f- ' CRES Monograph 5

V ■ / ** i .

Environmental water quality' # ■ *

a systems stud^inTJggeranong Creek and Kam bah Pool

Tom Beer, Peter C Ypung, Robert B Humphries and James S Burgess

UNCOCK)3 2 218159

This book was published by ANU Press between 1965–1991.

This republication is part of the digitisation project being carried out by Scholarly Information Services/Library and ANU Press.

This project aims to make past scholarly works published by The Australian National University available to

a global audience under its open-access policy.

CRES Monograph 5

Environmental water qualitya systems study inTuggeranong Creek and Kambah Pool

Tom Beer, Peter C Young, Robert B Humphries and James S Burgess

Centre for Resource and Environmental Studies, Australian National University,

Canberra.

c Centre for Resource and Environmental Studies 1982

National Library of Australia Cataloguing-in-publication entry

Environmental water quality.

Bibliography.ISBN 0 86740 018 8.

I. Water quality - Australian Capital Territory - Tuggeranong Creek. 2. Water quality - Australian Capital Territory - Kambah Pool. I. Beer, Tom, 1947-.II. Australian National University. Centre for Resource and Environmental Studies. (Series: CRES monograph; no.5).

628.1'61

Printed and manufactured in Australia by

The Australian National University

Distributed by ANU Press P.O. Box 4Canberra A.C.T. 2600.

library

i i i

PREFACE

Construction of an a r t i f i c i a l Lake Tuggeranong comprises one of the poss ib le options for the future development of the Tuggeranong region of the Austra lian Capital Te rr i to ry . In order to provide s c i e n t i f i c data as a basis for planning th i s s t ru c tu re and modelling i t s ef fec ts upon the down­stream Murrumbidgee, the National Capital Development Commission contracted various s tudi es . This monograph provides an account of the Centre for Resource and Environmental Studies (CRES) contr ibut ion to one of these known as the Murrumbidgee River Water Quality Study.

The raw data on which th is work is based is avai lable in a ser ies of working papers prepared by the CRES Applied Systems group. We must, in f a c t , emphasise th a t the CRES research programme has been a complete team e f fo r t ,w i th numerous individuals contr ibut ing in various ways. A l i s t of CRES team personnel and th e i r contribution is given below:

Tony Bayes Ruth Bel in Ju l i e Cathcart June Harries Alan Henderson Tony Jakeman Pat Mitchel1

Barbara Piper Chr is t ina Sirakoff David (Dingle) Smith Paul Steele

computer programming, f i e ld ass is tancei l l u s t r a t i o n ss e c r e t a r i a l , typings e c r e t a r i a l , typingresearch as s i s t an ce , f i e ld ass is tancemathematics, modellingcomputer programming, data ana lys is ,f i e ld ass is tances e c r e t a r i a l , typingdata ana lys is , computer programminghydrology, dye t r a c e r studiesf i e ld ass is tance

In addi t ion , the s tudents enrolled in the program for the Master of Resource and Environmental Studies provided ass is tance with the f i e l d work..

iv

CONTENTS

Page

P r e f a c e i i i

C o n t e n t s i v

CHAPTER 1 INTRODUCTION 1

1 . 1 I n l a n d A u s t r a l i a n W a t e r s 1

1 . 2 Aim o f t h e S t u d y 5

1 . 3 E x i s t i n g I n f o r m a t i o n 6

1 . 4 The C h a r a c t e r o f t h e T u g g e r a n o n g C r e e k C a t c h m e n t 7

1 . 5 M o r p h o l o g y 10

CHAPTER 2 QUIESCENT CONDITIONS 13

2 . 1 The S a m p l i n g P r o g r a m 13

2 . 1 . 1 F o r t n i g h t l y s a m p l i n g p r o g r a m 14

2 . 1 . 2 D a i l y s a m p l i n g p r o g r a m 15

2 . 2 S p a t i a l A n a l y s i s o f N u t r i e n t s 18

2 . 2 . 1 P h o s p h o r u s 18

2 . 2 . 2 N i t r o g e n 18

2 . 2 . 3 C h l o r o p h y l l a a n d p h a e o p h y t i n 20

2 . 2 . 4 D i s s o l v e d o x y g e n 22

2 . 2 . 5 T u r b i d i t y 22

2 . 3 N u t r i e n t B e h a v i o u r i n t h e R e t e n t i o n Pond 22

2 . 4 C o n d u c t i v i t y 27

2 . 5 E s t i m a t i o n o f F lo w s f r o m C o n d u c t i v i t y M e a s u r e m e n t s 29

2 . 6 A t t a c h e d A l g a e 31

2 . 7 B a c t e r i a l C o n t a m i n a t i o n o f T u g g e r a n o n g C r e e k 32

