Volume 2 Environmental Statement Annexes

Transcription

1 Walney Extension Offshore Wind Farm Annex B.7.D Volume 2 Environmental Statement Annexes Annex B.7.D: CRM and Migration Assessment Document Reference: APFP: 5(2)(a) Date: June 2013

2 DONG Energy March 2013 Walney Extension Offshore Wind Farm Technical Annex B7d: Collision Risk Modelling Methodology and Migration Assessment NIRAS Consulting Ltd Sheraton House, Castle Hill Cambridge CB3 0AX, UK Reg. No.: England & Wales T: +44 (0) F: +44 (0)1223

3 Document Control NIRAS Project Number Document Title Status Client Client Project No (if applicable) Client Contact Name N0052 Annex B7d - Collision risk modelling worked example Final DONG Energy Julian Carolan The following personnel are designated contacts for queries relating to this document: Name Job Title Telephone Matthew Hazleton Environmental +44 (0) 1223 [email protected] Consultant Ian Ellis Principal Ecologist +44 (0) [email protected] Revision Status for Issue Version 1 Name Date Checked by Robin Ward 01 March 2013 Accepted by Ian Ellis 04 March

4 Contents 1. Introduction Methodology Overview Bird data Bird survey data Daytime bird density Proportion of birds at rotor height Proportion of flights upwind Birds on migration Wind farm data Turbine data Other aspects of the CRM Large array correction Results Avoidance and attraction Flight height distribution Collision risk values Construction correction Walney Extension collision risk modelling References Appendix Appendix 1 Example spreadsheets Appendix 2 Birds on migration Overview Methodology Collision risk modelling

5 1. Introduction This technical annex provides a worked example of the Collision Risk Modelling (CRM) undertaken to inform the Environmental Impact Assessment (EIA) for the proposed Walney Extension Offshore Wind Farm (the Project ). Where appropriate, the example follows the format presented in Band (2012), produced for the Strategic Ornithological Support Services (SOSS) programme. This is a demonstration of the CRM process using gannet as an example. The collision risk values calculated for sensitive receptors at the Project site are detailed in Section 4 of this annex. 2. Methodology 2.1. Overview Figure 1 provides an overview of the information required for the CRM process and the key outputs from this process. Figure 1: Information required for and key outputs from the CRM process (Band, 2012) The CRM process can be described in five stages, as set out in Band (2012). These stages are shown in Table 1. The latest model enables the use of bird flight height distribution which is taken into account in Stage D. Table 1: The five stages used to calculate collision risk estimates Stage Stage A Stage B Description Collection of data relating to the number of flights which, in the absence of bird displacement, avoidance or attraction to the wind farm, are potentially at risk from wind farm turbines Estimation of the potential number of bird transits through the rotors of the wind farm using the flight activity data collected for Stage A 4

6 Stage Stage C Stage D Stage E Description Calculate the probability of collision during a single bird rotor transit Multiple the probabilities calculated in Stage C to yield the potential collision mortality rate for the bird species in question, allowing for the proportion of time that turbines are not operational, using data collected during Stage A Allow for the proportion of birds likely to avoid or be attracted to the wind farm either due to displacement, avoidance or attraction behaviour The following sections (Section ) outline the data required for the Input data spreadsheet of the Band (2012) model using the section headings as used in the model. The data outlined in the following sections is shown within the CRM tool in Appendix Bird data Information on the biometrics and behaviour of a species are required for this section of the CRM. The relevant data used for gannet are shown in Table 2. Biometric data (bird length and wingspan) was obtained from Robinson (2005). Information on the behaviour of gannet was obtained from Pennycuick (1987), for flight speed, Garthe and Hüppop (2004) for nocturnal flight activity and subjectively for the flight type of gannet. Most of the data in this section is used within the Single transit collision risk spreadsheet (Appendix 1) in the CRM tool to calculate the collision risk posed to a bird as a result of a single transit through a wind farm. This value is then used within the overall collision risk spreadsheet Site specific data on nocturnal flight activity are not available, therefore, the activity factor presented in Garthe and Hüppop (2004) is considered a reasonable estimate of nocturnal activity. The figure for nocturnal flight activity is defined on a scale of 1, hardly any flight activity at night, to 5, much flight activity at night. In the case of gannet, a nocturnal activity factor of 2, equates to approximately 25% of the level of activity during daylight hours The flight type of gannet is generally a mix of flapping and gliding however, flapping has been used in this CRM, providing a slightly more precautionary estimate of collision risk. Table 2: Information on the biometrics and behaviour of gannet used in collision risk modelling with Walney Extension Offshore Wind Farm Bird data Value Reference Bird length (m) 0.94 Robinson (2005) Wingspan (m) 1.72 Robinson (2005) Flight speed (m/s) 14.9 Pennycuick (1987) Nocturnal activity (1-5) 2 Garthe and Hüppop (2004) Flight type Flapping N/A 5

