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Assessing the value of historic spring flow records in Scotland A study focusing on the North Pentland Springs
A R Black, A M MacDonald and T Ball
Report to Scottish Environment Protection Agency March 2006
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Assessing the value of historic spring flow records in Scotland A study focusing on the North Pentland Springs A R Black1, A M MacDonald2 and T Ball1
1 Department of Geography, University of Dundee,
DUNDEE DD1 4HN 2 British Geological Survey, Murchison House,
West Mains Road, EDINBURGH EH9 3LA Report to Scottish Environment Protection Agency March 2006 SEPA’s contract manager for this project is: Jean Clews Corporate Office Scottish Environment Protection Agency Erskine Court The Castle Business Park STIRLING FK9 4TR Tel 01786 457700 Email [email protected] The University of Dundee’s project leader for this project is: Dr Andrew Black Department of Geography University of Dundee DUNDEE DD1 4HN Tel 01382 384433 Email [email protected] © University of Dundee 2006 Geological Information produced with Permission from the British Geological Survey, © NERC, 2006 This product includes mapping data licensed from the Ordnance Survey® with the permission of the Controller of Her Majesty’s Stationery Office. © Crown Copyright 2006. All rights reserved. Licence number 100037272 The financial assistance of the NERC British Geological Survey in the preparation of this report is gratefully acknowledged
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Assessing the value of historic spring flow records in Scotland: a study focusing on the North Pentland Springs A R Black, A M MacDonald and T Ball EXECUTIVE SUMMARY The study undertook analysis of data measured from three groups of springs in the Pentland Hills by the former Edinburgh & District Water Works and its successors between 1862 and 1982. These springs are (a) Colzium, Crosswood + North Listonshiels; (b) Westrig, Bavelaw and Listonshiels and (c) Black Springs. The study forms a scoping study to help indicate the value of the data and the potential for more detailed investigations. The objectives of this preliminary study were to (1) assess the relationship between the spring flow data and associated rainfall data; (2) identify step changes or trends in the data and, where possible, their causes; and (3) assess the value of the data. Analysis focused on the Black Springs data owing to their apparent temporal stability compared with the other series, and also the small size of the catchment, in the order of 1-2 km2. A range of investigations of the relationship between catchment precipitation and measured spring flow revealed statistical linkages with precipitation accumulations over 1-7 months. Precipitation totals were found to be able to explain up to 54% of the variability in monthly spring flow values, leaving 46% of the variability to be accounted for by other factors such as evaporation. An investigation into possible leakage or land use change effects showed no sign of these effects. It is concluded that the measured flows appear to be essentially free from these effects. Gradual decreases in spring flows over the 80 years from 1904, for which local precipitation data were available, appear to be the result of decreases in annual precipitation totals. This applies to all three groups of measured spring flows. The analysis of historical data from the Black Springs has shown the quality of data to be excellent, and there is great potential for identifying historical responses of spring flow to climate. This will form a valuable dataset for calibrating water resources models and assessing the possible effects of climate change. A request for further data from a variety of sources did not identify any other comparable datasets. This gives cause for concern that historic records maintained by municipal water undertakings around Scotland through the early 20th Century, or in earlier times, have largely been lost.
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The preliminary analysis of data from the Pentland springs has shown the data set to be of value and worthy of further study. Further work should focus on the following:
• Developing a further understanding of the Colzium, Crosswood & North Listonshiels and Westrig, Bavelaw & Listonshiels spring systems, particularly the latter, which appears to be dominated by groundwater with a moderate residence time.
• Further analysis of the historical data, particularly in terms of historical response to climate and extreme events.
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ACKNOWLEDGEMENTS ARB acknowledges the unique role of Frank Law, formerly Deputy Director of the NERC Institute of Hydrology, leading him to his first awareness of the collection of records on which this study is based, and providing great enthusiasm and a wonderful example for the task of extracting value from historic source materials. Scottish Water and its predecessors in Edinburgh are congratulated on their sound judgement in keeping safe the records through times in which pressures on office space have undoubtedly increased, and in which comparable records from elsewhere in Scotland have almost certainly been lost forever. Owen Bramwell, Ed Irvine, Dougie Scott and Michael Woodley at Scottish Water have provided valuable assistance in gaining access to these records and in providing relevant background information, and in years past, Jim Conlin, Stewart Roberts, Celia Binnie and Bernie Rodden have also helped in like manner. Several individuals have kindly responded to requests for information about the whereabouts of further sources of historic hydrological information, so thanks go to Peter Ede (Mott Macdonald), Ed McKenna (JBA Consulting Ltd), Richard Brown, Mike Cranston and Steve Anderton (SEPA), David Price (Jacobs Babtie) and Owen Bramwell (Scottish Water). The NERC British Atmospheric Data Centre and the Met Office are acknowledged for access to Blackford Hill precipitation data. Jean Clews, SEPA’s project manager, and her steering group colleagues Elaine Simpson and Drew Aitken, are thanked for making this research possible and for their valuable support and guidance over the course of the work. Similarly the British Geological Survey is thanked for making available additional staff time and laboratory analysis costs for the project.
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CONTENTS EXECUTIVE SUMMARY ..............................................................................................i ACKNOWLEDGEMENTS ........................................................................................... iii NOTES ON STATISTICAL TERMINOLOGY ...............................................................v 1 INTRODUCTION..................................................................................................1
1.1 Background ..................................................................................................1 1.2 Selection of springs ......................................................................................2 1.3 Objectives.....................................................................................................3
2 Spring flow data extraction and quality control.....................................................4 3 HYDROGEOLOGICAL SETTING OF THE NORTH PENTLAND SPRINGS.......6 4 FACTORS AFFECTING THE SPRING FLOWS ................................................14
4.1 Climate .......................................................................................................14 4.2 Land use change........................................................................................16 4.3 Leakage and maintenance of the springs...................................................16
5 STATISTICAL ANALYSES.................................................................................17
5.1 Decadal flow duration curves .....................................................................17 5.2 Time series analysis of Black Springs: independence, trend and step change ...................................................................................................................21 5.3 Harlaw precipitation correlations with Black Springs flows.........................24 5.4 Double mass plots......................................................................................30 5.5 Selected drought events: Black Springs.....................................................35
6 REVIEW OF OTHER SOURCES OF FLOW INFORMATION ...........................37 7 DISCUSSION: UTILITY OF THE SPRING FLOW SERIES ...............................38
7.1 Use of North Pentlands spring flow data for climate change or other purposes ................................................................................................................38 7.2 Future monitoring of the springs (all spring groups) ...................................39 7.3 Use of comparable data from other parts of Scotland ................................39
8 CONCLUSIONS AND RECOMMENDATIONS ..................................................40
8.1 Conclusions................................................................................................40 8.2 Recommendations for further work ............................................................41
REFERENCES...........................................................................................................42 BIBLIOGRAPHY ........................................................................................................42 Appendix 1: Ledger series held at Scottish Water’s Fairmilehead Works..................43 Appendix 2 Assessment of approximate catchment area of Black Springs ..............44 Appendix 3: Black Springs: Results of statistical analyses .......................................45 Appendix 4: Data CD ........................................................................Inside back cover
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NOTES ON STATISTICAL TERMINOLOGY Significance levels (denoted by p values): highly significant patterns are indicated by low probabilities (p values), meaning that the chance of the observed result being real is high, while the chance of it being a spurious result is low. E.g. p<0.02: a highly significant result – there is a 98% chance that the observed result (derived from a sample of data) is due to a real difference in the underlying data; there is only a 2% chance that the result is spurious. Coefficients of determination (denoted by r2 values): this is a measure of the extent to which the variance in a dependent variable can be explained by variance in one or more independent variables. In this report, only single independent variables are used, chiefly rainfall or time, being used to explain variance in spring flow values. r2 values are measured on a 0-1 (0-100%) scale. 0 indicates that there is no statistical relationship between the two variables while, conversely, 1 indicates that all of the variance in the dependent variable is explained by the independent variable. In such a case, all the points on a scatter graph showing values of the two quantities would lie on a perfectly smooth line. The r value which is squared to produce r2 is an index of correlation. Coefficient of variability (CV, measured on a 0-100% scale): this is a measure of variability within a data set, which allows comparisons to be made even when the means of each data set differ. The CV is obtained by dividing the sample standard deviation by the mean. A CV of 10% indicates that variability is small compared to the mean of the data, while a CV of 70% would indicate a much more relatively variable data set. Any introductory statistical text will provide further elaboration on these key concepts. The specific methods used in this report have been adopted following reference to Kundzewicz and Robson (2000).
