Diffuse Pollution Screening Tool: Stage 3

Transcription

1 Final Report Project WFD77 Diffuse Pollution Screening Tool: Stage 3 September 2006

2 SNIFFER 2006 All rights reserved. No part of this document may be reproduced, stored in a retrieval system or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise without the prior permission of SNIFFER. The views expressed in this document are not necessarily those of SNIFFER. Its members, servants or agents accept no liability whatsoever for any loss or damage arising from the interpretation or use of the information, or reliance upon views contained herein. Dissemination status Unrestricted Research contractor This document was produced by: ADAS Consulting Ltd, Woodthorne, Wergs Road, Wolverhampton, WV6 8TQ, England, UK The Macaulay Institute, Craigiebuckler, Aberdeen, AB15 8QH, Scotland, UK HR Wallingford, Howbery Park, Wallingford, OX10 8BA, England, UK SNIFFER s project manager SNIFFER s project manager for this contract is: Jonathan Bowes, SEPA, Clearwater House, Heriot-Watt Research Park, Avenue North, Riccarton, Edinburgh, EH14 4AP, Scotland, UK. SNIFFER s project steering group members are: Kirsty Irving, SNIFFER, First Floor, Greenside House, 25 Greenside Place, EDINBURGH EH1 3AA, Scotland, UK. Devina Park, River Basin Planning, EHS, Calvert House, 23 Castle Place, Belfast, BT1 1FY, UK. Lisa Condon, River Basin Planning, EHS, Calvert House, 23 Castle Place, Belfast, BT1 1FY, UK. Jannette MacDonald, Land Unit, SEPA Corporate Office, Erskine Court, Castle Business Park, Stirling, FK9 4TR, Scotland, UK. SNIFFER First Floor, Greenside House 25 Greenside Place EDINBURGH EH1 3AA

3 EXECUTIVE SUMMARY WFD77: Diffuse Pollution Sreening Tool Stage 3 (September, 2006) Project funders/partners: SNIFFER Background to research The first phase of this project investigated the feasibility of developing a Geographic Information System (GIS) based screening tool for diffuse pollution at the national scale, involving a review of available modelling methodologies and datasets. Relevant models to address individual pollutant pressures and appropriate datasets were found to have been developed in the past, but application of a screening tool at such a large scale, covering both rural and urban pressures, and considering all pressures, had not been attempted before. Nevertheless, it was concluded that a basic-level screening tool for Scotland and Northern Ireland was practicable and would be a significant contribution to the characterisation of water body catchments under the Water Framework Directive (WFD). Phase II of the project (WFD19, 230/8050) was therefore commissioned to develop, implement and apply a basic screening tool for all potential diffuse pollutants in order to assess the risk of individual waterbodies failing to meet good ecological status required under the WFD. The screening tool was built on simple models of pollutant pressures and loads delivered to these waterbodies. To achieve this, a national Environment Database was first constructed, containing environmental and agricultural statistical data summarised to 1km 2 grid cells suitable for visualisation and querying in a Geographic Information System. The database collates information on specific properties (e.g. land use, agricultural livestock numbers and population counts) controlling pollutant inputs and intrinsic environment properties (e.g. topography, soil physical properties and climate statistics) controlling risk of pollutant mobilisation and delivery. The database covers a land area of 78,770km 2 for Scotland and 14,140km 2 for Northern Ireland, and includes a modelled monthly water balance and index of landscape connectivity. The final database, including summaries of model results, contains more than 80 tables and 1,000 items of data for each 1km 2 cell. Modelling methodologies to calculate pollutant pressures and loads delivered to surface water bodies and to the base of the soil profile were developed for a) nutrient nitrate and phosphorus; b) heavy metals; c) acidification risk; d) suspended sediment; e) biochemical oxygen demand; f) priority substances and pesticides; g) and faecal indicator organisms. The methodologies were developed to work with environmental and agricultural data that were available for the whole of Scotland and Northern Ireland. The methodologies were generally based upon existing indicators of relative pollution risk that are appropriate for application at the regional and national scale, rather than detailed mechanistic modelling. The models also developed approaches that had previously been applied for policy work in the UK, including elements of the NIRAMS (Nitrogen Risk Assessment Model for Scotland) model of nitrate leaching and the Event Mean Concentration (EMC) model of pollutants in urban runoff, or are being developed for this purpose, such as the PSYCHIC model (Phosphorus and Sediment Yield Characterisation in Catchments). The models and Environment Database were linked to calculate pollutant pressures and loads for each 1km 2 cell across each country. Taken together, the models provided estimates of the diffuse pollutant loads derived from a) agricultural land; b) forestry; c) paved urban areas; d) road infrastructure; e) and septic tank diffuse sources. Additionally, estimates of the pollutant load from point sewage treatment discharges were made by use of per capita export coefficients. Summary statistics were calculated and stored in the national Environment Database, giving data on the proportion of the total pollutant load derived from each diffuse source. The calculated pollutant pressures were summed for the catchments of the river, coastal and lake water bodies defined by SEPA and the EHS for reporting under the WFD. Where monitoring data were available, the outputs from the models were validated against observed loads for selected pollutants. Observed loads were collated for 6 test catchments in Northern Ireland and 13 catchments in Scotland. In the absence of ecological criteria for good water status, the risk of failure i

4 was re-defined as the risk of failing to meet existing chemical water quality standards that were based on pollutant concentrations. These included the Environment Quality Standards (EQS) set for Priority Substances, the standards set for nitrate and pesticides under the Nitrates and Drinking Water Directives, and the SEPA Operational Standard for soluble phosphorus in freshwaters. In most cases, the selected modelling methodologies led to an over-estimate of risk, as they did not take account of dilution in the receiving water body or of retention. For nitrate, phosphorus, biochemical oxygen demand and suspended sediment, intermediate empirical statistical models were developed that predicted observed percentile pollutant concentrations from modelled total pollutant load and drainage. These models were then used to predict the likelihood that river water pollutant concentrations were greater than the appropriate standard for unmonitored catchments. The risk of failure due to priority substances and pesticide runoff was assessed by comparison of modelled concentrations in land drainage with standards. The results of these models are included in the Environment Database and allow assessment of the risk of failure due to diffuse sources only, point and diffuse sources. These results were combined with an expert assessment of the risk of failure for acidification, metals and faecal indicator organisms. Objectives of research The user-friendliness of the Environment Database produced during phase II of the project was thought to be restricting the wider dissemination of the valuable data contained therein. In addition new datasets and improved methodologies offered the opportunity to address some the weaknesses inherent in the modelling undertaken in phase II of the project. These were just some of the factors that drove Phase III of this project. The specific objectives were: Simplification and summarisation of the current waterbody database into a spreadsheet in order to facilitate comparison with other studies and visualisation through linkages with GIS technologies. Further characterisation of the waterbodies through the update of input data (waterbodies and their boundaries; point source inventory), taking account of retention of N and P, exploring an improvement of the regression models used to predict status and assess suspended sediment risk for two lower standards. Summarisation of the source apportionment data per waterbody along with agricultural census data to allow for the contextualisation and interpretation of these source apportionment summaries. Knowledge transfer through the development of a report and the provision of a workshop. Key findings and recommendations The development of the Summary Database Tools for Scotland and Northern Ireland facilitate access to the wealth of data that are housed within version 2 of the Environment Database in a logical and userfriendly manner. Importantly the tool allows comparison with WFD Article 5 Pressures and Impacts summary data, simple source apportionment, land cover and land use at a water body scale. In addition, associated tools and utilities allow the user to investigate the impacts of changing Environmental Quality Standards thresholds and associated impacts. The Summary Database Tool was used to undertake a preliminary interpretation of the version 2 Environment Database. The output from the models was used to calculate the relative importance of point and diffuse sources for each of the pollutant pressures, using simple per capita export models to characterise sewage treatment works discharges in Scotland and actual monitored discharges in Northern Ireland. Diffuse sources in Scotland accounted for c. 65% of phosphorus, 83% of nitrate and 99% of sediment losses, but only 32% of faecal coliform inputs to rivers. Roads and urban areas were found to make a significant ca 9% contribution to the total modelled sediment losses. In Northern Ireland diffuse sources accounted for c. 77% of phosphorus, 87% of nitrate and 99% of sediment losses, but only 10% of faecal coliform inputs to rivers. Roads and urban areas were found to make a significant ca 12% contribution to the total modelled sediment losses. ii

5 Analyses based on modelled nitrate, phosphorus, sediment and biochemical oxygen demand losses from agriculture and forestry determined that only 36% of Scotland and 39% of Northern Ireland could be demonstrated to be not at risk of failing to achieve good ecological status with confidence. It is necessary to emphasise that this analysis is risk averse. A significant land area could not be proven to be either failing or achieving good ecological status, so was included in the area at risk. In both countries, nitrate and sediment were not a major cause of failure according to current water quality criteria. Phosphorus losses resulted in the greatest land area designated at risk, and were primarily associated with agriculture. Other diffuse pollutant sources, including roads and urban areas, were more critical for losses of priority hazardous substances. The process of developing the screening tool methodology has identified a need for more extensive monitoring of priority substances, pesticides and metals concentrations in fresh waters throughout Scotland and Northern Ireland. At present, monitoring is confined to certain areas, for example developed areas on the coast in Scotland. The screening tool outputs can be used to target additional monitoring in areas at high risk. Also, there is a need to integrate existing hydrological and general water quality datasets to develop observed load estimates for every sub-catchment to facilitate improved validation of the pollutant load models. This will also require an improved and consistent inventory of point source inputs to the water bodies, along with estimates of retention losses, to allow a like for like comparison of modelled and observed loads. In summary, this research has provided SEPA and EHS with a significant data and model resource for characterisation of river and lake catchments for a wide range of urban and rural diffuse pollutants. The combined outputs will support further catchment scale pollution research, and ultimately the development of targeted and effective catchment management plans to meet the needs of the WFD. This increased ease of access to the Environment Database will allow further and a more thorough exploration of the dataset to inform WFD policy implementation and mitigation. Key words: Water Framework Directive, Diffuse Pollution, Screening Tool, Summary Database Tool, Scotland, Northern Ireland iii

6 TABLE OF CONTENTS EXECUTIVE SUMMARY 1 INTRODUCTION 1 2 UPDATES MADE TO THE INPUT DATA AND MODELLING METHODOLOGY USED TO CREATE VERSION 2 OF THE ENVIRONMENT DATABASE Point source data and pollution pressure calculations Updated catchment boundaries and waterbody types Inclusion of retention for N and P Improvement of the regression equations for N, P, SS and BOD 5 3 BRIEF DESCRIPTION OF THE SUMMARY DATABASE TOOL Background High Level Design Summary Sheets Detail Sheets Data Dictionary Sheet Administrator Update Sheet Confidence/Quality Numbers Phase 2 Modelling Approach Phase 2 Rural Pollution Pressures Phase 2 Urban Pollution Pressures Phase 2 Validation procedure Confidence/Quality Numbers Matrix Agricultural census data changes from 1997 to 2004 for Scotland Introduction National data Area Advisory Group (AAG) 15 4 SCOTLAND - INTERPRETATION OF THE SUMMARY DATABASE TOOL RESULTS Diffuse Pollution Issues in Scotland Summary of pollutant loads Comparison with Pressures and Impacts database River and Loch risk assessment by pollutant Nitrate, Phosphorus, Suspended Sediment and Biochemical Oxygen Demand Metals Faecal Indicator Organisms Pesticides and Acidity Source apportionment for AAGs and priority catchments NORTHERN IRELAND - INTERPRETATION OF THE SUMMARY DATABASE TOOL RESULTS River and Lough risk assessment by pollutant Nitrate, Phosphorus, Suspended Sediment and Biochemical Oxygen Demand Metals Faecal Indicator Organisms Pesticides and Acidity 62 REFERENCES 65 iv