V

CHAPTER 3

CHAPTER 4

CHAPTER 5

CHAPTER 6

STORM EVENTS

3.1 In t r o d u c t io n

3.2 Gauging the Concrete Channel a t S i te A

3.3 F lo w -v e lo c i t y R e la t ions

3 .4 Behaviour o f the System During Storms

3.5 F lo w -D u ra t io n -C o n ce n tra t io n

3.6 The Storm o f 4 January, 1980

3.7 Erosion in Tuggeranong Creek

3 .8 N u t r ie n t Loading and Land Use C h a r a c te r is t ic s

KAMBAH POOL AND THE MURRUMBIDGEE

4.1 H is t o r i c a l Data

4.2 L o n g itu d in a l V a r i a b i l i t y

4 .3 B io logy and Water Q u a l i t y o f Kambah Pool

4 .3 .1 Survey methods and data a n a ly s is

4 .3 .2 Resu lts and d iscu ss io n

4 .4 D iu rna l V a r ia t io n in D isso lved Oxygen

DISPERSION AND MIXING

5.2 Tuggeranong R e ten t ion Pond

5.3 Tuggeranong Creek Concrete Channel

5.4 Downstream Tuggeranong Creek

5.5 Kambah Pool

5.6 D ispe rs ion M ode l l ing

MATHEMATICAL MODELLING

6.1 A Flow Routing Model o f the Murrumbidgee R ive rSystem In c lu d in g Tuggeranong Creek

6.2 R a in fa l l -F lo w Model f o r Tuggeranong Creek

41

41

41

42

44

46

49

52

52

55

55

56

56

58

60

68

70

84

85

87

91

95

97

104

6 .3 A C onserva t ive P o l lu ta n t D ispe rs ion and T ra n s p o r ta t io n Model 119

vi

CHAPTER 6 MATHEMATICAL MODELLING (con t inued )

6.4 A P a r t i a l Steady S ta te Model f o r N on-conserva t ive P o l lu ta n ts

142

6.5 Recommendations on Future M ode l l ing S tud ies 149

CHAPTER 7 ESTIMATION OF NUTRIENT LOADING AND TROPHIC STATUS

OF LAKE TUGGERANONG

153

7.1 The P re d ic t io n o f Phosphorus and C h lo ro p h y l la C oncen tra t ion in Canberra 's Urban Lakes 153

7.2 E s t im a t io n o f the T roph ic S ta tus o f Lake Tuggeranong 155

7.3 The T roph ic S ta tus o f Kambah Poo l: Presentand Future 159

CHAPTER 8 PRINCIPAL FINDINGS 163

167LIST OF ABBREVIATIONS USED IN REFERENCES

REFERENCES 169

v i i

CONTENTS

Appendices are p ro v id e d on m ic r o f i c h in the back o f th e book

Page N<

APPENDIX 1 ALGAL DATA 1

BATERIOLOGICAL DATA 3

APPENDIX 2 CHARACTERISATION OF LONGITUDINALDISPERSION 1

1. I n t r o d u c t i o n 1

2. Dead Zone Processes 4

3. Problems in E s t im a t in g the D is p e r s io n C o e f f i c i e n t 7

4. D i s c r e t e - t im e Models 11

5. The I d e n t i f i c a t i o n and E s t im a t io n o f D i s c r e t e - t im e Models 16

6. Comparison W ith th e R ou t ing Procedure 17

7. D is c u s s io n and C o n c lu s io n s 2D

APPENDIX 3 L i s t i n g o f the w a te r q u a l i t y and f lo wdata used in p r o je c t 32

1

1. INTRODUCTION

1.1 Inland Australian Waters

Williams (1974) has suggested that inland Australian waters are different in many respects to the water bodies that have been examined in the northern hemisphere. First, discharge from rivers in Australia tends to be very variable in both the short and long term. While low flows predomin­ate, periods of very high flow occur intermittently. High flows have a flushing effect and are associated with substantially increased suspended and solute loads.

Secondly,concentrations of total dissolved solids are often higher than those reported in northern hemisphere studies. Some Australian inland lakes are hypersaline. Generally higher salinities reflect higher than nor­mal concentrations of sodium and chloride ions. However, i t has been suggested that concentration of plant nutrients such as nitrogen and phos­phorus, are often considerably higher than levels reported in many European studies. Williams suggests that some eutrophic lakes in Europe have P04-P values as low as 0.02 mg/1, levels that are not uncommon in Australian inland waters.

Thirdly, Williams suggests that a major source of energy for streams comes from fallen leaf material. In Australia this is from evergreen trees, and consequently occurs throughout the year. Many northern hemisphere situ­ations experience seasonal variations that result from deciduous tree inputs.

Finally, much of the fauna of Australian waters is endemic,with close relationships to marine l ife. Williams suggests that the overseas practice of using freshwater fauna to assess the extent of water pollution must first await detailed ecological studies of Australian fauna,and cannot rely on overseas research results.