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1 INTRODUCTION 1.1 Background This study has arisen as a result of a modest SEPA commission, seeking to assess the utility of an archive of spring flow records from the Pentland Hills. The records span more than 100 years, and may offer the opportunity to understand how spring flows have responded to rare historic drought episodes. Moreover, they may afford the opportunity to understand this response in a way which allows calibration of models of future response, particularly in the light of climate change. The records were first identified as having research potential in the mid-1990s, and were subject to a preliminary analysis in 2003 (Black, 2003). At the time of writing, Scottish Water are keen that a new home is found for the records, and discussions are taking place to effect this. The bulk of records is an issue (Figure 1.1 illustrates the holding of all ledgers of this sort by Scottish Water at their Fairmilehead works, occupying c.50m of shelf length), but until such time as all potentially useful data have been extracted into digital format, their continued storage appears entirely justifiable.
Figure 1.1. Ledgers of the former Edinburgh & District Water Works and its successors held at Fairmilehead, Edinburgh. The data on which this study draws were extracted from ledgers for Harlaw Reservoir. Photo: A R Black
Many other records are still held by Scottish Water for the Edinburgh area, including:
• spring flow measurements, obtained typically by volumetric measurement,
• for reservoirs, records of level, stored volume, ‘supply to town’, compensation water and spill
• rainfall (precipitation) associated with most of the above, and in exceptional cases, evaporation.
A list of the ledgers available is provided in Appendix 1.
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1.2 Selection of springs The choice of springs for study stems from a number of factors. While the ledgers afford opportunities to study a number of surface water sources, including the inflows to surface water reservoirs (see Black and Cranston, 1999 for such an attempt based on Talla Reservoir), it was felt that spring flows might offer benefits in terms of a more gradual response to precipitation than surface waters, such that recorded flows may be more representative of observed behaviour than would be the case for surface waters. Also, the catchments involved will be smaller and more controlled than many surface water catchments, so other changes such as land use can be more easily accounted for. The ledgers for Harlaw Reservoir appeared to contain the longest and most complete spring flow records of all the available ledgers. Flow measurements from three groups of springs have been recorded, and their basic characteristics are shown in Table 1.1: Spring group Period of record Mean
flow(l s-1)
Coefficient of variability of
weekly flows (%)
Complete-ness (%)
Colzium, Crosswood + North Listonshiels
Weekly 1904-1982 119.7 21.2 99
Westrig, Bavelaw and Listonshiels*
Weekly 1904-1982 65.6 10.7 99
Bavelaw and Listonshiels
Monthly 1862-1904 88
Black Springs Monthly 1862-1904 Weekly 1904-1982 18.0
68.1
9592
Table 1.1. Key characteristics of the available spring flow records * It is inferred from the information in this table that the Westrig springs were added to the Bavelaw and Listonshiels springs shortly before 1904, resulting in an approximate doubling of the recorded flows. Initially all of these records were viewed as having potential for study, but time constraints and preliminary analysis of the data suggested that effort should be focused just on the Black Springs. This was because the Black Springs appeared to be less affected by a long-term downward shift in mean flows than the other records, suggesting that it might be of higher quality. Also, the small flow from the system suggests that its catchment must be small and this is expected to mean a simple catchment in which any land use changes can be readily accounted for. The location of all the groups of springs included in this study are indicated in Section 3.
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1.3 Objectives The objectives of the research project are to use historical data on spring flows from Black Springs, Westrig, Bavelaw and Listonshiels and Colzium, Crosswood and North Listonshiels, in the Pentland Hills, according to their completeness and apparent quality, in order:
(1) To assess the relationship between the spring flow data and
associated precipitation data. (2) To identify step changes or trends in the data and, where possible,
their causes. (3) To assess the value of the data
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2 Spring flow data extraction and quality control All of the data for the springs described in Section 1.2 were obtained by volumetric flow measurement, as recorded on weekly operations logs which were posted to the offices of the water supply undertaking. These data have subsequently been entered onto spreadsheets by staff and students of the University of Dundee. The spring flow readings were made and recorded weekly, and the log sheets (now bound in ledgers) normally show both the time taken to fill the stipulated volume for the measuring house in question, and (from a look-up table) the flow rate associated with the recorded time. This allows transcription errors to be readily identified since any one measurement time must correspond to one flow rate only. Often transposed digits or difficulties in reading handwriting are the causes of apparent errors, and study of the likely options often allows a correction to be made. Figure 2.1 shows a measurement being made in 1999 at the West Rigg Measuring House. Figure 2.1 Flow measurement at West Rigg. Left: flows emerge from two distinct spring groups; centre: flow is diverted from channel to floor of measuring house; right: rise in water level of one foot is monitored using a float and timed. Photos: A R Black Figure 2.2 shows a ‘before an after’ comparison of the data obtained for the Westrig, Bavelaw and Listonshiels Springs, illustrating the benefit of the quality control process. Outliers from the best fit line, identified by eye, have been removed or corrected as appropriate. Where a specific reason for error can be identified, apparent errors in flow or time values have been corrected. Where the source of discrepancy between recorded flow and expected flow (based on recorded time) remains unclear, data have been recorded as missing. Rainfall data were consulted to ascertain whether short-term rises in flows were to be expected. The same procedures were followed for all three spring groups; the amount of scatter among the recorded data for the Black Springs and Colzium,
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Crosswood & North Listonshiels groups appeared visually less than found for Westrig, Bavelaw & Listonshiels. The quality controlled data are provided electronically as Excel files.
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190Xs191Xs192Xs193Xs194Xs195Xs196Xs197Xs198Xs
Figure 1.3 (a) Recorded time for 1’ rise in Westrig Measuring House for Westrig, Bavelaw and Listonshiels springs and recorded flow rates
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Figure 1.3 (b) Same data as for (a) above following quality control
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3 HYDROGEOLOGICAL SETTING OF THE NORTH PENTLAND SPRINGS
While measurements have been undertaken for just three combined sets of springs, there are four main sets that can be seen to have been developed on the North Pentlands. The location and geology of the springs are shown in Figures 3.1, 3.2 and 3.3. The springs generally rise in the Carboniferous Kinnesswood Formation – which is a highly productive aquifer within Scotland. Each of these groups is described in the following sections. Table 1.1 indicates mean flows and the associated variability of each of the sets of springs. The largest flow is from the Colzium, Crosswood and North Listonshiels Springs, and the least flow from the Black Springs.
Figure 3.1 shows the location of the North Pentland springs Note: outlines shown are not spring catchments The Black Springs: Bedrock geology is the Kinnesswood formation, although much of the catchment is within granite. There is no surface water drainage within the catchment, and superficial deposits comprise glacial till and talus (scree). There are only 3 springs in the system, and these were the subject of a field visit. Figure 3.4 shows an extract from the map made available by Scottish Water showing the location of these three springs. The Black Springs display a much more variable flow than the other two spring groups. A high coefficient of variability of the weekly flow values (68% - Table 1.1) indicates that shallow/quick response to rainfall dominates the behaviour of these springs, presumably corresponding to runoff from Black Hill and rapid flow through to the springs through the talus and permeable glacial till. Figure 3.5 illustrates the same variability using flow duration curves based on
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observed and standardised data: the Black Springs can be seen to display a much more variable flow than the other two spring groups. Relatively speaking, the empirical evidence of these graphs points to the Westrig, Bavelaw & Listonshiels and Colzium, Crosswood and North Listonshiels springs being supplied largely by large, slowly-responding aquifers, while the Black Springs appear to be supplied by a more responsive system – a point developed further at the end of this section.