7 2.3. Bird survey data Daytime bird density The monthly densities of birds in flight within the Project area, including a 4 km buffer, were calculated from aerial survey data collected between November 2010 and October 2012 for the Project site (Table 3) (Technical Annex B7a Sections 4.3 and 5.1). CRM was carried out using two datasets, one which had been corrected for construction activities at Walney I and II Offshore Wind Farms (Technical Annex B7a Sections 4.11 and 5.8 ) (Table 4) and one which had not (Table 5). There was at least one survey carried out for every month with survey data collected four times for some months resulting in multiple density values. The densities calculated from aerial surveys are shown in Table 4 and Table 5 with the peak densities in bold being those used for CRM. Table 3: Dates on which aerial bird surveys were undertaken for Walney Extension Offshore Wind Farm. January th & 28 th February March 1 st & 18 th 2 nd & 18 th 16 th April 8 th & 28 th 15 th May June 3 rd 20 th July 2 nd & 30 th 14 th August 22 nd September October 28 th 13 th November 10 th 6 th December 8 th 22 nd Table 4: The densities (individuals / km 2 ) of gannet calculated from construction corrected data collected during twenty-two aerial surveys (November 2010 October 2012) at Walney Extension Offshore Wind Farm. Those densities shown in bold were taken forward for use in collision risk modelling. Year Month Jan Feb Mar Apr May June July Aug Sept Oct Nov Dec Table 5: The densities (individuals / km 2 ) of gannet calculated from data collected during twenty-two aerial surveys (November 2010 October 2012) at Walney Extension Offshore Wind Farm. Those densities shown in bold were taken forward for use in collision risk modelling. Year Month Jan Feb Mar Apr May June July Aug Sept Oct Nov Dec 6

8 Proportion of birds at rotor height Two separate sources of data were used to estimate the proportion of birds at potential collision height (PCH), with PCH values for relevant species shown in Table 6. These PCH values are used in Option 1 within the CRM and their usage is explained in Section 3.2. The first approach was the use of a study by Cook et al. (2012) which utilized survey data collected as part of environmental impact assessments completed for operational, consented and proposed offshore wind farm sites in the UK and Europe. The proportion of birds flying at PCH was modelled for a range of seabird species and a confidence assessment of the results based on the performance of the model is also presented. The PCH for gannet presented in this study is 9.6%, with a very high associated confidence assessment The second approach was to calculate the proportion of birds at PCH using boat-based survey data collected between March 2012 and November 2012 at Walney Extension Offshore Wind Farm (Technical Annex B7a Section 5.2.5). During these surveys birds were assigned to one of three height categories, 0-22m, 22-30m or m. The proportion of birds at PCH (flight bands m and m) was calculated as 46.25% The higher figure calculated from the two approaches was taken forward for CRM. Table 6: PCH values taken from Cook et al. (2012) and calculated from flight height data for Walney Extension Flight heights (% at collision risk) Sample size Proposed PCH Species Calculated from boatbased data 1 CRM Option 1 2 (%) for use in SOSS guidance3 from boatbased data 4 Common scoter Red-breasted merganser Fulmar Manx shearwater Storm petrel Gannet Cormorant Oystercatcher Number of records (i.e. number of flocks) from boat-based surveys used to calculate the proportion of birds at collision height (PCH) at Walney Extension 2 Based on the most precautionary PCH value taking into account a minimum sample size of 50 flocks of birds. 3 Cook et al., 2012 with a collision risk window of m 4 Calculated from boat-based survey data collected at Walney Extension between March and November 2012 with a collision risk window of m 7

