An Assessment of the S u i t a b i l i t y of t h e Environment Agency’s Water -Qual i ty C lass i f ica t ion System for Use in Urban Catchments A Green, BSc, MSc a n d H. Faulkner, BSc, MSc, PhD*

Grade

A B C D E Ft

A b s t r a c t

DO (% saturation)

IO%ile

80 70 60 50 20 -

Despite the increasing range of water-quality indicators, the classification and target-setting strategy which has been adopted by the Environment Agency for England and Wales is dominated by the assessment of water chemistry at low flow. Using the example of Pymme’s Brook in north London, this paper examines the suitability of such data for classifying the quality of urban watercourses and its ability to reveal quality changes. The data expose a weakness in the Environment Agency’s methodology, because they suggest that, when used alone, chemical monitoring leads to water quality being greatly over-estimated and inappropriate targets being set. It is therefore recommended that other quality indicators should be fully integrated into the assessment system in order to overcome these problems.

Key words: Chemistry; classification; urban catchment; water quality.

BOD (mg/l)*

90%ile

2.5 4 6 8

15 -

Introduction

Amm. N (ms/l)

90%ile

0.25 0.6 1.3 2.5 9.0 -

Background The water quality of rivers in England and Wales was first classified comprehensively in 1970. However, a consist- ent methodology was not adopted until 1977 when the National Water Council (NWC) published its review of classification and discharge consent policy(’). This was based on the concentration of BOD, dissolved oxygen (DO) and ammoniacal nitrogen (amm. N), but there was scope for including a wide variety of other chemicals, if necessary. Class boundaries were established on the basis of contaminant levels required to protect different watercourse uses, and it became the norm to define the water quality of a river by specifying its NWC class(2). This was also the first time that a classification system had been used as a basis for setting water-quality objec- tives, because it established the principle that there should be no deterioration from current classification levels.

By the early 1990s, various inadequacies in the NWC system had emerged because (i) a degree of subjec- tive interpretation was required, and (ii) users were often unclear as to the distinction between its classification function and its use-related objective-setting functiod2). As a result, it was recommended that the two functions should be separated, by using a ‘general quality assess- ment’ (GQA) system for defining water quality, whilst

independently setting a range of use-related ‘statutory water quality objectives’ (SWQOS)(~) - a system which was later developed by the (then) National Rivers Authority)@).

The GQA scheme is intended to take a holistic approach to defining water quality by including the chemical, biological, nutrient, and aesthetic components of the status of a river, although to date only the chemical and biological elements have been implemented. Chemi- cally, only three determinants (BOD, DO and amm. N) are measured and used to grade a river’s quality on a scale A-F (Table 1). A more extensive list of determinants was rejected because (a) the cost would be prohibitive, and (b) new chemicals are being developed continuously; there- fore an extensive determinant list would have to change regularly - seriously undermining the temporal com- parability of the grading. The biological element also grades rivers on a scale A-F, although the system for doing so has still been only partially implemented. In principle, the ‘river invertebrate prediction and classifi- cation system’ (RIvPACS)(~) should be used to predict the Biological Monitoring Working Party (BMWP) score and ‘average score per taxon (ASPT) under clean con- ditions, and the observed and predicted values combined to produce an ‘ecosystem quality index’ (EQI). However, in the Thames region, an approximate classification based solely on the measured BMWP score of a water- course is used instead(5). In theory, the two assessment techniques should then be combined in order to produce an overall water-quality classification, the strengths of one system overcoming the weaknesses of the other; however, in reality, they are considered separately, with the emphasis being firmly on the chemical results.

When fully implemented, the system which is being introduced to set SWQOs will comprise a series of

Table 1. General qualiv assessment: chemical grading for rivers and canals

Water quality

Good

Fair

Poor Bad

*Research Assistant and Senior Research Fellow respectively, Department of Environmental Sciences, University of Hertfordshire, Bayfordbury Field Station, Hertford, UK.