Figure 3.2 Bedrock geology of the North Pentland Springs Note: outlines shown are not spring catchments
Figure 3.3 Superficial geology of the North Pentland Springs Note: outlines shown are not spring catchments
N Listonshiels
N Listonshiels
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Figure 3.4 Extract from Scottish Water map showing location of springs. Similar maps are available for the whole of the North Pentlands area. Westrig, Bavelaw and Listonshiels: Bedrock geology is entirely Kinnesswood Formation, and glacial sands and gravels are also important in the catchment. There are significant streams within the catchment, and many captured springs appear to capture groundwater rising at the heads of surface water tributaries. Many springs and wells are captured. This group of springs shows the least variability among weekly values, as indicated by a low coefficient of variability of 11% (Table 1.1) and a flat curve in Figure 3.5. Week by week, the flow of these springs is found to change only slowly. This suggests that the flows are mainly derived from a large aquifer. Colzium Springs: Bedrock Geology is the Kinnesswood and Ballagan Formations; superficial deposits comprise peat on the higher slopes and till lower down. The Carboniferous Ballagan Formation is formed of siltstones, mudstones and sandstones and is a moderately productive aquifer. There are significant streams within the catchment, and the springs tend to be captured at the head of many tributaries. Many springs and wells are captured. Crosswood Springs: Bedrock Geology is the Kinnesswood Formation; superficial deposits comprise mainly peat. There are significant streams within the catchment, and the springs tend to be captured at the head of many tributaries. Many springs and wells are captured.
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a)
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Figure 3.5 Flow duration curves based on all 1904-1982 observed data. (a) Measured flows; (b) Flows standardised by the long-term term mean The Colzium and Crosswood springs are measured together with a small number of springs at North Listonshiels, and have a CV of 21% (Table 1.1): about double the variability of the Westrig, Bavelaw and Listonshiels springs, but much less than that of the Black Springs. While some extensive field inspection would be required to investigate the relationship between the captured springs and the sources of the surface tributaries, it is likely that the extensive peat deposits within the catchment are responsible for the more responsive flow pattern than found in the Bavelaw, Westrig and Listonshiels flows.
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Chemistry samples have been taken from the Black Springs and the Bavelaw springs. The data are shown in Table 3.1 and Figure 3.6. The data are consistent with the Bavelaw springs having an origin from the Kinnesswood Formation – the chemistry is similar to that measured for the Kinnesswood Formation in other areas (see MacDonald and Ó Dochartaigh 2005 ) The chemistry data for the Black Springs are interesting. The data do not indicate a groundwater entirely derived from granite runoff, or the Kinnesswood Formation. The pH is higher than expected from granite runoff alone, and the HCO3 and Ca concentrations greater than expected for granite. However, concentrations are much lower than that measured from the Kinnesswood formation. Therefore, it is likely that there is either a mixing of Kinnesswood and granite groundwaters, or that granite waters are buffered by a short residence time in the superficial deposits which contain carbonate material.
Figure 3.6. Piper diagram of chemistry data from the Bavelaw Springs and Black Springs. Table 3.1 Chemistry data for the Black Springs and Bavelaw Springs Name pH Ca Mg Na K HCO3 Cl SO4 NO3Black Springs
7.3 15.5 1.86 9.1 0.72 58 7.9 7.04 0.44
Bavelaw Spring 1
8.2 69 10.3 5.59 1.16 256 5.74 4.65 0.21
Bavelaw Spring 2
8.2 62.1 11.6 6.1 1.36 252 5.98 5.07 0.29
All units except pH shown as mg l-1
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Black Springs: conceptual model The most likely source of water for the Black Springs is runoff and shallow groundwater from Black Hill which is transmitted through the superficial deposits to the spring. The spring in the quarry, located within gravely tills, acts as a drain for the area (Figure 3.7a). The glacial till is known to have a large component of sand and gravel in the area (see Figure 3.4 which shows gravel pits in the area). The bedrock geology of the area is complex. The spring is likely to rise on the Kinnesswood Formation, north of a faulted boundary with the microgranite (Figure 3.8). The microgranite in turn overlies Silurian deposits, although the depth at which this boundary occurs is unclear. The Silurian deposits are of the North Esk Group – a turbidite sequence of mudstones, siltstones and sandstones which is generally a poor aquifer. The relatively poorly mineralised groundwater, and flashy nature of the springs indicates that groundwater from the bedrock is unlikely to have a significant impact on rates of spring flow.
a)
b)
c) Figure 3.7 Black Springs. (a) Quarry from which main spring flow emerges; (b) engraved marker stones providing a possible source protection; (c) view of Black Hill indicating approximate extent of talus and measuring house (box). Photos: A R Black
Q U A R R Y
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There is a mismatch between the likely spring catchment area (0.5 km2 – see Figure 3.9) estimated from surface topography, and the amount of water the springs produce. The latter indicates a catchment area of between approximately 1 km2 and 2 km2 – see Appendix 2. Possibly the springs drain a larger area of Black Hill by using the permeable glacial deposits as a drain (Figure 3.8). Alternatively, and less likely, flow through fractures in the granite may travel through the baked margin with the Silurian deposits to increase the flow. .
Figure 3.8. Possible cross-section of the Black Springs
Figure 3.9 The location of the Black Springs
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Westrig, Bavelaw & Listonshiels and Colzium, Crosswood & North Listonshiels Springs: conceptual models The Westrig, Bavelaw & Listonshiels and Colzium, Crosswood & North Listonshiels spring groups occur over areas of many square kilometres. Generalised representations of the occurrence of spring flows in each are given in Figures 3.10 and 3.11.
Figure 3.10. Possible generalised cross-section of the Westrig, Bavelaw & Listonshiels springs group
Figure 3.11. Possible generalised cross-section of the Colzium, Crosswood & North Listonshiels springs group
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4 FACTORS AFFECTING THE SPRING FLOWS Initial reading of the long flow series from the springs raised questions about the influences which may have affected them over these long periods of record. Specifically:
• What effect did climatic variability have? • What effect did any land use changes have? • What effect arose from leakage or other maintenance-related issues
over the period of record? 4.1 Climate Fortunately, a highly complete precipitation record was available for Harlaw Reservoir, extracted from the same ledgers as the spring flow records. This record has not been subject to the quality control processes undertaken as matter of routine now by the Met Office, but it does offer the advantage of being very local to the study area. Possible transcription errors were looked for during data entry: the only issues that seem to have arisen are that occasionally daily readings have been missed, such that the gauge has continued to accumulate and a higher value is then found in the next reading. Remarkably, in 79 years of record, only 181 days were without daily readings, and of those, 149 were in the 1970s. There were no missing days between 1934 and 1964 inclusive (31 years). The annual total precipitation values are shown in Figure 4.1.
y = -1.7515x + 865.04R2 = 0.0784
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Figure 4.1 Annual precipitation totals for Harlaw 1904-1982 with linear best-fit line This plot shows an apparent decline over the period of data. Data were also available from the Blackford Hill Observatory, Edinburgh, from 1911 to 1982
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(courtesy Met Office/British Atmospheric Data Centre) and two comparisons between the two series are shown in Figures 4.2 and 4.3. A reasonably high coefficient of determination can be seen (r2=0.68) and visually the pattern of the two series seems to be similar through time. It is thought that the Harlaw data are therefore fit for purpose. Differences in exposure would be expected to lead to some differences in the precipitation recorded at these two sites, despite being just 10 km apart.
