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Results of a Water Chemistry Study of Loch Ness

Reproduced with the permission of the Scottish Naturalist
Copyright: May be used for private research. All other rights reserved

School of Applied Sciences,
University of Wolverhampton

In May 1992 students from the University of Wolverhampton carried out water sampling and chemical analysis at Loch Ness, to consider the logistics and possible value of such a study.

Loch Ness presents considerable logistic problems because of the size and nature of the loch and the catchment.  Maitland (1981) divided the catchment into four sub-catchments, based on the major drainage basins (see Figure 1, 7K map).  These sub-catchments can themselves be considered as diverse, because of the climatic domains, regional geology and land classification they span.

This short paper presents the results of the chemical analysis of the water samples taken.  A useful statistical method is suggested to establish a sampling strategy which could be representative of all the inputs to Loch Ness.


Sample Collection
Samples were collected from all the input streams, the output (River Ness) and both the North and South Basins of the loch, and the sampling sites are detailed in Figure 2 (9K map).  Glass bottles were used to collect the samples, which were stored in a domestic refrigerator prior to transport to Wolverhampton for analysis by Induction Coupled Plasma.  A broad scan programme was used for the elements shown in Figure 3: sodium (Na), magnesium (Mg), iron (Fe), calcium (Ca), manganese (Mn), zinc (Zn), nickel (Ni), copper (Cu) and phosphorus (P).


The detailed results presented in Figures 3a, 3b, 3c (15K tables) consist of nine variables on samples ultimately obtained from 82 sites; at site numbers 16, 19, 20 and 28 the stream-beds were dry at the time for collection, and although numbers 68 to 84 were allocated in advance, no suitable sites for these were actually found.

Vol:105 The Scottish Naturalist: Results of a Water Chemistry Study of Loch Ness p51

In an attempt to elucidate this complex data set, simultaneous R-mode and Q-mode factor analysis was applied.  R-mode and Q-mode factor analyses have previously been used in various studies to explore multivariate relationships within suitable data sets (Davies, 1986).  R-mode factor analysis explores the relationship of the variables, while Q-mode factor analysis attempts to explore relationships between the samples.  The methods are based on the calculation of eigenvectors which can be plotted on two-dimensional factor diagrams.  The application of simultaneous R-mode and Q-mode factor analysis extracts a common set of factors of the variable and sample factor loadings, which are relative to the same set of factors.  Variable and sample factor loadings can therefore be plotted in the same two-dimensional factor space.

A discussion of the mathematical procedure involved is given by Zhou, Chang and Davies (1983), and a worked example can be found in Walden (1990). 

The results of the first application of simultaneous R-mode and Q-mode factor analysis are shown on Figures 4 and Figure 5 (3K graphs).  These are identical factor space plots, but have been separated to give a clearer representation of the results.  Figure 4 gives the variable loadings, and Figure 5 gives the sample loadings.  The variance of the first two factors is 44.62%, which implies that the factor solution is not significantly reducing the dimensionality of the data set. 

Figure 4 implies that certain elements show signs of correlation, eg. Na, Mg and Ca have negative factor 2 loadings. 
Figure 5 cannot be readily interpreted; it does, however, imply certain groupings of the samples.

In future it is proposed to divide the original data set into two groups of variables, based on the results in Figure 4, and to apply simultaneous R-mode and Q-mode factor analysis to the two data sub-sets.

The samples will also be divided into two groups, based on the results in Figure 5: (a) positive on factor 1 loadings, and (b) negative on factor 1 loadings.  Using the original data, simultaneous R-mode and Q-mode factor analysis will also be applied to these two further data sub-sets.

 The results presented here are not yet complete, because of the author's commitments elsewhere.  It is believed, however, that the method proposed offers considerable potential for catchment-based studies of water chemistry.  To study a catchment as large and diverse as Loch Ness requires considerable resources which

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may not be readily available.  However, it is considered that an integrated desk-top study, such as Maitland (1981), and a one-off statistical analysis such as this, could develop a viable sampling strategy. 

The author would like to thank his colleagues and students at the University of Wolverhampton for all the work undertaken, and the Loch Ness and Morar Project for making this study possible.


Davies, J.C.  (1986).  Statistics and Data Analysis in Geology.  London: Wiley.

Maitland, P.S.  (1981).  Introduction and catchment analysis.  In:  The Ecology of Scotland's Largest Lochs: Lomond, Awe, Ness, Morar and Shiel. (Ed. P.S. Maitland).  Monographiae Biologicae, 44: 1-27.  The Hague:  Junk.

Walden, J.  (1990).  The Use of Mineral Magnetic Analysis in the Study of Glacial Diamicts.  Ph.D. Thesis, University of Wolverhampton.

Zhou, D., Chang, T. and Davies, J.C.  (1983).  Dual extraction of R-mode and Q-mode factor solutions.  Mathematical Geology, 15: 581-606.

Received May 1993


Mr. Peter H. Jenkins, School of Applied Sciences,

University of Wolverhampton, Wulfruna Street,





Water Chemistry of Loch Ness