9 Flight heights (% at collision risk) Sample size Proposed PCH Species Calculated from boatbased data 1 CRM Option 1 2 (%) for use in SOSS guidance3 from boatbased data 4 Skua sp Arctic skua Great skua Kittiwake Gull sp Black-headed gull Little gull Common gull Lesser black-backed gull Herring gull Great black-backed gull Sandwich tern Arctic tern Guillemot Razorbill Puffin Proportion of flights upwind The proportion of flights upwind was assumed to be 50% Birds on migration The methods used to obtain data for this section of the CRM process are not applicable to gannet and are therefore discussed in Appendix 2. CRM guidance (Wright et al., 2012) suggests that existing CRM methods be used to analyse the potential impact of a wind farm site on migratory movements of dispersive seabird species (fulmar and Manx shearwater) and those species which migrate along the coast (gulls and terns) Wind farm data A key parameter for the assessment of collision risk impacts on birds relates to the number of turbines. The worst case scenario for collision risk in this assessment is taken to be the development scenario comprising 207 x Siemens 3.6 MW SWT-120 class turbines This section of the CRM also requires the latitude of the wind farm site, needed to calculate the daylight hours in each month, important for the calculation of overall collision risk when apportioned between daylight and nocturnal activity The final input in this section is the width of the wind farm site which is used for large array correction. In the case of Walney Extension Offshore Wind Farm this is km Turbine data Further detail on the turbines which will be used at the wind farm is required to calculate the overall collision risk. The data relevant to this section for Walney Extension Offshore Wind Farm is shown in Table 8

10 7. These data represent the worst case scenario for collision risk assessment as this is the scenario which has the largest rotor swept area and therefore the greatest potential collision risk. Most of the data in this section (excluding operational efficiency of turbines) is transferred to the Single transit collision risk spreadsheet (Appendix 1) within the CRM tool to calculate the collision risk posed to a bird as a result of a single transit through a wind farm. The resulting value from this spreadsheet is then used within the overall collision risk spreadsheet (Appendix 1) Data relating to the monthly proportion of time for which the wind farm will be operational is also used in this section. There are certain occasions, such as periods of low wind speed or maintenance activities, when turbines are not rotating. This varies throughout the year and as such the proportion of time operational is used in the CRM. These data were supplied by the developer and are shown in Table 8. Table 7: Wind farm and turbine parameters used in collision risk modelling for Walney Extension Offshore Wind Farm Wind farm parameters Latitude Number of turbines 207 Width of wind farm (km) Turbine parameters No. of blades 3 Rotation speed (rpm) 13 Rotor radius (m) 60 Hub height (m) 82 Max blade width (m) 4.2 Pitch ( ) 6 Table 8: Monthly turbine operational time at Walney Extension Offshore Wind Farm Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Monthly proportion of time operational (%) Other aspects of the CRM Large array correction The large array correction factor, calculated automatically by the Large array correction spreadsheet using data provided for other aspects of the CRM, takes into the account the fact that a declining numbers of birds survive passage through initial rows of turbines, this reduces the probability of collision in later rows. This correction factor considers the width of the wind farm and likely number of turbine rows within the site. For gannet at the Project site, the large array correction factor does not result in a significant change to the overall collision risk (Section 3.3). 9