y = -0.3842x + 690.95R2 = 0.0053
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Figure 4.2 Harlaw and Blackford Hill annual precipitation totals 1904-1982: time series
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Figure 4.3 Harlaw and Blackford Hill annual precipitation totals 1904-1982: scattergraph
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4.2 Land use change Ordnance survey maps were consulted from University of Dundee holdings. These did not cover the whole of the study area for each OS edition, but coverage of the Black Springs was available for the First Edition (surveyed 1852) and for more recent periods. There is no evidence of afforestation or drainage, or of alteration of the extent of the quarry from which the main spring issues. There is therefore no evidence to suggest that land use change has had any appreciable effect on Black Springs during the period of record. 4.3 Leakage and maintenance of the springs There is the scope for leakage to have developed during the period of operation of the spring flow gathering network, which conveys the water to the measuring houses from which data have been obtained. Enquiries of Scottish Water indicate that periodic maintenance of the networks has been done routinely every few years, with silt cleared and repairs undertaken as necessary. However, it is thought that this activity has ceased c. 10 years ago, coinciding at least approximately with the cessation of use of the springs for supply, owing to known cryptospyridium problems. It is understood that Scottish Water now plans to bring the springs back into use, with appropriate treatment, in response to a need to diversify its source portfolio in response to Water Framework Directive pressures. Nevertheless, leakage may still have played a part in the pattern of flows observed in the data. This issue is addressed further in Section 5.
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5 STATISTICAL ANALYSES The purpose of this section is to assess the suitability of the recorded spring flows for future analyses, particularly modelling work which could be used to predict the past and therefore future response of the springs to climatic changes. A number of complementary approaches are developed:
• Decadal flow duration curves to assess the shift of flows over time across the spectrum of flow conditions (Section 5.1);
• Time series analysis of the Black Springs flows, to assess statistical significance of observed changes (Section 5.2);
• Precipitation correlations and use of the coefficient of determination (r2) to assess the extent to which variance in flows can be explained by variance in precipitation (Section 5.3); and
• Double mass plots which allow stability of response to be assessed graphically (Section 5.4).
In addition, it is opportune to illustrate spring flow behaviour in some periods of drought, and so some sample time series plots are presented in Section 5.5. 5.1 Decadal flow duration curves An initial inspection of the three flow series identified in Table 1.1 was undertaken by producing flow duration curves for each on a decadal basis. With time series of almost 80 years for each set of weekly measurements, the normal hydrological assumption of long-term stationarity would be expected to manifest itself in data with no long-term trend unless some source of change was exerting influence over the data. Therefore, the decadal flow duration curves would be expected to plot broadly on top of each other and show no systematic shift over time. The three plots obtained for the three groups of springs show the results obtained (Figures 5.1-5.3). All three plots show a pattern of diminishing flows with time, across the range of flows. They maintain approximately the same gradient while showing this displacement effect. The Colzium, Crosswood & North Listonshiels data (Figure 5.1) show the most marked jump: between the 1920s and 1940s, many points on the flow duration curve have dropped by approximately 30%. Decadal shifts in the Westrig, Bavelaw & Listonshiels data are more gradual but still amount to overall totals similar to the Colzium, Crosswood & North Listonshiels shifts. The shifts for Black Springs are again in the same generally downward direction over time, and are smaller in absolute amount given the lower flow rates from these springs. However, the relative shifts are slightly less extreme, and there seems to be a less strong change with time. A change in the shape of the curve for Black Springs in the 1970s and 1980s may be climatic in origin: these curves are affected by a high level of data incompleteness.
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Figure 5.1 Decadal flow duration curves: Colzium, Crosswood & North Listonshiels
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Figure 5.2 Decadal flow duration curves: Westrig, Bavelaw & Listonshiels
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193x
194x
195x
196x
197x
198x
Flow
(l s
-1)
Figure 5.3 Decadal flow duration curves: Black Springs
21
5.2 Time series analysis of Black Springs: independence, trend and step change
A key component of the study is to identify whether statistically significant trend and/or step change is present within the observed flows. In order to use the standard tests available and appropriate to the present study, the independence of data must also be assessed statistically: only if successive observations in time series are independent can the necessary tests be applied. Analysis has focused on Black Springs owing to its relatively modest change in runoff over the duration of record, interpreted as implying a high quality of data, and also supported by its small catchment size, interpreted as implying a relatively simple system. Summary results are presented here, with more detail being available in Appendix 3. Runoff seasonality and definition of seasons Figure 5.4 shows monthly mean precipitation and flows for Black Springs. As with other raingauges in the area, the precipitation record shows a summer maximum and winter minimum, in this case August and April being the months in question respectively. The maximum flow occurs in January and the minimum in July.
0
10
20
30
40
50
60
70
80
90
100
1 2 3 4 5 6 7 8 9 10 11 12
Calendar Month
Pre
cipi
tatio
n (m
m)/M
ean
flow
(l s
-1)
Mean rainfall (mm)Mean flow (l s-1)
Figure 5.4. Long-term average precipitation and flows: Black Springs (1904-82) For seasonal analysis, it was determined that seasons should be defined to minimise the within-season variability of flows. Calculation of standard deviations of monthly means for all possible definitions of seasons based on whole months led to the following seasons being adopted for analysis: Q1/Spring: February-April Q3/Autumn: August-October Q2/Summer: May-July Q4/Winter: November-January
22
Statistical analysis of flow data The object of this part of the analysis is to identify significant trends and step changes, as set out in the project specification. Significant results are expected to be common given the strength of the shifts observed from the decadal comparisons of flow duration curves, but nevertheless seasonal and sub-period breakdowns may illuminate particular aspects of the behaviour of the system. Appendix 3 provides full details of the test results, while this section considers the key results and their significance. Data were analysed using three periods, based on data availability:
• 1862-1958: longest available period of continuous data (1862-1903 based on data presented by Tait (1906))
• 1904-1958: data obtained from ledgers up to point of first major data interruption
• 1960-1973: further period of continuous data between gaps Independence The results of using the von Neumann ratio test (Kundzewicz and Robson, 2000) indicates that the assumption of independence can be made for all the series to be analysed (Appendix 3). This means that the step change and trend test results will therefore be valid. Step-change The great majority of applications of the distribution-free CUSUM test (Kundzewicz and Robson, 2000) did result in significant step change being identified at significance levels of 0.02 or better. Change points have been noted and occur on a number of different years for different seasons (Appendix 3). There is therefore no suggestion that one single change in the system has affected the flow patterns. However, the data used are the observed flows which also include climatic effects and indeed any other effects such as any relevant land use changes which may have affected the flow behaviour of the springs. Given that the step changes register for considerably different years depending on the season in question suggests that these changes are probably climatic in origin, reflecting random changes in precipitation. Substantial shifts in land use or in the connectivity between aquifer and outflow point would be expected to affect all seasons’ data. Arguably the most valuable finding from this analysis is that there is no single point in the 120 years of record at which flows suddenly change. This means that climate and the connectivity between the aquifer and its measured outflow become the key issues for further analysis of the data, although the effects of gradual land use change cannot be ruled out. Trend analysis Over each of the three periods analysed, annual flows decreased significantly, although in the short 1960-73 period, the significance of this trend was weak (p>0.1). Most analyses of seasonal values also produced significant
23
decreases with time. The most significant trend was found in May-July data (p=0.03) for both the long periods analysed (1862-1958 and 1904-1958), while February-April flows also showed reasonably strong significance in the recorded decreases (p=0.06-0.07). Correlations between annual and seasonal flows and precipitation are explored in Section 5.3 (and provide at least a partial physical explanation for the changes observed here). Further investigation of trends in seasonal precipitation totals and intensities would no doubt shed further light on the patterns observed, but have not been possible within the time constraints of this project. Table 5.1 shows the seasonal mean flows of the springs, and it can be seen that these significant decreases occur on the falling limb of the annual hydrograph. The two dry seasons (MJJ and ASO) have very similar mean flows while the same is true of the two wet seasons (NDJ and FMA), so the negative trend affects one wet and more especially the following dry season. Season Mean flow (l s-1)Q1 (FMA) 22.0Q2 (MJJ) 12.3Q3 (ASO) 13.2Q4 (NDJ) 24.4
Table 5.1. Mean flow in the four adopted seasons Analysis of the trend in the two months with lowest long-term average flows confirms the downward trend in these two months, June and July (Figure 5.5). Using data from all available years, June downward trend is significant at 0.02 and July is significant at 0.06.
