Wetland Hydrogeomorphic Classification for Scotland

Transcription

1 Final Report Project WFD66 Wetland Hydrogeomorphic Classification for Scotland November 2007

2 SNIFFER 2007 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: WWT Consulting Ltd (formerly Wetlands Advisory Service Ltd) Wildfowl & Wetlands Trust Slimbridge Glos. GL2 7BT UK SNIFFER s project manager SNIFFER s project manager for this contract is: Greg Fullarton, Scottish Environmental Protection Agency (SEPA) SNIFFER s project steering group members are: Gina Martin, SNIFFER Research Manager Vincent Fitzsimons, SEPA Willie Duncan, SEPA Ilka Bauer, SEPA Lorna Harris, SEPA Dominic Habron, SEPA Andrew McBride, SNH Andrea Johnstonova, RSPB SNIFFER First Floor, Greenside House 25 Greenside Place EDINBURGH EH1 3AA

3 FOREWORD Use of this report The development of UK-wide classification methods and environmental standards that aim to meet the requirements of the Water Framework Directive (WFD) is being sponsored by UK Technical Advisory Group (UKTAG) for WFD on behalf its member and partners. This technical document has been developed through a collaborative project, managed and facilitated by SNIFFER and has involved the Scottish Environment Protection Agency (SEPA), Scottish Natural Heritage (SNH) and the Royal Society for the Protection of Birds (RSPB). It provides background information to support the ongoing development of the standards and classification methods. Whilst this document is considered to represent the best available scientific information and expert opinion available at the stage of completion of the report, it does not necessarily represent the final or policy positions of UKTAG or any of its partner agencies. This report forms one of two outputs from Project WFD66. The other output is a geographical information system (GIS). Due to IP restrictions associated with background information used to develop the GIS, the GIS output has not been made publicly available. ACKNOWLEDGEMENTS This report was produced by Rob McInnes, Matthew Simpson, Michael Wallis, Anne Harrison and Denis Deasy. The authors would like to thank the following for useful discussions and contributions in developing the concepts in this report: Harvey Rodda, Hydro-GIS Ltd, UK Mark Brinson, East Carolina University, USA George Lukacs, James Cook University, Australia

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5 EXECUTIVE SUMMARY WFD66: Wetland Hydrogeomorphic Classification for Scotland (November, 2007) Project funders/partners: SNIFFER Background to research The EU Water Framework Directive (WFD), through its translation into Scots Law by the Water Environment and Water Services (Scotland) Act 2003 (WEWS) introduces a series of new wetland related duties for SEPA, and it has been recognised that an inventory of water body dependent wetlands will be an important first step in meeting these requirements. Objectives of research The overall objective of the project was to produce an inventory of water body dependent wetlands, based on readily available information, and to detail priorities for future research. Three specific objectives were identified from the outset of the project: To deliver an inventory of Scottish wetlands that are directly dependent on surface water bodies and groundwater bodies; To describe the pressures affecting wetlands listed on the inventory; and To develop a prioritised plan for future wetland characterisation work covering aspects of the wetland resource not included in the wetland inventory to be delivered through this project. Subsequent steps will enhance the level of detail contained within the inventory. The aim of this project was to deliver the initial phases of the inventory, and to develop a prioritised workplan to support its completion. However, due to limitations in national datasets, it has not been possible to deliver an inventory of Scottish wetlands. The project has produced a hydrogeomorphic classification of potential wetland areas within the Scottish landscape. Using this approach it is possible to construct an inventory of potential wetland sites and to assess their likely surface and groundwater dependence. Key findings and recommendations A GIS-based wetland hydrogeomorphic classification has been created for Scottish wetlands. The classification provides information on both designated and non-designated sites. Through a GIS it is possible to define the likelihood of dependency of any wetland area on surface and groundwater bodies by assessing likely water sources. Through an interpretation of the surface and groundwater sources it is possible to identify potential pressures on wetlands. The information generated within the GIS has been validated against digitized National Vegetation Classification (NVC) communities available for 176 SSSIs. The validation process recognizes that NVC communities are not perfect surrogates for defining wetlands and their water dependence. Correlations (both Spearman s and Chi-square) yield highly significant results. However, there are subtle relationships within the output data which need to be understood prior to drawing immediate conclusions. A high degree (>80%) of agreement has been achieved for predicting high groundwater dependency. A much lower degree (~50%) of agreement has been achieved for predicting low groundwater dependency. Hydrogeomorphic units derived to describe extensive peatland areas yield the best results for predicting the potential location of wetlands in the Scottish landscape. A variety of different hydrogeomorphic v

6 units demonstrate a strong association with wetland NVC communities. Mapping of these hydrogeomorphic units within the GIS generates an initial inventory of areas of high potential to support wetlands and provides information on the ground and surface dependent water bodies. A user s guide is provided to assist users in investigating the GIS and deriving information on water body dependency and potential pressures. The hydrogeomorphic classification is not a finished product and should be continually updated and reviewed to improve the ability to generate an accurate inventory of Scottish wetlands. A prioritized workplan is presented to inform future research needs. Key words: wetlands, inventory, surface water dependency, groundwater dependency, pressures, Water Framework Directive, GIS, hydrogeomorphic classification. vi

7 TABLE OF CONTENTS EXECUTIVE SUMMARY 1 INTRODUCTION Objectives Modification to objectives 1 2 LEGISLATIVE DRIVERS EU Water Framework Directive Water Environment and Water Services (Scotland) Act Water bodies Surface water body dependency Groundwater body dependency Pressures on Scottish wetlands 4 3 WETLAND INVENTORY AND CLASSIFICATION Review of wetland inventories Review of wetland classifications The Hydrogeomorphic (HGM) Approach 11 4 DEVELOPMENT OF THE WETLAND HYDROGEOMORPHIC CLASSIFICATION FOR SCOTLAND Hydrogeomorphic application for the Scottish wetland classification Geomorphic setting Water sources Output medium Limitations to the approach Data Defining hydrogeomorphology Information held within the wetland hydrogeomorphic classification for Scotland Water body dependency Likelihood of dependency Unified water body dependency classes (Class) Potential and actual pressures Hydrogeomorphic units Validation National Vegetation Classification data Testing association between predicted groundwater dependence class and the presence of groundwater dependent NVC communities Testing association between predicted hydrogeomorphic unit and wetland NVC communities Summary of validation Application of the wetland hydrogeomorphic classification GIS for Scotland Water dependent features Wetland classification and inventory 38 5 PRIORITISED WORKPLAN Introduction Task identification Prioritisation of tasks Example of further work 41 6 REFERENCES 45 vii

8 List of Tables Table 1 Examples of wetland classifications. 12 Table 2 Summary of water sources and sub classes. 20 Table 3 Unified water body dependency classes. 22 Table 4 Classes for potential pressures. 23 Table 5 Cross-tabulation between predicted groundwater dependency and NVC-based groundwater dependency scores. (Note: Values shown are numbers of validation points in each of the different categories). 27 Table 6 Occurrence of false negatives by NVC community (only NVCs that occur at least once in the validation dataset are shown). 28 Table 7 Occurrence of false positives by NVC community (only NVCs that occur at least once in the validation dataset are shown). 29 Table 8 Occurrence of false negatives by HGM unit. 31 Table 9 Occurrence of false negatives by HGM unit. 32 Table 10 Relationship between hydrogeomorphic unit and wetland or non-wetland NVC communities. 33 Table 11 SNH criteria for water dependency. 37 Table 12 Prioritised workplan. 40 List of Figures Figure 1 Example of water body dependency classes (Class). 22 Figure 2 Example of potential risk from point source pollution (PP_Point). 24 Figure 3 Example of hydrogeomorphic units. 25 Figure 4 Example Grid Stream output. 42 Figure 5 Example TOPMODEL output. 43 APPENDICES Appendix I Hydrogeomorphic classification of Scottish Wetlands Users Manual 49 Appendix II Hydrogeomorphic classification of Scottish Wetlands Metadata and 73 Assumptions Appendix III WFD UK TAG NVC groundwater dependency scores 89 Appendix IV Wetland NVC Communities 93 viii

9 1 INTRODUCTION The consultancy arm of the Wildfowl & Wetlands Trust, WWT Consulting (formerly the Wetlands Advisory Service), were appointed by the Scottish & Northern Ireland Forum for Environmental Research (SNIFFER) to develop an inventory of Scottish wetlands. An inventory would provide statutory agencies in Scotland with a tool which can assist in delivering governmental obligations as defined under the EU Water Framework Directive (WFD), which have been translated in Scots Law through the Water Environment and Water Services (Scotland) Act 2003 (WEWS). 1.1 Objectives The overall objective of the project was to produce an inventory of water body dependent wetlands, based on readily available information, and to detail priorities for future research. Three specific objectives were identified from the outset of the project: To deliver an inventory of Scottish wetlands that are directly dependent on surface water bodies and groundwater bodies; To describe the pressures affecting wetlands listed on the inventory; and To develop a prioritised plan for future wetland characterisation work covering aspects of the wetland resource not included in the wetland inventory to be delivered through this project. 1.2 Modification to objectives The aim of this project was to deliver the initial phases of the inventory, and to develop a prioritised workplan to support its completion. However, due to limitations in national datasets it has not been possible to deliver an inventory of Scottish wetlands. The project has produced a hydrogeomorphic classification of potential wetland areas within the Scottish landscape. Using this approach it is possible to construct an inventory of potential wetland sites and to assess their surface and groundwater dependence. Information on wetlands in Scotland is held in several locations. However, there is no consistent approach to defining or recording a wetland. For instance, on the Scottish Environmental Protection Agency (SEPA) Small Lochs database, information is held on a defined waterbody, but no information is held on the variability of the boundary and the position of ephemeral or seasonal wetlands which may be marginal to a loch depending on the prevailing climatic or water level regimes. Similarly, the Scottish Natural Heritage (SNH) database of Sites of Special Scientific Interest (SSSI) identifies wetland SSSIs, however, there is no indication of the special extent or geographic coverage of wetland within a defined SSSI boundary. In some cases the wetland may cover the entire SSSI and extend for some considerable extent beyond. In other cases wetland habitats may only account for a small area within a larger SSSI boundary. Other wetland areas, such as seeps and flushes on hillslopes are excluded from all nationally available datasets unless they are designated within a SSSI. The generation of an inventory of Scottish wetlands based on nationally available datasets would have identified certain known wetland areas, such as lochs and rivers, but would have been of questionable accuracy for other land classifications, such as SSSIs, and would have omitted many other wetland areas. especially ephemeral habitats such as seeps, flushes and seasonally inundated wetlands. 1

10 No single dataset exists to define the location of Scottish wetlands. The only national dataset which has wetland habitats defined within it is the Land Cover Map 2000 (LCM2000) (Fuller et al, 2002). As an aid to the implementation of, and reporting under, the UK Biodiversity Action Plan (BAP), the UK Biodiversity Group identified a framework of Broad Habitats to encompass the entire range of UK habitats. The descriptions of Broad Habitats was developed by the Joint Nature Conservation Committee (JNCC). LCM2000 aimed to contribute to the assessment of habitats by mapping, as far as possible, the widespread examples of terrestrial, freshwater and coastal Broad Habitats. While their mapping was always treated as a key objective, LCM2000 also aimed to record further details where possible, giving cover classes sought by other users. LCM2000 is a thematic classification of spectral data recorded by satellite images; external datasets add context to help refine the spectral classification. The spectral classes defined in the process can be combined into thematic components which can in turn be aggregated to build various classification schemes. LCM2000 aimed, where possible, to distinguish Broad Habitats; in practice, Target classes were considered the nearest match which could be achieved consistently and with a high level of accuracy. Subclasses were then defined to give, as far as possible, the full complement of Broad Habitats; they also defined details beyond the Broad Habitat classification. However, there are fundamental differences in the exact definitions of Broad Habitat-equivalent Target classes and Subclasses; differences in nomenclature reflect these. Subclasses were mapped consistently throughout the UK but sometimes with compromises on accuracy. Some Broad Habitats were subdivided at Subclass level where this was considered valuable for wider use of data. The class Variants are the thematic components of Target classes and Subclasses; they were recognised wherever possible (e.g. individual crops were distinguished where possible but could not be recognised once harvested). Fuller et al (2002) acknowledge that there are mismatches in the data and that some habitats are difficult to distinguish from others. For instance, rough (unmanaged) grasslands include elements of improved and semi-natural swards which are spectrally indistinguishable. Wetland habitats have been set as LCM Target classes including sea, estuary, water (inland), littoral rock and sediment, bogs (deep peat), fen, marsh and swamp. These also possess Subclasses and Variants. However, lowland grazing marsh is included in improved grassland. Therefore whilst the LCM2000 provides useful information on some of the Broad Habitats, it can not be used to define wetlands within the Scottish landscape. Consequently, the objectives were modified and existing national datasets were utilised to define the potential location of wetland habitats based on an assessment of hydrogeomorphic criteria. Using a hydrogeomorphic approach facilitates the definition of water sources and hence water dependency for the potential wetland sites. 2

11 2 LEGISLATIVE DRIVERS 2.1 EU Water Framework Directive On 23 October 2000, the "Directive 2000/60/EC of the European Parliament and of the Council establishing a framework for the Community action in the field of water policy" or for short the EU Water Framework Directive (WFD) was adopted. The WFD is a wide-ranging and ambitious piece of environmental legislation which applies to all water in the natural environment that is all rivers, lochs, estuaries and coastal waters as well as water under the ground. The basic objectives to be achieved as set out in Article 4(1) of the WFD are summarised below (Scottish Executive, 2006): prevent deterioration in the status of surface water bodies; protect, enhance and restore all bodies of surface water with the aim of achieving good surface water status by 2015; prevent deterioration of the status of groundwater bodies; protect, enhance and restore all bodies of groundwater with the aim of achieving good groundwater status by 2015; prevent or limit the input of pollutants to groundwater and reverse any significant and sustained upward trend in the concentration of pollutants in groundwater; comply with Europe-wide measures for dangerous substances; and achieve compliance with any relevant standards and objectives for protected areas. In Scotland, this work is being taken forward by the Scottish Environmental Protection Agency (SEPA), in conjunction with the Scottish Executive, in line with the timetable for action set in the Directive. SEPA is organising its work on the Directive under a number of key work areas: regulatory regimes; river basin characterisation; monitoring and classification; and river basin management planning. 2.2 Water Environment and Water Services (Scotland) Act 2003 In Scotland the WFD has been translated into the Water Environment and Water Services (Scotland) Act 2003 (WEWS). The aim of the WEWS Act is to protect and improve the water environment while also supporting the social and economic interests of those who depend on it. The WEWS Act identifies the SEPA as the competent authority for the Scotland River Basin District and gives certain duties to Scottish Ministers (Scottish Executive, 2006). The WEWS Act extends beyond the requirements of the WFD and introduces provisions which should result in better environmental improvements for Scotland. Specifically: WFD objectives will apply to coastal waters out to three nautical miles; The WEWS Act introduces specific requirements to identify pressures and impacts in wetlands directly dependent on a body of either surface or ground water. The WFD's monitoring requirements have also been extended to cover wetlands. In the WEWS Act (Part 1, Chapter 1, Section 3(5)) wetlands have been defined as an area of ground the ecological, chemical and hydrological characteristics of which are attributable to frequent inundation or saturation by water and which is directly dependent, 3