The changes that have occurred to the hydrologic regimes of Austral­ian urban waterways have become of greater concern to planners, engineers and public users as urban areas have grown. Until recently, the precise nature of the changes that have occurred has been inadequately studied. The paucity of local Australian information is mentioned by Hart (1974) in his Australian Water Resources Council sponsored compilation of Australian water quality cri teria. Similarly, the more recent studies by Cordery (1976a, b) reinforce Hart's conclusion. Cordery (1976b, p.3) notes that, 'very l i t t l e published data are available on the quality of urban runoff in Australia.

2

The data that have been published re late only to low flow conditions and hence are not rea lly representative of the to ta l flo w '.

Considerable data are available fo r a number of urbanised streams elsewhere in the world. Both Cordery (1976b) and Duncan and Douglas (1973) have reviewed th is information with respect to the Australian environment, and have attempted to summarise the changes to hydrologic regimes that are thought to accompany urbanisation.

Cordery (1976b) suggests that urbanised catchment discharges at times of flood are s ig n ific a n tly increased, those floods with return p e r i­ods of one year frequently being increased by up to three times the pre­urbanised discharge leve l. Following the work of H o llis (1975) he suggests that urbanisation increased larger floods by smaller amounts and that very large floods are increased by in s ig n ifican t amounts. S im ilar findings have been reported by Anderson (1970), da Costa (1970) and Leopold (1968).

Cordery (1976b) also reports that to ta l runoff volumes from urban­ised catchments can be increased by up to two times. This find ing is supported by Anderson (1970) and by Cordery (1976a). Considerable v a r ia b il­i t y in the size of the increase occurs largely as a resu lt of highly v a r i­able urban land uses and because of the numerous physiographic variables in the urban catchments.

The th ird major e ffec t of a change from rural to urban land use is the enormous increase in sediment loads carried by the streams during the construction phase of development. Numerous studies (Bryan, 1972; Dawdy, 1967; Walling and Gregory, 1970; Wolman, 1967 and Wolman and Schick, 1967) have demonstrated that both suspended load,, and concentration of the suspend­ed load,increase substantia lly in the early phases of urbanisation. Walling and Gregory (1970) demonstrated fo r Exeter that these patterns of high sedi­ment load decrease following the construction phase, and f in a l ly level o f f a fte r a period of s ta b ilisa tio n .

The fourth set of major changes that occur in streams a fte r urbani­sation involve morphologic changes to the stream channel and the bed. Frequent­ly channels are enlarged (Hammer, 1972) and bed sediment re -d is tribu ted .

Perhaps the most s ig n ifican t changes that occur follow ing urbani­sation are the changes in the chemical and bacterio logical characteristics of the water that essentia lly determine the qua lity of the water in the waterway. Cordery (1976b) suggests that runoff from urban areas can be

3

considered, 'roughly equivalent to the effluent from sewage treatment plants which provide primary and secondary treatment of domestic sewage' (Cordery, 1976b, p.2). Examination of urban stormwater reveals significantly higher concentrations of phosphates (Weibel e t d l . , 1964), nitrates (Angino e t d l . ,

1972) and the indicator bacteria E sch erich ia c o l i (Van Donsel e t a l . , 1967). Urban stormwater is frequently characterised by greater than normal biologi­cal oxygen demands, higher levels of heavy metals (particularly lead), high concentrations of oil and solids and lower concentrations of dissolved oxygen. Overseas workers have paid considerable attention to these effects and a selection of results are shown in Table 1.1. Considerable variation occurs from catchment to catchment, however deterioration in overall water quality is consistent.

The changes reported in overseas studies are consistent with studies that have been undertaken in Australia. Cordery (1976a), working in three urban catchments in Sydney noted that runoff carried greater concentrations and greater loads of 'pollutant' than effluent from secondary, sewage t rea t­ment plants. Similarly Duncan and Douglas' (1973) study of Dumaresq Creek (Armidale, N.S.W.) reports differences in water quality as a result of urbanisation, particularly in terms of phosphates, potassium and si l ica. Gutteridge, Haskins & Davey Pty. Ltd.,and the Environmental Protection Authority of Victoria (1981) studied pollution in urban Melbourne storm­water runoff. They emphasise that the high pollution episodes represent an ini t ial flush effect, but concede that on an annual basis the magnitude of pollutant exports when compared to loads from raw sewage, can be substantial. More recently a series of detailed studies have been made of the waterways of the Canberra region many of which have been reported in a recent National Capital Development Commission Technical Paper (NCDC, 1981).