0
10
20
30
40
50
60
70
1862
1867
1872
1877
1882
1887
1892
1897
1902
1907
1912
1917
1922
1927
1932
1937
1942
1947
1952
1957
1962
1967
1972
1977
1982
Mon
thly
mea
n flo
w (l
s-1
)
JuneJuly
Figure 5.5. Black Springs June and July flows through period of record
24
5.3 Harlaw precipitation correlations with Black Springs flows The results of the preceding section point strongly towards further investigating the control exercised by precipitation. The possibility remains at this stage of the analysis that precipitation is the dominant control accounting for variability in the spring flow data. However, one difficulty is in knowing what period(s) would be most appropriate for characterising precipitation in a way which best explains stream flow variance. A number of complementary approaches have therefore been used to investigate this link. Shift in response over time A further analysis was undertaken in order to assess whether low flow response was varying in relation to antecedent precipitation. If leakage was increasing with time, this analysis should allow such a trend to be seen, by demonstrating a decrease in flow over time for some given precipitation input. Plots were prepared to relate the minimum monthly flow to the total precipitation over preceding n-month periods (including the month of the minimum flow), where values of n = 1 to 12 months at one-month intervals were investigated. Coefficients of determination were used to identify the length of precipitation period best suited to analysis. This was found to be 7 months (r2 = 45%). Figure 5.6 shows data plotted by decade relating this 7-month precipitation to the monthly mean flow at the end of the period.
0
2
4
6
8
10
12
14
16
18
20
0 100 200 300 400 500 600 700 800 900
7-month precipitation (mm)
Mea
n flo
w in
drie
st m
onth
of y
ear (
l s-1
)
1900s1910s1920s1930s1940s1950s1960s1970s
Figure 5.6. Mean flow and 7-month precipitation for the month of lowest flow in each calendar year Figure 5.7 presents a simplification of these results, providing the mean decadal precipitation and mean decadal flow using the data presented in Figure 5.6. While there has been a gradual decrease in mean decadal flow, it has been accompanied by a mean decrease in precipitation as noted in other analyses above. Figure 5.6 provides no suggestion that flow for a given
25
precipitation input has been decreasing with time. This is a key finding, and is based on flows at the time of each year when (a) resource availability is most scarce, and (b) flows are less than in any other month in that year, so that response to recent precipitation is likely to be only a small fraction of the total flow. Under such conditions, system response might be expected to be at its most predictable, and sampling error should be at a minimum since little day to day variability would be expected. The decline in precipitation over the period considered here (1904-1982) is noteworthy. In Section 4.1, a decline in the Blackford Hill record over the same period is also noted, validating the trend shown, although the decline at Harlaw is more pronounced than at Blackford Hill (10 km to the north-east of Harlaw). While interannual variability can be accounted for by variability in synoptic conditions, this can also lead to local differences in precipitation totals, owing to differences in the exposure of individual gauges. Since 1982, conditions over all of Scotland have become wetter, particularly in the late 1980s and early 1990s (see e.g. Black and Burns 2002). Figure 5.7 Decadal means of the data presented in Figure 5.6. Lag time and seasonal comparisons Complementing the preceding low flow analysis, Figures 5.8 and 5.9 show the effect of plotting one and two of the winter seasons’ precipitation against the mean flow for the whole of the water year (October-September) in which they fell, offering explanation of 28% and 45% of the variance in the flow data. The seasonal effects of evapotranspiration and limits of infiltration capacity, especially important on granite, are expected to limit the total amount of flow variance which can be explained by seasonal precipitation data. Nevertheless, use of the 6-month precipitation data provides a statistical
10
12
14
16
18
20
22
350 375 400 425 450 475 500
7-month precipitation (mm)
Mea
n flo
w o
f dri
est m
onth
in y
ear
1900s
1910s1920s
1930s
1940s
1950s
1960s
1970s
0
2
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12
350 375 400 425 450 475 500
7-month precipitation (mm)
Mea
n flo
w o
f drie
st m
onth
in y
ear (
l s-1
) 1900s
1910s1920s
1930s
1940s
1950s
1960s
1970s
26
performance similar to use of 7-month precipitation values with the low flow data in Figures 5.6 and 5.7. A series of analyses were then undertaken seeking to explain seasonal flows by reference to preceding seasonal precipitation amounts. The results are shown in Figures 5.10-5.15.
y = 0.0352x + 13.092R2 = 0.2805
0
5
10
15
20
25
30
35
0 50 100 150 200 250 300 350
Feb-Apr Precipitation (mm)
Oct
-Sep
Mea
n Di
scha
rge
(l s-1
)
Figure 5.8. Water year flow vs February-April precipitation total
y = 0.0148x + 3.3799R2 = 0.4498
0
2
4
6
8
10
12
14
16
0 100 200 300 400 500 600 700
Nov-Apr Precipitation (mm)
Oct
-Sep
Mea
n D
isch
arge
(l s
-1)
Figure 5.9. Water year flow vs November-April precipitation total
27
y = 0.05x + 8.56R2 = 0.15
0
10
20
30
40
50
60
0 100 200 300 400 500 600rainfall mm
flow
(l s
-1
Figure 5.10 All seasons flow vs same season’s precipitation
y = 0.07x + 3.75R2 = 0.33
0
10
20
30
40
50
60
0 100 200 300 400 500 600rainfall mm
flow
(l s
-1
Figure 5.11 All seasons flow vs preceding season’s precipitation Using the coefficient of determination (r2) as a measure of explanation in the dependent variable flow, it can be seen that lagging all seasons’ flows behind precipitation by one season leads to a higher level of explanation than comparing precipitation with the flow in the same season, with r2 rising from 15% to 33%. However, surprisingly perhaps, comparing flow with precipitation for the same season, based on only one season of the year,
28
leads to r2 values of 36% for May-July and November-January and 54% for the other two seasons February-April and August-October. Repeating these analyses with a one season lag produced markedly lower r2 values in all seasons. In interpreting these results, the superior overall performance over an all-seasons analysis is thought to be a result of analysing less noisy data sets (only like seasons are combined in each of the seasonal analyses). The relatively poor performance in May-July (Figure 5.13) may be the result of flow in that dry season largely being a function of total recharge in the preceding winter, while similarly weak performance in November-January may be a result of some flow values appearing low in relation to the recorded precipitation because of snow falling and lying on the catchment without melting (Figure 5.15).