12 with regard to its water needs, on a body of groundwater or a body of surface water. This definition has been adopted throughout this report. 2.3 Water bodies The WFD covers all waters, including inland waters (surface water and groundwater) and transitional and coastal waters up to three nautical miles (and for the chemical status also territorial waters which may extend up to 12 nautical miles) from the territorial baseline of a Member State, independent of the size and the characteristics. This totality of waters is, for the purpose of the implementation of the Directive, attributed to geographical or administrative units, in particular the river basin, the river basin district, and the water body. In addition, groundwaters and stretches of coastal waters must be associated with a river basin (district). Through the wetland definition contained within the WEWS Act, it is established that wetlands are dependent on two different types of water bodies : groundwater bodies and surface water bodies Surface water body dependency Surface water body dependency in wetlands is related to their hydrological connectivity with a surface water body such as a loch or a river. This connectivity can take several forms depending on the surface water linkage. For a wetland to be dependent on a surface water body it is necessary to identify the linking mechanism. For instance a floodplain wetland may be linked with a stream channel water body through overbank flood events. Similarly, a wetland adjacent to a loch may be linked through a rise in water level in the loch water body. In addition, the surface water body may be a wetland in its own right Groundwater body dependency The dependence of wetlands on groundwater bodies is also a result of hydrological connectivity. The degree of dependency will vary depending upon whether the wetland is underlain by a low productivity or high productivity aquifer and whether there is a hydrological linkage mechanism between groundwater and the surface wetland. The dependency on a groundwater body does need to manifest itself through a surface expression of groundwater, such as a spring or a flush. Often the presence of elevated groundwater levels is a controlling mechanism on surface water processes. For instance, surface water run off can be a result of elevated levels of groundwater limiting infiltration. 2.4 Pressures on Scottish wetlands Wetlands the world over are subjected to pressures (MEA, 2005). Pressures may be local and minor but may also result in total wetland loss (Maltby and McInnes, 1997). Pressures on Scottish wetlands vary in their severity and extent (Gilvear and McInnes, 1994). A variety of impacts have altered and degraded wetlands. Afforestation and drainage for agricultural land claim has accounted for the loss of over 420 of the original 851 sites of primary raised bog (Lindsay, 1995). A study conducted in the 1990s indicated that the potentially large groundwater recharge catchments of coastal wetlands, together with increasing pressures in the coastal zone, dictate that diffuse pollution can threaten the integrity of hydrochemical processes in the aquifer and, if not carefully monitored and regulated, can threaten important freshwater wetlands in the coastal zone (Malcolm and Soulsby, 2001). 4

13 Seven primary pressure types have been identified for Scottish wetlands (SEPA, 2004): Point source pollution; Diffuse source pollution; Abstraction; Flow regulation; Artificial drainage; Morphological alteration; and Alien species. These pressures may impact on a wetland directly, or indirectly, by introducing a pressure on a water body upon which the wetland is dependent. It is possible to link a pressure to a wetland site through an understanding of the functional linkage between pressure and water source. It is also possible to qualify this linkage, or potential impact, by defining the likelihood of dependency of a wetland site on a water source. For instance, a wetland which has a high likelihood of being dependent on groundwater, theoretically, would be sensitive to groundwater abstraction. 5

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15 3 WETLAND INVENTORY AND CLASSIFICATION The classification and inventory of wetlands is fraught with difficulty (Scott and Jones, 1995). It has been important to distinguish between inventory, classification, assessment and monitoring when attempting to design a Scottish wetland inventory, especially since they require different categories of information. The distinctions are often confused. Working definitions reported by Finlayson et al (2001), and adopted herein, are: Wetland Inventory: the collection and/or collation of core information for wetland management, including the provision of an information base for specific assessment and monitoring activities. Wetland Classification: the systematic grouping of wetlands into categories on the basis of evolutionary or structural relationships which exist between and among them. (Note: this represents a generic definition and not one formally adopted by SEPA or advocated in the WFD or in the WEWS Act, where the term classification is used to refer to ecological status). Wetland Assessment: the identification of the status of, and threats to, wetlands as a basis for the collection of more specific information through monitoring activities. Wetland Monitoring: the collection of specific information for management purposes in response to hypotheses derived from assessment activities, and the use of these monitoring results for implementing management. (The collection of time-series information that is not hypothesis-driven from wetland assessment is here termed surveillance rather than monitoring.) The work produced within this report collates information on the basis of structural relationships which exist in order to produce a hydrogeomorphic classification of the Scottish landscape. This can help inform the identification of potential wetland areas and their water dependency, as well as potential threats, and other assessment and monitoring needs. 3.1 Review of wetland inventories Wetland inventory, assessment and monitoring have been increasingly addressed in international and national fora in recent years. Much of the international effort has been directed towards supporting the concept of wise use of wetlands advocated under the Ramsar Wetlands Convention (Scott and Jones, 1995, Finlayson & Davidson, 2001). Wetland inventories exist at a great variety of scales; from global through regional and national scales to wetland site-based work. Some recent broad-scale initiatives include: A global review of wetland resources that compiled and analysed information from national wetland inventory resources and evaluated the size and distribution of the global wetland resource (undertaken by Wetlands International for the Ramsar Convention) (Finlayson and Spiers 1999, Finlayson et al,1999); A pilot project designed to recommend and develop standard wetland inventory and assessment tools to meet the needs of sustainable wetlands management worldwide (undertaken by Wetlands International through the Biodiversity Conservation Information System (BCIS) network (Davidson 1999)); The first phase of a project working towards a Pan-European wetlands inventory (Wetlands International and the RIZA institute, Netherlands (Nivet and Frazier 2001)); 7

16 Continuing development and testing of wetland inventory and assessment tools through the MedWet initiative (Costa et al, 2001); Development of a draft framework for wetland inventory by the Scientific and Technical Review Panel of the Ramsar Wetlands Convention based on a resolution adopted by the Convention in 1999 (reproduced in Finlayson and Davidson 2001); and Development of the Asian Wetland Inventory using approaches derived from the recommendations presented at the workshops held in Dakar and supporting the concepts outlined in the Ramsar framework (Finlayson et al, 2002). The global review of wetland resources identified large gaps in the global wetland inventory effort, with many discrepancies in data management, inadequate documentation, inconsistencies in methods and poor communication of information. Often at national level a wetland inventory has to satisfy local needs and legislation. In Europe much of the work on wetland inventories has been highly variable and lacks uniformity (Hughes, 1995, Nivet and Frazier, 2001). However, in some countries wetland inventories have been developed and used to protect wetlands and address wetland degradation. In Sweden wetland inventory projects (VMI) were carried out in the 1980s with a view to increasing the overall knowledge-base about Swedish wetlands, combined with a nature conservation evaluation of the wetland resource aiming to prevent, where possible, further exploitation. Wetlands were categorised through the inventory work; the top 10% or so were classed as Class 1: "very high conservation value", representing the best examples of each wetland type in the biogeographical region, these regions being based largely on the Nordic Council's biogeographical map. Class 2 represented "high conservation value" and Class 3 "conservation value". Sites which had been highly degraded were assigned to Class 4: "no existing conservation value". The Swedish wetland inventory information has been stored in a database which provides details for more than 30,000 sites across Sweden. The inventory is being used in the daily conservation work at regional level by the Swedish Environmental Protection Agency. The majority of wetlands defined as Class 1 and Class 2 are now protected from pressures, especially drainage. In 2001 the project "Inventory of Bulgarian wetlands" was approved for the Small Grant Fund (SGF) of the Ramsar Convention (and taken over for direct funding by DGIS/Wetlands International, with assistance in financing the publication of the results from Pensoft Publishers). The purpose of the project was to develop the first inventory of Bulgarian wetlands, principally by collecting data about biotic and abiotic characteristics, functions, threats and positive actions related to the use of the wetlands; designing and developing a wetlands database (using a standardised format similar to the Ramsar Information Sheet and MedWet database (Costa et al, 2001)); publishing the results of the completed inventory; identifying the most problematic wetlands, including the shared catchments of the important rivers of the Balkan Peninsula and Europe; and identifying those wetlands that meet Ramsar criteria and considering adding them to the List of Wetlands of International Importance. The Foundation "Le Balkan-Bulgaria" has been responsible for executing the work under the supervision of the Ministry of Environment and Waters. In a recent report produced on delivering biodiversity plans in Ireland the implementation of the WFD is regarded as a very positive development, and one that should greatly enhance the protection of Ireland s main rivers, wetlands and water bodies (COMHAR, 2004). However, the report also recognises that despite progress with the WFD, there are many outstanding issues surrounding the protection of wetlands that need to be addressed, in particular reducing the negative impacts of arterial and field drainage and 8

17 halting wetland loss through infilling and reclamation. A key factor identified is the absence of a national wetland inventory, as it makes it impossible to identify the extent to which wetlands in Ireland are being destroyed. Wetland inventories can therefore be seen as vital tools for site assessment and monitoring as well as providing information at a national level. However, despite a range of national and international drivers, such as the WFD and the Ramsar Convention, the use of wetland inventories across Europe is limited. Furthermore, the development of inventories which allow water dependency to be defined and hydrological functioning to be evaluated is all but absent. 3.2 Review of wetland classifications Wetland classifications provide a systematic grouping of sites into categories on the basis of evolutionary or structural relationships which exist between and among them. Many classification techniques are descriptive rather than functional. A review of wetland classifications has been undertaken to assist in defining the criteria required and the approach to be taken in attempting to classify wetlands as the first part of delivery on a Scottish wetland inventory. Table 1 details examples of wetland classifications. The majority of wetland classifications have been developed in the USA, emphasising morphological topology, and tending to describe a wetland in terms of shape and situation. By not linking the identified wetland types to wetland functioning, many of these classifications lacked the practical significance required to develop an understanding of water body dependency. The following review is based on a more extensive synthesis produced in Simpson (2002). One of the earliest wetland classifications proposed was the hydrotopographical classification by Goode (1977). This described a number of classes that reflected water source, topography and nutrient status. However, there were a number of inconsistencies with this approach as some categories were characterised by the topography, within which the wetland occurs, whilst other categories were characterised by the topography of landscape elements within the wetlands. Maltby et al (1996) also argue that there was not enough detail in the description of hydrological controls. Gosselink and Turner (1978) concentrated their approach on the hydrology of a wetland. Gosselink and Turner (1978) argued that the principal factors controlling the species composition of wetland plant communities, primary productivity, organic deposition and flux, and nutrient cycling were the hydrodynamic characteristics of the wetland and not the geographical location. The hydrodynamic characteristics of a wetland are represented by a combination of water inputs, water outputs, type of flow and hydropulses (Gosselink and Turner, 1978). This classification represents the first attempt to link a wetland classification setting to a wetland s functioning. In the late 1970s and 80s a number of other wetland classifications were developed using the hydrotopographical approach. Novitzki (1979) used both water source and landform to describe the various wetland types found in Wisconsin. His wetland categories were: surface water depression, groundwater depression, surface water slope and groundwater slope. Gilvear et al (1989) expanded this approach for 60 wetland sites in East Anglia, UK, but concentrated in greater detail on the hydrological component. Seven major classes were developed indicating the relative contribution of surface runoff and groundwater as water source. Lloyd et al (1993) used this classification as a basis to assess a wetland s susceptibility to abstraction and pollution. McInnes (1991) and Gilvear and McInnes (1994) expanded this further to produce a hydrological classification based on water inflows and outflows as well as topographic position. 9

18 Other classifications using components of a hydrotopographical approach include: Wheeler (1984), which is essentially an adaptation of Goode (1977); Hollands (1987) classification of wetlands in glaciated areas, that uses the dominant, or combination of, surface and groundwater flows to distinguish the various wetlands types; the Canadian National Wetlands Working Group (1988) classification, which uses the five wetland classes of bog, fen, marsh, swamp and shallow water as the highest level of classification, with a further subdivision into 71 classes; and the hydrogeological approach of Kieselev (1975). More recent hydrotopographical classifications have been developed by Wheeler (1994), Semeniuk and Semeniuk (1995) for Australian wetlands, and the Canadian National Wetlands Working Group (1997). Wheeler (1994) uses a combination of the configuration of the landscape and the principal mechanisms of water supply to a wetland, to create the distinct wetland types within his classification. Semeniuk and Semeniuk (1995) take a slightly different approach by focusing on the degree of wetness of a wetland rather than the source of the water. They determined thirteen primary types of inland wetlands using the combination of host landform and hydroperiod (i.e. degree of wetness). The Canadian National Wetlands Working Group (1997) produced a reworking of the 1988 classification utilising new information on the role of hydrology and water chemistry. The revision retains the general focus of the first edition, by using the structure of wetland class, form and type, but adds more detail, beneath the original five major wetland classes, by creating 49 wetland forms with 72 associated sub-forms. The Canadian National Wetlands Working Group classification has been refined further into the Wetlands and Riparian Ecosystem Classification (WREC), which integrates several different classification models into a single hierarchical framework (McKenzie and Moran, 2004). In Europe the EUROWET project has developed a classification that combines the topographical position of the wetlands in the landscape and the nature of the water transfer mechanisms (Maltby et al, 2005). The aim of the classification system is to help the delivery of ecological objectives under the WFD. In the UK a recent development has been the production of a wetland framework for assessing the water supply mechanisms for wetlands (Wheeler and Shaw, 2000). The framework has been designed for assessing the impact of external influences such as water abstraction on wetland ecosystems. In this framework, wetlands are classified according to their position in the landscape (e.g. floodplain, coastal, hill slope), their hydrology (the Wetland Water Supply Mechanism Types or WETMECs) and ecological types. The WETMECs were identified using multi-variate analysis of wetland data in eastern England and represents the way water is supplied to the wetland (e.g. wetland fed by springs, seepages, groundwater, floods or rain). Ecological types are based on a combination of ph and nutrient availability. The work published in 2000 is being revised and updated and is due for full publication at a later date. The system is described as being 'bottom-up' as WETMECs were identified using real data on wetland hydrology and species rather than expert opinion. An individual wetland site may contain several WETMECs. Each WETMEC can occur in combination with a range of ecological types and vegetation types. However, in the field, each WETMEC will generally contain a single ecological type and will usually support just one type of vegetation. 10

19 3.3 The Hydrogeomorphic (HGM) Approach The hydrogeomorphic (HGM) approach achieves a link between classification and functioning through the separation of the landscape into different functional units. Hydrogeomorphology is the study of interactions between hydrology and geomorphology, and the associated landscape conditions that result. The hydrogeomorphic approach, pioneered in the USA (Brinson, 1993), aims to provide a classification and assessment that not only describes the characteristics of a wetland but also allows inferences on functioning to be made. It attempts to achieve this by assuming that the hydrogeomorphic setting of a wetland has a direct influence on a wetland s functioning. Brinson (1993) developed a functional classification based on the hydrogeomorphic setting of a wetland, which later underpinned the framework of a functional assessment system for riverine wetlands (Brinson et al, 1995). The guidebook for the application of hydrogeomorphic assessments to riverine wetlands (Brinson et al, 1995) acted as a guide and a procedural document for the development of the approach (Smith et al, 1995). More recently regional guidebooks for the USA have been developed from Brinson s work, to be used as a basis for assessing the range of functions a wetland can perform such as flood water retention or nutrient removal (Hauer et al, 2000). The review of the HGM approach is an on-going debate which is seeking to further the robustness of the link between hydrogeomorphology and function (Cole, 2006). Brinson s (1993) classification contains the three core components of: a) geomorphic setting, b) water source and its transport, and c) hydrodynamics. The classification places emphasis on the hydrologic and geomorphic controls that are responsible for maintaining many of the functional aspects of wetland ecosystems (Brinson, 1993). Hydrogeomorphic properties are used to delineate wetlands that have similar functional characteristics. Both hydrology and geomorphology underpin the establishment of the biological structural elements and the occurrence of processes within a wetland ecosystem. Brinson (1993) uses this concept to identify specific wetland types, through their particular hydrogeomorphic setting, and then infer the type of hydrological, biogeochemical, plant habitat and animal habitat functions those wetlands perform. 11