7 List of Figures Figure Schematic of the effect of nutrient retention, showing how much an input to a watercourse in a sub-catchment will be reduced before it has been delivered to the mouth of the catchment. The darker colours illustrate areas where a larger fraction of the inputs will be retained, while inputs in the lighter areas are less affected by retention processes. Consideration of the upstream catchments results in as much as a 35% difference in the magnitude of the retention factor... 4 Figure Illustration of an idealised flow exceedance curve for a clay catchment along with the corresponding pollutant concentration obtained when diluting a fixed point source. Time-weighted averaging yields a concentration of 2.86 mg/l while flow weighted averaging yields a concentration of 1.6 mg/l... 6 Figure 3.1 Screenshot of a summary page within the Summary Tool Figure Location of the Area Authority Groups in Scotland Figure Normalised cumulative areas for river Water Bodies in each P and I category, plotted against the probability of good status, denoted by P(good status), using Total Catchment Area data Figure Spatial distribution of the modelled likelihood of river water body nitrate concentrations from both diffuse and point sources meeting chemical water quality standards. Areas in red are in danger of not meeting good status Figure Spatial distribution of the modelled likelihood of (a) river water body phosphorus concentrations from both diffuse and point sources meeting chemical water quality standards. Loch catchments (b) at risk of failing to achieve good ecological status owing to phosphorus induced eutrophication. Areas in red are in danger of not meeting good status Figure Spatial distribution of the modelled likelihood of compliance with good status of river water body Suspended Sediment concentrations from both diffuse and point sources meeting chemical water quality standards of (a) 25mg/l, (b) 15mg/l and (c) 5mg/l Figure Spatial distribution of the modelled likelihood of compliance with good status of river water body Biochemical Oxygen Demand concentrations from both diffuse and point sources meeting chemical water quality standards. Areas in red are in danger of not meeting good status Figure Spatial distribution of river water bodies in which one or more modelled average metal concentration in surface drainage exceeded the relevant Environment Quality Standard. Areas in red are in danger of not meeting good status Figure Spatial distribution of river and coastal water bodies with high (> FC/km 2 ) and medium/low (< FC/km 2 ) risk of faecal coliform pollution arising from all sources. Areas in red are in danger of not meeting good status Figure Spatial distribution of river water bodies in which one or more modelled average pesticide concentration in surface drainage exceeded the relevant Environment Quality Standard. Areas in red are in danger of not meeting good status Figure Spatial distribution of river water bodies where one or more 1km 2 grid cell within these catchments is vulnerable to acidification according to the 1990 dataset. Areas in red are in danger of not meeting good status Figure Spatial distribution of river water bodies where one or more 1km 2 grid cell within these catchments is vulnerable to acidification according to the 2010 dataset. Areas in red are in danger of not meeting good status Figure Source apportionment of phosphorus loading to water for 5 catchments Figure Source apportionment of nitrogen loading to water for 5 catchments Figure Source apportionment of BOD loading to water for 5 catchments Figure Source apportionment of SS loading to water for 5 catchments Figure Agricultural land use in the 5 priority catchments Figure 5.1 Contextual map illustrating the extent of the River Basin Districts and associated surface waters v

8 Figure 5.2 Spatial distribution of the modelled likelihood of river water body nitrate concentrations from both diffuse and point sources meeting chemical water quality standards. Areas in red are at risk of failing to achieve good status Figure 5.3 Spatial distribution of the modelled likelihood of (a) river water body phosphorus concentrations from both diffuse and point sources meeting chemical water quality standards. Areas in red are at risk of failing to achieve good status. Lough catchments (b) at risk of failing to achieve good ecological status owing to phosphorus induced eutrophication Figure 5.4 The spatial distribution of monitored chemical water status for river water bodies. Areas in red are at risk of failing to achieve good status Figure 5.5 The spatial distribution of monitored chemical water status for river water. Areas in red are at risk of failing to achieve good status Figure 5.6 Spatial distribution of river water bodies in which one or more modelled average metal concentration in surface drainage exceeded the relevant Environment Quality Standard. Areas in red are at risk of failing to achieve good status Figure 5.7 Spatial distribution of river water bodies with high (> FC/km 2 ) and medium/low (< FC/km 2 ) risk of faecal coliform pollution arising from all sources. Areas in red are at risk of failing to achieve good status Figure 5.7 Spatial distribution of river water bodies with high (> FC/km 2 ) and medium/low (< FC/km 2 ) risk of faecal coliform pollution arising from all sources. Areas in red are at risk of failing to achieve good status Figure 5.8 Spatial distribution of river water bodies in which one or more modelled average pesticide concentration in surface drainage exceeded the relevant Environment Quality Standard. Areas in red are at risk of failing to achieve good status Figure 5.9 Spatial distribution of river water bodies where one or more 1km 2 grid cell within these catchments is vulnerable to acidification according to the 1990 dataset Figure 5.10 Spatial distribution of river water bodies where one or more 1km 2 grid cell within these catchments is vulnerable to acidification according to the 2010 dataset vi

9 List of Tables Table Threshold pollutant concentrations for defining good status for river waters Table Weighting factors for diffuse and point source contributions used to calculate timeweighted average concentrations... 7 Table Parameters of the regression models predicting observed pollutant concentrations as a function of predicted concentrations, for Northern Ireland and Scotland... 7 Table Parameters of the Phase II regression models predicting observed pollutant concentrations as a function of predicted concentrations, for Northern Ireland and Scotland Table Detail sheets provided in the Summary Tool Table Summary of the input, model and validation data quality used in the modelling of the various pollutants within the river, lough/loch and coastal catchments Table 3.4a - National Statistics from SEERAD Table 3.4b Landcover summary for each AAG in ha Table Changes in livestock numbers in Scotland between 1997 and Table Differences in area of crop grown throughout Scotland Table Differences in areal extent of a range of crops by Area Advisory Group I Table Differences in areal extent of uncropped by Area Advisory Group Table Differences in Cattle, Sheep and Pig livestock numbers between 1997 and 2004 by AAG Table Differences in Poultry and Fowl numbers between 1997 and 2004 by AAG Table Modelled total annual N, P, BOD, SS (tons/year), FIO (10 14 CFU/year) and metals losses (Kg/year) by source Table The modelled percentage failure of number of surface water bodies to achieve good status with respect to P, N, BOD, SS, FIO s, Metals, Pesticides and Acidity for rivers using local catchment data for the whole of Scotland summarised per AAG. The data are categorised according to the four categories of water body risk as defined by the Pressures and Impacts report, considering all pressures (data supplied by SEPA) Table River Water bodies showing a <20% likelihood of achieving good status, considering all pressures Table The proportion of loch catchments that fail to achieve good status as a result of diffuse sources of P Table 4.4: Source apportionment of N, P, BOD and SS to surface waters by AAG (tons/year) Table 4.5: Source apportionment of FIO losses to surface waters by AAG (10 14 CFU per year) Table 4.6: Source apportionment of metals losses to surface waters by AAG (Kg per year) Table 5.1 Modelled total annual nitrate, phosphorus, BOD and suspended sediment losses (tons per year) to surface and groundwater (N, P, BOD) by source for each River Basin District Table 5.2 The proportion (%) of river catchments that fail to achieve good status as a result of diffuse sources of N, P, BOD and SS summarised according to the diffuse pollution WFD risk categorisation Table 5.3 The proportion (%) of lough catchments that fail to achieve good status as a result of diffuse sources of P Table 5.4 The proportion (%) of river catchments that fail to achieve good status as a result of diffuse sources of FIO, Metals, Pesticides and Acidity summarised according to the diffuse pollution WFD risk categorisation Table 5.5 Modelled total annual Escherischia coliform losses (10 14 cfu per year) to surface and groundwater by source for each River Basin District Table 5.6 Modelled total annual metal losses (kg per year) to surface waters by source for each River Basin District vii

10 1 INTRODUCTION The implementation of the WFD is overhauling the management of the water environment within the EU. It is rationalising and updating water legislation and embodies the concept of integrated river basin management. The WFD s approach is integrated management at the River Basin level. Because it is a Framework Directive, it provides common approaches and common objectives, principles, definitions and measures. However, the specific measures required, including those to achieve the objective of good status, have to be determined at the local level. This is the role of the competent authority. In the case of Scotland that authority is SEPA while in Northern Ireland it is the EHS. Catchment characterisation, according to the Water Framework Directive timetable, for all water bodies and for all pollutants, represents a significant challenge for SEPA/EHS. Environmental objectives will be set through the river basin management planning process that will describe Programmes of Measures to achieve the objectives and monitoring programmes to assess change. Phase I of this project (WFD10, 230/8037) therefore investigated the potential for developing a GIS based Screening Tool which could identify those catchments within which water bodies are at risk from diffuse pollution pressures. The Screening Tool was to have national scope, and contribute to the needs of SEPA and EHS to prioritise water bodies, especially those in currently unmonitored areas, for further investigation. The project reviewed the availability, sources, costs and reliability of data that would be required to support the application of diffuse pollution models to predict whether a water body was at risk of failing one or more of the Directive s environmental objectives. The study concluded that the development of this tool was possible and recommended a model based assessment to support gaps in the existing monitoring network. Phase II of the project (WFD19, 230/8050) was therefore commissioned to develop, implement and apply a basic screening tool for all potential diffuse pollutants in order to assess the risk of individual waterbodies failing to meet the good ecological status required under the WFD. The screening tool was built on simple models of pollutant pressures and loads delivered to these waterbodies. Analysis of these results highlighted waterbodies where further monitoring or more complex modelling was required. All of these results along with a host of intrinsic environmental properties were summarised into the delivered Environment Database. The Screening Tool Environment Database containing more than 80 tables and 1000 data items for each of the 78, 770km 2 for Scotland and 14, 140km 2 for Northern Ireland was produced by Phase II of the SNIFFER identification and characterisation of diffuse pollution pressures project. The user-friendliness of this database is currently restricting the wider dissemination of the valuable data contained therein. This is just one of the factors that drove Phase III of this project. This need is heightened by the commitment of both SEPA and EHS to further characterisation of 1b waterbodies, being those waterbodies classified as probably being at significant risk (SEPA, 2005; EHS, 2005), for the forthcoming Significant Water Management Issues (SWMI) report. There is a need to further characterise 1b waterbodies by increasing confidence in the risk assessment. This would be achieved through addressing some of the reasons for the uncertainty surrounding their classification, namely, poor point source pressure data, retention of N and P by waterbody systems and an improvement in the regression models used to convert the load data to concentrations through the inclusion of, for example, factors like seasonality. In addition, source apportionment of each pollutant on a per waterbody basis is required for both the SWMI report as well as by sub-basin advisory groups in order that practical mitigation measures may be identified and implemented. While national and local statistics have been compiled and used from the Screening Tool Environment Database, waterbody statistics have not and are required to meet these objectives. Under Phase III of this project (WFD77), the primary project objectives were: Simplification and summarisation of the current waterbody database into a spreadsheet in order to facilitate comparison with other studies and visualisation through linkages with GIS technologies. 1