The paper reports considerable data that describe the quality of both rural and urban waters in the A.C.T. The amount of material presented indicates the substantial effort that has been made in these areas in the past few years. Many of the points made by overseas workers are reiterated in the report. Levels of phosphorus in forested and rural catchments were low (below 0.1 mg/1) while levels of 1.0 mg/1 and greater were detected in waters affected by sewage treatment plants. Higher levels of nitrogen were also associated with the effects of urbanisation and changes to fauna and flora are reported. Measurement of Eschericha c o l i and S trep tococcus fa e c a l is indicated that levels could be several orders of magnitude higher in urban streams particularly at times of high flow.

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Importantly the study emphasises the very considerable spatia l and temporal v a r ia b i l i t y that occurs in the volume and qua l i ty o f water in the

A.C.T.. Cordery (1976b) has also noted th is v a r ia b i l i t y and he suggests tha t, 'very l i t t l e progress has been made attempting to extend the results of studies of local areas to obtain a general theory o f the e ffects of urbani­sa t ion '. Numerical data are given of the changes in flood magnitude, sedi­ment load and water qua l i ty as a resu lt of urbanisation. However the lack o f general understanding of the processes involved in these changes means that the published information re a l ly only provides q u a l i ta t iv e indications of the changes that can be expected when changing the land use of an area from rura l to urban conditions. The resu lts described in Chapter 6 of th is monograph are a preliminary attempt to provide a general methodological framework fo r modelling these e f fec ts .

1.2 Aim o f the StudyThe overall aim o f the Murrumbidgee River water qua l i ty study is to

ensure tha t urban development in the Tuggeranong area does not have a deleterious impact on the recreational and aesthetic amenity of the Murrum­bidgee River. The spec if ic concern w ith in th is report is with the impact of po l lu t ion from Tuggeranong Creek and V il lage Creek on the immediate environ­ment of the Murrumbidgee River and, in p a r t ic u la r , on the uses of Kambah Pool.

Within th is overall framework, the Applied Systems Group of CRES was s p e c i f ic a l ly requested to :

( i ) Monitor the q u a l i ty and quantity o f discharges to the Murrumbidgee River and the q u a l i ty and flow o f the Murrumbidgee River above Tuggeranong Creek and through the Kambah Pool, fo r a range of flows.

( i i ) Undertake a programme of water q u a l i ty monitoring w ith in the Tugger­anong Creek system fo r a range of ex is t ing urban development patterns, drain types, and water po l lu t ion abatement structures.

( i i i ) Develop a ra in fa l l / r u n o f f model, to f a c i l i t a t e tes t ing of a range of water po l lu t ion control options, and the computation o f flow inputs fo r water qua l i ty studies.

( iv ) Analyse instream and inpool responses o f Kambah Pool, and represent these processes in terms o f a dynamic model.

(v) Model bacteria l and tu rb id i t y po l lu t ion and decay in th is system.

(v i ) Analyse the water qua l i ty performance of Kambah Pool using the model, with and without a simulated Lake Tuggeranong in the system.

6

(vii ) Analyse the water quali ty performance of Kambah Pool, using themodel, for the specified range of urban development patterns , drain types, and pollution abatement s tructures.

Our i n i t i a l response to the above proposals was to mount an inten­sive sampling programme. I n i t i a l ly i t was intended to determine the optimum sampling interval for this program on the basis of the above-listed object­ives but, in practice , the final sampling programme was completely determin­ed by financial constraints. Out of a total budget a llocat ion of $26,000 for CRES ac t iv i t ie s the maximum possible budget allocat ion for laboratory analysis was $12,000. However, as a full analysis of a single sample from a single sampling s i t e cost $20.40, the nine s ta t ion sampling programme original ly approved was immediately found to cost more than the budget allocat ion. The final programme planned within these constraints was there­fore, defined as follows:

(i) Regular for tnightly water quali ty sampling was undertaken at nine s i tes in the Tuggeranong-Murrumbidgee system from 4 June 1979 until 17 June 1980.

( i i ) Daily water quali ty sampling was undertaken at the same nine s i tes in the Tuggeranong-Murrumbidgee system from 25 February 1980 until 10 March, 1980.

( i i i ) Intensive sampling was undertaken during three storms on 8 August,1979, 11 November, 1979 and 10 January, 1980.

(iv) Dispersion, flow,and mixing cha rac te r is t ic s were examined by special dye experiments, consisting of injections of the conservative dye Rhodamine WT, on six separate occasions. Dye sampling of Kambah Pool and the Murrumbidgee was undertaken on 24 October, 1978 and 10 March, 1980; the Tuggeranong Creek retention pond was examined on 27 June, 1979 and 10 January, 1980, Tuggeranong Creek below the retention pond was investigated on 14 November 1978 and the Tuggeranong Creek concrete channel experiment took place on 27 June, 1979.

The resul ts of these investigations are presented in the subsequent chapters of this monograph and the final two chapters develop modelling methodologies based upon these resul ts .