20 Table 1 Examples of wetland classifications. Author Date published Country of origin Classification criteria Goode 1977 UK Water source, topography and nutrient status Gosselink and Turner 1978 USA Water inputs, outputs, type of flow and hydropulses Novitzki 1979 USA Water source and landform Gilvear et al UK Water sources of groundwater and run off and landform Gilvear and McInnes 1994 UK Water inflows, outflows and topography Wheeler 1984 UK Water source, topography and nutrient status Holland 1987 USA Water sources of surface runoff and groundwater flows Canadian National Wetlands Working Group 1988 Canada Descriptive classes, form and type Kiselev 1975 USA Hydrology and geology Wheeler 1994 UK Landscape and water source Semeniuk and Semeniuk 1995 Australia Landform and degree of wetness (hydroperiod) Canadian National Wetlands Working Group Wetland and Riparian Ecosystem Classification (WREC) 1997 Canada Descriptive classes, form, type, hydrology and nutrient status 2004 Canada Climate, soils and vegetation communities combined with hydrogeomorphic criteria EUROWET 2005 Europe Topographic position and water transfer mechanisms 12

21 4 DEVELOPMENT OF THE WETLAND HYDROGEOMORPHIC CLASSIFICATION FOR SCOTLAND 4.1 Hydrogeomorphic application for the Scottish wetland classification In the absence of suitable nationally robust datasets from which to construct an inventory of Scottish wetlands, and to further understand and predict water body dependency, an HGM approach has been adopted in order to define better the location of potential wetland areas in the Scottish landscape and to define their dependence on ground or surface water bodies. This approach allows water source to be defined and, consequently, linkage back to a dependent water body to be specified. By placing the water source in a geomorphic setting, wider linkages and interdependencies within the landscape can be derived. The following key criteria are derived: Geomorphic setting; and Water source Geomorphic setting Based on the HGM principles, it is possible to divide the Scottish landscape into six geomorphic settings (after Simpson, 2002). Wetlands can develop in these six settings. The following wetland types can exist: River marginal wetlands (RM); Basin wetlands (BA); Estuarine wetlands (ES); Coastal wetlands (CO); Extensive peatlands (EP); and Slope wetlands (SL). Not all the land within these geomorphic settings will be wetland. To be considered a wetland, land occupying these geomorphic settings needs to exhibit the following characteristics that apply to all wetlands: water should be at or near the land surface; the area should normally experience waterlogging of sufficient duration to support vegetation adapted to wet conditions (hydrophilic vegetation); and the soils should have developed properties associated with waterlogged conditions (hydromorphic or hydric soils) (Mitsch and Gosselink, 1993). This is similar to the definition adopted in the WEWS Act which defines a wetland as an area of ground the ecological, chemical and hydrological characteristics of which are attributable to frequent inundation or saturation by water and which is directly dependent, with regard to its water needs, on a body of groundwater or a body of surface water. It is possible to further divide wetlands occupying each geomorphic setting into subclasses through a refined interpretation of the geomorphic setting (Brinson et al., 1995, Simpson, 2002). For instance, basin wetlands may be represented by basins which are enclosed, those which have an outlet only or those which are characterised by both an inlet and an outlet. However, due to limitations imposed by the datasets employed to develop a hydrogeomorphic classification of Scottish wetlands, sub-division of geomorphic settings was not undertaken. Wetlands occupying the geomorphic settings can however be further divided into associated types based on their water sources. The concept of water sources is described in further detail below. 13

22 River marginal wetlands River marginal wetlands include all currently active and degraded floodplain ecosystems in which inundation by surface water and/or the prevalence of an elevated water table are regular phenomena. Also included are geomorphic features on the floodplain and the immediate valley slopes which fall within the contributory hydrological area of a river channel. Potential water sources are inundation from the river channel, groundwater, precipitation, and run off. Potential water losses are through water flow back to the channel after a flood event, run off, groundwater recharge and evapotranspiration. Water movement through river marginal wetlands is dominated by a lateral transfer of water. Basin wetlands Basin wetlands include all currently active or degraded topographic depression ecosystems, in which inundation by surface water and /or the prevalence of an elevated water table are regular phenomena. Basin wetlands occur in topographic depressions where the elevation contours are closed, allowing the accumulation of surface water, either as permanent standing water or as temporary accumulation. Basin wetlands consist of a range of varied habitats. They can be isolated or continuous habitats that are immediately adjacent to the accumulated water body, such as a wetland that develops on the shores of a lake. They can be floating mats of vegetation attached to the land that rise and fall with the water level of a lake or pond. They can also be continuous vegetated habitats that are located in frequently waterlogged depressions but, unlike the two other habitats, are not associated with an open body of water. The potential water sources are from inlet flow, inundation as a result of a rise in the level of the associated water body, precipitation, groundwater discharge and run off. Potential water losses are through evapotranspiration, groundwater recharge and drainage from an outlet. The dominant water movement is through vertical fluctuations in the level of the water body and in the level of groundwater. Basin wetlands can grade into other wetland types, e.g. the inlet of a basin wetland may have a river marginal wetland associated with it, upstream or downstream of the basin. Estuarine wetlands Estuarine wetlands include all currently active or degraded ecosystems that occur along the borders of an estuary. An estuary is defined as a narrow, semi-enclosed coastal body of water, which has a free connection with the open sea, at least intermittently, and is fed by freshwater emptying from an inland river catchment. The limits of an estuary, upstream of the channel, extend to where there is a regular tidal influence over the water level in the channel. This can be recognised by the occurrence of a high water mark of an average tide. Potential water sources are surface inundation from a rise in the tide, river flow or both together, groundwater, run off and precipitation. Potential water losses are from tidal exchange, groundwater recharge, run off and evapotranspiration. Estuarine wetlands can grade into river marginal wetlands upstream and into coastal wetlands along the coast from the estuary mouth. The dominant water movements are through lateral movement via the river channel and astronomical water movement due to fluctuations in the sea level. Coastal wetlands Coastal wetlands include all currently active or degraded ecosystems that occur along the boundary of marine and terrestrial environments. 14

23 The potential water sources for these wetlands are from surface inundation from the sea, groundwater, run off, precipitation and sea spray. Potential water losses are from tidal exchange, run off and evapotranspiration. The water movement within a coastal wetland is dominated by astronomical fluctuations of sea water level. Coastal wetlands are unlike estuarine wetlands, because they do not have a major river channel flowing through them and connecting to the sea Extensive peatlands Extensive peatlands are characterised by large peat deposits that significantly modify the local hydrology. Peat deposits can occur in all other types of major wetlands but only when they become large in extent are they classified as extensive peatlands. Extensive peatlands can develop across watershed boundaries and in favourable climatic conditions, such as wet, shady areas, and can even develop on valley slopes up to 35 o (Lindsay, 1995). The elevation and surface topography of an extensive peatland is either presently or historically controlled by the vertical build up of organic matter. Potential water sources to these wetlands are precipitation, groundwater and run off. Potential water losses are through outlet flow, evapotranspiration and groundwater recharge. The water movement is controlled by the retention and storage characteristics of peat deposits. Slope wetlands Slope wetlands occupy the areas transitional between the other wetland types. They are characterised by seepage zones, springs and flushes. The potential water sources for these wetlands are from the discharge of groundwater, run off and precipitation. Potential water losses are from groundwater recharge, run off and evapotranspiration. The water movement within a slope wetland is dominated by unidirectional downslope flow Water sources The water balance of any wetland can be written as: S = P + SWI + GWI - ET SWO - GWO Where S is change in storage, P is precipitation, SWI is surface water inflow, GWI is groundwater inflow, ET is evapotranspiration, SWO is surface water outflow and GWO is groundwater outflow. Precipitation and evapotranspiration are common to all Scottish wetlands, but the other variables only apply in certain circumstances. The vulnerability of a wetland to different pressures will be associated with various combinations of inflows and outflows, or water sources. For instance, groundwater abstraction would be unlikely to impact severely on a wetland without a groundwater inflow or outflow unless surface hydrological conditions are maintained by groundwater levels. Conversely, surface water pollution, and especially eutrophication, may only have an indirect impact on a wetland site receiving its water from precipitation and groundwater outflow. The following water sources have been used to establish the understanding of water dependency at each wetland site. 15

24 Precipitation Moisture that falls from the atmosphere to the terrestrial environment. The moisture can be in the form of rain, snow, sleet, hail, fog, etc. This water source is considered universal in the Scottish context. Surface water Surface water components include run off, inundation from the sea, inundation from a rise in tide and river flow, inundation from a rise in water body, overbank inundation from a channel and sea spray. These components are described below. Run off is the portion of precipitation that makes its way towards stream channels, lakes, or oceans as surface or subsurface flow. It describes the horizontal flow of water rather than the vertical flow, which is termed infiltration. Before run off can occur, precipitation must satisfy the demands of evapotranspiration, interception, surface detention, and channel detention, i.e. run off occurs when the ground can no longer absorb precipitation or when the ground cannot absorb precipitation fast enough. Run off also includes water flowing downslope under gravity or near the ground surface, that originates from a groundwater discharge site further up slope and is not able to infiltrate into the ground surface. Run off can also be termed as overland flow. Surface inundation from the sea occurs when there is a rise in tide and sea water covers the land surface. A combination of high tides and high winds gives rise to the greatest levels of inundation. Surface inundation from a rise in the tide, in river flow or in both together occurs when there is a rise in water level that covers the land surface. This rise in water level can be due to a rise in the sea water level as a result of an incoming tide, due to a rise in the river water level because of increased river flow or due to a combination of both. Surface inundation from a rise in water body level occurs when there is an increase of flow from either groundwater, precipitation, channel flow, run off, or any combination of these, to a water body, such as a lake or a loch, but not a river or stream channel, increasing its level. This increase in level allows inundation of the surrounding area. Surface overbank inundation from a channel occurs when normally dry areas are covered in water as high flows overtop the banks of the channel. Sea spray as a hydrological source occurs as a result of wave action of the sea and wind action. This action releases water droplets into the air which can fall onto areas near the sea, providing a source of water. This source can be of importance in producing higher levels of salinity. Groundwater The level below which all the pore spaces are totally filled with water is called the water table. The area above this level is called the unsaturated zone. Here the spaces in the rock and soil contain air and water. Water in this zone is called soil moisture. The entire region below the water table is called the saturated zone which is what is commonly termed as groundwater. Groundwater is continually flowing and will eventually reappear at the surface as groundwater discharge. This flow can be directly into streams, rivers, lakes, wetlands and oceans, or it may discharge in the form of springs and flowing wells. The WEWS Act defines groundwater as water which is below the surface of the ground in the saturation zone and in direct contact with the ground or subsoil. The data used within the hydrogeomorphic classification of Scottish wetlands show likelihood of dependency on a 16

25 groundwater body (aquifer) as defined by the different categories in the Combined Vulnerability and Aquifer map provided by SEPA. Whilst not necessarily a true water source, groundwater maintenance refers to the presence of near surface groundwater levels above which surface water variations may operate. The removal of this groundwater component would compromise the surface hydrological functioning of the wetland. For the purpose of deriving a unified dependency scoring system, groundwater maintenance has been combined with groundwater discharge to produce a single groundwater source category. 4.2 Output medium The hydrogeomorphic classification of Scottish wetlands has been developed within a GIS. The principal output of the project is a GIS which contains information on the water body dependency of, and pressures upon, potential wetland areas in Scotland, based on hydrogeomorphic criteria. This information can be presented visually through the production of maps, or statistically through the analysis of data fields derived from the associated attribute table. The classification does not distinguish between designated and non-designated sites in terms of defining water body dependency. Information on designated sites is held within the attribute table allowing interrogation of statutory sites in isolation if required. Similarly, the approach considers the relationships between hydrology and geomorphology at a landscape scale and consequently identifies both wetland and non-wetland areas. Work on the confidence limits (see below) indicates that the classification can be used to define potential wetland areas beyond the known or designated site network. 4.3 Limitations to the approach Data The major constraint on the development of a hydrogeomorphic classification of Scottish wetlands has been data available. Only readily available national datasets have been used. Local, potentially more detailed, datasets have not been used. Similarly, commercially available datasets have not been purchased. Data related issues have taken several forms: Accuracy of data; Presence or absence of data; Scale of data; Relevance of data; and Data processing. Accuracy of data It has been assumed that the original datasets used throughout the development of the classification are accurate. No independent evaluation of the original datasets has been conducted. This philosophy has also been applied to the datasets used to validate the outputs and to define confidence limits. Presence or absence of data Only datasets which provided full national coverage for Scotland were used. Datasets which provided local coverage were excluded. 17

26 Scale of data The original datasets have been provided at a variety of scales. Consequently, assumptions derived from these datasets will be scale-dependent. Relevance of data Some of the datasets hold useful information. However, the genesis and use of the dataset is task specific and not necessarily germane to providing information relevant to developing a wetland classification. For instance, the Institute of Hydrology predicted 100 year flood extent dataset provides out of channel flood depth estimates for flood return events with a 100 year frequency. This information is correct for its purpose. However, the usefulness of the dataset is limited when trying to define the likelihood of overbank inundation, and hence a dependency on a surface water body, on an annual basis. Data processing Working with national datasets has proved to be a challenge. The data processing time has been considerable. Future presentation and use of the classification needs to consider how to maximise the efficiency of data presentation Defining hydrogeomorphology The development of the Scottish wetland hydrogeomorphic classification has been an iterative and evolving process. Theoretical approaches were presented to the project steering group through meetings and reports. As the development process progressed the theoretical approach was revisited and modified accordingly. Two main modifications to the theoretical approach are manifest in the final output. Hydrodynamic The term hydrodynamic, as used here, refers to the motion of water and the capacity of the water to do work. Brinson (1993) identified three qualitative categories of hydrodynamic: (a) vertical fluctuations that result from evapotranspiration and subsequent replacement by precipitation or groundwater discharging into a wetland; (b) unidirectional flows that range from strong channel contained conditions to sluggish sheet flow across a floodplain; and (c) bi-directional flows resulting from tides. The process of understanding the hydrodynamics relies on relating the available datasets to data sources, such as Wheeler, et al. (2004) and Newbold and Mountford (1997), which define eco-hydrological relationships. However, detailed information on vegetation communities is not available at a national scale for Scotland. Land cover information provides general categories, but subtle differences within the broad vegetation communities are not available. Therefore, defining the hydrodynamic, such as whether the vegetation community is dominated by summer drawdown and winter inundation based on an understanding of the eco-hydrological functioning, has not been possible. Digitised NVC data was available for approximately 170 SSSIs. However, these sites, whilst representative, did not provide national coverage and they are limited to only being representative of designated areas. Consequently the data held within the digitised SSSI NVC dataset have only been used as part of a validation process and not for defining hydrodynamics. The absence of information on the hydrodynamics of a site limits the understanding of subtle eco-hydrological relationships. It also reduces the confidence in understanding the relative importance of different water sources. For instance, an area may be subject to both surface inundation from a rise in tide and from groundwater. The dominance of either 18