11 Further characterisation of the waterbodies through the update of input data (waterbodies and their boundaries; point source inventory), taking account of retention of N and P, exploring an improvement of the regression models used to predict status and assess suspended sediment risk for two lower standards. Summarisation of the source apportionment data per waterbody along with agricultural census data to allow for the contextualisation and interpretation of these source apportionment summaries. Knowledge transfer through the development of a report and the provision of workshops. 2

12 2 UPDATES MADE TO THE INPUT DATA AND MODELLING METHODOLOGY USED TO CREATE VERSION 2 OF THE ENVIRONMENT DATABASE Much of the work presented in this section will refer back to the methodology used in Phase II (WFD19 230/8050) of this project ( The report from that phase was very comprehensive and the user is referred to this report for further information. Changes made to the input datasets and modelling methodology are presented below. 2.1 Point source data and pollution pressure calculations Point source contribution to catchment loads was estimated from population data and per capita export coefficients in the previous phase of the project. Under Phase III, the point sources were estimated from Information on location and capacity of Sewage Treatment Works (STWs), provided by SEPA and EHS. These data were processed to estimate total pollutant load from STWs in each of the analysed catchments. For Northern Ireland, the provided data set contained information on type of treatment and consented discharges for 72 primary STWs. The tables in the Environment Database containing the 1km 2 gridded data were updated to reflect these point source estimates. Similar information was provided for Scotland, but the data were considered to be spatially incomplete and biased towards the south east of Scotland. Therefore a decision was made to revert to the original calculations based on population data and per capita export coefficients as used within Phase II of the project. For calculating pollutant loadings the dry weather flow (DWF) provided was used in conjunction with estimated effluent concentrations for phosphorus (P), nitrogen (N), Biochemical Oxygen Demand (BOD), Suspended Solids (SS) and Faecal Indicator Organisms (FIO). Where information on discharge and effluent concentration was available this data was used first. Where it was not available the DWF was used to estimate the number of people connected to the works assuming a dry weather flow of 280 l/person/day (derived from comparing the total DWF with the population of Northern Ireland). This in conjunction with the per capita export coefficients used in Phase II allowed for the calculation of concentrations in effluent water for P, N, BOD and SS and the subsequent calculation of loads. FIO loads were calculated using the information provided on the type of treatment for each STW along with measured effluent concentrations for different types of treatment according to Stapelton et al. (2002). 2.2 Updated catchment boundaries and waterbody types New sets of catchment boundary data were provided by SEPA and EHS. These included loch/lough and river catchments for both Scotland and Northern Ireland. Scottish coastal catchment boundaries were also provided. Loch and river catchment boundaries were supplied as nested and unnested polygons, i.e. as the total contributing area (TCA) to a loch/lough or a point along a river, and as local subcatchments (LC). For lough catchments in Northern Ireland, only TCA were provided. For P, N, BOD, SS and FIO, tables with total predicted load and percentage contributions from the different catchment sources were updated for the new catchment boundaries by summarising data held at a 1km grid cell level. These summaries were carried out by taking the average of the values of grid cell centroids falling within the catchment boundaries. For small catchments, containing less than 5 centroids, a buffer technique was used by which a circle with a radius of 3 km was created about the centroid of the catchment and grid cell data within this circle was used in the calculations. Likewise, grid data containing information on metals, pesticides and the occurrence of acid exceedances was also summarised for the catchments. Tables with information on local catchments and total contributing area have the postfix LC and TCA respectively in the version 2 database. 2.3 Inclusion of retention for N and P Phosphorus, nitrogen and other pollutants that enter watercourses will be affected by instream retention processes such as sedimentation and denitrification. This will result in a discrepancy between the losses from diffuse and point sources in catchments and what can be measured at monitoring stations at the outlet of the catchments. 3

13 To account for retention in river systems the gross loads of nitrogen and phosphorus were reduced using the method developed by Behrendt and Optiz (2000). This method can be used for large river basins, but since this may result in overestimates of the importance of retention of sources close to the catchment outlets and underestimates of the retention of sources in the headwaters, it was decided to calculate individual retention factors (net load / gross load) for each of the local catchments and use them to calculate total catchment retention as illustrated in Figure 2.1. Figure Schematic of the effect of nutrient retention, showing how much an input to a watercourse in a sub-catchment will be reduced before it has been delivered to the mouth of the catchment. The darker colours illustrate areas where a larger fraction of the inputs will be retained, while inputs in the lighter areas are less affected by retention processes. Consideration of the upstream catchments results in as much as a 35% difference in the magnitude of the retention factor. Retention factors were calculated based on catchment hydraulic load, where hydraulic load is defined as the annual runoff divided by the water surface area in the catchment using equation 2.1. as given by Behrendt and Optiz (2000). R f = L D N, P N, P 1 = 1+ a HL b 2.1 Where L N,P is the net loss of nitrogen or phosphorus and D N,P is the gross loss. The constants a and b set to 1.9 and 0.49 for total nitrogen, respectively while they are set to 13.3 and 0.93 for total phosphorus. The hydraulic load was calculated from the annual runoff and the surface water area calculated using the following empirical relationship in equation 2.2: As = ALAKE A 2.2 Where A LAKE (km 2 ) is the surface area of the lakes within the catchment and A is the catchment area (km 2 ) (Behrendt and Optiz, 2000). Pollutant losses originating from local catchments upstream of the catchment outlet will be affected by retention in all sub-catchments passed through en route to the outlet. The total effect of retention upstream of a point of interest was calculated using equation 2.3 (Behrendt and Optiz, 2000). 4

14 L jtotal, net = Rf n i, ds j, local L i, Local, gross i= 1 Rfj, ds Rf, 2.3 Where i = 1,2 n is the index of sub-catchments contributing to a catchment j for which the total net load, L j,total.net, is calculated. L i,local,gross is the local gross loss (before retention) from contributing catchments. Rf i,ds and Rf j,ds are the product of local retention factors for the catchments and all catchments downstream (to the main catchment outlet). Only the net load is displayed in the summary tool. The catchment average retention in Northern Ireland was estimated as being ~8% and ~12% for Phosphorus and Nitrogen respectively while for Scotland these were ~10 and ~13%. Vollenweider s estimate of phosphorus retention in lakes (OECD 1982) was used to calculate environmental concentrations of phosphorus in Scottish lochs and Northern Irish loughs. This method takes account of the effect of phosphorus retention, caused by for example sedimentation processes. The concentration of P in lakes was calculated using equation 2.4: 5 10 L C = H ( 1+ t) Where C is the predicted total phosphorus concentration (µg l -1 ), L is the catchment average load (kg P ha -1 ) and H is the modelled average catchment drainage (mm), and t is the average hydraulic resident time of the lake (yr). 2.4 Improvement of the regression equations for N, P, SS and BOD Phase II of the project utilised a predictive regression technique to relate modelled and measured pollutant concentrations with the confidence of these statistical relationships being used to derive a likelihood of achieving a good status as per the thresholds given in Table 2.1. This process was described fully in the Phase II report and readers are referred to this report should they require further detail. Phase III of this project sought to address some of the weaknesses in these relationships by: Using more recent and a longer period of monitoring data Time-weighted as opposed to flow-weighted modelled average concentrations Applying individual weights to the point and diffuse sources SEPA and EHS monitor concentration of soluble phosphorus, nitrate, suspended solids and biochemical oxygen demand at several sites in their monitoring networks. Monitoring data for was used in this study to calculate average and relevant percentile concentrations for the four pollutants. In this study only monitoring sites with more than 15 observations were used. In catchments containing more than one monitoring site, the highest measured value was used. Table Threshold pollutant concentrations for defining good status for river waters. Parameter Quality Threshold Value Phosphorus Average µg/l Calcareous Geology Concentration 40.0 µg/l Organic / Siliceous Geology Nitrate Suspended Sediment Biochemical Oxygen Demand 95 th Percentile Average Concentration 90 th Percentile 11.3 mg/l 25.0 mg/l 4.0 mg/l 5

15 New time-weighted concentrations were estimated from predicted loads for each of the local catchments where observed values were available. This enabled accurate comparisons of modelled and observed concentrations in these calibration catchments. Information on Hydrology Of Soil Type (HOST) (Boorman et al., 1995) was used to estimate the river flow regime. Each HOST class has an associated Q95 value describing how the soil will affect a river s responsiveness to rainfall. Using this information, Hyrdrologically Effective Rainfall (HER) weighted Q95 values were calculated for each catchment. These numbers could then be used in conjunction with information on HER to derive flow exceedance curves using a flow exceedance model (Anthony pers. comm.; Gustard et al. 1992). Pollutant loading from point sources can be assumed to remain constant during the year. The diffuse loading will, however, vary with runoff such that the relative point source contribution will be relatively higher during drier periods of the year. Therefore, flow and time weighted concentration will differ as illustrated in Figure 2.2. Having derived flow exceedance curves and assuming a constant concentration in diffuse runoff, it was possible to mix the constant load from point sources with the diffuse contribution varying across the year to calculate time-weighted concentrations. Figure Illustration of an idealised flow exceedance curve for a clay catchment along with the corresponding pollutant concentration obtained when diluting a fixed point source. Timeweighted averaging yields a concentration of 2.86 mg/l while flow weighted averaging yields a concentration of 1.6 mg/l. Concentration (mg/l P) Percent of Time Flow Exceeded (%) Flow (m3/s) Conc (mg/lp) Flow (m3/s) For the calibration catchments, the newly calculated concentrations were plotted against the observed and log-log linear regressions were derived for each pollutant. At this stage it was possible to apply separate weighting factors to diffuse and point contributions. By minimising the sum of squares of the differences between modelled and predicted values by changing the weighting factors for diffuse sources and point sources it was possible to improve the regressions. The weighting factors used can be found in Table 2.2. The new linear regression equations can be found in Table 2.3. Using the statistics derived in this exercise it was possible to calculate confidence intervals, and to calculate the probabilities of a given catchment being of good status as outlined in the report of Phase II of this project. It was also possible to estimate the likelihood of good status assuming no point source contribution by eliminating the weighting factor for the point source contribution. The regression equations are comparable to those derived in Phase II of this project (Table 2.4) and are not significantly better or worse. While it might be tempting to suggest that they have not been improved, they have been derived using a sounder methodology that addressed a number of weaknesses and more robust and recent base data. The results can be found in the status tables in the database (e.g. tblinterstatusphosphorus for river phosphorus status). For BOD and SS in Northern Ireland, the correlations were considered too weak to be used with any confidence (r 2 = 0.17 and 0.31). The calculation of loads and average concentrations from observed data is liable to significant error due to the infrequency of sampling with respect to changes in flow conditions and transport capacity of the river along with the methodologies not taking account of sources which may be locally significant, such as industrial discharges. Hence in Northern Ireland for SS and BOD only the 6

