WFD fish barrier classification - Dominic Habron, SEPA
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Talks provided at the Scottish Fisheries Co-ordination Centre/Institute of Fisheries Management MAPPING FISHERIES workshop in Edinburgh on March 1st-2nd 2016
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WFD fish barrier classification - Dominic Habron, SEPA
- 1. Water Framework Directive (WFD) fish barrier classification Dominic Habron Geographic Information Analyst SEPA
- 2. Content • Water Framework Directive • Fish barrier classification • River Obstacles app
- 3. Water Framework Directive • Requires rivers’ and lochs’ morphological continuity to be assessed • Classification undertaken since 2008
- 4. Information Systems classification WB Map WB Map WB Map CCS (Central Classification System) Phytoplankton Tool (Phytoplankton) DALES (Phytobenthos) LEAFPACS (Macrophytes) WFD60 (Benthic Invertebrate Fauna) CPET (Chironomid pupae Exuviae) NS SHARE (Benthic Invertebrate Fauna) HIFI (Fish Fauna) DARES (Phytobenthos) LEAFPACS (Macrophytes) RIVPACS (Revised) (Benthic Invertebrate Fauna) ARTIFICIAL INTELLIGENCE (Benthic Invertebrate Fauna not until 2009) FAME (Fish Fauna) HIFI (Fish Fauna) RIVERS GROUNDWATER QUANTITATIVE GROUNDWATER CHEMICAL (QUALITATIVE) MImAS (MORPHOLOGY Type and Pressure) CANAL Composition and Abundance Bloom Characteristics Phytoplankton Biomass Composition/ Abundance Accelerated Growth Undesirable Disturbance Bacterial Tufts Composition and Abundance Composition/ Abundance Disturbance Ratio Diversity Profundal Inverts Acidification Chironomid pupal Exuviae NS SHARE (Fish Fauna) Species Composition Abundance Disturbance Sens. species Age structure Species Composition Composition / Abundance Accelerated Growth Undesirable Disturbance Bacterial Tufts Composition/ Abundance Composition/ Abundance Disturbance ratio sensitive / insensitive taxa Diversity ?????? Composition / Abundance Type specific disturbance sensitive species Age structure of fish Species Composition WATER CHEMISTRY EQS for priority substances Chemistry Analysis Priority Substances HYDROLOGY (WFD48 Bands) LF2K CLAS Licensed Abstraction Nitrate/phosphate data (WQ50) Groundwater group recharge data Groundwater group reference data LF2K Pressures Types Macrophytes WISE GIS Lake Biological Status High Good Moderate Poor Bad GW Quantitative Status Good Poor River Biological Status High Good Moderate Poor Bad SW Chemical Status Good Failing to Achieve Good Manual Intervention Chemistry Surface Waterbody Status High, Good, Moderate, Poor, Bad GW Chemical Status Good Poor Hydro- Morphological Status High Good Moderate Poor Bad Overide Options on Classification Phytoplankton Marine Plant Toolkit (Macroalgae, Angiosperms Saltmarsh Benthic Invertebrate Fauna Fish fauna (Estuaries Only Hydromorphological MARINE (Coast and Estuarine) Marine Biological Status High Good Moderate Poor Bad Composition and Abundance Bloom Characteristics Phytoplankton Biomass Composition and Abundance Species Richness Composition / Abundance Type specific disturbance sensitive species Age structure of fish Composition / Abundance Ration insensitive /sensitive taxa Diversity Morphological Conditions Tidal Regime LHS Data Heavily Modified Water Body LAKES OUTPUTS ‘Expert’ Interpretation Phase (Expected but loosely defined at present) Ecology Physico-chem EQS Canal Type latitude Fish, diatoms, phytoplankton Canal Ecological Status High Good Moderate Poor Bad Canals GROUNDWATER WFD66 Wetlands WFD66 EQS Ground Waterbody Chemical Status Good,Poor WB Map WB Map WB Map (Monitoring Point/WB Conversion) WB Map WB Map Ground Waterbody Quantative Status Good, Poor Hydrology Data Ecology Surface Waterbody Status High, Good, Moderate, Poor, Bad Overall Surface Waterbody Status High, Good, Moderate, Poor, Bad Ecology Physico- chemical EQS Ecological Physico- Chemical Status High, Good, Moderate, Poor,Bad WB Map Common