y = 0.09x + 8.23R2 = 0.55
0
10
20
30
40
50
60
0 50 100 150 200 250 300 350rainfall mm
flow
(l s
-1
Figure 5.12 February-April flow vs same season’s precipitation
29
y = 0.05x + 2.65R2 = 0.38
0
10
20
30
40
50
60
0 50 100 150 200 250 300 350
rainfall mm
flow
(l s
-1
Figure 5.13 May-July flow vs same season’s precipitation
y = 0.07x - 2.10R2 = 0.53
0
10
20
30
40
50
60
0 100 200 300 400 500 600
rainfall mm
flow
(l s
-1
Figure 5.14 August-October flow vs same season’s precipitation
30
y = 0.09x + 5.46R2 = 0.38
0
10
20
30
40
50
60
0 100 200 300 400
rainfall mm
flow
(l s
-1
Figure 5.15 November-January flow vs same season’s precipitation Some lag is evident in the response of the system, but perhaps the reason why correlations appear to be reasonably strong with a range of lag times is that there is more than one mode of response in the Black Springs system, ranging from perhaps just a few weeks to a few months. This would be supported by the noticeable week-to-week variability within the observed data and is entirely compatible with the identification of a seven-month precipitation accumulation period in the first part of this section. The significance of these precipitation analyses together is that land use and system leakage appear to have had no systematic detectable effect, and that the data are good for analysis throughout the period of record in terms of flow response to climatic inputs. Scatter within the graphs is therefore attributed to random climatic effects, such as the distribution of precipitation intensities within the period leading to an observed flow and variability in evaporative loss e.g. due to time of year and temperature and sunshine conditions. Regional climate change studies will indicate the nature of change expected in these aspects of precipitation and other climate variables over the coming decades. 5.4 Double mass plots Figures 5.16-5.18 show double mass plots for each of the three measured groups of springs against precipitation. A double mass plot allows continuity of response to be assessed visually. Precipitation data from the Harlaw raingauge provide an appropriate reference point in this case, since the preceding sections have illustrated that there is significant precipitation
31
variability between years. Use of the double mass plots therefore allows an assessment of whether spring flow is being maintained relative to precipitation. Put another way, it allows assessment of whether there is continuity of response. This is important in the context of this project since, if continuity is demonstrated, it suggests that continuity could be assumed in the future, and that calibrations based on these data could be used for climate change impact modelling purposes. Inspection of the plots shows a generally steady gradient for the Westrig, Bavelaw & Listonshiels and Black Springs (Figure 5.16), but a noticeable change in gradient in the Colzium, Crosswood & North Listonshiels (Figure 5.17) plot (around 1923). Either side of that change, the Colzium, Crosswood & North Listonshiels data do seem to plot at a steady gradient also, but the change suggests that in the early 1920s a change took place which led to a lower amount of spring flow per unit precipitation. There is not a strong link between this finding and the time series analyses for Colzium, Crosswood & North Listonshiels, but nevertheless, the suggestion must be made that around that time, these springs either developed a leak which has not be rectified, or may have been subject to some land use change which leads to a reduction in spring flows. Alternatively perhaps, one or more of the springs changed naturally, such that the point of flow emergence changed and has not been capped. For Black Springs, the even gradient of the double mass plot in Figure 5.18 and the precipitation correlations in Section 5.3 provide independent and complementary assessments of the stability of hydrological response to precipitation over time. This is a strong endorsement of the reliability of the Black Springs data set, and gives encouragement to its further use. Only a double mass plot is available for Westrig, Bavelaw & Listonshiels, however the results from this analysis also indicate stability of response, and so should also be taken as an encouragement for further study, including precipitation correlations over appropriate accumulation periods, as illustrated for Black Springs.
32
0
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40
60
80
100
120
140
160
180
0 10000 20000 30000 40000 50000 60000 70000
Harlaw precipitation (mm)
Wes
trig
, Bav
elaw
& L
isto
nshi
els
flow
(MCM
)
Figure 5.16 Double mass plot for Westrig, Bavelaw & Listonshiels (Plot symbols identify continuous periods of data. Average annual precipitation and flow values assumed in gap years (1959+1963). Straight line provided to allow assessment of uniformity of relationship between precipitation and flow.)
33
0
50
100
150
200
250
300
350
0 10000 20000 30000 40000 50000 60000 70000
Harlaw Precipitation (mm)
Colz
ium
, Cro
ssw
ood
& N
List
onsh
iels
flow
(MCM
)
Figure 5.17 Double mass plot for Colzium, Crosswood & North Listonshiels (Plot symbols identify continuous periods of data. Average annual precipitation and flow values assumed in gap years (1959+1963). Straight line provided to allow assessment of uniformity of relationship between precipitation and flow.)
34
0
5
10
15
20
25
30
35
40
45
50
0 10000 20000 30000 40000 50000 60000 70000
Harlaw Precipitation (mm)
Blac
k Sp
rings
flow
(MCM
)
Figure 5.18 Double mass plot for Black Springs (Plot symbols identify continuous periods of data. Average annual precipitation and flow values assumed in gap years (1959, 1974-78). Straight line provided to allow assessment of uniformity of relationship between precipitation and flow.)
35
5.5 Selected drought events: Black Springs The results of Sections 5.3 and 5.4 suggest that the most notable droughts of the record may be examined and compared. Time constraints allow only the briefest of illustrations here, but those concerned with management of these springs in the future are encouraged to undertake further analyses as required, e.g. using the data supplied with this report. Figures 5.19-5.21 show differences in the rate of fall of the spring flows, with the 1955 and 1960 curves providing similar recession curves, while the 1972 curve falls more rapidly and with an interruption in the observed data, following a winter with minimal recharge. It may be possible to calculate a decay constant for the rate of fall, which would provide ready progress in quantifying the behaviour of the springs.
0
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02/0
7/19
54
02/0
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55
Flow
(l s
-1)
0
10
20
30
40
50
60
70
80
Wee
kly
prec
ipita
tion
(mm
)
Figure 5.19 1955 low flow period: Black Springs flow (continuous line) and Harlaw weekly precipitation (vertical columns)
36
0
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07/0
8/19
59
07/0
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07/1
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60
Flow
(l s
-1)
0
10
20
30
40
50
60
70
80
Wee
kly
prec
ipita
tion
(mm
)
Figure 5.20 1959/1960 low flow period: Black Springs flow (continuous line) and Harlaw weekly precipitation (vertical columns)
0
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40
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60
06/0
8/19
71
06/0
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Flow
(l s
-1)
0
10
20
30
40
50
60
70
80
Wee
kly
prec
ipita
tion
(mm
)
Figure 5.21 1972 low flow period: Black Springs flow (continuous line) and Harlaw weekly precipitation (vertical columns) The data presented in these plots will be of considerable value in any future attempt to calibrate the response of these springs to climatic events. Often hydrologists have only relatively short periods of data for calibration, so to have extreme events at a weekly time-step, from a period of almost 80 years, allows scope for rigorous testing of model structures and parameter values. Such modelling can then be used in prediction of response to future climatic conditions, using downscaled data from general circulation models. Unfortunately, the 1959 low flow event occurs at the end of a gap in the data, and may be of limited value in modelling.
37
6 REVIEW OF OTHER SOURCES OF FLOW INFORMATION
At present, the annual ledger series listed in Appendix 1 are the only source of long-term historic spring flow data known to the authors from anywhere in Scotland. Enquiries have been made through contacts in Scottish Water, SEPA, consultancies and research institutions, but no details of any new sources have come forward. Responses to the same enquiries do point to the assumed existence of operations logs required to be kept under Reservoirs Act legislation. No respondent has come forward with details of where historic records of this kind are kept by any operating authorities, but it is understood that computerised systems are used for the recording and archiving of contemporary data. Much remains to be done therefore to identify any source of further records which could be used for future calibration of groundwater models, and further efforts to identify any hidden or forgotten records would seem to be warranted. The possibility must be recognised however that large volumes of records similar to those used for the Edinburgh area in this study have been lost from elsewhere in Scotland – indeed perhaps for most areas. This would represent a highly regrettable loss of potential. A converse view is that of those consulted about the existence of these records, only two knew of the existence of the Edinburgh records. Therefore, the problem may be how to access people who would know of any relevant records held elsewhere.
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7 DISCUSSION: UTILITY OF THE SPRING FLOW SERIES
7.1 Use of North Pentlands spring flow data for climate
change or other purposes The primary question in this study has been whether the spring flow records analysed give reason to support use of these and other similar records in the future. In order to answer the question, assessments of data quality are needed, particularly whether there is stability of hydrological response over time, and such assessments have been provided principally in Sections 5.3 and 5.4. The principal anticipated future use would involve assessing how these springs would respond to climate change. In fact, the analyses provide some very encouraging conclusions in this regard:
• The response of Black Springs to precipitation does appear to have been uniform over the extended period 1904-82, as indicated by precipitation correlations and a double mass plot.