16 observed values are shown in the Summary Database Tool for catchments where these are available together with a nationwide estimate of the likelihood of good status. This likelihood is derived from the distribution of observed values, assuming a normal distribution. Table Weighting factors for diffuse and point source contributions used to calculate timeweighted average concentrations. Northern Ireland P N BOD SS Diffuse source weighting factor Point source weighting factor Scotland P N BOD SS Diffuse source weighting factor Point source weighting factor Table Parameters of the regression models predicting observed pollutant concentrations as a function of predicted concentrations, for Northern Ireland and Scotland. Regression Model n r 2 Observation Northern Ireland Phosphorus ln(obs) = 1.293*ln(pred) Average Nitrate ln(obs) = *ln(pred) th percentile BOD ln(obs) = *ln(pred) th percentile Suspended solids ln(obs) = *ln(pred) Average Scotland Phosphorus ln(obs) = 0.714*ln(pred) Average Nitrate ln(obs) = *ln(pred) th percentile BOD ln(obs) = *ln(pred) th percentile Suspended solids ln(obs) = 0.316*ln(pred) Average Table Parameters of the Phase II regression models predicting observed pollutant concentrations as a function of predicted concentrations, for Northern Ireland and Scotland. Regression Model n r 2 Observation Northern Ireland Phosphorus ln(obs) = 1.771*ln(pred) Average Nitrate ln(obs) = 0.753*ln(pred) th percentile BOD ln(obs) = 0.262*ln(pred) th percentile Suspended solids ln(obs) = 0.334*ln(pred) Average Scotland Phosphorus ln(obs) = 0.775*ln(pred) Average Nitrate ln(obs) = 0.882*ln(pred) th percentile BOD ln(obs) = 0.147*ln(pred) th percentile Suspended solids ln(obs) = 0.351*ln(pred) Average 7

17 3 BRIEF DESCRIPTION OF THE SUMMARY DATABASE TOOL 3.1 Background The SNIFFER Environment Database containing more than 80 tables and 1000 data items for each of the km 2 for Scotland and km 2 for Northern Ireland was produced by Phase II of the SNIFFER identification and characterisation of diffuse pollution pressures project. The user-friendliness of this database is currently restricting the wider dissemination of the valuable data contained therein. This is just one of the factors driving Phase III of this project. This project has therefore designed and constructed a tool to summarize the data held within the Screening Tool Environment Database into an MS Excel spreadsheet, and provide some basic search and querying functionality based on standard Excel filtering functionality. The tool contains administrator update functionality to automatically draw the data from the updated database. The design specification of this Diffuse Pollution Screening Tool Summary spreadsheet derives from a workshop held in Edinburgh on the 13 th February 2006 between the project consortium and SNIFFER. 3.2 High Level Design The Tool consists of one.xls file for each country. The files contain: One summary sheet for each of the catchment types One detail sheet per catchment type per pollutant One Data Dictionary sheet describing each piece of data and where appropriate how it was calculated or the original database field code. One Administrator Update page The catchment types for each country are: Scotland: River (Total and Local) Loch (Total and Local) Coastal (Local only) NI: River (Total and Local) Lough (Total and Local) Total and local refer to the catchment hierarchy. Total refers to all the total upstream sub-catchments that drain into the catchment while local refers to the sub-catchment only Summary Sheets There is one summary sheet for each of the following catchment types: River Loch/Lough Coastal. Therefore the Summary sheets provided are: Scotland: River_Sum Loch_Sum Coastal_Sum NI: River_Sum Lough_Sum 8

18 Each row on the Summary sheets summarises information for each catchment (referenced by the unique ID provided by SEPA/EHS) and includes the following information (detailed column by column specifications are presented in Appendix 1): Unique Catchment ID (Column A below) Area Advisory Group (Scotland) / River Basin District (NI) (Column B) Catchment properties (Columns C to E) Screening Tool predicted Overall Status Flag (Column M) Good status likelihoods for each of Phosphorus (P), Nitrogen, BOD, Suspended Sediment (SS) (Columns N, X, AH and AR) Confidence in likelihoods for P, N, BOD, SS (Cells N2, X2, AH2 and AR2) Exceed/Not Exceed flag for Faecal Indicator Organism (FIO), Metals (MET), Pesticide (PEST), ACID (1998), ACID (2010) (Columns BB-BF) Pressures and Impacts (P&I) Database Data (Only for Scotland) (Columns F to L, not shown) Land use breakdown for Agriculture (Columns BG to BW, not shown) Figure 3.1 Screenshot of a summary page within the Summary Tool. 9

19 3.2.2 Detail Sheets Table 3.1 shows the details sheets that have been provided. In general terms (detailed column by column specifications are presented in Appendix 1), these sheets show: For P, N, BOD and SS o Rainfall for local and accumulated catchments o Geology o Retention data for Diffuse and All sources for local catchments only (N and P only) o Annual Load from Diffuse and All sources for local and accumulated catchments o Volume based mean Concentration from Diffuse and All sources for local and accumulated catchments o Good status likelihood for Diffuse and All sources and for local and accumulated catchments o Confidence ratings for the good status likelihoods for Diffuse and All sources and for local and accumulated catchments o Good/Fail flag based on user entered concentration threshold for Diffuse and All sources and for local and accumulated catchments o NB data will be shown for local catchments only for Coastal catchments For MET, PEST o Hydrologically Effective Rainfall (MET) / Catchment Average Volume of Runoff Event Water (PEST) for local and accumulated catchments o Overall Exceed/Not Exceed flag indicating whether catchment exceeds on one or more user entered thresholds for local and accumulated catchments o Individual metals inputs for local and accumulated catchments o Individual substance concentrations for local and accumulated catchments o Exceed/Not Exceed flag for each individual substance based on user entered concentration thresholds for local and accumulated catchments o NB data will be shown for local catchments only for Coastal catchments For ACID o A binary rating which signifies whether catchment contains one or more 1km square (from UCL) associated with an exceedance point for 1998/2000 & 2010 for Accumulated and Local catchments. Please refer back to the methodology used in Phase II (WFD19 230/8050) of this project ( for further details. The purpose of the details sheets is to show the pollutant loads and concentrations for each accumulated and local catchment and to allow the user to explore that data with their own concentration threshold values. These sheets are also used as the lookup data behind the Summary sheets. Table Detail sheets provided in the Summary Tool Catchment Type Pollutant Sheet Name Country River Phosphorus River_P Scot & NI Nitrogen River_N Scot & NI BOD River_BOD Scot & NI Sediment River_SS Scot & NI Faecal Indicator Organisms River_FIO Scot & NI Metals River_Met Scot & NI Pesticide River_Pest Scot & NI Acid River_Acid Scot & NI Loch/Lough Phosphorus Loch/Lough_P Scot & NI Nitrogen Loch/Lough_N Scot & NI 10

20 BOD Loch/Lough_BOD Scot & NI Sediment Loch/Lough_SS Scot & NI Metals Loch/Lough_Met Scot & NI Pesticide Loch/Lough_Pest Scot & NI Acid Loch/Lough_Acid Scot & NI Coastal Phosphorus Coastal_P Scot Data Dictionary Sheet Nitrogen Coastal_N Scot BOD Coastal_BOD Scot Sediment Coastal_SS Scot Faecal Indicator Organisms Coastal_FIO Scot Metals Coastal_Met Scot Pesticide Coastal_Pest Scot Acid Coastal_Acid Scot A sheet giving metadata on the columns contained within the spreadsheet is provided. This sheet gives descriptions of the data items, how the data was calculated where appropriate, and also where appropriate, the field code within the database to enable tracing back to the database. To supplement the data dictionary, pop up notes are embedded in the field heading on each work sheet Administrator Update Sheet This sheet presents a series of macro-enabled user controls that automatically retrieve the data from the Screening Tool Environment Database, filter and format the data and populate the relevant Worksheets within the spreadsheet. This sheet is password protected, so only authorized users have access to the page. This data refresh is only guaranteed to work if undertaken by such an authorized user. 3.3 Confidence/Quality Numbers These numbers were generated in order to summarise the confidence in and quality of the various aspects of the modelling process, namely input data compilation and usage, model application/development and the degree of validation undertaken along with the quality of the validation data and process. Each of these were allocated a category which best described it ranging from 1 (good) through 2 (moderate) to uncertain (3). In order to assess these categories a summary of the modelling process that was undertaken for each pollutant is summarized in the following two sections highlighting the rural and urban pollution pressures. The following summaries were compiled from the Phase II report that contains a lot more detail and readers are referred to this report Phase 2 Modelling Approach A detailed modelling methodology and justification were given for the model approaches selected for each of the diffuse pollutant pressures, along with their sensitivities and limitations, in the Phase II report. In general, the models were able to provide annual estimates of total pollutant load delivered to surface waters. Modelling methodologies were selected that combined intrinsic and specific datasets to provide qualitative and quantitative measures of the pollutant loading input to the river and lake waters. The models were required to work with the environmental data available for the whole of Scotland and Northern Ireland. The requirement for national screening meant that the selected modelling methodologies were relatively simple, and would not take account of any in-river transport or processes. Models used were, as far as possible, well established and of an appropriate level of complexity for between catchment comparisons. The methodologies were peer reviewed at a workshop attended by experts from SEPA, EHS, DARD and Forest Research Phase 2 Rural Pollution Pressures 11

21 Nitrate: Nitrate leaching risk was assessed using a simplified version of the NIRAMS model. The simplification removed the hydrological routing function that models the transport of water and solute N from the land to surface water bodies. This simplification makes assumptions about the equilibrium between surface and groundwater nitrate concentrations, but this was not believed to be an important issue in most areas. Inputs and their uncertainty relate to the agricultural practice and statistics data used to determine nitrogen inputs. Model uncertainty pertains to simplification of the model and the simplified functions used to determine and leach the residual nitrogen, as the latter is highly dependant on hydrological conditions. Phosphorus: Three components of Phosphorus were modelled using an early version the process based PSYCHIC model, that which is bound and adsorbed to soil particles, that which is soluble and soil derived and that which is incidental and derived from applied manures and fertilisers. Inputs and their uncertainty relate to these different components soil type, texture, slope, slope length and landscape connectivity for the first, soil type and chemistry for the second and agricultural practice and statistics data for the third. Model uncertainty may be introduced in that PSYCHIC has been calibrated and validated for lowland, arable and grassland agriculture and as such results for areas of humose/peaty and upland soils should be treated with caution. Likewise areas with fine scale undulating topography, like the drumlindominated landscape south of Lough Neagh, where the effects of flow accumulation and transport capacity are unknown should also be treated with caution. This work did not consider the contribution to diffuse phosphorus loading made by bank erosion. Sediment: Sediment was also modelled using the PSYCHIC model. Similar to that described for Phosphorus, inputs and their uncertainty relate to soil type, texture, slope, slope length and landscape connectivity. Model uncertainty may be introduced in that PSYCHIC has been calibrated and validated for lowland, arable and grassland agriculture and as such results for areas of humose/peaty and upland soils should be treated with caution. Likewise areas with fine scale undulating topography, like the drumlin-dominated landscape south of Lough Neagh, where the affects of flow accumulation and transport capacity are unknown should also be treated with caution. This work did not consider the contribution to diffuse sediment loading made by bank erosion, nor did it take account of retention in the river or lake systems. Biochemical Oxygen Demand: The PSYCHIC algorithms that were used for calculating incidental phosphorus losses from farmsteads and manure spreading were adapted to calculate BOD losses by simple substitution of the available phosphorus content of manures for an estimated BOD content. Inputs and their uncertainty relate to the agricultural practice and statistics data used in the incidental losses estimates by PSYCHIC. Although the majority of the diffuse load of BOD is considered to originate from animal manures, our modelled BOD loads were expected to underestimate the observed loads because of the unknown contribution from industrial point sources and additional contributions from decaying organic matter originating from eroded peat soils and forest leaf litter. It is also important to note that the error in the modelled urban loads is likely to be highest in the moderately urbanised catchments, because of uncertainty in the percentage paved area and representative Event Mean Concentrations. Metals: Given the slow leaching rate of metals the primary transport mechanism is through physical processes, particulate movement and surface runoff. Heavy metals were assessed using a simplified approach whereby atmospheric deposition data and the soil binding capacity of a soil specific to a metal were used in conjunction with the modelled sediment losses to predict total metal load to water. The average annual bucket concentration for each metal has been calculated for surface water in each catchment by dividing the predicted metal load from all sources, including urban runoff, by the predicted hydrologically effective rainfall (HER). This provides the basis for comparison with EQS values for each metal and to identify catchments where the predicted metal concentrations exceed or are approaching whatever EQS values SEPA or EHS choose to implement. Inputs and their uncertainty relate to the deposition values and soil type and chemistry. Model uncertainty is largely as a result of the simplified approach using the metal binding capacity assessment. Faecal Indicator Organisms: FIOs were modelled using a simplified version of the PAMIMO-C model. The processes were simplified by functionally relating all losses to livestock numbers, sub-surface and overland flows, which are derived from the water balance model. Entrainment curves for flow dependencies were used such that: 12