1.3 Existing InformationThe A.C.T. Region Water Quality Study (Department of Construction,

7

1978; hereafter referred to as the Basin Study) incorporated bacte rio log i­ca l, hydrological and water qua lity sampling of Tuggeranong Creek and Kambah Pool on an approximately fo rtn ig h tly basis. The existence of th is data set - acquired before construction of e ither the Tuggeranong retention pond or the concrete channel - allowed us to analyse changes in catchment behaviour since these structures were b u i lt .

In addition, the urban geology of Tuggeranong has been studied by the Bureau of Mineral Resources (Jacobson, e t a l . , 1975) who pointed out, in re la tion to the hydrology and drainage of the region, that groundwater extraction from bores in the region formerly took place fo r domestic and stock use. The water qua lity of th is groundwater was quite variable with to ta l dissolved solids ranging from 200 to 1100 parts per m illion and with bicarbonate as the dominant cation. Their results show l i t t l e difference in concentrations of suspended solids among groundwater bore samples and surface water samples from Tuggeranong Creek.

Although the Basin study covers the general hydrology of the A.C.T. region, a more detailed study of the hydrology of the Isabella plains was completed by the Department of Construction (1977) in order to obtain design c r ite r ia fo r the concrete channel that was b u i lt to guide Tuggeranong Creek. This concrete channel was constructed to completely contain the three year

3flood, with a flow expected to exceed 100 m /s fo r an urban catchment. By contrast the three year flood fo r a rural catchment is only expected to

3produce a 20 m /s flow at the end of the concrete channel.

1.4 The Character of the Tuggeranong Creek Catchment

There are four separate te rra in patterns:

( i ) F la t, a llu v ia l, deposits comprise the Isabella Plains, thecentre o f which was a natural swamp p rio r to the introduction of the concrete drainage channels that now comprise the upper portion of the Tuggeranong Creek system.

( i i ) Gently sloping colluvium deposits occur extensively in Kambah, much of Wanniassa and east of Gowrie.

( i i i ) Undulating S ilu rian lands comprise the suburbs of Wanniassa,Monash and Gowrie.

(iv ) Strongly undulating S ilu rian rock outcrops compromise the h i l l ­top reserves and lands upstream of the Tuggeranong pine plantation.

8

The characteristics of each of these terra in types is given by the CSIRO (1976) and, in terms of soil type and drainage may be summarised thus:

( i ) f l a t a l luv ia l deposits are gradational s i l t y clay over heavy clay which is in turn over sand and gravel. 10% of the terra in has top­soil to a depth of 2 to 5 m whereas 90% consists of soil of greater than 10 m depth. Occasional streams with incised channels pass through;

( i i ) colluvium deposits are sandy s i l t overlying heavy clay which is in turn over s t ra t i f ie d material. 62% of the area has topsoil of va r i­able depth, and the rest consists of soil of 2.5 m depth. There are discontinuous streams, and the area is l iab le to sheet flow;

( i i i ) undulating Silurian lands consist of duplex sandy s i l t over heavy clay which is , in turn, overlying decomposed rock. The topsoil is shallow, less than 1 m, and comprises 70% of the area. The remain­ing 30% has a soil depth of 1 to 2 m. This soil produced broad dendritic drainage types.

( iv ) the Silurian rock outcrops overlay sandy medium textured clay which is i t s e l f over decomposed rock. This region has a dendrit ic drain­age type.

The total surface of the Tuggeranong Creek - Village Creek catchment 7 2is 6.4 x 10 m (6,442 ha) and, on the basis of land use characterist ics, i t

would be possible to estimate tota l nutrient loadings. Table 1.2 gives estimates for these based on data obtained in V ictoria.

TABLE 1.2 Estimated Generation Parameters for Total Phosphorus Loadings (Source: Gutteridge, Haskins and Davey, 1979)

Development Intensity Estimated GenerationLand Use (average gross area/ Parameters fo r Total

dwelling; ha/dw) Phosphorus (kg/ha/year)

Forest >50 0.1Grazing 15 0.1Intensive C 1 - 3Agriculture D

Urban sewered 0.3 0.6Urban unsewered

. high density 0.3 12

. low density 1.0 3

9

PINE

Sampling S ite

20000

Met r es

Tu ggeran ong C reek -

M u rru m b id g e e River System

KAMBAH \ POOLS

Figure 2.1

10

Because of the current building activity within the Tuggeranong Creek catchment, i t is unclear whether i t should be considered to be urban, rural, or a mixture of both. Urban and rural catchment have different hydro- logical characteristics (Australian Rainfall and Runoff, 1977, p. 74) and in Chapter 6 we examine the urbanisation of the catchment in terms of i t s hydro- logical character.