27 a vertical or bi-directional hydrodynamic remains ambiguous without additional information. Therefore, a dependency on both a transitional (estuarine) water body and groundwater is established, but the principal hydro-ecological driver may not be established. Groundwater maintenance The original intention was to distinguish between the manifestation of groundwater at surface, such as through spring discharges, and the maintenance of elevated groundwater levels as a driver for surface hydrological processes. However, the datasets have limited this output. A single groundwater dataset has been derived. However, it is possible to interpret this dataset in conjunction with the surface information and draw assumptions on the role of groundwater in maintaining and influencing surface water processes. 4.4 Information held within the wetland hydrogeomorphic classification for Scotland Original datasets have been interpreted and integrated to generate a range of information held within the GIS. The information provided can be interpolated and presented in many forms. To meet the objectives of this project the primary derived data of importance are: Water body dependency; Potential and actual pressures; and Hydrogeomorphic units Water body dependency Scottish wetlands are dependent on groundwater bodies, surface water bodies, precipitation, surface water run off or a combination of all four. Water body dependency has been derived through analysis and integration of the datasets held within the GIS. Information on datasets used and the algorithms employed are provided in Appendix 1. Dependency is established where a hydrological linkage mechanism can be demonstrated. The hydrological mechanisms which link a water body as a water source to a wetland are based on an understanding of hydrological processes and are explained in the algorithms used to derive datasets (Appendix 1). Precipitation is considered to be a universal water source in the Scottish context. The Scottish wetland classification defines whether the dependence is on ground or surface water, thus: wetland dependant on a surface water body; wetland dependant on a groundwater body; and wetland dependant on a combination of groundwater and surface water bodies. Water dependency does not mean that the wetland is adjacent or contiguous to a water body all of the time. For instance, the water body may be a river, but the wetland area may occupy a floodplain location several hundred metres distant except in times of spate. Therefore, in some situations the wetland could be considered adjacent to the dependent water body but this is not necessarily so all of the time. Wetland dependency on a surface water body is defined through interpreting the six possible surface water sources. The dependency on a groundwater body is confined to a single water source component (Table 2). Not all water sources are considered to be dependent on a water body. Precipitation is not dependent on a water body. Surface water run off is not considered to be associated with a water body but tends to occur on slopes where rainfall intensity is so great that infiltration rates are exceeded by downslope 19

28 movement of water. However, surface water run off can still be an important component of wetland sites or an important contributor to downslope wetland sites. Any location in Scotland, both wetland and non-wetland, will be represented by a combination of the six surface water sources and groundwater. Interpretation of the combinations of water sources is important to understand the dynamics and interdependency of water bodies. Table 2 Summary of water sources and sub classes. Water source class Sub-class Water body dependent Precipitation Precipitation N Surface water Run off N Surface inundation from the sea Surface inundation from rise in tide, in river flow or in both together Surface inundation from a rise in water body level Surface overbank inundation from a channel Sea Spray Y Y Y Y Y Groundwater Groundwater Y Likelihood of dependency The degree of dependence on a water body varies from wetland to wetland. For instance, a fringing reed-swamp along the margins of a loch has a distinct high level of dependence on the surface water body. However, contiguous areas of the same wetland some distance from the loch shore may only have a moderate level of dependence, for instance, only during extended wet periods when the loch water levels are elevated. Based on an understanding of the environmental variables controlling hydrological processes, three levels of dependency have been defined according to the likelihood of linkage between a water body and a wetland: High likelihood of dependency (H); Moderate likelihood of dependency (M); and Low likelihood of dependency (L). The likelihood of dependency results from an analysis of the potential hydrological sources and pathways which form the linkage between the water body and the wetland. For instance, to derive the likelihood of an area to receive overbank inundation, and hence be dependent on a river water body, three datasets were combined: Institute of Hydrology Predicted 100yr Flood Extents; SEPA WFD River Waterbodies; and SEPA Flooding 20

29 Extents. The following assumptions were placed on the data to define the likelihood of dependency on receiving water from overbank flooding: High likelihood of dependency: 100yr Flood >2m deep (assuming that the greatest level of inundation represents topographic lows and areas prone to more frequent flooding that shallower areas) + Presence of River Waterbody (assuming that the presence of a defined surface water body would be indicative of a landform prone to inundation, even if the inundation was confined to the channel) + Presence of Flooding Extents Polygon (assuming that areas that are defined as being subjected to flooding are inundated from water derived from the adjacent channel) Moderate likelihood of dependency: 100yr Flood 1-2m deep + Absence of River Waterbody + Presence of Flooding Extents Polygon Low likelihood of dependency: n/a + Absence of River Waterbody + Absence of Flooding Extents Polygon Different levels of likelihood of dependency are possible for the six surface water sources occurring at a location. For example, a location may have a high likelihood of dependency of overbank inundation from a channel, but low likelihood of dependency on the other five sub-classes. In this situation the default is always to the highest level of dependency. Therefore the overall assessment of surface water dependency will reflect the highest individual sub-class. Similarly, the degree of dependency for groundwater utilises information developed by SEPA to screen groundwater vulnerability (SNIFFER, 2004). Using the inverse relationship between criteria which have been developed to describe pathways between ground surface and water table it has been possible to predict the likelihood of an area being supplied with a groundwater source and hence supporting a dependence on a groundwater body. Information on drift thickness, conductivity and aquifer type have been assessed. The following assumptions were placed on the data to define the likelihood of dependency on a groundwater body: High likelihood of dependency: Intergranular, High Productivity Drift Aquifer + Dominantly Intergranular, Highly Productivity Aquifer Moderate likelihood of dependency: Intergranular, Moderate Productivity Drift Aquifer + Fractured, Very Low Productivity Aquifer Low likelihood of dependency: Intergranular, Low Productivity Drift Aquifer + Fractured, Very Low Productivity Aquifer Unified water body dependency classes (Class) A unified dependency scoring system (or a unified water body dependency class) has been produced by combining the water body dependency with the likelihood of dependency (see Appendix 1). In the GIS this is termed Class. Table 3 summarises the full range of water body dependency classes used in the Scottish wetland classification. Figure 1 demonstrates an example output from the GIS for an area of the upper River Clyde. Several different water body dependency classes are present demonstrating subtle differences in the landscape. The main floodplain area of the River Clyde (1 and 2) is dominated by Class 1 (high likelihood of dependency on groundwater and surface water body), and Class 3 (low likelihood of dependency on groundwater and high likelihood of dependency on a surface water body). The banks adjacent to the main floodplain and on the downstream side of river bends (3) are characterised by Class 4 (high likelihood of dependency on groundwater and moderate likelihood of dependency on a surface water 21

30 body). The slopes above the main floodplain (4) are dominated by Class 7 (high likelihood of dependency on groundwater and low likelihood of dependency on a surface water body). The more gentle slopes above the River Clyde (5) are characterised by Class 9 (low likelihood of dependency on groundwater and low likelihood of dependency on a surface water body). Table 3 Unified water body dependency classes. Class Groundwater Surface water 1 H H 2 M H 3 L H 4 H M 5 M M 6 L M 7 H L 8 M L 9 L L Figure 1 Example of water body dependency classes (Class)

31 Within Scotland each water body has been assigned a unique identifier. By interrogating the GIS it is possible to link the groundwater and surface dependency to actual water bodies as identified by the SEPA water body identification number Potential and actual pressures Information has been collated on the different pressures which potentially impact on Scotland s wetlands and the water bodies that they are dependent upon. Two approaches have been developed within this project: theoretical and actual risk. The theoretical risk associated with pressures has been based on professional judgement and published information. This has integrated the water body dependency classes with the seven potential pressures and generated three risk classes: high, moderate, low (Table 4). Point sources of pollution have a highest risk associated with high dependency on surface water and a moderate or high dependency on groundwater. Risks are lowest where surface water dependency is low. It is assumed that the pathway for point sources of pollution will normally be surface waters, consequently Classes 1, 2 and 3 carry the highest risk. The same is essentially valid for diffuse pollution, however, risks remain moderate where dependency on a groundwater body is moderate or high if the diffuse pollution has impacted groundwaters. Table 4 Classes for potential pressures. Class Code Pressure PP_Point Point Source H H H M M M L L L PP_Diffuse Diffuse Source H H H M M M M M L PP_Abstrac Abstraction H H H H M M H M L PP_Flow Flow regulation H H H M M M L L L PP_Artific Artificial recharge H M L H M L H M L PP_Morphol Morphological alteration H H H M M M L L L PP_Alien Alien Species H H H M M M L L L Abstraction forms a theoretically high risk on all classes where a dependency on a waterbody is high (Classes 1, 2, 3, 4 and 7). This risk reduces as waterbody dependency reduces. Flow regulation only occurs on surface waters. Therefore, this risk associated with this pressure is only high where dependency on a surface water is high and low where dependency is low. Morphological alteration only applies to surface water bodies. Consequently the assessment of risks and pressures is the same as for flow regulation. Artificial recharge is associated primarily with groundwater bodies. Therefore, the risk of changing conditions is highest in association with high dependency on groundwater bodies (Class 1, 4 and 7). 23

32 Alien species are a problem confined to surface waters. Therefore, the risk of their transference and contamination is highest in association with high dependency on surface water classes (Class 1, 2 and 3). Figure 2 Example of potential risk from point source pollution (PP_Point) Figure 2 illustrates how the information held within the Scottish wetland hydrogeomorphic classification GIS can be manipulated to generate a potential risk map for point source pollution for an area of the Upper Clyde. The presence of several different water body dependency classes is reflected in the level of risk present. The main floodplain area of the River Clyde (1) is dominated by a high risk from point source pollution due to the high likelihood of dependency on groundwater and surface water body. The banks adjacent to the main floodplain (3) are characterised by moderate risk from point source pollution due to the high likelihood of dependency on surface water body and low likelihood of dependency on groundwater body. This risk extends along the tributary draining from the East (2) due to the moderate likelihood of dependency on groundwater and high likelihood of dependency on a surface water body. The slopes above the main floodplain (4) are characterised by a low risk due to the high likelihood of dependency on groundwater and low likelihood of dependency on a surface water body. Here the main source of potential pressure is more likely to be from abstraction or artificial recharge rather than point source pollution. The more gentle slopes to the North of the main floodplain (5) are also dominated by areas of low risk, but with low likelihood of both surface water and groundwater bodies. Actual risks have been compiled from the WFD Water bodies datasets. Each WFD Water bodies dataset records a WFD_Char indicating whether the water body is at risk or not. Four categories are used: 1a - At risk 1b - At risk (probably) 24

33 2a - Not at risk (probably) 2b - Not at risk It is possible to generate both the actual risk at a site and compare it with potential risk to understand current and future pressures on wetlands Hydrogeomorphic units It is possible to divide the landscape into homogeneous landscape units based on the hydrogeomorphic approach. These landscape units, or hydrogeomorphic units, define an area of homogeneous geomorphic setting and water body dependency. These are generated by combining the water body dependency classes (Class 1 to 9) with the geomorphic setting (BA, ES, CO, RM, SL, EP) within the GIS (see Appendix 1). The information generated provides an understanding of how the landscape is functioning in relation to water sources and geomorphic features. The example provided in Figure 3 demonstrates the variety of hydrogeomorphic units which exist in the same example shown in Figures 1 and 2 from the upper Clyde. Figure 3 Example of hydrogeomorphic units The main floodplain area of the River Clyde (1 and 3) is characterised by river marginal areas (RM1 and RM4) associated with the floodplain. The tributary draining from the east (2) is characterised as a slope (SL) rather than river marginal environment. The valley bottom does not possess the properties of a river margin in so far as there are no recent alluvial deposits and steep slopes extend to the valley bottom. The hydrology of the valley bottom is dominated by low likelihood of dependency on groundwater and high likelihood of dependency on a surface water body (SL3). The slopes above the main floodplain (4) are dominated by slope unit SL7 indicating a high likelihood of dependency on groundwater and a low likelihood of dependency on a surface water body. The more 25

34 gentle slopes above both the main River Clyde and the tributary (5) are characterised by slopes with low likelihood of dependency on groundwater and low likelihood of dependency on a surface water body (SL9). 4.5 Validation The analysis used to derive the water body dependency classes and the other derived datasets assumes that the data provided were accurate at their spatial scale. The combination of datasets presents two principal outcomes: the combination of two or more datasets could improve accuracy of prediction; or the combination of two or more datasets could increase error. Therefore, there is a need for independent validation of the assumptions employed and the derived information generated. Key to the validation was: (a) an assessment of whether the water dependent class (1 to 9) reflected known water dependency for given wetland areas; and (b) to what extent could hydrogeomorphic types or units be used as a surrogate for predicting wetland location and water dependency National Vegetation Classification data Digitised National Vegetation Classification (NVC) data (Rodwell, 1998a,b&c, 2000a&b) has been received for a total of 176 designated Scottish wetlands (SSSIs) covering an area of 317,839ha. The digitised vegetation maps have been produced by field survey. Whilst there is always the potential to introduce error, through surveyor experience, time of survey, accuracy of field mapping, competency of digitising or goodness of fit to a certain NVC category, for the purpose of the validation exercise it is assumed that any error is equally distributed across all sites and community types and is, therefore, negligible. The analysis also assumes that the main driver of vegetation community manifestation is hydrology rather than site management or other external factors. Often this will not be the case as management practices will mask the underlying hydrological conditions through drainage, cutting, grazing or burning, for instance. The NVC dataset has not been used in deriving water dependency classes or hydrogeomorphic units and can be considered as independent. In addition the UK WFD Technical Advisory Group (UK TAG) have invested considerable effort into defining a draft list of groundwater dependency for wetland NVC categories (Appendix III). This information has been utilised in the validation process. It should be noted that the information presented in Appendix III is still in draft pending completion of expert review. In order to extract a sample of points for validation and statistical analysis, a set of random points was overlain on both the outputs developed in the Scottish wetland hydrogeomorphic classification GIS and the NVC dataset provided by SNH, and relevant fields (GEOMORPHIC, CLASS and NVC information) were extracted at each of these points. Only points that produced valid information in both datasets were retained, yielding a total of n = 7,066 points for further processing and analysis Testing association between predicted groundwater dependence class and the presence of groundwater dependent NVC communities NVC communities considered to have different degrees of groundwater dependence were taken from the draft list developed by the UKTAG. Dependency scores used are for Scottish communities, as assigned by SNH. In many cases, NVC data had been recorded in the form of mosaics, i.e. multiple NVCs were associated with a given data point. Only points that had at least one community included on the draft UKTAG list were retained, 26