22 Total E. coli loss to surface water = EC farm+channel. SoilBurden. S(SSF+OVF, farm type) + EC SSF. SoilBurden. S(SSF, soil) + EC OVF. SoilBurden. S(OVF, soil) This procedure is essentially a smart dynamic export coefficient approach, which works well for a system with continuous inputs. Each factor depends on an export coefficient EC, livestock number or soil burden and a mobility factor, which is flow dependent with SSF the sub-surface flow and OVF the overland flow. Inputs and their uncertainty relate to the agricultural practice and statistics data used, while the model uncertainty stems from the combination of the discharge probability density functions with the entrainment ratios to produce the probability of E. coli losses with SSF, OVF, or total discharge for each grid-cell. Pesticides: For surface waters, the average concentration of pesticide entering rivers via drain flow and surface runoff during the peak flow following rainfall events was calculated using the field component of SWATCATCH, the SWAT model (Brown and Hollis, 1996). Inputs and their uncertainty relate to the agricultural practice and statistics data used to determine loads along with the generated daily time series of rainfall to which SWAT is particularly sensitive. Acid: Efforts to investigate acidification risk did not entail a modelling approach. Rather, use was made of existing datasets that have been created under UK-wide efforts. These data include a freshwater sensitivity rating based on intrinsic environmental data from the Centre for Ecology and Hydrology (CEH) Freshwater Sensitivity Map and critical loads exceedance data from the UK National Focal Centre s work on guiding policy to reduce the environmental impacts of transboundary air pollutants, such as sulphur dioxide Phase 2 Urban Pollution Pressures The load of urban pollutants to receiving waters can be represented simply as the product of runoff and an event mean concentration (EMC) of pollutant (Mitchell et al., 2001). For this work, pollutant loads for each of the 1km 2 cells in the reference grids were calculated from literature values of EMCs for a range of general pollutants and priority hazardous substances, and modelled average annual runoff under longterm climate conditions. All loads from roads and urban areas were assumed to discharge directly into surface waters. The modelled loads were converted into mean annual concentrations by dilution with the mean annual river flows. The concentrations were compared with Environment Quality Standards (EQS) to establish whether a site was at risk of failing to meet standards for good ecological status, based only on the urban diffuse load. Inputs and their uncertainty relate to the generalised nature of the EMCs and the volume of runoff such that the spatial pattern of the calculated loads is generally the same for each pollutant, in proportion to the paved area and volume of runoff from each cell Phase 2 Validation procedure As part of the testing of the model implementations, model predictions of total pollutant loads output by the selected pressure models were compared against observed river data for 13 catchments from Scotland and 6 from Northern Ireland. The catchments were selected as being representative of the range of catchment environments and having adequate monitoring data for the calculation of pollutant loads. For each test catchment, modelled loads were calculated from the total losses tabulated in the Environment Database for each 1km 2 intersecting the catchment boundaries. Comparison with the observed loads was restricted to selected metals, soluble phosphorus, nitrate, suspended solids and biochemical oxygen demand. The modelled output for total phosphorus has been compared to the available data for monitored SRP (soluble reactive phosphorus). Overall, the comparisons of modelled and observed pollutant loads for the small number of test catchments demonstrated that the selected models were able to provide pollutant load estimates that were generally comparable to observed loadings. However, uncertainty in both the observed and modelled data precluded a strong statement of validation, i.e. that the models were able to give an accurate measure of pollutant pressure for an individual catchment. However, the calibration of the models against a wider set of observed concentration data proved the ability of the models to discriminate catchments of relatively high and low risk. 13

23 3.3.5 Confidence/Quality Numbers Matrix The confidence/quality numbers given to each of the modelling processes for each of the pollutants for each of the waterbody types are summarized within Table 3.3. These assessments are expert driven and reflect the state of the models used in Phase II of the project, e.g. an early versus the current version of the PSYCHIC model, as well as the updates effected during Phase III, e.g. N retention. Table Summary of the input, model and validation data quality used in the modelling of the various pollutants within the river, lough/loch and coastal catchments. Catchment Type Pollutant Input Data Quality Model Quality Validation Data Quality River Phosphorus Nitrate BOD Sediment FIO Metals Pesticide Acid 1 N/a 2 Loch/Lough Phosphorus Nitrate 2 2 N/a BOD 2 2 N/a Sediment 2 2 N/a FIO 3 3 N/a Metals 3 2 N/a Pesticide 3 2 N/a Acid 2 2 N/a Coastal Phosphorus 3 2 N/a Nitrate 2 2 N/a BOD 3 2 N/a Sediment 3 2 N/a FIO 3 2 N/a Metals 3 2 N/a Pesticide 2 2 N/a Acid 1 2 N/a 1=Good; 2=Moderate; 3=Uncertain 3.4 Agricultural census data changes from 1997 to 2004 for Scotland The modelling for Phases I and II utilised Agricultural Census data from 1997 for Scotland. This has been highlighted as a potential weakness of the study and this analysis investigates the changes that have occurred within the various Area Advisory Groups (AAG) over the last 7 years ( ) Introduction The Agricultural and Horticultural Census returns for 1997 and 2004 were compared to assess changes in Scottish agriculture. The Scottish Executive collects these data in June of each year. The two years chosen were selected owing to: (1) the original screening tool used the 1997 census returns, (2) the 2004 census data are the most current and readily available data. The data were examined at a national scale as well as by the SEPA Area Advisory Groups (AAG). It should be pointed out that the boundaries of the AAGs do not correspond exactly with the boundaries of 14

24 the agricultural census data that is reported by Parish. Therefore, the agricultural returns data for some Parishes is used more than once as part of the Parish falls within one or more AAG. Since the Agricultural census data cannot be disaggregated below the Parish level, it is impossible to tell what land use occurred within each sector of the Parish that overlaps the AAG boundary. Thus the total area of cropping calculated by summing the data reported by AAG would exceed that reported nationally National data Nationally compiled statistics taken from the Scottish Executive website for the period between 1997 and 2004 show that there was a total reported increase in the area of cultivated land (Table 3.4a). This includes crops, grasslands less than 5 years old, grasslands more than 5 years old and temporarily setaside land. The figures quoted within the screening tool for Rough grassland were taken from the Land Cover Map (LCM) and not from the Agricultural and Horticultural Census data as these census figures only include sole grazing rights areas and therefore no comparison between 1997 and 2000 was possible. The increase in the area of cultivated land was in the region of ha. However, the main increase was in managed grasslands greater than 5 years old (permanent or long ley pasture) while the extent of young managed grassland and arable land fell (Table 3.4a). This increase in old managed grassland was not reflected in an increase in livestock but rather the reverse for grazing animals such as cattle and sheep. All cattle sectors saw a decline in the number of animals by between 3.5 and 13% (with a 5.5% reduction overall). The national sheep flock fell by over 1.5M animals, a 16.3% reduction between 1997 and The pig herd also saw a fall of over pigs (almost 27% decline since 1997) while poultry and other fowl saw an increase of over 11% each (a total in excess of birds). We estimate that these reductions in stock numbers have led to an overall 13% reduction in N returns from livestock, nationally. This decline reflects economic drivers like CAP reform as well as the Foot and Mouth outbreak in Within the land cultivated for crops (including short ley pasture of less than 5 years old) there has been a large percentage increase in the area of combinable peas and beans though this amounts to an increase in land of only ha (Table 3.6). The main decreases have been in the area of cereals and forage crops (the latter probably reflecting the decline in livestock numbers). Over less ha of land were sown to cereals (including oilseed rape and linseed) in 2004 as compared to 1997 but there was a rise in the area of land set aside or in fallow by ha. Based on cropping areas and annual average fertilizer use on crops, we estimate that these changes will have led to about a 10% reduction in fertilizer N inputs to crops between 1997 and This is expected to have a <10% reduction in nitrate leaching, so on a national basis, will have a slight impact on predictions of nitrate leaching Area Advisory Group (AAG) SEPA has identified 10 Area Advisory Groups (AAG) within Scotland: Argyll, Clyde, Forth, North East Scotland, North Highland, Orkney and Shetland, Solway, Tay, Tweed, and West Highland. Although the land use changes reported nationally were generally reflected by the land use changes within the AAGs this was not always the case. Table 3.4b has been provided to contextualise the areas of land use described below. Argyll AAG: Argyll had the smallest change in the area of cropped land in Scotland but the largest change in the land under set-aside, an increase of 997% that is a land area of 366 ha (Table 3.8). The number of cattle fell by over and the number of sheep by almost , 5.2 and 12.2 % respectively which is slightly less than the national average for sheep but about the national average for cattle. Clyde AAG: The Clyde AAG has seen a considerable drop in the area of cereals and of potatoes and other root crops (approximately and 380 ha respectively or 13.7 and 32.2 percent of their 1997 levels) with a rise in the area of land set aside to 1248 ha. The numbers of all livestock have dropped in the Clyde AAG. Forth AAG: Forth AAG has seen a drop in all the main cropping types (apart from combinable beans and peas) and in all livestock categories. The area under cereals fell by has in the period between 1997 and 2004 while the area of set-aside rose by ha. 15

25 North East Scotland AAG: The North East Scotland AAG saw the largest decline in the area of cereals grown ( ha) but this was only 10.4 % of the 1997 levels. There was a small increase in the area of combinable beans and peas. The decline in the area of forage cropping reflects the decrease in the number of sheep and cattle. Significantly, the number of poultry and other fowl rose by almost 60% each (an increase of 1.8M birds) and accounts for approximately half of the increase throughout Scotland. North Highland AAG: Cropping in the North Highland AAG followed the national trend overall including an increase in the area under potatoes and root vegetables. The area under set-aside almost doubled over the period 1997 to 2004 but the most dramatic increase was in the number of poultry and fowl with an additional 3M birds, a rise of 300%. The number of sheep, cattle and pigs all declined and there was a increase of ha in the area set aside. Orkney and Shetland AAG: Orkney and Shetland AAG showed some of the smallest changes overall except in the numbers of pigs, fowl and dairy and the area of set aside, forage and root crops. The numbers in all livestock categories fell. Solway AAG: The numbers of all livestock in the Solway AAG fell between 1997 and The area of bare, fallow and set-aside land rose by ha while the area of cereals declined by almost 1 200ha. Tay AAG: The Tay AAG saw one of the largest declines in the area of land under cereals (over ha) but this was only a 10% change in the 1997 extent. There was a 10% increase in the area of potatoes and root crops (2 250 ha) and an increase of ha of bare, fallow and set aside land. The numbers of animals in all livestock categories fell. Tweed AAG: The Tweed AAG saw the largest increase in the area of land used to grow combinable beans or peas and this represented a doubling of the area from 1997 to The area of cereals fell by ha which represents a fall of 10% on 1997 levels. Forage crops and potatoes also declined but setaside doubled to 6 000ha. The numbers of pigs, cattle and sheep all fell in the Tweed AAG but the number of poultry and fowl doubled to birds during the period 1997 to West Highland AAG: The area of all crops grown in the West Highland AAG declined over the period 1997 to 2004 with the area of set-aside and bare or fallow land increasing but by less than half the area previously under cropping. There were small increases in the numbers of beef cattle, poultry, fowl and pigs and small decreases in the numbers of dairy cattle and a sizeable decline in sheep numbers. 16