*Suppressed by adding allylthiourea $i.e. Quality which does not meet the requirements of grade E in respect of one or more determinants

0 J CIWEM, 2000, 14, A p r i l 131

A . Green and H Faulkner on

Table 2. River ecosystem classification water-quality criteria

BOD (mg/l)

90%ile

2.5

- Class Total

ammonia (as N) (ma/l)

90%ile

0.25 RE1

RE2

RE3

RE4

RE5 -

4.0

~

DO (% sat.)

10%ile

80

70

60

50

20

0.6

6.0

8.0

1.3

2.5

15.0 1 9.0

RE refers to ‘river ecosystem’

95%ile

0.021

0.021

0.021

-

-

different use-related quality schedules (stipulated by the Water Resources Act 1991) with a rivers compliance, with cach being assessed separately - the most stringent requirements for each determinant forming the quality target. However, as yet, only the levels for ‘river eco- system’ (RE) use have been established under the Surface Waters (River Ecosystem) (Classification) Regulations 1994@), which stipulate the requirements for five differ- ent classes of river ecosystem based upon a group of determinants extended from those used in the GQA system (Table 2). Therefore, despite the greater range of water-quality monitoring techniques which has been developed over recent years, for historical reasons the EA still relies heavily on the chemical analysis of spot samples taken at low flow for both its GQA system and for setting SWQOs.

Study Catchment Pymme’s Brook rises in rural Southern Hertford-

shire (north of Monken Hadley) before flowing south east through the built-up areas of East Barnet, Arnos Grove and New Southgate, to join the River Lee in Edmonton (Fig. 1). Being on the outskirts of london, for many years most of its 45-km2 catchment has been heavily urbanised - mainly for residential purposes, although there are some industrial sites towards the downstream end of the catchment. The only truly rural area is in the extreme north - the remaining open ground comprising a series of urban parks and recreational spaces. As a result, the river has been considerably altered, so that a large proportion has either been culverted or constrained in a concrete channel; but in East Barnet and Arnos Grove, where the brook flows through a series of parks, the channel has been

PH

ower limit as 5%ile ipper limit i s 95%ile

6.0-9.0

6 .O-9 .O

6.0-9.0

6.0-9.0

-

Hardness (as CaCO,)

( m Q 4

21 0 >10 and 250 >50 and 51 OC

>loo sf 0

>I 0 and 250 250 and sl OC

>loo 51 0

>I 0 and 250 >50 and >lo(

>I 00 21 0

>I 0 and 250 >50 and 21 O(

>I 00 -

Dissolved copper (ue/l)

95%ile

5 22 40

112 5

22 40

112 5

22 40

112 5

22 40

112 -

95%ile

30 200 300 500 30

200 300 500 300 700

1000 2000

300 700

1000 2000 -

maintained in a much more natural state. However, even here it is heavily managed, therefore the channel is regularly cleared and a series of re-oxygenation weirs has been installed to improve water quality(7).

Contaminants enter the watercourse from a range of non-point sources (urban runoff, internal combined sewer overflows and misconnections) at a large number of small surface-water outfalls, and consequently there is a marked water-quality problem resulting from high levels of organic pollution and low concentrations of DO. Many pollutant sources in the catchment are primarily storm driven, resulting in considerable temporal variability in water quality, with pollutant concentrations often peaking during high-flow periods. These events are rarely sampled by current EA sampling procedures and, as a result, it has been suggested that the official water- quality classification for the brook is inappropriate@).

East Barnet Sewerage Scheme In early 1996, work was completed on a low-level

intersecting sewer known as the East Barnet foul-water sewerage scheme. It was commissioned by Thames Water Utilities Ltd in order to address flooding and water- quality issues - specifically the problem of crude sewage discharging to the brook via combined sewer overflows (CSOs). The design specifications were that (a) there should be no surcharge in the main sewers from the one- in-one year event (not overflows), (b) there should be no surface flooding from the one-in-five year event, and (c) the risk of internal property flooding should be lower than one-in-ten years. Accordingly, 3.25 km of main sewer were upgraded and seven unsatisfactory CSOs were removed. This inevitably led to an increase in both the total and peak discharge of the system, not all of