to all Surface Water Media WB Map WB Map WB Map CCS (Central Classification System) Phytoplankton Tool (Phytoplankton) DALES (Phytobenthos) LEAFPACS (Macrophytes) WFD60 (Benthic Invertebrate Fauna) CPET (Chironomid pupae Exuviae) NS SHARE (Benthic Invertebrate Fauna) HIFI (Fish Fauna) DARES (Phytobenthos) LEAFPACS (Macrophytes) RIVPACS (Revised) (Benthic Invertebrate Fauna) ARTIFICIAL INTELLIGENCE (Benthic Invertebrate Fauna not until 2009) FAME (Fish Fauna) HIFI (Fish Fauna) RIVERS GROUNDWATER QUANTITATIVE GROUNDWATER CHEMICAL (QUALITATIVE) MImAS (MORPHOLOGY Type and Pressure) CANAL Composition and Abundance Bloom Characteristics Phytoplankton Biomass Composition/ Abundance Accelerated Growth Undesirable Disturbance Bacterial Tufts Composition and Abundance Composition/ Abundance Disturbance Ratio Diversity Profundal Inverts Acidification Chironomid pupal Exuviae NS SHARE (Fish Fauna) Species Composition Abundance Disturbance Sens. species Age structure Species Composition Composition / Abundance Accelerated Growth Undesirable Disturbance Bacterial Tufts Composition/ Abundance Composition/ Abundance Disturbance ratio sensitive / insensitive taxa Diversity ?????? Composition / Abundance Type specific disturbance sensitive species Age structure of fish Species Composition WATER CHEMISTRY EQS for priority substances Chemistry Analysis Priority Substances HYDROLOGY (WFD48 Bands) LF2K CLAS Licensed Abstraction Nitrate/phosphate data (WQ50) Groundwater group recharge data Groundwater group reference data LF2K Pressures Types Macrophytes WISE GIS Lake Biological Status High Good Moderate Poor Bad GW Quantitative Status Good Poor River Biological Status High Good Moderate Poor Bad SW Chemical Status Good Failing to Achieve Good Manual Intervention Chemistry Surface Waterbody Status High, Good, Moderate, Poor, Bad GW Chemical Status Good Poor Hydro- Morphological Status High Good Moderate Poor Bad Overide Options on Classification Phytoplankton Marine Plant Toolkit (Macroalgae, Angiosperms Saltmarsh Benthic Invertebrate Fauna Fish fauna (Estuaries Only Hydromorphological MARINE (Coast and Estuarine) Marine Biological Status High Good Moderate Poor Bad Composition and Abundance Bloom Characteristics Phytoplankton Biomass Composition and Abundance Species Richness Composition / Abundance Type specific disturbance sensitive species Age structure of fish Composition / Abundance Ration insensitive /sensitive taxa Diversity Morphological Conditions Tidal Regime LHS Data Heavily Modified Water Body LAKES OUTPUTS ‘Expert’ Interpretation Phase (Expected but loosely defined at present) Ecology Physico-chem EQS Canal Type latitude Fish, diatoms, phytoplankton Canal Ecological Status High Good Moderate Poor Bad Canals GROUNDWATER WFD66 Wetlands WFD66 EQS Ground Waterbody Chemical Status Good,Poor WB Map WB Map WB Map (Monitoring Point/WB Conversion) WB Map WB Map Ground Waterbody Quantative Status Good, Poor Hydrology Data Ecology Surface Waterbody Status High, Good, Moderate, Poor, Bad Overall Surface Waterbody Status High, Good, Moderate, Poor, Bad Ecology Physico- chemical EQS Ecological Physico- Chemical Status High, Good, Moderate, Poor,Bad WB Map Common to all Surface Water Media
- 5. H G M P B H G M P B H G M P B H G M P B H G M P B H G M P B Biological quality elements General chemical & physicochemical quality elements Specific pollutants Priority substances & other EU-level dangerous substances F G F G F G F G F G F G F G Ecological Status Chemical Status Surface Water Status Lowest classed substance Lowest classed element Lowest classed element F G GH M Lowest of chemical & ecological status H G M P B H G M P B H G M P B H G M P B Hydromorphological quality elements H G M P B H G M P B H G M P B H G M P B F G F G F G F G F G F G F G GH M H G M Lowest classed element
- 6. Data sources • Fishery Research Service / Marine Scotland data • Fishery Trusts workshops • SEPA fishery ecologists / regulatory staff • River Obstacles app