35 restricting analysis to points likely to represent actual wetland communities (n = 6,564). NVC dependency score assigned to a given point was either that of the (single) community present, or that of the highest (most dependent) of any of the communities making up a mosaic. Overall statistical association between predicted groundwater dependency (scores 1 to 3) and groundwater dependence of actual NVCs present (UKTAG scores 1 to 3) were tested using (a) rank correlations, and (b) chi-square contingency analysis. The former is more suited to the ordinal-scale data, whereas the latter treats score values as categorical. Correlation (Spearman s ρ = 0.238, p < 0.001) and chi-square (χ 2 = 404.2, p < 0.001) analysis both yield highly significant results, indicating a positive association between expected NVC groundwater dependence and the predicted groundwater dependency scores. However, the correlation coefficient is weak, and cross-tabulation of scores (Table 5) indicates that the predicted output and NVC groundwater dependency scores behave differently in a number of ways. It is worth noting that NVC data are not a perfect proxy for defining actual dependence on a groundwater body and that more than one community may be present representing a range of groundwater dependencies. Therefore, any discrepancies may not reflect a failure of predictions, rather individual variation needs to be considered on a case-bycase basis. The prediction of groundwater dependencies has a tendency to predict dependency as either high (1) or low (3), with only 2.8% of all samples falling into the medium category (2) (Table 5). In the NVC data over a third (35.0%) of all points come out as medium dependency on groundwater. Table 5 Cross-tabulation between predicted groundwater dependency and NVCbased groundwater dependency scores. (Note: Values shown are numbers of validation points in each of the different categories). NVC GW score Predicted Groundwater Dependency score Total (8.24%) (0.2%) (2.4%) (10.9%) (24.1%) (1.4%) (9.5%) (35.0%) (26.0%) (1.2%) (26.9%) (54.1%) Total (58.4%) (2.8%) (38.8%) (100%) Given this low frequency of predicting medium groundwater dependency (and the fact that medium dependency in NVC data can mean different things), the following points focus on high and low cases. The two datasets demonstrate a high degree of agreement for predicted high groundwater dependency (1) and high NVC groundwater dependency (1) for 541 (~82%) of the 716 points assessed. This relatively high level of agreement extends across all NVC categories such as mire, grassland, woodland, etc. For points which were predicted to have low groundwater dependency (3) and low NVC groundwater dependency (3) positive correlation accounts for 1,767 (~50%) of the 3,550 points. 27

36 For 160 (~22%) of the 716 points associated with strong NVC groundwater dependency (1) the groundwater dependence predicted is low (3). If the NVC groundwater dependency provides a correct indication of actual groundwater dependence, these points are false negatives in a regulatory context (i.e. if the predicted outcome was used for regulatory screening, the presence of highly groundwater dependent communities could be missed for approximately a fifth of all sites not supporting information on NVC communities.) By relating the proportion of observations in the full validation dataset to the observations which predict low groundwater dependence for NVC categories, it is possible to assess any anomalies between the output datasets. The results are summarised in Table 6. Certain strongly groundwater dependent NVC categories are predicted as having a low groundwater dependence a disproportionate number of times. M6 Carex echinata- Sphagnum recurvum mire tends to predict low groundwater dependence in approximately 86% of all cases. M10 Carex dioica-pinguicula vulgaris mire and M7 Carex curta- Sphagnum russowii mire also disproportionately predict low groundwater dependency. Table 6 Occurrence of false negatives by NVC community (only NVCs that occur at least once in the validation dataset are shown). NVC community Number (and %) of validation points that are predicted low groundwater dependency Number (and %) of points with this NVC in the full validation dataset CG11 2 (1.3%) 55 (0.8%) CG12 0 (0.0%) 29 (0.4) M10 9 (5.6%) 112 (1.7%) M11 3 (1.9%) 64 (1.0%) M12 0 (0.0%) 13 (0.2%) M14 3 (1.9%) 12 (0.2%) M31 0 (0.0%) 18 (0.3%) M32 12 (7.5%) 69 (11%) M37 0 (0.0%) 4 (0.1%) M5 3 (1.9%) 5 (0.1%) M6 138 (86.3%) 370 (5.6%) M7 6 (3.8%) 16 (0.2%) M9 1 (0.6%) 3 (0.0%) SD15 0 (0.0%) 9 (0.1%) SD16 0 (0.0%) 2 (0.0%) SD17 0 (0.0%) 6 (0.1%) U15 0 (0.0%) 4 (0.1%) U16 1 (0.6%) 16 (0.2%) U17 0 (0.0%) 13 (0.2%) W20 1 (0.6%) 2 (0.0%) W4 4 (2.5%) 38 (0.6%) W7 0 (0.0%) 18 (0.3%) 28

37 The main reason for the high variation on these communities could be a result of poor goodness of fit to reference NVC communities or an association with a variety of water sources. For instance, M6 Carex echinata-sphagnum recurvum mire is currently classified as (2) being likely to have some dependency on groundwater discharge at most sites on the UK WFD Technical Advisory Group website ( tag_guidance/article_05/). This indicates that water sources either direct from recognised aquifers or indirectly as recharge from minor aquifers in superficial deposits and/or with other sources (surface runoff, overbank flooding etc) are very important. However, latest UKTAG drafts of groundwater dependency have reclassified it as (1) strong groundwater dependency. The literature is inconclusive. JNCC (2004) suggests that M6 Carex echinata-sphagnum recurvum mire can occur in a variety of locations and be supported by a range of water sources including springs, acid flushes and run off. Similarly, Rodwell (1998b) is inconclusive suggesting that the through put and flushing of water can be from springs and seeps or by the concentration of drainage water-tracks or streams. Failure to accurately predict the distribution of M6, for example, could simply mean that in Scotland, this community is mainly fed by shallow GW flows rather than from the underlying GW body. Therefore, the disproportionate response of the data may be exaggerated for NVC categories which are less clearly dependent on a groundwater body as a source. False positives have also been investigated. Assuming that the NVC category provides a correct indication of actual groundwater dependence, false positives occur where highly groundwater dependent communities are predicted instead of predicting low groundwater dependence. In a regulatory context this would result in action being invoked far more frequently than is required. False positives account for 1,706 (~48%) out of 3,550 points with NVC communities where groundwater discharge is usually considered irrelevant (Table 5). Cases where false positives occur are summarised in Table 7. Table 7 Occurrence of false positives by NVC community (only NVCs that occur at least once in the validation dataset are shown). NVC Number (and %) of validation points that are predicted strong groundwater dependency Number (and %) of points with this NVC in the full dataset CG13 0 (0%) 9 (0.1%) CG14 0 (0%) 2 (0.0%) H (10.6%) 657 (10.0%) H (25.4%) 735 (11.2%) H13 25 (1.5%) 32 (0.5%) H14 25 (1.5%) 58 (0.9%) H15 1 (0.1%) 20 (0.3%) H16 11 (0.6%) 14 (0.2%) H17 0 (0.0%) 23 (0.4%) H19 29 (1.7%) 48 (0.7%) H20 31 (1.8%) 47 (0.7%) H21 36 (2.1%) 195 (0.6%) H22 25 (1.5%) 37 (0.6%) H9 5 (0.3%) 36 (0.5%) M1 35 (2.1%) 151 (2.3%) M (23.0%) 1606 (24.5%) 29

38 NVC Number (and %) of validation points that are predicted strong groundwater dependency Number (and %) of points with this NVC in the full dataset M18 53 (3.1%) 814 (12.4%) M (16.4%) 1163 (17.7%) M2 7 (0.4%) 66 (1.0%) M20 15 (0.9%) 88 (1.3%) M (10.4%) 487 (7.4%) M3 9 (0.5%) 67 (1.0%) MG5 5 (0.3%) 12 (0.2%) S10 1 (0.1%) 2 (0.0%) S14 0 (0.0%) 1 (0.0%) S19 1 (0.1%) 1 (0.0%) S21 0 (0.1%) 1 (0.0%) S22 0 (0.0%) 2 (0.0%) S26 0 (0.0%) 1 (0.0%) S27 1 (0.1%) 9 (0.1%) S28 3 (0.2%) 4 (0.1%) S4 1 (0.1%) 7 (0.1%) S9 0 (0.0%) 4 (0.1%) U10 43 (2.5%) 70 (1.1%) U12 5 (0.3%) 5 (0.1%) U13 8 (0.5%) 25 (0.4%) U14 0 (0.0%) 1 (0.0%) U19 0 (0.0%) 3 (0.0%) U2 1 (0.1%) 1 (0.0%) U (8.3%) 285 (4.3%) U21 2 (0.1%) 4 (0.1) U4 156 (9.1%) 485 (7.4%) U5 221 (13.0%) 651 (9.9%) U7 75 (4.4%) 144 (2.2%) U8 10 (0.6%) 25 (0.4%) U9 3 (0.2%) 3 (0.0%) NVC communities not usually associated with groundwater, that are predicted to occupy areas highly dependent on groundwater, include the following calcifugous grasslands and montane communities: U4, U5, U7, U10 and U20; heath communities: H10, H12, H13, H14, H20 and H22; and mire community M25. Many of the these vegetation communities are characteristic of upland areas which experience high rainfall and humid conditions. These habitats are often characterised by moist soils with humic and sometimes peaty properties (Rodwell, 1998b, 1998c). It is possible that the predicted criteria are incorrectly interpreting drift geology and deriving a strong dependency on a groundwater body for these areas. Or alternatively, these communities may be associated with water sources other than groundwater in some locations. 30

39 4.5.3 Testing association between predicted hydrogeomorphic unit and wetland NVC communities Further analysis of false negatives investigated the relationship between hydrogeomorphic units with a predicted low groundwater dependency and NVC categories which are characterised by a strong groundwater association (i.e. areas which support highly groundwater dependent vegetation communities but which would be missed in a screening exercise if predicted hydrogeomorphology was used as a surrogate for wetland type). The NVC communities with a strong association with groundwater demonstrate a disproportionate association with the following hydrogeomorphic units: 6_EP, 9_EP, 9_CO and 9_Slope (Table 8). The extensive peatland (EP) hydrogeomorphic units comprise considerable areas of M6 Carex echinata-sphagnum recurvum mire, thus replicating the error of uncertainty of water source identified above. The mire communities dominate the assessment of the hydrogeomorphic units (greater than 95% of the validation points are associated with mire communities). Subtle differences in the vegetation of these mire communities may not always be accurately determined during the NVC mapping process. Similarly, a range of hydrological mechanisms may be operating in association with a groundwater source which may be skewing the predicted outcomes. Table 8 Occurrence of false negatives by HGM unit. HGM Unit Number (and %) of validation points that are predicted as low groundwater dependency Number (and %) of points with this HGM in the full dataset 3_Slope 2 (1.3%) 43 (0.7%) 3_EP 1 (0.6%) 17 (0.3%) 3_BA 2 (1.3%) 5 (0.1%) 3_RM 0 (0.0%) 5 (0.1%) 3_CO 3 (1.9%) 35 (0.5%) 3_ES 0 (0.0%) 0. (0.0%) 6_Slope 0 (0.0%) 43 (0.7%) 6_EP 8 (5.0%) 117 (1.8%) 6_BA 0 (0.0%) 1 (0.0%) 6_RM 0 (0.0%) 4 (0.1%) 6_CO 1 (0.6%) 50 (0.8%) 6_ES 0 (0.0%) 3 (0.0%) 9_Slope 50 (31.3%) 542 (8.3%) 9_EP 73 (45.6%) 1356 (20.7%) 9_BA 0 (0.0%) 0 (0.0%) 9_RM 3 (1.9%) 12 (0.2%) 9_CO 17 (10.6%) 349 (5.3%) 9_ES 0 (0.0%) 0 (0.0%) The vast majority of NVC communities with no association with groundwater that occur in areas predicted as being highly dependent on groundwater tend to be associated with slopes (hydrogeomorphic categories: 1_Slope, 4_Slope and 7_Slope) (Table 9). Whilst 31

40 highly groundwater dependent communities, such as M14 Scheonus nigricans- Narthecium ossifragum mire, do occur on slopes, not all slopes support highly groundwater dependent communities. However, small flushes and seeps are often highly common but are under-recorded habitats. If seeps and flushes occurred in areas under pasture or more intensive management it is possible that an alternative vegetation community, more closely associated with management, may be recorded. Table 9 Occurrence of false negatives by HGM unit. HGM Unit Number (and %) of validation points that are predicted as high groundwater dependency Number (and %) of points with this HGM in the full dataset 1_Slope 149 (8.7%) 410 (6.2%) 1_EP 1 (0.1%) 1 (0.0%) 1_BA 3 (0.2%) 4 (0.1%) 1_RM 8 (0.5%) 22 (0.3%) 1_CO 6 (0.4%) 16 (0.2%) 1_ES 0 (0.0%) 0 (0.0%) 4_Slope 32 (1.9%) 52 (0.8%) 4_EP 1 (0.1%) 1 (0.0%) 4_BA 1 (0.1%) 2 (0.0%) 4_RM 7 (0.4%) 19 (0.3%) 4_CO 2 (0.1%) 3 (0.0%) 4_ES 0 (0.0%) 0 (0.0%) 7_Slope 1426 (86.6%) 3168 (48.3%) 7_EP 21 (1.2%) 45 (0.7%) 7_BA 0 (0.0%) 0 (0.0%) 7_RM 42 (2.5%) 74 (1.1%) 7_CO 6 (0.4) 12 (0.2%) 7_ES 1 (0.1%) 1 (0.0%) Further analysis has been conducted through an assessment by area of wetland and non-wetland hydrogeomorphic units. Using the digitised NVC data from the SNH designated sites, comparisons have been made based on area (Table 10). These are descriptive rather than rigorously statistical, however, they provide an indication of the extent of different hydrogeomorphic units in Scotland and their association with wetland vegetation communities. All polygons less than 0.01ha were excluded from analysis to eliminate artefacts of data processing. This analysis assumes a priori knowledge that some sort of wetland is present or not. To achieve this each of the NVC communities present within the SNH dataset were classified as wetland or non-wetland. This was described through a review of published information including Rodwell (1998a, 1998b, 1998c, 2000a, 2000b), Wheeler et al. (2004), Lindsay (1995) and JNCC (2004). For each NVC community information was sought on the habitat description, the altitude and climate, the soils and the amount of organic or humic material, the underlying geology, the degree of waterlogging, the presence of surface water, any hydrological mechanisms or associations and any features unique to the occurrence of the vegetation community in Scotland. Where sub- 32

41 communities were described these were assigned to the code of the main NVC community. The full list of wetland NVC communities used in this analysis are presented in Appendix IV. All other NVC communities were considered to be non-wetland. Table 10 Relationship between hydrogeomorphic unit and wetland or nonwetland NVC communities. HGM Unit Total area for HGM Unit (ha) Total area for 'wetland' NVC communities covered by HGM Unit (ha) Total area for 'nonwetland' NVC communities covered by HGM Unit (ha) % of HGM Unit accounted for by 'wetland' NVC Wetland HGM Unit 1_EP > 90% 2_EP % 3_EP < 75% 4_EP No data 5_EP _EP _EP _EP _EP _BA _BA _BA _BA _BA _BA _BA _BA _BA _RM _RM _RM _RM _RM _RM _RM _RM _RM _Slope _Slope _Slope _Slope _Slope _Slope _Slope _Slope _Slope

42 HGM Unit Total area for HGM Unit (ha) Total area for 'wetland' NVC communities covered by HGM Unit (ha) Total area for 'nonwetland' NVC communities covered by HGM Unit (ha) % of HGM Unit accounted for by 'wetland' NVC Wetland HGM Unit 1_CO > 90% 2_CO % 3_CO < 75% 4_CO No data 5_CO _CO _CO _CO _CO _ES _ES _ES _ES _ES _ES _ES _ES _ES The traffic light system displayed in Table 10 indicates green where an hydrogeomorphic unit shows more than a 90% correlation with wetland NVC communities. Amber shows hydrogeomorphic units which account for between 90 and 75% and red shows where correlation is less than 75%. Some relatively clear patterns emerge from this simple analysis. Unsurprisingly, six of the nine extensive peatland (EP) hydrogeomorphic units are closely related to wetland NVC communities (1_EP, 5_EP, 6_EP, 7_EP, 8_EP and 9_EP), of which the majority are mire communities. Over 84% of the other three extensive peatland HGM units (2_EP, 3_EP and 4_EP) are accounted for by wetland NVC communities. This would suggest that, at a descriptive level, the extensive peatland hydrogeomorphic units show a good correlation with wetland NVC communities and hence could be used as a surrogate for identifying wetland areas in the landscape. The picture is not as clear for the other five geomorphic settings. The basin units show varied results. One category (2_BA) is not accounted for in the SNH NVC dataset. 3_BA, 6_BA and 9_BA show a strong correlation with wetland NVC communities (99.4%, 98.9% and 96.1% respectively). However, the remaining hydrogeomorphic units are weakly correlated with wetland NVC communities or are not represented. The basin units account for a relatively limited area and are defined primarily by the presence of a lake or lacustrine drift deposits. Much of the NVC mapping does not extend into open water areas, therefore, the majority of the basin areas are not represented by NVC communities. The NVC communities tend to represent more marginal or mixed wetland and nonwetland communities within a larger basin area. Based on this descriptive analysis, the majority of basin hydrogeomorphic units represent poor surrogates for defining wetland areas. 34