132 0 J.CIWEM, 2000, 14, April

An Assessment of the Su i tab i l i t y of the Environment Agency’s Water-Quality Classi f icat ion System for Use i n Urban Catchments

, -,- - - - /

I I

/ \

\ -

A H

Approx. 1 !un

\

J

f I

R. Thames

Silver Street

, / I r d - Watercourse /

\ - A - - Catchment Boundary Parks & Open Spaces

\

- Zone of Construction for the East Bmet

c - ’ - - - \ - -

Fig. 1. Pymme3 Brook study catchment which could be passed on to the lower reaches of the network without causing problems elsewhere. Therefore, the storage capacity of the system was considerably increased by the construction of three on-line attenu- ation tanks, in order to absorb a large percentage of the additional flow for release over a longer period of time. The two main tanks have been fitted with modern over- flows, incorporating ‘Storm King’ hydrodynamic particle separators in order to remove gross solids from any discharges which occur, although there is consider- able debate surrounding the extent to which they will remove buoyant organic material and other floating materiaU9J0).

The construction of this scheme was completed at the start of 1996. However, preliminary work com- menced in late 1992 when the sewers were flushed prior to catchment modelling; therefore, for the purposes of this study, the years 1993-95 (inclusive) are described as the construction period.

Aims

The aims of this paper are:

(i) To assess the ability of low-flow chemical moni- toring in order to determine the water-quality status of urban rivers, by comparing the chemical- quality classification of Pymme’s Brook with its properties as determined, using other quality indicators; and

(ii) To consider if this form of data collection is sufficient to allow temporal changes to be identified in urban areas, by examining the data for evidence of long-term trends and changes resulting from the construction of the East Barnet sewerage scheme.

foul water sewerage scheme

M e t h o d o l o g y

Data Collection and Preparation Print-outs of the chemical-quality data in the Pymme’s Brook catchment over a twenty-year period (1979-1998) were obtained from the EA. The samples were taken at a total of seven sites; however, only one location was used regularly throughout the period of interest - namely the downstream end of the watercourse above its confluence with Salmon Brook. Seven determinants were examined on a regular basis; pH, DO, BOD, total ammonia, un- ionised ammonia, total oxidised nitrogen, and ortho- phosphate. Although only the first five determinants are used in either the GQA or SWQO systems, the data relating to all seven are considered here.

In order to ensure that the data were comparable with those used by the EA during their assessments of the catchment, the standard EA data preparation method- ology was adopted@). This states that only those samples taken during routine pre-determined sampling pro- grammes will be included, in order to avoid the possibility of samples taken as part of specialised investi- gations (which may not be representative of general water quality) undermining the validity of the system. There- fore, samples taken outside the normal course of events were excluded from this assessment. Similarly, the standard methodology stipulates that when samples are quoted as having ‘less than’ a given concentration, the value will be taken as zero, and that when quoted as ‘greater than’ a given concentration, the specified value will be used; therefore the data set was amended to take this into account. The resulting data set was then used as the basis for analyses requiring annual data; however, when GQAs or SWQOs were involved, further process- ing was required. The standard methodology states that, where three full years of data are available, the samples taken in the preceding three years will be used for classifi-

0 J C IWEM, 2000, 14, Apr i l 133

A. Green and H. Faulkner o n

cation purposes. Therefore, in this study, the classifi- cation for each year was based on a rolling amalgamation of the year in question and the preceding two years; the exceptions are the first two years of the obtained data set (1979 and 1980) which were (as stipulated) based on one and two years of data respectively.

Analysis of Data The data were assessed using EA methodologies to

(i) determine the GQA classification to which it corres- ponded, and (ii) assess compliance with SWQOs. Both of these are based on defined data percentiles (Tables 1 and 2), calculated from the mean and standard deviation of the samples. The 95% confidence limits within which the relevant percentiles lie are calculated, the upper limit being used for 5- or 10-percentiles and the lower limit being used for 90- or 95-percentiles, in order to (a) take into account the fact that spot samples only provide an estimate of actual water quality, and (b) avoid unneces- sary expenditure on remediation schemes. The results of both the GQA and SWQO compliance tests were plotted on an annual basis (Fig. 2).