- 10. SEWEB – WMS
- 14. River Network - fish obstacles
- 15. River Network - fish obstacles
- 16. River Network - fish obstacles
- 17. River Network - fish obstacles length method
- 18. River Network - fish obstacles
- 20. River Network - fish obstacles
- 21. River Network – slope points 0 100 200 300 400 500 600 700 -2.0 0.0 2.0 4.0 6.0 8.0 10.0 12.0 fryminest slope % fry abundance
- 22. River Network – slope points 0 20 40 60 80 100 120 140 160 -2.0 0.0 2.0 4.0 6.0 8.0 10.0 12.0 parrminest slope % parr abundance
- 23. River Network – slope points
- 24. River Network – slope points
- 25. River Network – slope points
- 26. River Network – slope points
- 27. River Network – slope points
- 30. Water Environment Fund • Annual fund of £2 million managed by SEPA supported by SG, SNH & FC • The fund aims to restore rivers, lochs and their catchments which have been damaged by historical activities. • By: • restoration of morphology • removal of barriers to fish migration
- 36. Future Developments • Water Network Layer • Wetted area
- 37. Benefits of OS Network • Detail - 1:1250 (urban) to 1:10,000 (mountain & moorland)
- 38. Benefits of OS Network • Inclusion of width & gradient
- 39. Benefits of OS Network • Included within One Scotland Mapping Agreement (OSMA)
- 40. Thank you for listening Questions?
Editor's Notes
- Good morning, working with GIS for SEPA for 15 years, with a focus of river networks. SEPA undertakes a water quality classification as required by the Water Framework Directive. One of the parameters used in the classification is an assessment of the amount of potentially suitable habitat that is inaccessible due to artificial barriers to fish migration. This assessment is undertaken using SEPA’s version of the 1:50,000 Centre for Ecology and Hydrology (CEH) digital river network along with a dataset of obstacles to fish migration. SEPA has recently been involved in the development of the River Obstacles mobile phone app which is hoped will improve the quality and quantity of data available for the WFD classification assessment.
- What I’m not going to talk about is, flooding. Flood mapping is managed by SEPA’s Hydrology function which has representation on our internal working group.
- WFD requires rivers’ and lochs’ morphological continuity to be assessed.
- First slide is the size of the IS task Second shows what IS systems SEPA had for 2006 classification. (hatched stuff – we sort-of have something) Can see huge scale of work required. Developing IS systems to support classification Budget limited Won’t be able to integrate all tools in time for first classification in early 2008 Significant piece of work This project will link to the RBMP data project; we will be displaying all monitoring networks and classification results on intranet (at least, we hope to!).
- As with any data set, there are caveats to be applied to the data. The Trusts only recorded barriers for approximately 80% of Scotland The accuracy of recording varies, as does the transposition onto the GIS layer – there is a risk that some barriers have been allocated to the wrong tributary at a confluence Barrier permeability was only assessed for salmon. Consequently, a barrier recorded as being passable may be impassable for eels or lamprey
- Data schema showing attributes stored per barrier.
- Map showing distribution of barriers to migratory fish as of 29/2/16. Note the few points within the English part of the River Tweed.
- Size of word is relative to the number of occurrences of the barrier type within the GIS dataset.
- Barriers data is visible on the SEWEB mapping application: http://map.environment.scotland.gov.uk/seweb/map.htm?menutype=0&layers=2
- The dataset can also we viewed via the SEPA hydrography web map service, directly in your GIS software, e.g. ArcGIS , QGIS. Just type in SEPA in the search box and click return.