1.5 Morphology

The physical characteristics of stream channels govern the hydro­dynamics of flow and, therefore, the patterns of deposition, channel scour, and sediment transport. During low-flow conditions, the Murrumbidgee River is shallow and the bed is composed almost entirely of rock outcrop with alluvial sand, gravel, cobbles and boulders. During Summer, growth of attach­ed algae and emergent vegetation would be expected. During floods, veloc­i t ies are sufficiently high to transport large quantities of sediment and gravel as bedload. Morphologically, this is an eroding reach.

Kambah Pool, which, under low flow conditions at least , is deep and slow moving can be considered as a depositional reach with sediments sett!ing out in the pool. Prior to this study i t had been considered a large s t i l l ­ing basin behind a weir. Similarly, the tributary streams and gullies are erosional while the man-made weirs and proposed lake would be expected to be depositional.

In the developed areas, substantial modifications to the natural drainage patterns have been made. Catchdrains around the hi l ltop reserves direct flows around urban areas and, in a few cases, out of Tuggeranong Creek catchment. Runoff from allotments and roads in minor storms (the one to five year flood) is piped underground into Tuggeranong North and Tugger­anong Creek channels which have concrete lined inverts (one year flood capacity). Runoff from large storms (the hundred year flood) is designed to be confined to roadways and to defined grass floodways, the major ones being Village Creek (Kambah) and Wanniassa North and South floodways. Near built up areas grass floodways adjacent to the lined channels are designed for the probable maximum flood. In other areas, such as the proposed golf course, flooding under such extreme conditions is tolerable.

At the downstream end of the Tuggeranong Creek channel, a weir has recently been constructed as a s i l t trap and conditions upstream and down­stream of the weir were monitored as part of this study. A further weir and a dam (to form 'Lake Tuggeranong') are presently proposed upstream and down-

11

stream of the weir.

The concrete channel s tarts at the Tharwa road, but the catchment area continues upstream of th is . Tuggeranong Creek in these upstream areas is composed of deeply eroded creek-beds. Construction work involved in building the concrete channel and the new Tharwa road system appears to have forced the creek to undergo some very sharp and unnatural changes in d ire c t­ion and there is evidence of some s i l t accumulation in the water entering the channel due to the gradual erosion of these sharp bends. Observation of th is area indicates that i t may also be a major source of tu rb id ity during high flow episodes; indeed, i t would appear that the creek immedi­ately upstream of the concrete channel sometimes overflows a containment embankment and flows trans ien tly down an old watercourse. Further evalu­ation of th is upstream area seems necessary and better matching of the flow patterns in the upstream natural creek and the concrete channel seems to be called fo r.

13

2. QUIESCENT CONDITIONS

2.1 The Sampling Program

For the regular for tnightly water quali ty sampling, as well as for the daily sampling over the two week period, nine s i te s were chosen as follows: (see Figure 2.1).

Site A: This s i t e was at the end of Tuggeranong Creek concrete channel,and at the upstream end of the exist ing retention pond.

Site B: Downstream of the retention pond, at the roadbridge over ErindaleDrive.

Site C: Village Creek, upstream from i t s confluence with TuggeranongCreek.

Site D: Tuggeranong Creek Gauging Station.

Site E: Tuggeranong Creek upstream of i t s confluence with the MurrumbidgeeRiver.

Site F: Murrumbidgee River a t Pine Island.

Site G: Murrumbidgee River upstream of Kambah Pool.

Site H: Murrumbidgee River downstream of Kambah Pool.

Site I : Tuggeranong Creek at the Monaro Highway crossing before commence­ment of the concrete channel.

The distances between s i tes are given in Table 2.1.

At each of these s i t e s , the following water quali ty variables were monitored on a for tnightly basis from 4th June 1979 until 17th June 1980.

. Temperature (°C)

. Dissolved oxygen (ppm)

. Turbidity (an approximate measure of total suspended solids and colour) (NTU)

. Chlorophyll (ug/1)a

Phaeophytin ( a chlorophyll decomposition product) (yg/1). Conductivity (an approximate measure of total dissolved sol ids ,

i . e . sa l t s ) (ymho/cm). Total Organic Carbon (mg/1). Total Phosphorus (ug/1). Total Nitrogen (ug/1)

14

. Nitrate and Nitr ite (NC>2/N03) ( i .e. oxidised nitrogen)

. Kjeldah1 Nitrogen (the sum of organic nitrogen and ammonia).

Phosphorus is measured directly as total phosphorus, and the soluble phos­phorus fraction is broken down into:

. Total Filterable Phosphorus (which measures soluble organic and inorganic phosphorus) and

. Filterable Reactive Phosphorus (which approximates PO or soluble inorganic P of other workers).

If i t is assumed that free ammonia is low in the system, then 'available1 nitrogen may be approximated by oxidised nitrogen and 'available' phosphorus by f i l terable reactive phosphorus.

All the samples, except the bacteriological ones, were collected by workers from the Centre for Resource and Environmental Studies who also measured the in s itu temperature and dissolved oxygen. The samples were then transported to the Canberra College of Advanced Education for subse­quent analysis by Dr. R. Rosich and his s taff .