Temporal changes in individual determinant concentrations were assessed by plotting the annual concentration ranges (Fig. 3) and performing an analysis of variance between the periods prior to 1979-1992, during 1993-1995, and since the construction of the East Barnet sewerage scheme - using all the qualifying data - and based on a Fisher's 'protected least significant differ- ence' (PLSD) test("). In addition, temporal changes in concentration during the three defined periods were

assessed by performing a trend analysis for each determinant in each period (Fig. 4 and Table 3.)

Results

Fig. 2 shows the chemical GQA of Pymme's Brook as calculated using the EA's water-quality data and method- ology. To ensure parity in the methods, it was confirmed that the 1993 classification (calculated for the present study) was convergent with that published by the EA in 199S('), on the basis of data collected between 1991 and 1993 - both of which placed the brook in Class C. The resulting patterns of change in GQA class show that, for most of the 1980s, the quality rarely improved beyond that of Class D (fair); however, since 1989 it has been Class C (fairly good), or occasionally Class B (good) - suggesting a slight improvement in quality over time. It is also noticeable that the brook has consistently met its SWQO of having an ecosystem classification of RE4.

Fig. 3 reveals a marked increase in pH and a decrease in BOD towards the end of the study period. When an analysis of variance between the three periods relating to the East Barnet sewerage scheme was carried out, it was found that the p H was significantly higher (p<O.OOOl) after the scheme was completed than it was prior to construction starting. Most of this change occurred before completion of the scheme - the increase in pH from the pre-scheme period to the construction period being significant at the 99% confidence level (p = 0.004), and the difference between the post-scheme

Calculated RE determinant level ' T

5 ! ; I I ! I I I I I I : I I i I I I ! I

Fig. 2. Calculated GQA and SWQO classifications: Pymme's Brook

134 0 J CIWEM, 2000, 14, Apr i l

A n Assessmen t of t he S u i t a b i l i t y of t h e E n v i r o n m e n t Agency ' s Wate r -Qua l i t y C l a s s i f i c a t i o n S y s t e m fo r Use i n U r b a n C a t c h m e n t s

(a) 8.4

8.2

8.0

7.8

7.6

7.4

7.2

7.0

16 r r 14

E l2 6 10 r r

r I

Date Date

r 110

3 100 B 8 90 z R 80 8

.$ 70

a 60

2.0 1.8 1.6

6 1.4 6 ; 1.2 g 1.0 .- 6 E 0.8 $ 0.6

0.4 0.2 0.0

T I

50

Date Date

r 1,

0.000 J--

Date Date

3.0

90-percentile 75-percentile

25-percentile 10-percentile

0 Mean B

n

r

31.5

2 1.0

0

e

O 0.5

0.0 L m m 2

Date

Fig. 3. Determinant concentrations in Pymme's Brook

0 J CIWEM, 2000, 14, A p r i l 135

A . Green a n d H. Fau lkne r o n

I

i . . . 1. I .. . . . . . . . . .. ~ . . . . . . . . . . .

8 I :. ; ;-i ..Am.- . . * .&,IWy. 1 7=cif."'~.~..'-"'::'"'--:: -;:=?::~:~-*-

I . . . . . . . _I.. . (. . 2 . *..-. ... - .. a. . . . . . . p i *=- ..... ...... ." ...... .. :. . . . . . . . . .

. . 8 .

1977 1980 1983 1986 1988 1991 1994 1997 1999 Date

I .

3 10 e

P 8 -

6

4 -

1 2 1

o!-*.-- --- t----

1977 1980 1983 1986 1988 1991 1994 1997 1999 Date

3~ 1 I

. . . .

1977 1980 1983 1986 1988 1991 1994 1997 1999 1977 1980 1983 1986 1988 1991 1994 1997 1999 Date Date

(6) 0.06 16

14

GI2

5 El0 I

0

. . . . . *.