- The first result is the one to use – SEPA Hydrography service.
- Contains WFD water bodies & obstacles amongst other things.
- Although I’m focusing on the River Almond catchment here, this analysis was carried out for the whole of Scotland in one go. Analysis conducted with ESRIs Network Analyst extension to ArcGIS. Start with just the river network – could be any network, e.g. the OS Water Network.
- Although I’m focusing on the River Almond catchment here, this analysis was carried out for the whole of Scotland in one go. Analysis conducted with ESRIs Network Analyst extension to ArcGIS. Start with just the river network – could be any network, e.g. the OS Water Network.
- Add obstacles to fish migration – green triangles are natural barriers, e.g. water falls, red circles are impassable artificial barriers. Other symbols are partially passable obstacles.
- The tools in Network Analyst allow the identification of all the rivers upstream of each obstacle (coloured sections of river network). This analysis excluded the headwaters of the network (catchment area < 1.5km2), hence the fine blue head water streams have not been highlighted.
- Classification model for river length – takes the output from the first model and works out the classification status of each baseline water body intercatchment.
- The final stage of this analysis is the classification of each sub-catchment based on the length of river excluded / highlighted on the previous slide. These results help prioritise where to spend resources by targeting which barriers to remove to provide the most habitat & in what order.
- Using the location of sample sites where salmon were present, the slope statistics for each site were calculated along the network to the river mouth. The graphs below (from Alistair Duguid, taken from data from over 1600 SEPA and fishery trust electrofishing sites) show that salmon fry and parr do not occur on rivers with a maximum slope > 10%.
- Based on the evidence of the graphs above a slope cut off value of 10% was used to define whether or not a particular river reach was a suitable habitat for salmonids. The snapshot below shows the resulting point dataset symbolised by slope value (red: > 10% slope, blue <= 10% slope).
- ArcGIS model developed to produce points at a defined interval along a river network & calculate the slope over a defined river length. Again, this uses ArcGIS Network Analyst to use the connectivity of a network dataset to generate information.
- River Earn catchment used for test purposes. Work linked to the obstacles to fish migration work as river slope impacts on the migration of salmonids.
- Points are 50m apart and those in red are where the slope in greater than 10% over a distance of 1km, blue points have a slope < 10%. Zooming in on the area highlighted…..
- You can see how the model has picked out the steeper slopes with the red dots.
- Example of where the inclusion of slope has identified a barrier that it wouldn’t be worth trying to mitigate as all the habitat upstream is too steep. Previous iterations of the classification could have highlighted this barrier for removal, albeit with a low priority.
- 2014 classification results. Can see impact of individual barriers on entire catchments, e.g. Loch Shin dam, Milnbie Caul on the River Annan and also those catchments with multiple barriers e.g. the River Almond.
- Internal tool developed by ESIU team to take outputs from the fish barrier classification, including barrier sequencing & amount of upstream habitat and provide a prioritised list highlighting those barriers that should be tackled first.
- iPhone & Android mobile phone app for recording location of barriers. Developed by SEPA, RAFTS & EA with Natural Capital as the contractor.
- Allows the user to submit information about an obstacle, including a photo & associated information such as height of structure or waterfall. SEPA can import any new barrier locations into our own system for validation by our fishery ecologists & if they pass this step, then they can be added to our national dataset and if assessed to be impassable, used in the WFD classification.
- Issues that I’d like to look at in the future, relate to making use of the OS water network layer, e.g. improving the measure of habitat quality by making use of the river width data to generate a value for wetted area.
- The examples shown have used a 1:50,000 river network, but the same processes could be run on a more detailed river network such as the OS Water Networks layer. Here we see the significant additional features captured in the water networks layer compared with the 1:50k network (blue).
- Width value shown in table for the stretch of river highlighted in pink. Width values - needed for calculation of wetted area – useful in ecology for quantification of habitat. Width values – change in width could highlight a constriction. Gradient – change from high to low gradient could highlight a point at which flow could leave a channel.
- Included within OSMA – unlike previous river networks.