43 The results are similar for river marginal hydrogeomorphic units with no distinct pattern emerging. 2_RM, 3_RM, 5_RM, 6_RM and 9_RM all demonstrate a strong association with wetland NVC communities. Of these, HGM units 2_RM and 5_RM are of limited geographic extent. The majority of the river marginal areas are accounted for by 7_RM which supports 82.3% wetland NVC communities. Given the expected relationship between fluvial water sources and river marginal hydrogeomorphic units it is surprising that the most extensive hydrogeomorphic unit is characterised by high groundwater and low surface water dependency. A possible explanation for this could be the maintenance of high water levels in shallow drift aquifers and the limited extent of predicted overbank inundation. The slope hydrogeomorphic units are the most extensive in Scotland. This is not surprising given that Slope could be considered the background default for all areas which are not distinct geomorphic features. Because of the extensive nature of the slope hydrogeomorphic units they are associated with a wide variety of NVC communities. Slope hydrogeomorphic units only appear strongly associated with wetland NVC communities within 6_Slope and 9_Slope. Both of these hydrogeomorphic units are characterised by low groundwater dependency and moderate to low surface water dependency respectively. Given that over 60% of the area of slope hydrogeomorphic units supports mire vegetation communities (in total more than 60% of the total area of slope hydrogeomorphic units supports mire communities) it is possible that the high degree of association with wetland NVC communities is due to extensive areas of ombrogenous mires, such as M17-Scirpus cespitosus-eriophorum vaginatum blanket mire, M18-Erica tetralix-sphagnum papillosum raised and blanket mire, M19-Calluna vulgaris-eriophoroum vaginatum blanket mire and M20-Eriophoroum vaginatum blanket and raised mire. However, closer examination of this indicates that ombrogenous mire systems only account for 8.5% of the land area associated with wetland NVC communities carried by 6_Slope and 9_Slope. This suggests that a variety of wetland communities occur in association with these two slope hydrogeomorphic units and their use as surrogates for wetland identification may be limited. The majority of coastal hydrogeomorphic units are strongly associated with wetland NVC communities. Only 1_CO, 2_CO and 4_CO demonstrate a weak association. However, 9_CO accounts for over 80% of the total coastal geomorphic area. Of this area, 75% of the wetland NVC communities are represented by five ombrogenous mire communities: M1-Sphagnum auriculatum bog pool community, M2-Sphagnum cuspidatum bog pool community, M17-Scirpus cespitosus-eriophorum vaginatum blanket mire, M18-Erica tetralix-sphagnum papillosum raised and blanket mire and M19-Calluna vulgaris- Eriophoroum vaginatum blanket mire. Indicating that 9_CO may be a good predictor of rain fed wetland systems in the coastal areas of Scotland. The estuarine geomorphic unit covers a limited area. This is a result of seaward limitations placed on the dataset in order to exclude permanently flooded tidal areas and to focus on the tidally inundated marginal areas. Over 60% of the estuarine hydrogeomorphic units comprise 6_ES, indicating a low predicted groundwater dependency and a moderate dependency on surface water. Over 65% of 6_ES comprises three swamp and tall-herb fen communities: S4-Phragmites australis swamp, S5-Glyceria maxima swamp and S28- Phalaris arundinacea tall-herb fen commonly associated with surface inundation from surface waters. It is possible that the importance of surface water, and possibly tidal input, is being underestimated in the estuarine environment for these wetland NVC communities. 35

44 4.5.4 Summary of validation The following key points summarise the validation exercise and help to inform applications available for the hydrogeomorphic classification of Scottish wetlands. NVC data are not perfect proxies for defining both water dependency and the presence or absence of a wetland. The validation process is strongly skewed towards the use of mire community information with greater than 95% of the validation points being represented by mires. Correlations (both Spearman s and Chi-square) yield highly significant results indicating a positive association between expected and predicted NVC groundwater dependence. The prediction of groundwater dependency tends to predict as either high or low rather than medium. There is a high degree (>80%) of agreement for predicting high groundwater dependence in relation to high NVC groundwater dependency. There is a much lower degree (~50%) of agreement for predicting low groundwater dependence in relation to low NVC groundwater dependency. False negatives exist in approximately 22% of cases where low predicted groundwater dependence occurs in association with high NVC groundwater dependence. False positives also exist in approximately 48% of cases where high predicted groundwater dependence occurs in association with low NVC groundwater dependence. Extensive peatland hydrogeomorphic units provide, unsurprisingly, the best surrogates for defining potential wetland areas. A variety of hydrogeomorphic units demonstrate a strong association with wetland NVC communities. The following hydrogeomorphic units have a strong spatial (>90%) correlation with wetland NVC communities: BA EP ES Slope RM CO 3_BA 1_EP 6_ES 6_Slope 2_RM 3_CO 6_BA 5_EP 9_ES 9_Slope 3_RM 5_CO 9_BA 6_EP 5_RM 6_CO 7_EP 6_RM 7_CO 8_EP 9_RM 8_CO 9_EP 9_CO Whilst the analysis suggests that these relationships may be real and, therefore, their value as surrogates high, it is recommended that field testing is undertaken to provide an independent verification. The validation has focussed on groundwater dependency due to limited information on clear surface dependency associated with NVC communities. 4.6 Application of the wetland hydrogeomorphic classification GIS for Scotland Water dependent features A set of criteria have already been developed by the UKTAG on the WFD to identify water dependent habitats and species for Natura 2000 sites. In Scotland SNH has produced a list of SSSIs notified for water dependent features. In order to maintain consistency in identifying water dependent features the same method was used to identify water dependent SSSI features as for Natura 2000 sites. Each feature for which SSSIs have 36

45 been notified has been categorised into a water dependency class (1, 2, 3, 9, 99) listed in Table 7 (excluding earth science features). Where it has not been possible to make a decision on whether a feature is water dependent it was assigned to category 99. This is mostly relevant to sites notified for groups of invertebrates for which more information should become available as further Site Condition Monitoring work progresses and it is hoped that there will be progressively fewer sites assigned to category 99. The decision as to which water dependency category a feature should be placed was made based on information from the following sources: Natura water dependent species and habitats (from the UKTAG); BAP water dependent habitats and species based on research and BAP water and wetland habitats and species report; Consultation with relevant specialists (sub set of features); NBN Checklists from the species dictionary; Searches of species dossiers, species guides etc.; and Where there was any doubt, the lists were referred to SNH s specialist staff for clarification. Table 11 SNH criteria for water dependency. Category Species Habitats 1 Aquatic species (e.g. fish, cetaceans, pearl mussel) Habitats which consist of water as defined in WFD 2.2. and (e.g. oligotrophic waters, estuaries, and eelgrass beds) 2 Species with at least one aquatic life stage (breeding, incubation, juvenile development, sexual maturation, feeding or roosting e.g. many birds or invertebrates) 3 Species that rely on non-aquatic but water-dependent habitats e.g. Killarney Fern see 2 or 3 in Habitats column Habitats which rely on frequent inundation or saturation from surface waters, or a supply of groundwater (alluvial alder wood, blanket bog, fens) should this include Machair which is seasonally water logged Non-aquatic habitats which rely on a direct influence of water e.g. spray, humidity (bryophyte-rich gorges) 9 All other species - not water dependent All other habitats - not water dependent 99 Insufficient information Insufficient information Within this project, this approach has been extended to all Ramsar and Natura 2000 sites. This has been based on a literature review and expert opinion. All water dependent species and habitats listed for Scottish Ramsar and Natura 2000 have been assigned a water dependency category (1, 2, 3, 9 or 99) as defined in Table 7. This information has been provided in electronic format with the GIS. Within a GIS it is possible to select any SSSI, Ramsar or Natura 2000 site and assess whether it supports a water dependent feature. Whilst this is vitally important information 37

46 within a regulatory context, the presence of a water dependent feature does not define the presence of a wetland. For instance, certain wetland birds may breed on sites which do not possess wetland characteristics. Similarly, the presence of wetland habitats within a designated site is not evidence that the entire site is a wetland. Therefore, information on water dependent features can be used as a verifier, but not as a definer of presence or absence of wetland Wetland classification and inventory No inventory of Scottish wetlands exists. A primary objective of this project has been to develop an inventory of Scottish wetlands and to define dependence on surface or groundwater bodies. In the absence of a definitive inventory it is necessary to generate data, or surrogate information, which can predict where wetlands may exist in the landscape. The hydrogeomorphic approach has yielded variable results. Overall the information generated shows, on the surface, a strong degree of correlation, especially for wetlands dependent on groundwater bodies. However, the accuracy of the hydrogeomorphic data is variable. The results allow a degree of narrowing down for regulatory application and for determining dependence on a surface or groundwater body. However, any application needs to be aware of the variability of the predicted outcomes and assess any regulatory decision against this. Certain hydrogeomorphic units allow the prediction of the presence or absence of wetland areas within the Scottish landscapes to a relatively high level of confidence. It is possible to map these hydrogeomorphic units and generate an inventory of areas within the Scottish landscape with high potential to support wetlands. These areas can be assessed in relation to their dependent water bodies. In the absence of primary information on the location, type and hydrological functioning of wetlands in Scotland, this project delivers the initial framework on which to build a more detailed inventory. The hydrogeomorphic approach provides a logical framework within which to understand how wetlands behave and their associated water dependency. Further validation and field based verification will improve the confidence and accuracy of the data held within the GIS. 38

47 5 PRIORITISED WORKPLAN 5.1 Introduction A key objective of this study is to develop a prioritised plan for future work covering aspects not included in the work delivered through this project. This project represents the initial phases of the inventory process. Whilst the outputs can deliver on a variety of issues they still need further refinement, validation and development. This requires a prioritised workplan to support its completion. 5.2 Task identification A register of queries and suggestions has been maintained for the duration of the project. Every time an issue has been raised, for instance regarding availability of data, understanding of relationships, future application, etc, a comment has been added to the register. This has produced a variety of eclectic tasks across a range of disciplines. The contents of the register have been reviewed and have been classified into work areas. Each work area has been given a priority. The priorities do not, however, take into account every potential end use of an inventory. Therefore, it is possible that the project steering group may wish to evaluate the priorities against their own criteria of need. Similarly, issues such as internal training and familiarisation have been excluded. The focus, and hence the prioritisation, has been on improving the quality and accuracy of the output in terms of defining water body dependency. 5.3 Prioritisation of tasks The tasks recorded in the register can be divided into two main categories: Verification The need to check and validate assumptions made in the hydrogeomorphic classification; and Data supplementation The need to supplement existing data to improve the accuracy of the outputs from the hydrogeomorphic classification. Between these two categories there is a feedback loop: verification identifies issues and data needs, data supplementation is then required, supplementary data is added, verification of new data identifies issues and data needs, etc. Therefore the future workplan should be seen as an evolving process, rather than a finite set of tasks. The actual tasks can be divided into two further categories: Field based The need to visit sites and either collect data for verification purposes or for data supplementation purposes; and Desk based The need to acquire and add further data sources, or the need to model existing or future data. The workplan is set out in Table 12. Each task has been categorised according to the categories defined above. A priority has been assigned to each task based on the following: High (H) High priority to understand better the accuracy of the assumptions made in the hydrogeomorphic classification and to improve the quality of the outputs. Low (L) Low priority to add value and to develop further the potential of the hydrogeomorphic classification to understand wetland functional issues. 39

48 Table 12 Prioritised workplan. Verification Field based Ground-truthing of water dependency relationships in designated sites (H) Ground-truthing of water dependency relationships in non-designated sites (H) Ground-truthing of potential and actual pressures (H) Data supplementation Completion of NVC mapping for all designated sites in Scotland (H) Mapping of sea spray extent (L) Classification of land adjacent to streams and rivers in terms of depth, duration and frequency of overbank inundation (H) Desk based Ground-truthing of geomorphic settings (L) Critical evaluation of the assumptions adopted in deriving the datasets (H) Evaluation of water dependency relationships based with site-specific empirical data (H) Evaluation of soils data at a local level to assess value of integrating a national soil dataset (H) Pan-Scotland verification of all protected sites against known NVC classes (H) Evaluation of the use of aerial photographs to validate outputs from classification (L) Evaluation of potential and actual pressures (H) Multivariate analysis / principal component analysis of NVC and water body dependency classes (H) Evaluation of cross-border compatibility of approach (L) Critical evaluation of the approach taken within the classification through comparison with other approaches to implementing the WFD in Europe (L) Evaluation of functional assessment potential of the classification to understand better the role wetlands play in providing ecosystem services such as attenuating flooding, removing nutrients, etc. (L) Integration of soils data at a local level (H) Integration of soils data at a national level, such as the Scottish Soils Database (H) Integration of hydrochemical datasets to improve understanding of water dependency and to assess better risk of pressures (H) Digitisation and integration of NVC data for all designated sites in Scotland (H) Integration of a water table data layer which defines mean summer and winter water levels in relation to depth below ground surface (H) Evaluation of other data sets which could be used to improve accuracy of geomorphic settings (L) Improved understanding of surface water sources by developing further derived data sets through simple hydrological modelling (H) Integrate climatic information to refine understanding of the balance between surface water, groundwater and precipitation (L) Attempt to quantify water source dependency relationships through a development of a simple water balance model (L) Provide a mechanism to allow original, and hence derived, datasets to be updated (L) 40