26 Table 3.4a - National Statistics from SEERAD Area of cropping (ha) and number of holdings Difference in area between 1997 and 2004 %age difference Number of holdings Tillage area (ha) Grass under 5 years old (ha) Arable (tillage area + grass under 5yrs old) (ha) Grass over 5 years old (ha) Total crops and grass (ha) Total grassland(ha) Total area (ha) (minus indicates a decline from 1997) Table 3.4b Landcover summary for each AAG in ha AAG Sea, estuary and inland water Rock, sediment and bare ground Saltmarsh, bog and fen Rough grazing Woodland Managed grassland Arable Urban and peri-urban Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland

27 Table Changes in livestock numbers in Scotland between 1997 and 2004 Livestock type Changes in animal numbers between 1997 and Difference %age difference Beef cattle Dairy cattle Other cattle All cattle Poultry Fowl Pigs Sheep (minus indicates a decline from 1997) Table Differences in area of crop grown throughout Scotland Crop type Changes in area of crop (ha) between 1997 and Difference (ha) %age difference Beans & peas Cereals Forage crops Fruits Potatoes & root vegetables Fallow Set Aside (minus indicates a decline from 1997) 18

28 Table Differences in areal extent of a range of crops by Area Advisory Group I Area Advisory Group Changes in area of crops grown between 1997 and (ha) 2004 (ha) Beans & Peas Cereals Difference (ha) % age difference 1997 (ha) 2004 (ha) Difference (ha) % age difference Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland (minus indicates a decline from 1997) Table 3.7 (cont) Area Advisory Group Differences in area of crops grown between 1997 and (ha) 2004 (ha) Forage crops Potatoes & root vegetables Difference (ha) % age difference 1997 (ha) 2004 (ha) Difference (ha) % age difference Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland (minus indicates a decline from 1997) 19

29 Table 3.7 (cont) Area Advisory Group Differences in area of crops grown between 1997 and (ha) 2004 (ha) Fruits All crops Difference (ha) % age difference 1997 (ha) 2004 (ha) Difference (ha) % age difference Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland (minus indicates a decline from 1997) Table Differences in areal extent of uncropped by Area Advisory Group Area Advisory Group Differences in area of uncropped and total area of arable land between 1997 and (ha) 2004 (ha) Set aside Bare & fallow Difference (ha) % age difference 1997 (ha) 2004 (ha) Difference (ha) % age difference Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland (minus indicates a decline from 1997) 20

30 Table Differences in Cattle, Sheep and Pig livestock numbers between 1997 and 2004 by AAG Area Advisory Group (AAG) Changes in animal numbers between 1997 and 2004 Beef cattle Dairy cattle difference % age difference % age Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland (minus indicates a decline from 1997) Table 3.9 (cont) Area Advisory Group (AAG) Changes in animal numbers between 1997 and 2004 Other cattle Total cattle difference %age difference %age Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland (minus indicates a decline from 1997) 21

31 Table 3.9 (cont) Area Advisory Group (AAG) Changes in animal numbers between 1997 and 2004 Sheep Pigs difference %age difference %age Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland (minus indicates a decline from 1997) Table Differences in Poultry and Fowl numbers between 1997 and 2004 by AAG Area Advisory Group (AAG) Changes in animal numbers between 1997 and 2004 Poultry Fowls difference %age difference %age Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland (minus indicates a decline from 1997) 22

32 4 SCOTLAND - INTERPRETATION OF THE SUMMARY DATABASE TOOL RESULTS 4.1 Diffuse Pollution Issues in Scotland This report will focus on the following pollutant groupings, Nitrate; Phosphorus, Sediment, Biochemical Oxygen Demand and Metals; Faecal Indicator Organisms; Priority Substances/Pesticides and Acidity. Figure 4.1 shows a map of the Area Advisory Groups (SEPA, 2005). These boundaries are shown in subsequent figures illustrating likelihood of good status across Scottish rivers and lochs. The main diffuse pollution issues in Scotland are: nitrate leaching to ground and surface waters from fertilisers and manures, especially in the Nitrate Vulnerable Zones of Eastern Scotland (North East, Tayside, Forth and Tweed AAGs) and the Dumfries and Nithsdale basin (Solway AAG); phosphorus and sediment runoff from sloping arable land in Eastern Scotland (North East, Tayside, Forth and Tweed AAGs) as well as loss from urban point sources (sewage treatment works); pesticide runoff and leaching from intensive arable and horticultural land in Eastern Scotland (North East, Tayside, Forth and Tweed AAGs); faecal indicator organism (FIO) and BOD runoff and leaching from intensive livestock (dairy and beef) especially in South West Scotland (Clyde and Solway AAGs). There are also significant point source loads from sewers and roads Summary of pollutant loads Table 4.1 summarises the modelled total annual nitrate, phosphorus, BOD and SS losses (tons per year) as well as FIO (10 14 cfu per year) and metals (kg per year) from diffuse and point sources. Around 83% of N comes from diffuse sources with agriculture accounting for the vast majority of this (~89%). Similarly P losses are primarily diffuse in nature (~65%) with agriculture a key source (~80%). In contrast, while diffuse sources of BOD are dominant (~77%) the agricultural contribution is low being only ~24%. Agriculture is, however, a primary source of suspended sediment accounting for 90% of the load from diffuse sources that represent 99% of the total load. The summary tool does not present full source apportionment for FIOs, but the diffuse sources comprise 32% of the modelled total FIO loading. See also Table 4.5 for further FIO detail and Table 4.6 for further metals detail. Table Modelled total annual N, P, BOD, SS (tons/year), FIO (10 14 CFU/year) and metals losses (Kg/year) by source Diffuse Sources Point Sources Pollutant Urban Roads Agriculture Forestry Septic Tanks Sewage Discharges N P BOD SS Diffuse Sources Point Sources Pollutant Urban Roads Agriculture and Forestry Septic Tanks Sewage Discharges FIO Metal Atmospheric Deposition Urban Roads Erosion Cd Cu Pb Ni Zn

33 Figure Location of the Area Authority Groups in Scotland 24

34 4.2 Comparison with Pressures and Impacts database The WFD Article 5 classification Pressures and Impacts database was provided by SEPA. This allowed a comparison to be made with the Screening Tool output. Table 4.2 shows the modelled percentage failure of surface water bodies to achieve good status with respect to P, N, BOD, SS, FIOs, Metals, Pesticides and Acidity for rivers using local catchment data for the whole of Scotland and for each advisory area. The data are categorised according to the four categories of water body risk as defined by the Pressures and Impacts (P&I) report (SEPA, 2005), considering all pressures (data supplied by SEPA). These categories are: 1a. Definitely at risk of pollution 1b. Probably at risk of pollution 2a. Possibly at risk of pollution 2b. Definitely not at risk of pollution In doing so we are able to compare the P and I Across Scotland there is predicted high likelihood of failure (<80% probability of good status) for 37% of catchments with respect to P. Note that according to the Screening Tool output, of the four pollutants with quantitative compliance estimates (P, N, BOD and SS) it is the P status that controls overall status across most river catchments (~82%), with BOD controlling status in ~16% and N in the remaining ~2%. This suggests that the focus of attention for achieving improved compliance of surface waters should be Phosphorus. Of the other pollutants considered, high likelihood of non-compliance for pesticides (~36% of water bodies) and metals (~65%) is very frequent. NOTE: In interpreting the maps for N, P, BOD and SS, the categories in the legend show the predicted likelihood of achieving good status. A threshold value of >80% has been interpreted as a high likelihood of compliance with good status, and a threshold of <20% as a high likelihood of failure to achieve good status. In interpreting the maps for pesticides and metals (Figures 4.7 and 4.8) the legends should be interpreted as showing a high risk of failure or a low risk of failure. The results show a generally decreasing percentage of Screening Tool predictions of low likelihood of achieving good status for water bodies from 1a to 1b to 2a to 2b P and I status. However it is difficult to distinguish between the 1b and 2a categories overall, using the Screening Tool data. Further in depth statistical analysis might help, but this is beyond the scope of the current project. Fig 4.2 shows the cumulative frequency distribution of the probability of good status, P (good status), for river water bodies, by P and I status, by scaled cumulative areas within each P and I category. It can be seen that the proportion of catchment areas of water bodies achieving a high probability of good status (P>0.8) increases in the expected order (45% of 1a area, 58% of 1b area, 67% of 2a area and 77% of 2b area). This suggests that the Screening Tool is producing useful information on water body status overall, but the status of individual water bodies may be unreliably simulated. Water bodies with a low P(good status) need to be investigated further, before prioritisation for action takes place. This investigation should include further elaboration of the reason for low status, within the Screening Tool (is it P, N, BOD or SS) and exploration of source apportionment. Table 4.3 shows the River Water Bodies with P(<20%) of good status. Further investigation shows that the reason for the low P(good status) in all these cases is P losses. Most of these are in the P and I 1a category, but some are in the 1b, 2a and 2b categories, and these warrant further investigation. These water bodies are likely to be potential priorities for mitigation of pollution. It should also be noted that these are generally small catchments and as such the uncertainty associated with the Screening Tool modelled values will be high and this should be borne in mind. 25

35 Figure Normalised cumulative areas for river Water Bodies in each P and I category, plotted against the probability of good status, denoted by P(good status), using Total Catchment Area data P (good status) a 1b 2a 2b 0 0% 20% 40% 60% 80% 100% normalised cumulative area in Pressures and Impacts class The equivalent comparison for Loch Water bodies shows higher failure rates for 1a, 1b and 2a than for 2b, but no clear difference between 1a, 1b and 2a. Screening tool failures (probability of good status <0.8) occur on 86% of water bodies for P overall (excluding 127 water bodies which had unknown returns), much the most frequent cause of failure. The percentage of water bodies failing for acidity dropped from 18% to 11% between the 1998 and 2010 conditions. 9% of lochs failed for pesticides and 12% for metals. 26

36

37 Table The modelled percentage failure of number of surface water bodies to achieve good status with respect to P, N, BOD, SS, FIO s, Metals, Pesticides and Acidity for rivers using local catchment data for the whole of Scotland summarised per AAG. The data are categorised according to the four categories of water body risk as defined by the Pressures and Impacts report, considering all pressures (data supplied by SEPA). AAG WFD Diffuse Risk Category No. of Waterbodies P N BOD SS FIO MET PEST ACID(1998) ACID(2010) Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland 1a b a b Total a b a b Total a b a b Total a b a b Total a b a b Total a b a

38 Solway Tay Tweed West Highland All Scotland 2b Total a b a b Total a b a b Total a b a b Total a b a b Total a b a b Total