1977 1980 1983 1986 1988 1991 1994 1997 1999 1977 1980 1983 1986 1988 1991 1994 1997 1999 Date Date

4 -

1 I I

E 3 1

t - 1979. I992

1993 - 1995

1996 - 1998

. _ _ _ _

........

1977 1980 1983 1986 1988 1991 1994 1997 1999 Date

Fig. 4. Determinant trends in Pymmek Brook during construction of East Barnet sewerage scheme

136 0 J CIWEM, 2000, 14, Apr i l

An Assessment of the Suitability of the Environment Agency’s Water-Quality Classification System for Use i n Urban Catchments

Table 3. Trend line equations and R2 values for East Barnet sewerage scheme

Determinant 1 Period

PH

BOD (mg/l)

Dissolved oxygen (YO sat.)

Total ammonia (mg/l N)

Un-ionised ammonia (mg/l N)

Oxidised nitrogen (mg/l N)

Orthophosphate (mg/l N)

Pre-scheme Construction Post scheme Pre-scheme Construction Post scheme Pre-scheme Construction Post scheme Pre-scheme Construction Post scheme Pre-scheme Construction Post scheme Pre-scheme Construction Post scheme Pre-scheme Construction Post scheme

period and the construction period significant at the 95% confidence level (p = 0.363). The decrease in BOD also occurred during the construction period, which was significantly (at the 99% confidence level) lower than the pre-scheme period (p = 0.003), but in this case there was subsequently no significant change between the con- struction and post-scheme period (p = 0.483). However, the decrease in BOD was not matched by an increase in DO, in that there were no significant differences between any of the periods. The only other significant scheme- related change was in the concentration of orthophos- phate, which was significantly lower in the construction period than either before (p = 0.015) or after (p = 0.041) the scheme was constructed.

When assessing water-quality trends (determinant against time using least squares regression (Fig. 4 and Table 3)), few of the calculated relationships were found to be significant at the 90% confidence level. The exceptions to this were (i) a gradual decrease in DO (p = 0.0003) and oxidised nitrogen (p<O.OOOl), (ii) an increase in orthophosphate concentration (p<O.OOOl) prior to the construction of the East Barnet sewerage scheme, (iii) a rapid increase in the concentration of un-ionised ammonia (p = 0.01 17), and (iv) a reduction in oxidised nitrogen (p = 0.0181) during the construction period. However, more importantly, the observed trends provide supporting evidence for a marked increase in pH during the construction period. An equivalent increase in the un-ionised ammonia Concentration, and a steady reduc- tion in the concentration of oxidised nitrogen throughout the period of study, are also suggested by the plots, although no significant differences between any of the periods were revealed in the analysis of variance.

Discussion

The low-flow sampling strategy, adopted by the EA, is based on the premise that, due to the limited scope for

Trend line equation

y = -(1E-5)~ t 8.1256

y = (2E-5)x t 7.3499 y = -0.0001~ t 8,0584 y = 0.0002x t 3.9774 y = -0.0005~ t 21.643 y = -0.0021~ t 142.52 y = -0.0072~ t 316.62 y = -0.0014~ t 125.28 y = (5E-6)x t 0.2646 y = 0 .0001~ - 4.3058 y = -0.0002~ t 8.6043 y = (3E-7)~ - 0.0051 y = (7E-6)x - 0.2408 y = -(1E-6)~ t 0.0483 y = -0.0004~ t 17/75 y =- -0.0014~ t 49.736 y = -0.0006~ t 26.569 y = (1E-4)~ t 2.0298 y = 0.0002X - 6.7752 y = -(5E-5)~ t 2.4726

y = 0.0002~ t 1.621 5

R2

0.006 0.072 0.001 0.007 0.002 0.005 0.050 0.050 0.002 0.000 0.036 0.062 0.007 0.173 0.008 0.1 23 0.153 0.019 0.066 0.057 0.002

dilution of effluents, their concentration is likely to be the greatest at this time. However, although this may be the case when the contamination is from a well-defined point source, discharging all the time, it has been found to be (at best) a dubious assumption when it comes to urban r iver~@.’~J~) , because the process of contamination is often complex - driven by a large number of surface- water and CSO outfalls, the delivery patterns of which are extremely variable. This variability results from the fact that discharges from outfalls of this type are heavily influenced by catchment diversity and climatic con- ditions, such that many of them only discharge during storm events; consequently current sampling regimes may be missing the worst problems.