49 5.4 Example of further work One of the tasks identified early on in the development of the hydrogeomorphic classification was the lack of information on surface water pathways, especially for first order streams in the upper catchment. Many of these do not appear on datasets provided. Often these small streams are important as water sources for downstream wetlands. Similarly, they can be an important component in the gradation from precipitation (ombrogenous) dominated wetland systems. Failure to recognize them could result in a misunderstanding of surface water dependency and may be undermining the designation of water dependency classes as discussed above. The development of the Scottish wetland hydrogeomorphic classification within a GIS allows a range of opportunities to refine the derived datasets. Modelling of data using ESRI software, such as Spatial Analyst or 3D Analyst, in conjunction with readily available hydrological models may represent a simple method to improve the accuracy of the surface water dependency relationships. This issue has been defined in the Improved understanding of surface water sources by developing further derived data sets through simple hydrological modelling task in Table 12. In an attempt to evaluate the practicality and value of this approach, a GIS based method to assist in defining potential wetlands through the identification of surface water pathways was investigated. The approach effectively defines a stream network based on the surface topography of the digital terrain model (DTM). If the area where this method is applied is completely impermeable then the surface water pathways should replicate the surface water drainage network. If, however, the area has a permeable geology then the surface water pathways would show the paths that surface water would take if the water table was at the surface. It is likely, therefore, that in permeable areas with a fluctuating water table, wetlands would form along those areas where water may flow for some part of the year, so in this sense the surface water pathways can act as a guide to the potential location of wetlands. Two routines were attempted to define the surface water pathways. One is the in-built hydrological routine within the Arc GIS Spatial Analyst extension, given the name Grid Stream for this study; the other is the topographic index used in the hydrological process model, TOPMODEL (Beven and Kirkby, 1979). The first of these approaches, Grid Stream, defines the flow direction of each cell in a DTM and then the flow accumulation, that is the number of upstream cells which flow into each cell. A threshold flow accumulation value is then selected to identify stream cells depending on the cell resolution and size of the study area. For this study this was taken to be 100 cells following test runs with various threshold values. All cells above the threshold value then represent drainage pathways. The TOPMODEL index (I) is defined by the equation: I = ln(a/tan B) Where A is the upstream contributing area (i.e. the flow accumulation) and B is the cell slope in degrees. The index describes the tendency of the water to accumulate (A) and move downslope (B). For steep slopes at the edge of the catchment, A is small and B is large, giving a small value for the index. High index values are found in valley bottoms with a large contributing area and small slope. Once calculated, a threshold value of the index was selected (a value of 4 was used) to identify those cells which are likely to promote surface runoff. As with the Grid Stream routine, the threshold values were taken 41

50 after testing a number of different values. The index is not a strict definition of the drainage pathways but rather a more probabilistic measurement that surface runoff will take place at these locations. This is the major difference between the TOPMODEL index and Grid Stream. Both techniques were applied to the 50m DTM provided for the study, clipped to the Clyde catchment boundary. Extracts from the derived grids are shown in Figures 4 and 5 with the OS basemap as a background layer to validate the effectiveness of each method for reproducing the drainage pathways. Figure 4 Example Grid Stream output. The results show that the Grid Stream method produces a drainage network which is very similar to the main streams and rivers on the OS 1:50,000 basemap. An even closer fit could be achieved either through using a smaller grid cell size for the DTM or assuming a lower number of contributing cells for the threshold value. The TOPMODEL index method produces a more scattered output and the river channels are not so well represented, often being discontinuous. The channels themselves are not reproduced by the index since, once water is flowing, it may take a path over steep cells which have a low index value. Some detailed TOPMODEL studies have used methods to remove all channel cells from the analysis and just considered those cells which generate surface runoff (e.g. Günter et al, 1999). There are, however, a number of cells with a high TOPMODEL index which are some distance from the stream channels. Ground-truthing in these cells would assist in determining whether they do actually generate surface water dependent wetlands. 42

51 Figure 5 Example TOPMODEL output. This simple modeling approach demonstrated that additional derived data can be generated to assist in understanding water sources. The Grid Stream and TOPMODEL index can both be used at the catchment scale for identifying areas of surface water, either as actual drainage pathways (Grid Stream) or as cells which have the potential to generate surface runoff (TOPMODEL). The techniques need to be validated using ground-truthed or desk-based data. However, with the TOPMODEL index in particular, a more rigorous validation could be undertaken using the mapped SSSI NVC information and field evidence. 43

52 44

53 6 REFERENCES Beven, K. J. and Kirkby, M. J. (1979) A physically based, variable contributing area model of basin hydrology. Hydrol. Sci. Bull Brinson, M.M. (1993) A Hydrogeomorphic Classification for Wetlands. Technical Report WRP-DE-4. U.S. Army Corps of Engineers. Brinson, M.M., Hauer, F.R., Lee, L.C., Nutter, W.L., Rheinhardt, R.D., Smith, R.D. and Whigham, D.(1995) Guidebook for application of hydrogeomorphic assessments to riverine wetlands. Technical Report TR-WRP-DE-11, Waterways Experiment Station, Army Corps of Engineers, Vicksburg, MS. Canadian National Wetlands Working Group (1988) Wetlands of Canada, Ecological Land Classification Series, No. 24, Environment Canada, Ottawa, Ontario. Canadian National Wetlands Working Group, (1997) The Canadian Wetland Classification System. Ed. B.G. Warner and C.D.A. Rubec. Wetlands Research Centre, University of Waterloo, Waterloo, Ontario. Cole, C.A. (2006) HGM and wetland functional assessment: Six degrees of separation from the data? Ecol. Indicators. 6: COMHAR (2004) Recommendations on the Implementation and Review of the National Biodiversity Plan. Report from The National Sustainable Development Partnership. Dublin, Ireland. Costa, L.T., Farinha, J.C., Tomas-Vives, P., Hecker, N. and Silva, E.P. (2001). Regional wetland inventory approaches the Mediterranean example. In Wetland inventory, assessment and monitoring - Practical techniques and identification of major issues: Introduction and review of past recommendations, eds. Finlayson, C.M., Davidson, N.C. and Stevenson N.J. Supervising Scientist Report 161, Supervising Scientist Division, Environment Australia, Darwin, Australia. pp Davidson, N.C. (1999). Wetlands and biodiversity. Creation of global assessment tools for conservation, status, needs and priorities. BCIS/NORAD. Wetland pilot project. Phase I progress report, February 1999, unpublished report, Wetlands International, Wageningen, The Netherlands. Finlayson, C.M. and Davidson, N.C. (2001) Wetland inventory, assessment and monitoring Practical techniques and identification of major issues: Introduction and review of past recommendations. In Finlayson, C.M., Davidson, N.C. and Stevenson, N.J. (eds) (2001) Wetland inventory, assessment and monitoring: Practical techniques and identification of major issues. Proceedings of Workshop 4, 2nd International Conference on Wetlands and Development, Dakar, Senegal, 8 14 November 1998, Supervising Scientist Report 161, Supervising Scientist, Darwin. pp Finlayson, C.M., Davidson, N.C. and Stevenson N.J. (2001) Wetland inventory, assessment and monitoring Practical techniques and identification of major issues: Summary. In Finlayson, C.M., Davidson, N.C. and Stevenson, N.J. (eds) (2001) Wetland inventory, assessment and monitoring: Practical techniques and identification of major issues. Proceedings of Workshop 4, 2nd International Conference on Wetlands and Development, Dakar, Senegal, 8 14 November 1998, Supervising Scientist Report 161, Supervising Scientist, Darwin. pp

54 Finlayson, NC Davidson and NJ Stevenson (eds) (2001) Wetland inventory, assessment and monitoring: Practical techniques and identification of major issues. Proceedings of Workshop 4, 2nd International Conference on Wetlands and Development, Dakar, Senegal, Finlayson, C.M., Davidson, N.C., Spiers, A.G. and Stevenson, N.J. (1999) Global wetland inventory Status and priorities. Marine and Freshwater Research 50, Finlayson, C.M., Howes, J., Van Dam, R., Begg, G. and Tagi, K. (2002) The Asian Wetland Inventory as a tool for providing information on the effect of climate change on wetlands in Asia. Workshop on climate change and wetlands, Kushiro, Japan, September Finlayson, C.M. and Spiers, A.G. (eds) (1999) Global review of wetland resources and priorities for wetland inventory. Supervising Scientist Report 144, Supervising Scientist Group, Environment Australia, Canberra. Fuller, R.M., Smith, G.M., Sanderson, J.M., Hill R.A., Thomson, A.G., Cox, R., Brown, N.J., Clarke, R.T., Rothery, P. and Gerard, F.F. (2002) Land cover map 2000: A guide to the classification system. Centre for Ecology and Hydrology. Project. T02083j5/C Draft unpublished report. Gilvear, D.J. and McInnes, R.J. (1994) Wetland hydrological vulnerability and the use of classification procedures: a Scottish Case study. Jn. Env. Man. 42, Gilvear, D.J., Tellam, J.H., Lloyd, J.W. and lerner, D.N. (1989) The hydrodynamics of East Anglian fen systems, Unpublished final report to Nature Conservancy, National River Authority and Broads Authority. Goode, D. (1977) Peatlands, A Nature Conservation Review, Vol. 1, Ratcliffe, D.A. (ed), Cambridge University Press, pp Gosselink, J.G. and Turner, R.E. (1978) The role of hydrology in freshwater wetland ecosystems, In: Good, R.E., Whigham, D.F. and Simpson, R.L. (eds), Freshwater Wetlands, Ecological Processes and Management Potential, Academic Press, New York, pp Günter, A., Uhlenbrook, S., Leibundgut, C., and Seibert, J. (1999) Estimation of saturation excess overland flow areas: comparison of topographic index calculations with field mapping. In Diekkrüger, B., Kirkby, M.J. and Schröder, U. (Eds.) Regionalization in Hydrology, IAHS Publication no. 254, Wallingford, UK. Hauer R.F., Cook, B.J., Gilbert, M.C., Clairain E.C. and Smith, R.D. (2000) A Regional Guidebook for Assessing the Functions of Intermontane Prairie Pothole Wetlands in the Northern Rocky Mountains. The University of Montana and U.S. Army Corps of Engineers. Hollands, G.G., (1987) Hydrogeologic classification of wetlands in glaciated regions. In: Kusler, J. (Ed), Wetland Hydrology, Proceedings from a national wetland symposium, Association of State Wetland Managers, Inc., Berne, New York, pp Hughes,J.M.R. (1995) The current status of European wetland inventories and classifications. Vegetatio. 118,

55 JNCC (2004) Common standards monitoring guidance for lowland wetland habitats. JNCC. Peterborough. Kieselev, P.A. (1975) Study of the water balance of stratified aquifers based on the analysis of their regime during hydrogeological investigations of marshy lands and adjacent areas, In: Proceedings of Minsk Symposium, Hydrology of Marsh-ridden Areas, pp UNESCO, IAHS. Lindsay, R. (1995) Bogs: The Ecology, Classification and Conversation of Ombrotrophic Mires. Scottish Natural Heritage, Perth. Lloyd, J.W., Tellam, J.H., Rukin, N. and Lerner, D.N. (1993) Wetland vulnerability in East Anglia: a possible conceptual framework and generalised approach, J. Env. Management 37, pp MacKenzie, W.H. and Moran, J.R. (2004). Wetlands of British Columbia: a guide to identification. British Columbia Ministry of Forests, Victoria. Malcolm, R. and Soulsby, C. (2001) Hydrogeochemistry of groundwater in coastal wetlands: implications for coastal conservation in Scotland. Sci. Total Environ. 265(1-3): Maltby, E., Hogan, V. and McInnes, R.J. (1996) Functional analysis of European wetland ecosystems Phase 1 (FAEWE). EUR 16132, European Commission, Luxembourg. Maltby, E. & McInnes, R.J. (1997) Functions and Degradation of Wetlands. In Brune, E., Chapman, D., Gwynne, M.D. & Pacyna, J.M. (eds) The Global Environmental: Science, Technology and Management. Vol. I. VCH, Weinheim Maltby, E., Sgouridis, F., Négrel, P. and Petelet-Giraud, E. (2005). EUROWET, Integration of European wetland research in sustainable management of the water cycle. Technical guidance. European Union. McInnes, R. J. (1991) A Classification of Scottish Wetlands. Unpublished MSc Thesis, University of Stirling. Millenium Ecosystem Assessment (2005) Ecosystems and Human Well-being: Wetlands and Water Synthesis. World Resources Institute, Washington, DC. Mitsch, W.J. and Gosselink, J.G. (1993) Wetlands. Van Nostrand Reinhold, New York, USA. Newbold, C. and Mountford, J.O. (1997) Water Level Requirements of Wetland Plants and Animals. No. 5. English Nature Freshwater Series. English Nature, Peterborough. Nivet, C. and Frazier, S. (2001) A review of European wetland inventory information. Preliminary (incomplete) report prepared in the framework of A Pilot Study towards a Pan-European Wetland Inventory, a cooperative project between Wetlands International Africa, Europe, Middle East and the Dutch Institute for Inland Water Management and Waste Water Treatment (RIZA). Novitzki, R.P. (1979) Hydrological characteristics of Wisconsin s wetlands and their influence on floods, stream flow and sediment, In: Greeson, P.E., Clark, J.R. and Clark, 47

56 J.E. (eds), Wetland Functions and Values: the state of our understanding, Am. Water Res. Ass., Minneapolis, U.S.A. pp Rodwell, J.S. (Ed) (1998a) British Plant Communities: Volume 1: Woodlands and scrub, Cambridge University Press. Rodwell, J.S. (Ed) (1998b) British Plant Communities: Volume 2: Mires and heath, Cambridge University Press. Rodwell, J.S. (Ed) (1998c) British Plant Communities: Volume 3: Grasslands and montane communities, Cambridge University Press. Rodwell, J.S. (Ed) (2000a) British Plant Communities: Volume 4: Aquatic communities, swamps and tall-herb fens, Cambridge University Press. Rodwell, J.S. (Ed) (2000b) British Plant Communities: Volume 5: Maritime communities and vegetation of open habitats, Cambridge University Press Scott, D. A. and Jones, T.A. (1995) Classification and inventory of wetlands: A global overview. Vegetatio. 118, Scottish Executive. (2006) Implementation of the Water Environment and Water Services (Scotland) Act 2003 Annual Report to the Scottish Parliament Scottish Executive, Edinburgh. Semeniuk, C.A. and Semeniuk, V. (1995) A geomorphic approach to global classification for inland wetlands. Vegetatio. 118, Simpson, M.R. (2002) A Functional Classification of European Wetlands. Unpublished PhD Thesis, Royal Holloway, University of London. Smith, R.D., Amman, A., Bartoldus, C., and Brinson, M.M. (1995) An Approach for Assessing Wetland Functions Based on Hydrogeomorphic Classification, Reference Wetlands, and Functional Indices. US Army Engineer Waterways Experiment Station, Wetland Research Program Technical Report. SNIFFER (2004) Development of a groundwater vulnerability screening methodology for the Water Framework Directive. Final Report Project WFD28. SNIFFER, Edinburgh. Wheeler, B.D. (1984) British fens: a review. In: Moore, P.D. (ed), European Mires, Academic Press, London, pp Wheeler, B.D. (1994) Towards a hydrotopographical classification of British Wetlands, Draft discussion document, Department of Animal and Plant Sciences, University of Sheffield, U. K. Wheeler, B.D., Gowing, D. J.G., Shaw, S.C., Mountford, J.O. and Money, R. P. (2004) Ecohydrological Guidelines for Lowland Wetland Plant Communities. (Eds. A.W. Brooks, P.V. José and M.I. Whiteman). Environment Agency (Anglian Region). Wheeler, B.D. and Shaw, S.C. (2000) A wetland framework for impact assessment of statutory sites in eastern England. R&D technical report W6-068/TR1. Environment Agency 48