39 Table River Water bodies showing a <20% likelihood of achieving good status, considering all pressures. WB Id Area Advisory Group WB Name P and I Area (km 2 ) TCA Status North East Scotland Scatter Burn 1a North East Scotland Den Burn 1a North East Scotland Auchinyell Burn 1a North East Scotland Hol Burn 1a North East Scotland Elrick Burn 1a North East Scotland West Tullos Burn 1a North East Scotland Mains of Dyce Burn - d/s airport 1a North East Scotland Farrochie Burn 1a North East Scotland Findon Burn 1a North East Scotland Far Burn - d/s airport 1a North East Scotland Brodiach Burn / Ord Burn 1a Forth Liggat Syke 1a Clyde Tassie Burn 1a Forth Bighty Burn 1a Forth Calais Burn 1a North East Scotland Trib of Youlie Burn - Tarves 1a Clyde Browns Burn 1a Clyde Markethill Burn 1a Clyde Capelrig Burn 1a Forth East Burn/Den Burn 1a Clyde Tollcross Burn 1a Clyde Camlachie Burn 1a Forth Murray Burn 1a Clyde Molendinar Burn 1a Tay Perth Lade 1a Clyde Bagabout Burn 1a Clyde South Burn 1a North Highland Tyock Burn 1a Clyde Malls Mire Burn/Polmadie Burn/Cityford Burn 1a Clyde Red Burn 1a Forth Red Burn 1a Clyde Blacklaw Burn 1a Clyde Lees Burn 1a Forth Ryal Burn/Beugh Burn 1a North East Scotland South Mundurno Burn 1b Clyde Dalzell Burn 1b Forth Braid Burn 1b Clyde Cadzow Burn 1b North East Scotland Blackdog Burn 1b North East Scotland Gelly Burn 1b Forth Pittendreich burn 2a North East Scotland Bucks Burn 2b North East Scotland Kirkton Burn 2b Orkney and Shetland Ham Burn 2b

40 Table The proportion of loch catchments that fail to achieve good status as a result of diffuse sources of P. P and I category P 1a 93% 1b 90% 2a 94% 2b 77% 4.3 River and Loch risk assessment by pollutant The risk assessments provided in the following sections are for all sources of pollution and indicate those catchments at risk of failing to achieve good status. This risk is assessed using all of the contributing waters to each sub-catchment yet the maps indicate only the catchments that fail to achieve good status. Catchment management initiatives would need to target not only this specific catchment where failure occurs but also all of the upstream catchments as well in order to effectively address the problem. Comparisons of status maps with the previous phase should bear this in mind as maps in this previous phase denoted the entire contributing area as at risk as well Nitrate, Phosphorus, Suspended Sediment and Biochemical Oxygen Demand Figure 4.3 shows the spatial distribution of the N status for all sources within the Area Advisory Groups for (a) river and coastal catchments. For rivers, the catchment area that has a high likelihood of failure for N status (> 11.3 mg/l NO 3 -N) has decreased significantly, compared with the previous version of the Tool. This is most likely a result of utilising more recent and raw monitoring data as opposed to the summary statistics used in phase 2. However, there is still significant likelihood of failure for the Almond catchment in Forth AAG, the Eden catchment, the Angus coastal catchments and lower reaches of the North and South Esk in Tayside AAG, the Ythan catchment in North East AAG, and some pockets in Tweed and Teviot catchments in Tweed AAG. Figure 4.4 shows the calculated likelihood for good P status. The revised likelihood of good P status has increased compared to the original simulations. This is likely to be a function of the new regression equation and possibly the inclusion of retention. It can be seen that the likelihood of good status (100 µg/l soluble P for calcareous geology, 40 µg/l for siliceous geology) for P is 80% or less across virtually all of Forth and Clyde AAGs, as well as Eastern Scotland (Angus, North East Scotland AAGs) below the Cairngorms and Highland Boundary fault. Much of Orkney, and northeastern parts of North Highland, as well as southern Kintyre and Arran also fall below an 80% likelihood of compliance. Using the 15 mg/l SS standard, the revised likelihood of good SS status has been reduced, with large areas of Tayside AAGs showing only moderate ( ) likelihood of passing for SS. Using the 5mg/L standard, large areas of all the AAGs show only a moderate likelihood or worse, of passing for SS. Using the 4 mg/l threshold for rivers, the revised likelihood of good BOD status shows a larger area of high likelihood of good status, compared to the original simulations, owing to the new regression equations. For Lochs, there were no failures observed due to diffuse pressures, but several Lochs failed for all sources, including Bardowie Loch, Loch Birnie and Loch Ascog (all small Lochs in Clyde AAG) Metals The metals thresholds used are unchanged from the previous version. No catchment scale presentation of metals compliance was given in this version. The plot (Fig 4.7a and b) shows that much of Eastern Scotland (North Eastern, Tayside, and Forth AAGs) and the Central Belt (Forth and Clyde AAGs) river catchment areas are at risk of failing for metals concentration. Failures for Loch catchments coincide with what was observed for BOD, emphasising the key role of urban and road point sources in controlling metal pollution. 31

41 Figure Spatial distribution of the modelled likelihood of river water body nitrate concentrations from both diffuse and point sources meeting chemical water quality standards. Areas in red are in danger of not meeting good status. 32

42 Figure Spatial distribution of the modelled likelihood of (a) river water body phosphorus concentrations from both diffuse and point sources meeting chemical water quality standards. Loch catchments (b) at risk of failing to achieve good ecological status owing to phosphorus induced eutrophication. Areas in red are in danger of not meeting good status. (a) 33

43 (b) 34

44 Figure Spatial distribution of the modelled likelihood of compliance with good status of river water body Suspended Sediment concentrations from both diffuse and point sources meeting chemical water quality standards of (a) 25mg/l, (b) 15mg/l and (c) 5mg/l. (a) 35

45 (b) 36

46 (c) 37

47 Figure Spatial distribution of the modelled likelihood of compliance with good status of river water body Biochemical Oxygen Demand concentrations from both diffuse and point sources meeting chemical water quality standards. Areas in red are in danger of not meeting good status. 38

48 Figure Spatial distribution of river water bodies in which one or more modelled average metal concentration in surface drainage exceeded the relevant Environment Quality Standard. Areas in red are in danger of not meeting good status. 39

49 4.3.3 Faecal Indicator Organisms Many of the river catchments in SW Scotland (Clyde and Solway AAGs) have potential to cause high loadings of FIOs to water, due to livestock sources. There are also upper reaches of rivers in Forth and Tweed AAGs at risk of high FIO loading Pesticides and Acidity The area of river failures for pesticides is slightly higher than in the previous report (eg in Eastern part of Solway AAG, Western Tweed AAGs), because the non-priority substances have been included. For example, there are over 500 local river catchments failing for carbofuran, and over 300 for metazachlor. A very large proportion of the total catchment area of Scotland is predicted to fail on at least one pesticide EQS. The area of failures for acidity decreases from 1998 to However, significant catchment areas still fail (eg Tummel and upper Tay in Tayside AAG, Orchy and Awe in Argyll AAG, Bladnoch, Black Water of Dee in Solway AAG). These are principally failures from natural, not anthropogenic causes Source apportionment for AAGs and priority catchments. Table 4.4 summarises the source apportionment of pollutants to surface waters by AAG. It can be seen that across Scotland loading of N and P to waters is dominated by sources from Agriculture and STWs. BOD is split between 4 main sources, namely urban runoff, roads, sewage treatment works and agriculture. Losses of SS are dominated by agricultural sources. Across the AAGs these trends vary according to the degree of urbanisation that affects not only the area of urban and road surfaces and the prevalence of septic tanks and STWs but also the amount of agriculture and forestry. Table 4.5 summarises source apportionment of FIOs by AAG. The Clyde, Forth, Tayside and North East AAGs are dominated by sewage treatment works while the Argyll and Solway AAGs are dominated by diffuse sources. Across Scotland, diffuse sources account for ~32% of estimated FIO inputs. Table 4.6 summarises the source apportionment of metals by AAG. In almost all metals the urban and road areas are the primary sources. Variations in these between the AAGs generally reflect the degree of urbanisation and road surface areas. 40

50 Table 4.4: Source apportionment of N, P, BOD and SS to surface waters by AAG (tons/year). Diffuse Sources Point Sources Pollutant AAG Urban Roads Agriculture Forestry Septic Tanks Sewage Discharges N Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland Scotland P Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland Scotland BOD Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland Scotland SS Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland Scotland Table 4.5: Source apportionment of FIO losses to surface waters by AAG (10 14 CFU per year). Diffuse Sources Point Sources 41

51 Pollutant AAG Urban Roads Agriculture and Forestry Septic Tanks Sewage Discharges FIO Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland Scotland Table 4.6: Source apportionment of metals losses to surface waters by AAG (Kg per year). Metal AAG Atmospheric Deposition Urban Roads Erosion Cd Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland Scotland Cu Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland Scotland Pb Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland Scotland Ni Argyll Clyde Forth

52 North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland Scotland Zn Argyll Clyde Forth North East Scotland North Highland Orkney and Shetland Solway Tay Tweed West Highland Scotland Figures 4.12 to 4.15 show the source apportionment of P, N, BOD and SS for the priority catchments identified in the tender document, Piltanton Burn (Solway AAG), Niddry Burn (Forth AAG),Youlie Burn (North East Scotland AAG), Dighty Water and Lunan Water (both Tayside AAG). Figure 4.16 shows the proportions of these catchments given to arable crops, managed grass, and rough grass. The phosphorus loading shows that sewage treatment works are the major contributor in the Niddry Burn and the Dighty Water, while in the Lunan Water and the Youlie Burn, agricultural runoff and drainage dominate. Losses of P to the Piltanton Burn are relatively small, because much of the vulnerable intensively managed grassland and cropland in this catchment is on relatively flat land. Urban runoff makes a significant contribution to the Dighty Water. The Nitrogen loading shows that agricultural leaching of N to groundwater is a major contributor to all catchments, and this route is dominant for the Piltanton Burn, the Youlie Burn and the Lunan Water. Runoff and shallow drainage dominate the contribution to the Niddry Burn and sewage works are codominant in the Dighty Water. Despite the high proportion of managed grass in the Piltanton catchment, the total loading of N in the catchment is lower than the others, The stocking density of cows (0.5 beef units and 1.0 dairy units per ha of managed grass) is comparable, but there are much smaller concentrations of poultry and/or pigs than in the Niddry, Youle and Dighty Waters. This suggests that contributions from bovine livestock to N leaching may be underestimated by the Screening Tool. A cross check for another bovine livestock dominated catchment (Cessnock Water) showed that this had similar nitrate leaching losses per animal to the Piltanton Burn catchment. The BOD loads show that urban and road runoffs are major contributors to the total pollution in all the catchments. In addition, sewage inputs are dominant in the Niddry Burn and the Dighty Water. The agricultural contributions are larger where there is a larger proportion if grass in the catchment. The predicted suspended solids load are quite low in all catchments, reflected in the high pass rate for surface water bodies across Scotland for this pollutant. Urban runoff is a significant contributor to total SS load in the Dighty Water, but not in the other catchments. Four of the catchments show a low probability of achieving good status for these pollutants, Of these four, all show failure for P, Niddry and Youlie Burns show failure for N, and none show failure for BOD or SS. All these priority catchments show failure for FIOs (except Lunan Water), Metals and Pesticides, and passes for Acidity. 43

53 Figure Spatial distribution of river and coastal water bodies with high (> FC/km 2 ) and medium/low (< FC/km 2 ) risk of faecal coliform pollution arising from all sources. Areas in red are in danger of not meeting good status. 44

54 Figure Spatial distribution of river water bodies in which one or more modelled average pesticide concentration in surface drainage exceeded the relevant Environment Quality Standard. Areas in red are in danger of not meeting good status. 45