2.1.1 Fortnightly sampling program

The values of the above determinands have all been plotted and are given by Henderson (1980). Though these variables differ somewhat from those sampled during 1976-77 and documented in the Basin Study, we have also compared water quality determinands for the 1976-77 period, and i t is apparent that there have been changes to the system over that period.Table 2.2, for example, l i s t s the mean and standard deviation of the values of the water quality parameters at the Tuggeranong Creek gauging station (Site D) and just downstream of Kambah Pool (Site H) for the 1976-1977 and 1979-80 periods. There are substantial differences in the observed concen­trations in the Tuggeranong system and a priori i t is not clear whether these changes emanate from

(a) the construction of the Tuggeranong retention pond; or(b) different flow conditions during the two sampling periods.

This point will be discussed in greater detail in Section 2.3.

15

TABLE 2.1

TUGGERANONG CREEK0 km taken a t Sta t ion 1, Monaro Highway crossing

reach length, km cumulative

* I to A 5.2di s tance , km

5.2A to B 1.0 6.2

t B to D 1.7 7.9D to E 1.0 8.9E to Murrumbidgee confluence 0.4 9.3

VILLAGE CREEKC to D 0.7 -

MURRUMBIDGEE RIVER

F to Tuggeranong Creek 1.9Tuggeranong Creek confluence to G 4.3 13.6G to H 1.0 14.6

* Tuggeranong North Arm and the Wanniassa South Floodway enter th i s reach t Vi llage Creek enters th i s reach

2.1.2 Daily sampling program

In an attempt to obtain a b e t t e r understanding of the shor ter term v a r i a b i l i t y of the system, i t was decided to mount a dai ly sampling program over a two week period from February 25, 1980 unt i l

March 10, 1980. The water qual i ty determinands deta i l ed above were sampled and the data p lo t ted in time ser ie s format. Unfortunately no ra in occurred during th i s period and the consequent low flow condi tions revealed very l i t t l e about the shor t term behaviour of the system.

On the basis of the dai ly and fo r tn igh t ly sampling re su l t s and the shor t er term storm sampling r e s u l t s (see Chapter 3) , we are led to postulate tha t the Tuggeranong system has e s s e n t i a l l y two modes of behaviour:

( i ) a long term seasonal v a r i a b i l i t y th a t can be adequately exam­ined with a fo r tn ig h t ly sampling frequency,

( i i ) shor t term dynamics ar is ing from storm conditions which, except for the Murrumbidgee River s i t e s , are inadequately sampled even on a dai ly bas is .

16

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Figure 2.2

T o ta l F il te ra b le Phosphorus , Mean & S tandard E rro r

p g / i3 ° ,

10

0 1 2 3 4 5 6 7 8 9 10 Ü 12 13 14 15

km

Figure 2.3mq/ i

14- F ilte ra b le R e a c tiv e P hosphorus

2

o0 2 3 4 5 6 7 8 9 10 11 12 13 14 15

km

Figure 2.4

M9/> T o ta l Phosphorus

10

0 --------- --------- --------- --------- --------- --------- ■------------------ --------- --------- ,---------------------- — ,— ---- --------- ,0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

km

18

2.2 Spatial Analysis of Nutrients

The longitudinal mean water chemistry concentration profiles, along with their standard errors, have been plotted for five sampling sites on Tuggeranong Creek, and three on the Murrumbidgee River, from Pine Island to below Kambah Pool. These data are highly variable but i t has been assumed that the variations in mean concentrations are meaningful and the interpre­tation is based on this assumption. Plots of the measured variables of the twenty-eight fortnightly samples, along with the results from the two weeks of daily sampling,are given in Figures 2.2 to 2.13.

2.2.1 Phosphorus

We assume that the fractions of P measurement relate to each other in the following way:

Filterable reactive P(FRP) - POTotal f i l terable P (TFP) = organic P(0P) + FRP Total P(TP) = TFP + particulate P (PP).

Particulate P is a complex fraction containing an unknown mixture of organ­isms (e.g. algae, bacteria, protozoans), detritus and particle-bound inor­ganic phosphorus, and may be estimated as follows:

PP = TP - TFP.

Examination of Figures 2.2 - 2.4 shows l i t t l e evidence of strong variations in the concentration of any phosphorus fraction along the length of Tuggeranong Creek or the Murrumbidgee. There is a sl ight (non-signifi­cant) increase in mean P (all fractions) across the dam between sites A and B, and a tendency for a concentration decline thereafter. There is no indi­cation that the two streams entering reach I - A, or Village Creek which enters reach B - D, contribute substantial amounts of phosphorus to Tugger­anong Creek. The observed fall in mean total P concentration (Figure 2.4) in reach B - E suggests that dilution or storage of P may be taking place. Further analysis of the time series, as undertaken in section 2.3 is required to distinguish between these possibi l i t ies . The Murrumbidgee shows virtually no change in P status with distance.