• The response of the Westrig, Bavelaw and Listonshiels Springs also appears to be essentially stable over the period 1904-82, as revealed by a double mass plot, though it is not quite a straight as that for Black Springs. No precipitation correlation plots have been provided, but it is suggested on the basis of Section 5 that the double mass plot appears to be a more discerning test than the precipitation correlation.
• The response of the Colzium, Crosswood & North Listonshiels Springs appears to have changed in the 1920s, but after accounting for precipitation trend, appears to have been stable since (see Figures 5.1 and 5.17). This may therefore still provide some calibration opportunity. Use of such a calibration would require use of the assumption that no further change would occur in future, which would appear reasonable so long as land use changes and new leaks can be guarded against.
As the recorded spring flows do demonstrate generally that they have responded to precipitation uniformly over the period of records, then this provides an argument that the development of models to simulate hydrological response to changing climatic conditions should be possible. Such model development will need to simulate the evaporative effects of temperature and radiation changes in controlling losses from the ground surface; such activity is a key component of much climate change modelling work already under way. Models using these data will benefit from calibration over a long period, and including some rare drought episodes not captured in more recent records. For application of results to the future, the springs must be maintained to the condition that they had up to the 1980s/90s (at which point we understand that maintenance activities were abandoned). It is assumed that this would be possible, and indeed desirable if the springs are to be brought back into production.
39
7.2 Future monitoring of the springs (all spring groups) Future monitoring of the North Pentland springs (Westrig, Bavelaw & Listonshiels; Colzium, Crosswood & N Listonshiels; and Black Springs), would serve two principal purposes:
• It would allow any change in the period since 1982 to be quantified, and may point to the existence of leaks which could be looked for and repaired.
• It would allow response to climatic shifts to be quantified, thereby continuing to support the benefit of future model calibration.
Continuation of the historically used volumetric flow measurement methods offers the attraction of consistency. Though it could be perceived as ‘old-fashioned’, it is quick in practice and dependable. The necessary infrastructure is thought to be in place and to need no maintenance. The only equipment an operator would require is a stop-watch and the look-up table for the measuring house in question (such a table is known to have still been in use in 1999). Operator visits at a weekly interval would required. It is only the staff time cost issue which might be used to argue for an alternative measurement strategy. If this were the case, in-pipe ultrasonic measurement systems should be capable of providing the necessary data, and would in addition provide data at a far finer time step than has been available in the past, e.g. hourly. If such systems are used, the facility to use the volumetric flow measurement equipment in the measuring houses should still be used at the times of instrument download, to provide a check on the quality of the logged data. 7.3 Use of comparable data from other parts of Scotland Enquiries about further sources of historic data from other parts of Scotland have so far revealed little to give hope of similar series from outwith the former Edinburgh Water Works source areas. While historic rainfall series are available for many locations, reservoir records are very rare and records of other springs flows are not available. Nevertheless, further analysis of the Westrig, Bavelaw & Listonshiels, and the Colzium, Crosswood and North Listonshiels series can usefully be done. Appendix 1 reveals that a separate series for just Colzium and Crosswood (without North Listonshiels) is available for apparently 40+ years, and series also exist for Swanston and Comiston Springs; these also warrant further investigation and analysis. Enquiries will continue after the completion of this report to assess whether any comparable records can be obtained from other parts of Scotland, and an update issued if any new information is found.
40
8 CONCLUSIONS AND RECOMMENDATIONS 8.1 Conclusions This study has sought to assess the potential of historic records of spring flow to support the calibration of numerical models for assessing yield in response to past and future climatic conditions. Specifically, the objectives of the study were to (1) assess the relationship between the spring flow data and associated rainfall data; (2) identify step changes or trends in the data and, where possible, their causes; and (3) assess the value of the data. The study focused primarily on data from Black Springs, the smallest of the three separately-measured sources represented in the records available to the study. Statistically significant downward step changes and significant trends were found in annual and seasonal time series, with a lack of consistency among the dates at which step changes occurred. Correlation analyses, and the use of double mass plots for all three spring groups, revealed a common cause of flow reductions in the form of reducing precipitation over the period 1904-1982 for which most data were available. For Black Springs, a highly responsive spring system, complementary evidence from precipitation correlation and double mass plots indicated that over the 1904-1982 period, the hydrological response of the springs was essentially uniform. A double mass plot for the Westrig, Bavelaw & Listonshiels time series (representing a highly-buffered system) demonstrated a relatively uniform response over the same period, while data for Colzium, Crosswood & North Listonshiels (slightly less well buffered) indicated a change in response around 1923, but reasonably consistent behaviour since then. All three spring groups are therefore found to offer utility for modelling, though the latter two should be subject to more detailed analysis, e.g. correlation, to obtain a more detailed assessment of their performance, before being used for modelling work. Such work would usefully include assessment of the effects of climate changes predicted for the coming decades of the 21st Century. The greatest (and indeed most fundamental) obstacle to further application of such spring flow data appears to be data availability: an email survey to identify similar records for other parts of Scotland was essentially fruitless, save for identifying a small number of additional records for the Edinburgh area. Further efforts should therefore be made in trying to identify any further such records, which would help improve the understanding of spring flow response to extreme dry periods in other areas, and which could help enhance the basis on which the effects of climate change might be assessed in future. Further recommendations to progress the work are made in the following section.
41
8.2 Recommendations for further work
1. Extract new spring flow series from ledgers for Colzium and Crosswood (only), Swanston and Comiston.
2. Undertake analyses similar to those reported in detail for Black
Springs, for Westrig, Bavelaw & Listonshiels and for Colzium, Crosswood & North Listonshiels, and for the series noted at 1 above. This should allow quality issues to be addressed, e.g. is there evidence of long-term shift due to leakage or other causes, and if successful, should allow further analyses to be undertaken to characterise response to precipitation over appropriate period(s).
3. Update all existing series with any data available from Scottish Water.
Data are reported to be available for 1983-2002 but perhaps only in aggregate form for all of the groups of springs considered in this report, which would probably offer little value.
4. Access any available Scottish Water chemistry data from the North
Pentland springs and analyse to examine whether a decoupling occurs in summer with older water (from Devonian), or older young water (from talus) emerging in baseflow conditions. Residence time indicators would assist in this work.
5. If such data as described at 4 do not exist, student projects and/or a
one-year monitoring programme, particularly to identify seasonal changes, may help to further understand the relative proportions of deeper and shallow groundwater.
6. Continue monitoring sources which have been monitored over most of
the past century or longer, in order to provide an empirical basis for assessing and modelling future effects of climate change.
7. Consult a reference source in the National Library of Scotland which
has come to light only in the closing stages of the project, and which might give more insight into the construction of the springs (Colston, 1890).
8. Develop numerical models to quantify the effects of variability in
seasonal precipitation totals and intensities on spring flows.
9. Obtain appropriate storage arrangements for the ledgers presently held at Fairmilehead, i.e. in a controlled environment offering protection from damp and extremes of temperature.