This situation is exacerbated by the data-handling system which is used to assign a river to a GQA class because, in deciding what value to attribute to the allotted percentile of each determinant, the most lenient 95% confidence limit is used, rather than the calculated percentile itself. This is carried out in order to ensure that the problems encountered in a particular watercourse are not exaggerated, thereby avoiding ‘unnecessary expen- diture on improvements to discharges which are not truly justified’(6). However, given that the samples (on which the process is based) are already likely to have been taken at times when contamination is at a minimum, it is probably giving a river’s water quality a little too much benefit of the doubt to further increase the likelihood of allocating it a high classification in this way. Therefore, in combination, these two sources of error mean that the GQA system (as currently applied) is seriously flawed when it comes to the assessment of water quality in urban areas.

For evidence of the inappropriateness of the classifi- cations produced by this methodology, it is necessary to look no further than the EA’s own biological assessment of Pymme’s Brook(I2). Although biology is not solely dependent upon water quality, this suggests (based on BMWP scores obtained between 1991 and 1994) that,

0 J CIWEM, 2000, 14, April 137

A . Green and H . Faulkner on

except in the rural area just below Jack’s lake (where it is classified as Class C (fair)), the quality falls into Class D (poor) or Class E (very poor)), which contrasts sharply with the chemical classification. In theory, given the eventual scope of the GQA system to encompass chemical, biological, nutrient and aesthetic-quality indi- cators, the problems which are encountered when using the chemical system in urban catchments could be offset by the other indicators. At present, biological monitoring is only carried out to a limited extent, and the findings are rarely fully integrated into the assessment of a catch- ment; instead they are treated as a separate entity - the emphasis still being on chemical-quality indicators.

Possibly of more concern is the fact that, although statutory water-quality objectives are aimed at protecting a river’s ecosystem quality, at present they are only set on the basis of chemical-quality indicators. The likelihood is that, in urban areas, the compliance with SWQOs is of little relevance to true environmental conditions, as a result of the inappropriate way in which compliance with targets is assessed. The target for the Pymme’s Brook catchment is ‘river ecosystem’ (RE)4, which is being complied with as defined in the Regulations; however, this is supposed to mean that the water is ‘of fair quality and suitable for coarse fish population^('^), and clearly this is not the case. Therefore, if water-quality targets are to be set in chemical terms, it is important that the overall target in terms of a use type is matched up with an appropriate target in terms of measurable chemical parameters. In the case of Pymme’s Brook, in common with many other urban rivers, there is a mismatch in that the chemical determinant characteristics defined as being appropriate for an RE4 target, are not adequate for producing the target ecology. This seriously undermines the value of the river ecosystem classification system, because it would appear that in urban areas the water- quality problems are being greatly under-estimated. For instance, in the Lower Lee catchment management plan, only one section of the River Lee was found not be complying with its short-term provisional water-quality objective(12), and for Pymme’s Brook considerable stretches of river are failing to meet the required goals.

If chemical monitoring is to play an important part in the assessment of water quality and the setting of targets, a method must be found to ensure that the targets are appropriate to the environmental properties being assessed. At present, the system would appear to be too heavily biased towards accepting the quality of water; therefore in urban areas a means must be found to re- dress the balance. This could be carried out in several ways; for example, different chemical targets could be set for urban catchments, or the way in which compliance is assessed could be altered when dealing with urban rivers by making the test more stringent - perhaps by using the mean rather than 90- or 10-percentile values. In order to maintain a system in which a consistent methodology can be used, the most appropriate approach is probably the one recommended by the EA themselves - namely the incorporation of other measures of quality. It is therefore vital that the biological element of the GQA system is fully integrated into the assessment schedule, rather than (as is the case at present) being treated as a separate less important measure of quality.