11 3. Results 3.1. Avoidance and attraction There is no Natural England guidance on the avoidance rate to be used in CRM, but guidance published by Scottish Natural Heritage (SNH, 2010) indicates that, in the absence of evidence for an alternative value, a default avoidance rate of 98% should be used. This value applies to gannet and is highlighted where appropriate. In this assessment a range of avoidance rates are presented, including a precautionary rate of 98% There is no evidence to suggest gannets will be attracted to the Project site, if the wind farm is constructed. Therefore, there are no additional factors required for the CRM in relation to this behaviour Flight height distribution The Band collision risk model contains a number of non-editable spreadsheets which are used to calculate data used to populate the Overall collision risk spreadsheet (Appendix 1). The Overall collision risk spreadsheet contains three options which calculate collision rates based on different methods to calculate the number of flights at risk: - Option 1: Uses a PCH calculated from site-specific data and assumes flights are evenly distributed across all rotor heights (the basic model); - Option 2: As above (the basic model), but uses a PCH calculated using generic flight height distribution data; and - Option 3: Making use of generic flight height distribution data to calculate the collision risk in each part of the rotor and summing the risk (the extended model) Information on flight height distributions, required for options 2 and 3, are obtained from the spreadsheet that accompanies Cook et al. (2012). This information is entered in the Flightheight spreadsheet within the CRM. For Option 3, the data within the Flightheight spreadsheet is then used within the Extended spreadsheet to calculate collision and flux integrals based on the flight height distribution data For the purposes of the assessment of Walney Extension, collision risk values calculated by Option 3 are presented. Option 3 utilises the extended model within the Band (2012) CRM which calculates the collision risk to birds across the entire rotor swept area. This method is used as it is considered that there are no particular ecological circumstances that would result in non-standard behaviour of birds at Walney Extension (following the Band (2012) guidance). Further to this, the site-specific flight height data (used in Option 1) presents an overly precautionary estimate of collision risk as the upper flight height band recorded during site-specific surveys ranged from 30 to 222 m, 80 m above the height at which collision would occur Collision risk values Table 9 presents the overall collision risk for gannet at Walney Extension Offshore Wind Farm, at a range of avoidance rates, using the PCH values obtained from boat-based surveys and from Cook et al. (2012) Table 10 presents collision rates for gannet taking into account large array correction. 10

12 Avoidance rate (%) Avoidance rate (%) Table 9: Annual collision rates for gannet, at a range of avoidance rates, using a number of methods (PCH and flight height distribution data) to calculate collision risk Collision risk (birds/annum) Flight height distributions Option 1 Option 2 Option 3 PCH values 46.25% 9.6% No avoidance 22,180 4,604 3,404 1, , Table 10: Annual collision rates for gannet, at a range of avoidance rates, using a number of methods (PCH and Flight height distribution data) to calculate collision risk, taking into account large array correction. Collision risk (birds/annum) Flight height distributions Option 1 Option 2 Option 3 PCH values 46.25% 9.6% 95 1, Construction correction Construction correction affected two of the maximum densities used for collision risk modelling, June and July. The CRM was conducted again using the revised densities with the resulting collision risk values shown in Table

13 Avoidance rate (%) Table 11: Annual collision rates for gannet, at a range of avoidance rates, using a number of methods (PCH and flight height distribution data) to calculate collision risk taking into account construction activity at Walney I and II. Collision risk (birds/annum) Flight height distributions Option 1 Option 2 Option 3 PCH values 46.25% 9.6% No avoidance 22,276 4,624 3,419 1, , Walney Extension collision risk modelling 4.1 This section presents collision risk modeling results for all sensitive receptors recorded at the Project site. Using a precautionary approach data calculated from construction corrected data has been used to populate the Daytime bird density row of the Input data spreadsheet (Appendix 1). The parameters used for each sensitive receptor within CRM are shown in Table 12. Table 12: Information on the biometrics and behaviour of sensitive receptors used in collision risk modelling with Walney Extension Offshore Wind Farm Species Bird length (m) Wingspan (m) Flight speed (m/s) Nocturnal activity factor Flight type Black-headed gull Flapping Common gull Flapping Common scoter Flapping Fulmar Gliding Gannet Flapping Great black-backed gull Flapping Great skua Flapping Guillemot Flapping Herring gull Flapping Kittiwake Flapping Lesser black-backed gull Flapping Little gull Flapping Manx shearwater Gliding Razorbill Flapping 12

14 4.2 The results of collision risk modeling for all sensitive receptors recorded at the Project site are shown in Table 13. Option 3 of the Band (2012) CRM is presented as it is believed that there are no particular ecological circumstances in the vicinity of the Project site that would lead to any species exhibiting atypical behavioral patterns. Table 13: Annual collision risk rates for sensitive receptors with Walney Extension offshore wind farm Species Total SPA population (no. of birds) 5 Avoidance (%) No avoidance Proportion of SPA population represented by collision risk (%) 6 Black-headed gull N/A Common gull N/A 1, Common scoter N/A Fulmar N/A Gannet 64,920 1, Great black-backed gull N/A 2, Great skua N/A Guillemot N/A Herring gull 22,000 5, Kittiwake N/A 4, Lesser black-backed gull 79,000 2, Little gull N/A Manx shearwater 325, Razorbill N/A Includes only SPAs within foraging range of the Project site for each species presented in Table 2 of Technical Annex B7a. 6 Collision risk values at an avoidance rate of 98% were used to calculate the proportion of each SPA population impacted by collision risk at Walney Extension 13

