calculate the probability of a bird being hit in
each transit
The Solution
• A model to predict the time spent in the windfarm airspace based on territory / nest locations and ranging behaviour
• Species-specific information derived in part from the Atmos GIS database
The Solution
How to define nest locations?
1. Historical nest locations provided by SNH and local raptor study group
2. Worst case nest locations based on interpretation of aerial photography
3. Random nest locations within SPA based on breeding populations CO
NFIDENTIAL
The Model
• Define nest locations• Map the ranging behaviour per nest• Combine overlapping buffers as a grid• Calculate the time spent in the turbine
envelope• Correct for time spent at risk height• Substitute for observed activity levels
in existing random CRM
The Result
• Low risk of adverse impacts on populations
• Provided sufficient information to allow SNH to remove their objection and pass appropriate assessment
Further use in Pre-planning
Cumberhead wind farm• Turbines < 2km from same SPA
• Operational commercial forestry
• Low activity levels of SPA species
• Is survey data representative?
Additional Model Validation
• Incorporated active survey data to appraise worst case locations
The Result
• Model predicted low risk of adverse impacts on populations
• Case was made to reduce survey effort from 2 years to 1
• Rationale accepted by consultees and project submitted June 2015 and consented February 2016
• Significant saving of time and money for client
SNH Guidance
• Work was undertaken in close contact with SNH
• Modelling approach included in new SNH guidance:
• Wind farm proposals on afforested sites - advice on reducing suitability for hen harrier, merlin and short-eared owl
Further applications
• Incorporating habitat suitability into bird distribution
• Assessing different species (with different behaviour and distribution) at different sites
• Re-powering of existing sites using historic data?