With regard to the ability of chemical water-quality

indicators to pick up changes, it is interesting to note that, in the second half of the 1990s, there was an increase in pH and a decrease in BOD. This could be important in that both BOD and pH are known to be affected by the presence of organic matter, because the breakdown of organic matter creates a biochemical oxygen demand, and the process of that breakdown releases acids which reduce the pH of a watercourse. The increasing trend in the concentration of un-ionised ammonia during the construction period may be less revealing because it is pH dependent. Indeed, for EA purposes, it is calculated from the measured concentration of total ammonia, using the equation:

where: UnAmm = un-ionised ammonia (mg/l) TotAmm = total ammonia (mg/l) t = temperature (“C)

Therefore, in the absence of a significant change in the concentration of total ammonia (as is the case in this study), an increase in p H will automatically lead to an increase in the recorded concentration of un-ionised ammonia.

Bearing in mind that the impact of the East Barnet sewerage scheme is supposed to occur during storm events, and the fact that at low flow there is considerable opportunity for re-oxygenation, it is perhaps not surpris- ing that the observed changes are not more noticeable. It is still possible that the EA’s data reveal a slight positive impact on low-flow water-quality resulting from the scheme because, although the BOD of the samples is considerably lower than that of samples taken during storm events(16), if the input of organic matter during storms has been reduced, there is likely to be less build- up within the bed sediments of the catchment, which would reduce the organic breakdown even at low flow and, as a result, the BOD would decrease and the pH would increase.

Conclusions

1.

2.

3.

4.

5 .

The method of assessing river-water quality using chemical determinants sampled at low flow is flawed with respect to urban catchments, because it fails to assess conditions during storms, when contamination is likely to be at its worst. Meaningless ecological targets are being set because their chemical characterisation is not being con- sidered (in reality). The means of assessing compliance with targets, and quantifying general water quality, must be signifi- cantly altered to allow managers and practitioners to obtain a more accurate impression of the situation facing them. If fully implemented, the GQA and SWQO systems would be of considerably more value to the water industry than is presently the case, allowing decisions to be made on the basis of quantifiable parameters. The chemical-monitoring system which has been adopted by the Environment Agency has identified some long-term changes in water quality, which may

138 0 J CIWEM, 2000, 14, Apr i l

An Assessment of the Suitability of the Environment Agency's Water-Quality Classification System for Use in Urban Catchments

6 .

be as a result of the construction of the East Barnet sewerage scheme, via a reduction in the input of organic matter to the watercourse. In general, the use of chemical determinants can be sensitive enough to play an important role in the management of urban watercourses, but only if used in combination with other quality indicators.

(5) (6)

(7)

Acknowledgements (8)

The authors wish to thank the staff of the Environment Agency's Hatfield office for their assistance in obtaining the data on which this paper is based, and both the Environment Agency andThames Water Utilities Ltd for funding the research project of which this work forms part.

(9)

(10)

(11) References NATIONAL WATER COUNCIL. River Water Quality: the Next Stage. Review of Discharge Consent Conditions. NWC, London, 1977. NIXON, S. C., CLARKE S. J., DOBBS, A. J. ANO EVERARO, M. Development and Testing of General Quality Assessment Schemes. NRA, Bristol, 1996. DEPARTMENT OF THE ENVIRONMENT. Freshwater Quality: Government Response to the Sixteenth Report of the Royal Commission on Environmental Pollution. DOE, London, 1995. Moss, D., FURSE, M. T., WRIGHT, J. F. AND ARMITAGE, P. D. The prediction of the macro-invertebrate fauna of unpolluted running water sites in Great Britain using environmental data. Freshrat. B i d , 1987,17, (l), 14.

(12)

(13)

(14)

(15) (16)

I ,

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