15 5. References Band, B. (2012). Using a collision risk model to assess bird collision risks for offshore wind farms with extended method. Report to Strategic Ornithological Support Services, March Cook, A.S.C.P, Johnston, A., Wright, L.J. and Burton, N.H.K. (2012). SOSS-02 A review of flight heights and avoidance rates of birds in relation to offshore wind farms. Report to Strategic Ornithological Support Services. Garthe, S. and Hüppop, O. (2004). Scaling possible adverse effects of marine wind farms on seabirds: developing and applying a vulnerability index. Journal of Applied Ecology, 41(4), Pennycuick, C.J. (1987). Flight of auks (Alcidae) and other northern seabirds compared with southern Procellariiformes: ornitholodite observations. Journal of Experimental Biology 128: Robinson, R.A. (2005) BirdFacts: profiles of birds occurring in Britain & Ireland (BTO Research Report 407). BTO, Thetford ( accessed on 01/03/2013). SNH. (2010). Use of Avoidance Rates in the SNH Wind Farm Collision Risk Model. Scottish Natural Heritage Information & Guidance Note. Wright, L. and Austin, G. (2012) SOSS Migration Assessment Tool Instructions. British Trust for Ornithology, Thetford, Norfolk. Wright, L.J., Ross-Smith, V.H., Austin, G.E., Massimino, D., Dadam, D., Cook, A.S.C.P., Calbrade, N.A. and Burton, N.H.K. (2012) SOSS-05 Assessing the risk of offshore wind farm development to migratory birds designated as features of UK Special Protection Areas (and other Annex 1 species). Report to Strategic Ornithological Support Services 14

16 6. Appendix 6.1. Appendix 1 Example spreadsheets Data as used in the Input data spreadsheet within the Band (2012) CRM tool

17 6.1.2 Results as presented in the Overall collision risk spreadsheet within the Band (2012) CRM tool 16

18 6.1.3 Data as presented in the Single transit collision risk spreadsheet in the Band (2012) CRM tool 17

19 6.2. Appendix 2 Birds on migration Overview This section uses recently published guidance from the BTO (Wright and Austin, 2012), relating to the SOSS Migration Assessment Tool (MAT), which details a method in which the migration passages of migratory species can be calculated. This guidance (Wright and Austin, 2012) states that, as a general rule, the use of the MAT is not relevant for pelagic seabirds, such as gannet, or land-based seabirds that follow the coastline during migration. However, this approach was used, were appropriate, in the CRM process for other species For seabirds the Band (2012) collision risk modelling calculates a flux factor from densities recorded at the Project site. An example of this process for great skua is shown in Figure 2. Converting from bird density to rotor transits Worked example Great skua v Bird flight speed 14.9 m/s D A Bird density per unit area birds/km 2 R Rotor radius 60 m T Number of turbines 207 TπR 2 Frontal area of all rotors 2,341,115 m 2 t Hours active in October 309 hours F Flux factor 2,569 Q 2R Proportion flying at risk height 4.3% Total bird transits through rotor in June 110 birds Figure 2: Converting from bird density to rotor transits great skua worked example Methodology The MAT utilizes 251,599 lines of connectivity which were constructed as line of sight sea crossings for migrants travelling across UK waters. These lines were then assigned on a species specific basis based on the migration routes presented in Wright et al. (2012) Provided with the guidance is a GIS shapefile which is used to determine those lines of connectivity which interact with a wind farm site. A dataset which details those lines which interact with the wind farm site can then be extracted from GIS and imported into the MAT. In the case of Walney Extension this dataset contained 2754 lines of connectivity The next stage in the process is to decide which sea crossings are pertinent to the wind farm being assessed. The following sea crossings were selected for Walney Extension based on the descriptions given in Wright and Austin (2012): 18