55 Figure Spatial distribution of river water bodies where one or more 1km 2 grid cell within these catchments is vulnerable to acidification according to the 1990 dataset. Areas in red are in danger of not meeting good status. 46

56 Figure Spatial distribution of river water bodies where one or more 1km 2 grid cell within these catchments is vulnerable to acidification according to the 2010 dataset. Areas in red are in danger of not meeting good status. 47

57 Figure Source apportionment of phosphorus loading to water for 5 catchments Phosphorus kg pollutant/ha Forest Seepage To Groundwater Forest Runoff/Drains Agricultural Seepage to Groundwater Agricultural Runoff/Drains Road Runoff Sewage Treatment Works Septic Tanks Urban Runoff Piltanton Burn Niddry Burn Youlie Burn Dighty Water (lower) Lunan Water Figure Source apportionment of nitrogen loading to water for 5 catchments Nitrogen kg pollutant/ha Forest Seepage To Groundwater Forest Runoff/Drains Agricultural Seepage to Groundwater Agricultural Runoff/Drains Road Runoff Sewage Treatment Works Septic Tanks Urban Runoff 10 0 Piltanton Burn Niddry Burn Youlie Burn Dighty Water (lower) Lunan Water 48

58 Figure Source apportionment of BOD loading to water for 5 catchments BOD kg pollutant/ha Forest Seepage To Groundwater Forest Runoff/Drains Agricultural Seepage to Groundwater Agricultural Runoff/Drains Road Runoff Sewage Treatment Works Septic Tanks Urban Runoff Piltanton Burn Niddry Burn Youlie Burn Dighty Water (lower) Lunan Water Figure Source apportionment of SS loading to water for 5 catchments Suspended solids kg pollutant/ha Forest Drains Forest Runoff Agricultural Drains Agricultural Runoff Road Runoff Sewage Treatment Works Septic Tanks Urban Runoff 50 0 Piltanton Burn Niddry Burn Youlie Burn Dighty Water (lower) Lunan Water 49

59 Figure Agricultural land use in the 5 priority catchments Agricultural Land use rough grass managed grass crops proportion of catchment (%) Piltanton Burn Niddry Burn Youlie Burn Dighty Water (lower) Lunan Water 50

60 5 NORTHERN IRELAND - INTERPRETATION OF THE SUMMARY DATABASE TOOL RESULTS The Water Framework Directive (WFD) is transposed in Northern Ireland via the Water Environment (Water Framework Directive) Regulations (Northern Ireland) 2003 ( The purpose of the Directive is to protect all waters, including rivers, lakes, transitional, coastal and groundwater. Under the current classification system there are 550 River, 24 Lake, 7 Transitional, 20 Coastal and 61 groundwater bodies wholly or partly within Northern Ireland (EHS, 2005). This report will focus on the river and lake water bodies and attempt to further the characterisation of these water bodies. Figure 5.1 Contextual map illustrating the extent of the River Basin Districts and associated surface waters Northern Ireland is divided into 3 International River Basin Districts (IRBD) and one River Basin District (RBD). However the Shannon covers a very small fraction of the country and this report will focus on the North Eastern RBD, the Neagh Bann IRBD and the North Western IRBD (See Figure 5.1). The North Eastern RBD (NERBD) covers an area of 3074 km 2. It is bounded to the North and East by the North Channel. The Antrim and Mourne mountains in the Northern and Southern portions, respectively, of this RBD not only impact on the topography but also contribute to the watershed delineation. Major rivers include the River Lagan and the River Bush with the Lagan flowing northeastwards to enter Belfast Lough. The Belfast and Strangford Loughs are two large sea inlets within the NERBD. The northern part of the NERBD is sparsely populated and dominated by rural agriculture and some fish farming. The central portion of the RBD is dominated by the capital city Belfast and surrounding urban areas, is more densely populated and contains the bulk of the industry. The southern part of the RBD is characterised by highly productive farmland within the Lagan valley. The Neagh Bann RBD is an international (NBIRBD) with 5740 km 2 of the 7900 km 2 of its area occurring in Northern Ireland. The NBIRB is bounded by the North Channel, the Republic of Ireland in the south, the Sperrin Mountains in the west and the Antrim Mountains in the east. The hydrology of the IRBD is dominated by Lough Neagh, which is located in its centre and is 396km 2 in size, as well as the River 51

61 Bann. Landuse around the Lough is typified by improved pasture while productive farmland stretches to the north and south. Urban areas centre on Coleraine and Ballymena in the north and Craigavon, Armagh and Newry in the south. The North Western International River Basin District (NWIRBD) covers an area of 4785 km 2 in Northern Ireland, representing approximately 39% of its total area. The NWIRBD is bounded by the North Sea, the Sperrin Mountains in the east and to the west and south by the Republic of Ireland. The hydrology of the IRBD is dominated by the fresh water lakes of Upper and Lower Lough Erne as well as the river Foyle and its tributaries. The population density is generally low with the main urban centres being Londonderry, Omagh and Enniskillen. The northern part of the district is characterised by arable agriculture while the south supports coniferous plantations and stock farming. Using the Summary Database Tool for Northern Ireland a comprehensive set of results were extracted from version 2 of the Environment Database. These results were summarised for each River Basin District (See Figure 5.1) and coupled to the updated catchment boundaries supplied in order to display these spatially. The interpretation of these results is outlined in the following chapter. 5.1 River and Lough risk assessment by pollutant This section will focus on the following pollutant groupings, Nitrate; Phosphorus, Suspended Sediment, Biochemical Oxygen Demand and Metals; Faecal Indicator Organisms; Pesticides and Acidity Nitrate, Phosphorus, Suspended Sediment and Biochemical Oxygen Demand Nitrate The modelled loads of Nitrate for each RBD are summarised in Table 5.1 where it will be noted that agricultural sources account for the vast majority of this load. Small but significant contributions are also made by STW point sources, septic tanks and urban runoff. The distribution of the likelihood of achieving good status, as illustrated in Figure 5.2, indicates that the vast majority of river waterbodies in all of the RBDs do not appear to be affected by Nitrate pollution with only a few catchments exhibiting a medium likelihood of achieving good status. This observation is supported when comparing the proportion of catchments that fail to comply with Environmental Quality Standards (EQS) as summarised within Table 5.2, where only 0.73% of Northern Ireland river waterbodies are at risk of failing due to nitrate. Visual comparison of these mapped results with those from Phase II of the project indicates that catchments that exhibited problems at stage II are still possibly problematic. However the improvements made to the modelling methodology, notably the inclusion of retention, may have improved the likelihood of achieving good status within these problem catchments. Phosphorus The modelled loads of Phosphorus for each RBD are summarised in Table 5.1 where it will be noted that agricultural sources account for the largest proportion of this load along with STWs and septic tanks. The STW values are elevated in those RBDs with larger urban areas, namely the NERBD and the NBIRBD. The distribution of the likelihood of achieving good status, as illustrated in Figure 5.3 (a), indicates that many catchments, primarily in the southern portions, of the NERBD and the NBIRBD have a low or moderate likelihood of compliance. In contrast, much of the NWIRBD has a moderate to high likelihood of compliance with small problem areas associated with STWs and arable agriculture. Comparison of the proportion of river catchments that fail to comply with EQS as summarised within Table 5.2 indicates that Phosphorus is a primary environmental pressure in many of the 1a and 1b catchments. Visual comparison of Figure 5.3(a) with the results from Phase II of the project indicates that there have been improvements in the likelihood of achieving good status in many places, mainly in headwater areas, for example the Roe Catchment in the NWIRBD. These can largely be attributed to the more recent datasets used in the regression model. Likewise, there are areas that have a lower likelihood of achieving good status. These areas are predominantly in the lowlands, for example the areas south of Armagh in the NBIRBD, the River Lagan valley in the NERBD and the River Foyle valley in the NWIRBD. These changes in likelihood are driven in part by the inclusion of STW data, for example along the Bann River 52

62 north of Lough Neagh, as well as the improvements made to the regression equations through the use of more recent monitoring data. As illustrated in Figure 5.3 (b), there is a more distinct distribution of Phosphorus status within loughs with the vast majority of catchments failing to meet the requisite EQS. The results tabulated in Table 5.3 support this visual assessment with more than 85% of lough waterbody catchments in each RBD failing to achieve good status. Visual comparison with the results from the river waterbody analysis (Figure 5.3 a) indicates that these are largely in agreement. One possible area of disagreement is evident in the southern part of the NWIRBD and is likely a function of the lough status being a comparison between modelled TP and an EQS based on SRP. Suspended Sediment The modelled loads of Suspended Sediment (SS) for each RBD are summarised in Table 5.1 where it will be noted that agricultural, road and urban sources account for the largest proportion of this load. The regression equation produced for SS for Northern Ireland was poor (See Table 2.3) despite the more recent monitoring data and regression technique. As such the results have not been mapped. Figure 5.4 illustrates the compliance of river catchments utilising observed data. It will be noted that large parts of the country appear to comply even with the lower threshold of 15 mg/l being considered. Biochemical Oxygen Demand The modelled loads of Biochemical Oxygen Demand (BOD) for each RBD are summarised in Table 5.1 where it will be noted that agricultural, road, STWs and urban runoff sources account for the largest proportion of this load. The regression equation produced for BOD for Northern Ireland was mediocre (See Table 2.3) despite the use of more recent monitoring data and the improved regression technique. As such the results were not mapped. Figure 5.5 illustrates the compliance of river catchments utilising observed data. 53

63 Table 5.1 Modelled total annual nitrate, phosphorus, BOD and suspended sediment losses (tons per year) to surface and groundwater (N, P, BOD) by source for each River Basin District Diffuse Sources Point Sources Pollutant River Basin District Urban Roads Agriculture Forestry Septic Tanks Sewage Discharges N Neagh Bann North Eastern North Western Northern Ireland P Neagh Bann North Eastern North Western Northern Ireland BOD Neagh Bann North Eastern North Western Northern Ireland SS Neagh Bann North Eastern North Western Northern Ireland

64 Table 5.2 The proportion (%) of river catchments that fail to achieve good status as a result of diffuse sources of N, P, BOD and SS summarised according to the diffuse pollution WFD risk categorisation. River Basin WFD Diffuse Risk Category Number of Waterbodies P N 1a Neagh Bann 1b a North Eastern North Western Northern Ireland Total a b a Total a b a Total a b a Total Table 5.3 The proportion (%) of lough catchments that fail to achieve good status as a result of diffuse sources of P. River Basin District P Neagh Bann North Eastern North Western Northern Ireland

65 Figure 5.2 Spatial distribution of the modelled likelihood of river water body nitrate concentrations from both diffuse and point sources meeting chemical water quality standards. Areas in red are at risk of failing to achieve good status. 56

66 Figure 5.3 Spatial distribution of the modelled likelihood of (a) river water body phosphorus concentrations from both diffuse and point sources meeting chemical water quality standards. Areas in red are at risk of failing to achieve good status. Lough catchments (b) at risk of failing to achieve good ecological status owing to phosphorus induced eutrophication. (a) (b) 57

67 Figure 5.4 The spatial distribution of monitored chemical water status for river water bodies. Areas in red are at risk of failing to achieve good status. Figure 5.5 The spatial distribution of monitored chemical water status for river water. Areas in red are at risk of failing to achieve good status. 58

68 Figure 5.6 Spatial distribution of river water bodies in which one or more modelled average metal concentration in surface drainage exceeded the relevant Environment Quality Standard. Areas in red are at risk of failing to achieve good status. 59