57 Appendix I Hydrogeomorphic classification of Scottish Wetlands Users Manual 49

58 HYDROGEOMORPHIC CLASSIFICATION OF SCOTTISH WETLANDS USERS MANUAL Introduction The hydrogeomorphic classification of Scottish wetlands has many potential uses. It can be used to define, for any area, the potential water source and consequently the water body dependency. In can be applied in a regulatory framework to assist with the assessment of potential impacts, or it could be used to understand better the hydrological drivers behind ecological functioning at a site. In order to use the classification, a basic level of knowledge of GIS is required. To assist users in understanding some of the potential applications of the classification, a summary of uses are described in simple steps below. The wetland hydrogeomorphic classification is intended to be an evolving tool to assist in the understanding and protection of Scotland s important wetland resource. In order to develop further the tool it is necessary to update existing original and derived datasets and to evaluate, and indeed re-evaluate, the assumptions in the derived datasets. To achieve this, a description of data layers used within the GIS is provided in Appendix II. Scenarios for use The potential uses of the classification are complex and many. Seven simple scenarios are presented to explain some of the outputs available from the GIS. The scenarios are divided into simple Steps. Many of these steps are universal, irrespective of the use. The universal activities are described below. Universal activities Add data: click on the + button in the toolbar to open the Add Data window. Locate the required data from the appropriate file and click ADD. Click on the box next to the layer name in the contents table to display a tick (if not already ticked). See Scenario 1: step 1 below for an example of the procedure for displaying a specific data layer. Display information about an area: click on the site for interrogation using the Identify (i) tool in the toolbar, to display the attributes table for the area. Remove unwanted categories: Open the Symbology field in the Layer Properties window for the selected data layer. Click on the appropriate category and then on the Remove tab. Re-order categories: Open the Symbology field in the Layer Properties window for the selected data layer. Select a category and use the arrows on the right-hand side of the window to move it up or down the list as required. Change category fill colours: Open the Symbology field in the Layer Properties window for the selected data layer. Select an appropriate colour scheme from the Colour Ramp drop down box, OR double-click on each category separately and select appropriate fill colours. Remove category outlines: To remove all outlines double-click on the all other values category and set the Outline Width to zero. 50

59 Example area The following map shows a 1:50,000 area from the Upper Clyde Catchment, which was chosen as a useful example for the following scenarios, given the presence of four SSSIs (see below for site names) and the variety of different hydrogeomorphic units and water body dependency classes within the area. Cranley Moss Carstairs Kames Carnwath Moss Cleghorn Glen River Clyde Meanders Description of scenarios Scenario 1: Define water body dependency for a designated SSSI wetland site Rationale: A user wants to know whether a wetland, or part of a wetland, SSSI is dependent on a water body. Step 1: In the contents table, double click on data layer SNF01.copy to open the Layer Properties window. In the Symbology field, select data layer Class (water body dependency layer) from the drop down box under Value Field. 51

60 Step 2: Click on the Add All Values tab to display the water body dependency categories. To remove unwanted categories, re-order categories, change category colours and remove outlines, follow the procedures outlined above. 52

61 Step 3: Click on Apply and then OK to close the Layer Properties window and display the water body dependency data layer. 53

62 Step 4: Display the SSSI data layer. 54

63 Step 5: Identify a SSSI for interrogation. Either: (a) click within the SSSI using the i tool to generate an attributes table displaying the SSSI information. Use the zoom in tool in the toolbar to zoom to the appropriate SSSI. OR (b) to find a particular SSSI, right-click on the SSSI layer in the contents table and select open attributes table. Select the SITE NAME field. From the options tab select find and replace and type in the required site name. Click Find Next to locate the site in the table. Click on the left hand box on the row for the required SSSI (this will contain the symbol ) to highlight the row. Close the attributes table. Right-click on the SSSI layer in the contents table and select Selection, then Zoom to Selected Features. The selected SSSI will appear on the map. 55

64 (a) (b) 56

65 Step 6: Click on the area for interrogation using the i tool to generate an attributes table for the area. From the Layers drop down box select the WFD66 data layer to display information on the water body dependency of the area. Final output: The water dependency class (Class) will be exhibited in the attribute table, along with the SEPA water body identification codes and the surface and groundwater catchments, this will define the likelihood of dependency on a water body. 57

66 Scenario 2: Understanding surface water body dependency for a designated SSSI wetland site Rationale: A user wants to know whether a wetland, or part of a wetland, SSSI is dependent on a surface water body. Step 1: In the contents table, double click on data layer SNF01.copy to open the Layer Properties window. In the Symbology field, select surface water dependency data layer (SW_Dep) from the drop down box under Value Field. See Scenario 1: step 1 for example of procedure. Step 2: Click on the Add All Values tab to display the surface water dependency categories. To remove unwanted categories, re-order categories, change category colours and remove outlines, follow the procedures outlined above. See Scenario 1: step 2 for example of output. Step 3: Click on Apply and then OK to close the Layer Properties window and display the surface water dependency data layer. See Scenario 1: step 3 for example of output. Step 4: Step 5: Display the SSSI data layer. Identify a SSSI for interrogation. Either: (a) click within the SSSI using the i tool to generate an attributes table displaying the SSSI information. Use the zoom in tool in the toolbar to zoom to the appropriate SSSI. OR (b) find a particular SSSI: right-click on the SSSI layer in the contents table and select open attributes table. Select the SITE NAME field. From the options tab select find and replace and type in the required site name. Click Find Next to locate the site in the table. Click on the left hand box on the row for the required SSSI (this will contain the symbol ) to highlight the row. Close the attributes table. Right-click on the SSSI layer in the contents table and select Selection, then Zoom to Selected Features. The selected SSSI will appear on the map. See Scenario 1: step 5 for examples of procedure. Step 6: Click on the area for interrogation using the i tool, to generate an attributes table for the area. From the Layers drop down box select the SW_Dep data layer to display information on the surface water body dependency of the area. 58

67 Final output: The water dependency class (Class) will be exhibited in the attribute table along with the SEPA water body identification code and the surface water catchment. The constituent components of the surface water sub-classes are also displayed so that the type of surface water source, and hence the linkage to a surface water body, can be understood. 59

68 Scenario 3: Define groundwater body dependency for a designated SSSI wetland site Rationale: A user wants to know whether a wetland, or part of a wetland, SSSI is dependent on a groundwater body. Step 1: In the contents table, double click on data layer SNF01.copy to open the Layer Properties window. In the Symbology field, select data layer GW_Dep from the drop down box under Value Field. See Scenario 1: step 1 for example of procedure. Step 2: Click on the Add All Values tab to display the groundwater body dependency categories. To remove unwanted categories, re-order categories, change category colours and remove outlines, follow the procedures outlined above. See Scenario 1: step 2 for example of output. Step 3: Click on Apply and then OK to close the Layer Properties window and display the groundwater body dependency data layer. See Scenario 1: step 3 for example of output. Step 4: Step 5: Display the SSSI data layer (See Scenario 1: step 4 for example of output). Identify a SSSI for interrogation. Either: (a) click within the SSSI using the i tool to generate an attributes table displaying the SSSI information. Use the zoom in tool in the toolbar to zoom to the appropriate SSSI. OR (b) find a particular SSSI: right-click on the SSSI layer in the contents table and select open attributes table. Select the SITE NAME field. From the options tab select find and replace and type in the required site name. Click Find Next to locate the site in the table. Click on the left hand box on the row for the required SSSI (this will contain the symbol ) to highlight the row. Close the attributes table. Right-click on the SSSI layer in the contents table and select Selection, then Zoom to Selected Features. The selected SSSI will appear on the map. See Scenario 1: step 5 for examples of procedure. Step 6: Click on the area for interrogation using the i tool, to generate an attributes table for the area. From the Layers drop down box select the GW_Dep data layer to display information on the groundwater dependency of the area. 60

69 Final output: The water dependency class (Class) will be exhibited in the attribute table, along with the SEPA water body identification code and the groundwater catchment. This will define the likelihood of dependency on groundwater. 61

70 Scenario 4: Define water body dependency for a non-designated wetland site Rationale: A user wants to know whether a wetland, or part of a non-designated wetland, is dependent on a water body. Step 1: In the contents table, double click on data layer SNF01.copy to open the Layer Properties window. In the Symbology field, select data layer Class (water body dependency layer) from the drop down box under Value Field. See Scenario 1: step 1 for example of procedure. Step 2: Click on the Add All Values tab to display the water body dependency categories. To remove unwanted categories, re-order categories, change category colours and remove outlines, follow the procedures outlined above. See Scenario 1: step 2 for example of output. Step 3: Click on Apply and then OK to close the Layer Properties window and display the water body dependency layer. See Scenario 1: step 3 for example of output. Step 4: Step 5: Use the zoom tool in the toolbar to display the appropriate area for interrogation. Click on the area for interrogation using the i tool to generate an attributes table displaying information on the water body dependency of the area. See Scenario 1: step 6 for example of final output. 62

71 Scenario 5a: Identify pressures on a designated SSSI wetland site Rationale: A user wants to define the potential pressures on designated SSSI wetland site. Step 1: In the contents table, double click on data layer SNF01.copy to open the Layer Properties window. In the Symbology field, select the required pressure risk layer (e.g. PP_Point) from the drop down box under Value Field. See Scenario 1: step 1 for example of procedure. Step 2: Click on the Add All Values tab to display the pressure categories. To remove unwanted categories, re-order categories, change category colours and remove outlines, follow the procedures outlined above. See Scenario 1: step 2 for example of output. Step 3: Click on Apply and then OK to close the Layer Properties window and display the pressure layer. See Scenario 1: step 3 for example of output. Step 4: Step 5: Display the SSSI data layer (See Scenario 1: step 4 for example of output). Identify a SSSI for interrogation. Either: (a) click within the SSSI using the i tool to generate an attributes table displaying the SSSI information. Use the zoom in tool in the toolbar to zoom to the appropriate SSSI. OR (b) find a particular SSSI: right-click on the SSSI layer in the contents table and select open attributes table. Select the SITE NAME field. From the options tab select find and replace and type in the required site name. Click Find Next to locate the site in the table. Click on the left hand box on the row for the required SSSI (this will contain the symbol ) to highlight the row. Close the attributes table. Right-click on the SSSI layer in the contents table and select Selection, then Zoom to Selected Features. The selected SSSI will appear on the map. See Scenario 1: step 5 for examples of procedure. Step 6: Click on the area for interrogation using the i tool to generate an attributes table for the area. From the Layers drop down box select the required pressure risk data layer to display information on the potential pressure for the area. 63

72 Final output: The potential pressure codes are provided for the seven possible pressures (SEPA, 2004) and evaluated as high, medium and low. 64

73 Scenario 5b: Identify pressures on a non-designated wetland site Rationale: A user wants to define the potential pressures on a non-designated wetland site. Step 1: In the contents table, double click on data layer SNF01.copy to open the Layer Properties window. In the Symbology field, select the required pressure risk layer from the drop down box under Value Field. See Scenario 1: step 1 for example of procedure. Step 2: Click on the Add All Values tab to display the pressure categories. To remove unwanted categories, re-order categories, change category colours and remove outlines, follow the procedures outlined above. See Scenario 1: step 2 for example of output. Step 3: Click on Apply and then OK to close the Layer Properties window and display the pressure risk layer. See Scenario 1: step 3 for example of output. Step 4: Step 5: Use the zoom tool in the toolbar to display the appropriate area for interrogation. Click on the area for interrogation using the i tool to generate an attributes table displaying information on the potential pressure for the area. See Scenario 5: step 6 for example of final output. 65

74 Scenario 6a: Understand the hydrogeomorphic functioning of a designated wetland SSSI Rationale: A user wants to understand further the relationship between water source, water body and landscape so that a more detailed understanding of the SSSI can be achieved. Step 1: In the contents table, double click on data layer SNF01.copy to open the Layer Properties window. In the Symbology field, double-click on the categories tab and select Unique values, many fields. Select TYPE from the first drop down box under Value Field, and the hydrogeomorphic unit (Hydrogeomo) category from the second drop down box. Example of procedure: Step 2: Click on the Add All Values tab to display the hydrogeomorphic unit categories. To remove unwanted categories, re-order categories, change category colours and remove outlines, follow the procedures outlined above. See Scenario 1: step 2 for example of output. Step 3: Click on Apply and then OK to close the Layer Properties window and display the hydrogeomorphic unit layer. See Scenario 1: step 3 for example of output. 66

75 Step 4: Step 5: Display the SSSI data layer (See Scenario 1: step 4 for example of output). Identify a SSSI for interrogation. Either: (a) click within the SSSI using the i tool to generate an attributes table displaying the SSSI information. Use the zoom in tool in the toolbar to zoom to the appropriate SSSI. OR (b) find a particular SSSI: right-click on the SSSI layer in the contents table and select open attributes table. Select the SITE NAME field. From the options tab select find and replace and type in the required site name. Click Find Next to locate the site in the table. Click on the left hand box on the row for the required SSSI (this will contain the symbol ) to highlight the row. Close the attributes table. Right-click on the SSSI layer in the contents table and select Selection, then Zoom to Selected Features. The selected SSSI will appear on the map. See Scenario 1: step 5 for examples of procedure. Step 6: Drag the SSSI layer heading in the contents table below the hydrogeomorphic unit layer. Alter the transparency of the layer to a level that allows the SSSI layer to be viewed beneath the hydrogeomorphic unit layer. Click on the area for interrogation using the i tool to generate an attributes table displaying information on the potential pressure for the area. 67

76 Example output: 1 3b 3a 2 Final output: The different hydrogeomorphic units are displayed in the example output. Three different hydrogeomorphic areas are highlighted: 1. Cranley Moss SSSI is dominated by an extensive peatland wetland area (TYPE EP) characterised by the moderate likelihood of a surface water source and low likelihood of a groundwater source (Class 6), where the main input is from the rise of an adjacent water body; 2. The River Clyde Meanders SSSI is a river marginal area (TYPE RM), characterised by a high likelihood of having both surface water and groundwater sources (Class 1), where the main inputs are highly likely to be from overbank flow, and moderately likely to be from the rise in an adjacent water body; and 3. Cleghorn Glen SSSI: a) A slope dominated area characterised by the high likelihood of having both surface water and groundwater sources (Class 1). The main input is highly likely to be from overbank flow. b) A river marginal area (TYPE RM) situated downstream of the slope dominated area of 3a. This section is also characterised by the high likelihood of having both surface water and groundwater sources (Class 1). The main input is highly likely to be from overbank flow. 68

77 Scenario 6b: Understand the hydrogeomorphic functioning of a designated wetland SSSI Using the procedure described in Scenario 6a, additional data layers can be overlaid by substituting the SSSI layer with different data layers. The output below gives an example of how a digitised NVC category data layer can be overlaid to allow the user to identify differences in hydrogeomorphic units between different NVC communities within an SSSI. 69

78 Scenario 7 : Generating a Wetland Inventory Rationale: A user wants to generate a wetland inventory for the whole of Scotland. Step 1: In the contents table, double click on data layer WFD66 to open the Layer Properties window. In the Symbology field, select Hydrogeomo field from the drop down box under Value Field. See Scenario 1: step 1 for example of procedure. Step 2: Click on the Add All Values tab to display the Hydrogeomo categories. For each wetland likelihood value, hold down the shift key and click on each individual Hydrogeomo value that corresponds to the value. High Likelihood of Wetland: BA EP ES Slope RM CO 3_BA 1_EP 6_ES 6_Slope 2_RM 3_CO 6_BA 5_EP 9_ES 9_Slope 3_RM 5_CO 9_BA 6_EP 5_RM 6_CO 7_EP 6_RM 7_CO 8_EP 9_RM 8_CO 9_EP 9_CO Once all required values are selected, right click on one of the highlighted values and select Group Values. All selected values are now grouped together under one field. Left click in the label field and insert the correct Value (H/M/L). See below for example. 70

79 Step 3: Once all Hydrogeomorphic values are grouped into their correct wetland likelihood value, click on Apply and then OK to close the Layer Properties window and display the Wetland Inventory layer. Step 4: Click on an area for interrogation using the i tool, to generate an attributes table for the area. 71

80 Final output: The user will have generated a map of the likelihood of wetlands being present, evaluated as high, medium and low, from the Hydrogeomorphic data. 72