20 - England and Wales Bristol Channel to England and Wales Irish Sea - England and Wales Irish Sea to England and Wales Irish Sea - England and Wales Irish Sea to Northern Ireland Celtic Seas coast - England and Wales Irish Sea to Scottish mainland Celtic Seas coast - Republic of Ireland Celtic Seas Eastern coast to England and Wales Irish Sea - Spanish North coast to England and Wales Irish Sea The final stage of the MAT requires two pieces of information relating to the population estimated to interact with the Project site. The first piece of information is the population size of the considered species that occurs in UK waters. These values were obtained from Wright et al. (2012). The second piece of information is a population correction factor which estimates the percentage of the GB population that interacts with the wind farm footprint. The population of each species predicted to interact with the footprint of the wind farm was estimated using the population of each species cited for SPAs connected with the Project site (Table 14) (Stroud et al., 2001). The proportion was calculated by comparing the total population of a species cited for connected SPAs and the GB population size. 19

21 Table 14: Species, SPA populations and the proportion of the GB population interacting with Walney Extension used for migratory collision risk assessment SPA populations (number of individuals) Species Duddon Estuary SPA Martin Mere SPA Mersey Estuary SPA Mersey Narrows and North Wirral Foreshore SPA Morecambe Bay SPA Ribble and Alt Estuaries SPA The Dee Estuary SPA Total Proportion of UK population interacting with the east Irish sea region (%) Shelduck - - 5,039-6,372 4,103 6,827 22, Wigeon ,699-84, Teal , ,641 5,918 25, Pintail 1, ,744-2,804 3,333 6,498 17, Oystercatcher ,572 16,159 28,434 92, Ringed plover 628-1, , Golden plover - - 3,070-4, , Grey plover ,813 6,073 2,193 10, Knot 4, ,655 29,426 57,865 21, , Sanderling 1, ,466 6,172-9, Dunlin ,300-52,671 39,952 22, , Black-tailed godwit ,739 2, Bar-tailed godwit ,344 2,611 18,958 1,013 25, Curlew ,620-4,028 17, Redshank 2,289-4,689-6,336 2,708 8,451 24, Turnstone , ,

22 Collision risk modelling The number of movements across the wind farm footprint calculated by the MAT (Table 15) were then used within the Band (2012) collision risk model. Two key months during each migration period were arbitrarily chosen (March and October), which were populated with the number of movements across the wind farm footprint. Table 15: Number of movements of wading and waterfowl species across Walney Extension Offshore Wind Farm Species Number of movements across wind farm footprint Shelduck 1,243 Wigeon 4,711 Teal 1,403 Pintail 1,000 Oystercatcher 5,126 Ringed plover 210 Golden plover 398 Grey plover 561 Knot 6,897 Sanderling 539 Dunlin 12,915 Black-tailed godwit 142 Bar-tailed godwit 1,903 Curlew 982 Redshank 1,361 Turnstone As stated in Band (2012), the proportion of birds on migration at rotor height is likely to be different from the proportion of birds at collision height (PCH) when not on migration for a number of species. Wright et al. (2012) makes recommendations on the values to use for the proportion of birds at rotor height. For wading birds and waterfowl Wright et al. (2012) recommends a PCH of 25 % and 15 %, respectively The width of the migration corridor, required for the migratory stage of the CRM, was calculated using ArcGIS. The migration corridor was taken as the longest width of the Project site running from northeast to south-west. This gave a value of 7.34 km. The proportion of flights upwind for migratory species was assumed to be 50% for all species Table 16 shows the results of collision risk modelling for all wader and waterfowl species that may potentially interact with the Project site. A default avoidance rate of 98%, as recommended by SNH guidance (SNH, 2010), is presented alongside the number of collisions assuming no avoidance.

23 Table 16: Collision risk estimates (collision per annum) for wading and waterfowl species for Walney Extension. Species No avoidance 98% avoidance Shelduck 31 1 Wigeon 98 2 Teal 27 1 Pintail 22 0 Oystercatcher Ringed plover 6 0 Golden plover 13 0 Grey plover 18 0 Knot Sanderling 16 0 Dunlin Black-tailed godwit 5 0 Bar-tailed godwit 64 1 Curlew 38 1 Redshank 46 1 Turnstone