Durham E-Theses Spatial and temporal water quality in the River Esk in relation to freshwater pearl mussels BALMFORD, DAVID,SAMUEL How to cite: BALMFORD, DAVID,SAMUEL (2011) Spatial and temporal water quality in the River Esk in relation to freshwater pearl mussels, Durham theses, Durham University. Available at Durham E-Theses Online: http://etheses.dur.ac.uk/861/ Use policy The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that: • a full bibliographic reference is made to the original source • a link is made to the metadata record in Durham E-Theses • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders. Please consult the full Durham E-Theses policy for further details. Academic Support Oce, Durham University, University Oce, Old Elvet, Durham DH1 3HP e-mail: [email protected] Tel: +44 0191 334 6107 http://etheses.dur.ac.uk 2 Spatial and temporal water quality in the River Esk in relation to freshwater pearl mussels David Balmford Thesis for M.Sc. (by research) Durham University, Department of Geography June 2011 Declaration This thesis is the result of my own work and has not been submitted for consideration in any other examination. Material from the work of other authors, which is referred to in the thesis, is acknowledged in the text. Statement of copyright The copyright of thesis rests with the author. No quotation from it should be published without his prior written consent and information derived from it should be acknowledged. ii Acknowledgements A number of people have helped with this study who I would like to thank. Firstly, I am very grateful to the North York Moors National Park Authority who sponsored me through the year. In particular, thank to Simon Hirst, the leader of the Esk Pearl Mussel and Salmon Recovery Project, for his help with fieldwork and local knowledge of the Esk catchment and the pearl mussel population. I would like to thank Doctor Louise Bracken and Professor Tim Burt, my supervisors, for their guidance and encouragement with this project. Also, the laboratory staff and technicians , in particular, Amanda Hayton, Martin West, Mervyn Brown, Edward Million, Neil Tunstall and Kathryn Melvin for their help in the laboratory and field. Finally, I would like to thank my friends and family for their support and encouragement throughout the year, and to those who accompanied me and helped with fieldwork at the study catchment. iii Abstract: Spatial and temporal water quality in the River Esk in relation to freshwater pearl mussels (David Balmford) Riverine systems provide networks of habitats, resources and biodiversity. Globally, riverine biodiversity is under threat due to a variety of human activities; diffuse pollution, particularly in agricultural catchments, raises challenges to river environments. This work addresses the water quality in the River Esk (North York Moors National Park) and its impact on biodiversity, namely the rare, declining population of freshwater pearl mussels (Margaritifera margaritifera). Water quality parameters were monitored both spatially and temporally and the drivers of water quality were investigated. Monthly sampling was undertaken at twenty sites within the Esk catchment. High-resolution monitoring was enabled by three autosamplers and two pressure transducers, which allowed for assessment of the water quality at both baseflow and stormflow. Anion and cation analysis were conducted on all samples and field-based characterisation furthered by use of a YSI multi-parameter probe. Results revealed a number of concentration hotspots with values of nitrate that are thought unsuitable for freshwater pearl mussels. Other water quality variables were all within acceptable limits. Concentrations of nitrate in sub-catchments with smaller upstream areas proved to be more variable than in larger catchments. Land cover was found to be a key driver of concentration: high upstream percentage of improved pasture resulted in high nitrate concentration; high upstream percentage of moorland resulted in low nitrate concentration. During storm events, concentrations of key parameters were greater than limits suggested for pearl mussels (nitrate up to approximately 3.0 mg l-1 as opposed to limit of 1.0 mg l-1 proposed by Skinner et al. (2003)); this raised the fundamental question of exposure time. The process of connectivity was considered by the application of the risk-based hydrological model SCIMAP. This highlighted a number of areas that could adversely affect the pearl mussel population; these results will require further validation. Empirical work provided a foundation for future management recommendations. A case is made for the importance of expansion or addition of riparian buffer zones. This study demonstrates the importance of obtaining high-resolution data sets to understand habitat quality. The worth of these data is demonstrated in planning interventions in catchments to enable the Water Framework Directive (WFD) and UK Biodiversity Action Plan (BAP) standards to be met. iv Contents Acknowledgements iii Abstract iv Contents v List of Figures vii List of Tables xi 1. Introduction 1 1.1 Research background 1 1.2 Study Rationale 2 1.3 Aim and objectives 3 1.4 Thesis outline 3 2. Literature Review 4 2.1 Introduction 4 2.2 Water Quality: current understandings 4 2.2.1 Diffuse pollution 4 2.2.2 Spatial patterns 5 2.2.3 Temporal patterns 6 2.2.4 Drivers of water quality 8 2.3 Management 11 2.3.1 Expectations 11 2.3.2 Mechanisms 13 2.4 Freshwater Pearl Mussels 14 2.4.1 Pearl mussels and water quality 15 2.4.2 Case study: Pearl mussels in the River Esk 16 2.5 What are the gaps? 17 2.6 Summary 18 3. Methodology and Sites Outline 19 3.1 Introduction 19 3.2 The study area 19 3.2.1 Location and topography of the River Esk 19 3.2.2 Geology 20 3.2.3 Climate 22 3.2.4 Land use and vegetation 22 3.3 Site locations 25 3.4 Field techniques 28 3.4.1 Monthly monitoring system 28 3.4.2 High-frequency sampling 28 3.5 Laboratory techniques 31 3.5.1 Anion and cation analysis 31 3.5.2 Suspended sediment concentration 33 3.6 Catchment characterisation 33 3.7 Summary 37 4. Spatial variations in water quality in the River Esk 38 4.1 Introduction 38 4.2 Parameter patterns 38 4.2.1 Spatial distribution of anions and cations 39 4.2.2 Spatial distribution of other parameters 45 4.3.3 Inter-variable relationships 48 4.3 Spatial results: catchment size trends 52 v 4..4 Land cover patterns 56 4.5 Summary 59 5. Temporal variation in water quality in the River Esk 60 5.1 Introduction 60 5.2 Temporal Variation 60 5.2.1 Monthly scale 60 5.2.2 Longer-term scale 65 5.2.3 Other parameters 68 5.3 Catchment size influence at a temporal scale 71 5.4 The temporal influence of land cover 74 5.5 Hourly scale: autosamplers 79 5.5.1 Baseflow water quality 79 5.5.2 How does the water quality respond to an increase in discharge? 82 5.5.3 How does the potassium concentration respond to an increase in discharge? 86 5.5.4 How does the nitrate concentration respond to an increase in discharge? 88 5.5.5 How does suspended sediment respond to discharge? 91 5.5.6 Hysteresis in water quality variation 93 5.6 Summary 95 6. Accounting for connectivity using SCIMAP 97 6.1 Introduction 97 6.2 Results 97 6.3 Summary 110 7. Discussion 111 7.1 Introduction 111 7.2 Summary of main findings 111 7.3 Implications for the freshwater pearl mussel 113 7.4 Future management options for the River Esk catchment 117 7.5 Implications for European legislation/directives 121 7.6 Summary 123 8. Conclusion 125 8.1 Central conclusions 125 8.2 Limitation to study 126 8.3 Suggested further work 127 References 129 vi List of Figures 2. Literature Review Figure 2.1 ‘Relationship between drainage basin area and nitrogen fluxes in Europe and North America’ (from Burt and Pinay, 2005: 298) 8 Figure 2.2 Diagram to illustrate the central purpose of the UK BAP (from DEFRA, 2007) 13 3. Methodology and sites outline Figure 3.1 Catchment topography from Esk catchment Digital Terrain Model (DTM) (10 x 10 m resolution) 20 Figure 3.2a Bedrock geologies in the Esk catchment and the surrounding region 21 Figure 3.2b Drift geology of the Esk catchment and the surrounding region 22 Figure 3.3 Catchment land cover map (Centre for Ecology and Hydrology (CEH)) 24 Figure 3.4 Location map of sample sites within the Esk catchment 27 Figure 3.5 Stage record at Danby (daily average stage) from mid-October 2009-early July 2010 30 Figure 3.6 Stage record at Grosmont (daily average stage) from mid-June 2009-mid-May 2010 31 Figure 3.7 Conceptual flow chart model of the component of SCIMAP demonstrating how they interact (from: www.scimap.org.uk) 36 4. Spatial variations in water quality parameters in the River Esk Figure 4.1 Spatial distribution of annual concentrations of selected anions; (a) chloride and (b) bromide 39 Figure 4.2 Spatial distribution of annual concentrations of calcium 41 Figure 4.3 Spatial distribution of annual concentrations of potassium 43 Figure 4.4 Spatial distribution of annual concentrations of nitrate 44 Figure 4.5 Diagrams to represent the spatial distribution of annual figures for parameters (a) pH, (b) conductivity and (c) dissolved oxygen 47 vii Figure 4.6 Relationship between annual mean concentrations of sulphate and magnesium from all sites investigated in the Esk catchment 50 Figure 4.7 Examples of relationships between variables with high r-values 51 Figure 4.8 The relationship between annual average nitrate concentrations and catchment areas 53 Figure 4.9 ‘Relationship between drainage basin area and nitrogen fluxes in Europe and North America’ (modified from Burt and Pinay, 2005: 298) 54 Figure 4.10 Relationship between annual nitrate concentrations and the three most dominant land cover catergories within the study area in the Esk catchment, (a) arable, (b) improved pasture, and (c) moorland (at 18 degrees of freedom (as n=20) 95% significance level= +/-0.44; 99% significance level= +/-0.56; 99.9% significance level= +/-0.68) 56 & 57 5.