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REFERENCES Black, A R (2003) Pentland Springs – an untapped store of knowledge. Abstract of paper presented to joint meeting of the Hydrogeology group of the Geological Society of London and the Scottish Hydrological Group, November 2003, Stirling. Available http://www.geolsoc.org.uk/template.cfm?name=Groundwater_in_Scotland Black, A R and Burns, J C (2002) Re-assessing the flood risk in Scotland. The Science of the Total Environment, 294, 169-184. Black, A R and Cranston, M D (1999) Derivation of an 88-year inflow record for Talla Reservoir, Scotland, with special reference to low flows. J.CIWEM, 13, 423-429 Colston, J (1890) The Edinburgh and District Water Supply. Privately Published, Edinburgh. Kundzewicz and Robson (Eds) (2000) Detecting trend and other changes in hydrological data. WMO/TD-No.1013. World Climate Programme Data and Monitoring WCDMP-45. WMO, Geneva. MacDonald, A M and Ó Dochartaigh, B (2005) Baseline Scotland: an overview of available groundwater chemistry data for Scotland. British Geological Survey Technical Report CR/05/239N. Tait, W A P (1906) The Talla Water-Supply of the Edinburgh and District Waterworks. Mins Proc Inst Civ Eng 167, 102-152. BIBLIOGRAPHY Jardine, R W (1993) James Jardine and the Edinburgh Water Company. Newcomen Soc Trans 64, 121-129. Leslie, A (1883) The Edinburgh Waterworks. Mins Proc Inst Civ Eng, 74, 91. Reid, W C (1913) The Yield of Various Catchment-Areas in Scotland. Mins Proc Inst Civ Eng. 194.
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Appendix 1: Ledger series held at Scottish Water’s Fairmilehead Works Name Earliest
year Latest year
Notes
Crosswood Reservoir 1904 1982 Harperrig Resr 1904 1982 Includes Crosswood, Colzium Springs:
time to raise water 1’ over an area of 100 sq ft (Thrashiedean Cistern) ~1940-1982
North Pentlands 1880 1915 Data include Clubbiedean, Torduff, Juniper Green Pipe, Kinleith Mill Water Springs
Torduff, Clubbiedean, Bonaly
1945 1982
Fortnightly Returns 1894 1911 Seems similar contents to N Pentland Reservoir volumes
Swanston/Swanston Works & Comiston
1906 1977 Greencraig Well Spring; Howden/Greencraig Burn; Peewit & Sandglass; Swan & Fox; Hare Springs
Rosebery & Edgelaw 1894 1982 Harlaw & Threipmuir 1897 1982 Source of data for this study; also
includes reservoir data Westrig Cistern: 200sq ft area: Listonshiels & Bavelaw; Colzium, Crosswood & N Listonshiels. Black Springs Cistern: 60.25 sq ft area: Black Springs only. Time for 1’ rise in each.
Gladhouse Reservoir 1896 1982 Talla Reservoir 1907 1982 Fruid Reservoir 1969 1982 Mortmore Reservoir 1904 1982 Glencorse/Loganlea 1904 1982 Bangour Village Water Works
1935 1948
Morton Reservoirs/Filters
1975 1982
Talla Resr Rainfall & Evap
1907 1973
Talla Resr Rainfall 1974 1982 Landowners Pipe 1904 1949 Firhill Tank Penicuick Works Rosebery Filters Craiglockhart Tank Fairmilehead Sand Filters
Fairmilehead Works/Filters
Alnwickhill Works/Filters
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Appendix 2 Assessment of approximate catchment area of Black Springs 1. Estimate mean annual evaporative loss (mm a-1) Two natural gauged catchments are available in the local area, with annual loss figures as follows:
Braid Burn @ Liberton 419 mm a-1 North Esk @ Dalkeith Palace 396 mm a-1
Assume a round number value of 400 mm a-1 2. Calculate approximate annual catchment average runoff depth using formula
runoff = precipitation - losses Estimated annual rainfall over catchment 900 mm a-1 Annual evaporative loss 400 mm a-1 Available runoff depth if 100% drains to Black Springs as groundwater 500 mm a-1 3. Estimate catchment area using formula area = volume ÷ depth Average annual runoff volume from Black Springs catchment 566056 m3 a-1 Average annual runoff depth 500 mm a-1 ∴Catchment area = volume ÷ depth = 1132112 m2 or 1.13 km2 4. Assuming only 50% of the runoff from the catchment percolates into groundwater system, inferred catchment area = 1.13 km2 x 2 = 2.26 km2 Lower and upper bound effective catchment area values therefore taken as 1.13 km2 and 2.26 km2 respectively.
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Appendix 3: Black Springs: Results of statistical analyses Von Neumann Ratio test - tests the independence of successive observations of some quantity (Kundzewicz and Robson, 2000). 1904-58: the longest gap-free period in this record. Purpose of test is to assess underlying behaviour of the system, thereby assessing applicability of tests of step change and trend (which assume independence). Series tested:
• Annual data • Seasonal data for 3-month seasons beginning February, May, August
and November (because this choice leads to lowest within-season variability between monthly flows)
Results: The null hypothesis is that observations are independent unless the test suggests otherwise. None of these tests led to rejection of the null hypothesis at significance levels of 30% or less. The values are therefore assumed to be independent, a finding which accords with visual inspection of the series. The test was implemented using a newly-written Excel spreadsheet, which was successfully tested with purpose-built data sets to ensure that independence could be rejected where appropriate. Test of step change significance This test seems perhaps a little unnecessary, given the striking evidence of the flow duration curves presented in the first progress report. Nevertheless, application of an appropriate test will quantify the significance of the differences which exist between different periods within the observed time series. The same annual time series as listed above will be used:
• Annual data • Seasonal data for 3-month seasons beginning February, May, August
and November The distribution-free CUSUM test was chosen since some of the data sets show skew, and also because this test needs no known time of change to be supplied. Kundzewicz and Robson (2000) identify this test along with the median change point test, the Mann-Whitney test and the Kruskall-Wallis test as available options. Years of step change have been obtained by using the approximate year of maximum cumulative departure in annual values from the median, using a scoring system which scores a below-median value as -1 and a greater-than median value as +1. Where a maximum occurs twice in close
46
succession, the intermediate year between maxima is recorded, e.g. maximum deviations in 1968 and 1970 would be recorded as 1969. Results are shown in Table B1, along with results of trend analysis. Significance of trend Linear regression lines were fitted using Excel, using flow as dependent and year as independent variables. This allowed the sign of the regression equation (+ or – with respect to time) and its significance to be obtained using a t-test. The results are shown in Table B1.
Series Period Significance level of step
change (approx years
of step change)
Sign and significance
level of regression
Annual spring flow 1862-58 0.01 (1882, 1892, 1932,
1938)
- 0.03
Annual series of seasonal Feb-Apr flows
1862-58 0.01 (1927) - 0.06
Annual series of seasonal May-Jul flows
1862-58 0.01 (1890, 1909)
- 0.03
Annual series of seasonal Aug-Oct flows
1862-58 NS - NS
Annual series of seasonal Nov-Jan flows
1862-58 0.01 (1882) - NS
Annual spring flow 1904-58 0.01 (1932, 1938)
- 0.10
Annual series of seasonal Feb-Apr flows
1904-58 0.01 (1927) - 0.07
Annual series of seasonal May-Jul flows
1904-58 NS - 0.03
Annual series of seasonal Aug-Oct flows
1904-58 NS + NS
Annual series of seasonal Nov-Jan flows
1904-58 0.02 (1939) - NS
Annual spring flow 1960-73 0.01 (1968) - 0.20 Annual series of seasonal Feb-Apr flows
1960-73 0.02 (1967) - 0.20
Annual series of seasonal May-Jul flows
1960-73 0.20 (1963) + NS
Annual series of seasonal Aug-Oct flows
1960-73 0.01 (1968) - NS
Annual series of seasonal Nov-Jan flows
1960-73 0.01 (1969) - 0.01
Table B1. Results of step change and trend analyses NS: not significant
Appendix 4: Data CD Time series for the following are included on the CD provided as a Microsoft Excel file. Weekly spring flow measurements for:
• Black Springs 1904-82 • Westrig/Bavelaw & Listonshiels 1904-82 • Colzium, Crosswood & N Listonshiels 1904-82
Monthly averages of flow measurements for Black Springs 1862-1982 Daily rainfall observations for Harlaw 1904-82 Supplementary notes are included in the Excel file.