2.2.2 Nitrogen

Nitrogen is measured as only two fractions. Firstly as oxidised N (NO + NO ), the highly soluble, vir tually non-binding form of N readily available for use by plant and micro-organisms. The second fraction is

19

Figure 2.5M9/Ix 1 0 2

Oxidised Nitrogen

72 U

Figure 2.6

K je ldah l N itrogen

Figure 2.7

20

total Kjeldahl N, which includes free NH +, soluble organic N and particular organic N. Free NH + is most probably rare in this well-oxygenated system, and NO /NO -N is probably the dominant 'available' nitrogen fraction. Total nitrogen can be approximated by the addition of total Kjeldahl-N and NO /NC -N. Nitrogen is highly mobile, and is very weakly bound in i ts organic forms. Most particulate N (not measured in this study) is probably incor­porated into organisms or detri tus.

Examination of Figures 2.5 and 2.6 reveals what are possibly signif­icant changes in N status along Tuggeranong Creek. There are rapid rises in mean NO- /NC -N (Figure 2.5) within reaches I - A and B - D, suggesting either

(i) that the two drains and Village Creek both contribute signif i­cant amounts of inorganic nitrogen, or

( i i ) that the buildup of inorganic nitrogen is due to the intrusion of groundwater that contains a high ni trate content, and that the loss of this nitrogen is inhibited by the rapid flow along, for example, the concrete channel.

I t is diff icult to choose between the two possibi l i t ies , especially since we believe (Beer, 1979) that the 'weepholes' along the concrete chann­el appear to be highly effective groundwater interceptors during low-flow conditions.

There is some evidence for denitr if ication or biological uptake of inorganic N within the Tuggeranong Creek retention pond - total Kjeldahl-N rises within the reach A - B, although perhaps not s ignif icantly, then declines downstream to the Murrumbidgee. The losses of both NO /NO -N and Kjeldahl-N downstream of the retention pond reflect an unknown combination of dilution, uptake and storage and atmospheric N loss. The Murrumbidgee shows virtually no longitudinal variation in N status.

2.2.3 Chlorophyl1 and phaeophytin

Suspended chlorophylla from phytoplankton should below in a variable, fast flowing stream habitat. The only potentially suitable s i te for phyto­plankton growth is the Tuggeranong Creek retention pond although high turbid­ity and short water residence times during large flows may lessen i t s sui ta­bi l i ty . Examination of Figure 2.8 shows an anomalous pattern of longitudinal mean chlorophyl1 concentrations. The reach I - A shows sl ightly elevated chlorophyll, and concentrations decline thereafter. The decline within the dam (reach A - B) indicates that major phytoplankton growth does not occur

21

Figure 2.8p g /l C h lo ro p h y lla

10 11 12 13

Figure 2.9

Mg/i3 0-,

2.5-

2 .0 -

1.5-

1.0 -

.5-

0 -

P haeophytin

0 1 2 3 4 5 6 7 1 9 11 12 13 "l4 15

km

Figure 2.10

ppm14-

D isso lved O xygen

4

2

8 9 10 lT 12 13 14 15

km

22

there. The reasons fo r the higher values in reach I - A are not clear.

There is v ir tu a lly no longitudinal varia tion in chlorophylla in the Murrumbidgee. Phaeophytin, the primary decomposition product of chlorophyll, and indicative of algal death, shows l i t t l e longitudinal varia tion at a ll (Figure 2.9).

2.2.4 Dissolved oxygen

Mean dissolved oxygen concentrations (Figure 2.10) are s lig h tly supersaturated in both streams, probably due mainly to turbulent mixing rather than high primary production. The Kambah Pool sites were examined to better distinguish these p o s s ib ilit ie s , and the results are given in Chapter 4.

2.2.5 Turbid ity

Turbid ity is a composite variable, consisting of an unknown combin­ation of suspended solids (e.g. clay p a rtic le s ), chlorophyll and dissolved colour due to tannic compounds resulting from the decomposition of te rres­t r ia l and aquatic vegetation. Both the Tuggeranong Creek retention pond and Kambah Pool show increased mean tu rb id ity compared with the remainder of the sampling points (Figure 2.11). The major source of tu rb id ity in th is area is usually suspended clay pa rtic les , but the tu rb id ity difference upstream and downstream of the Tuggeranong retention pond is persistently v is ib le .The typical s itua tion consists of c lear, bluish water in the dam area of the retention pond, and murky greenish water in the pond that has formed at the foot of the spillway.

We would in fe r from th is that water overtopping the spillway churns up the mud and earth at the foot of the spillway producing the observed tu rb id ity peak at Site B.

2.3 Nutrient Behaviour in the Retention Pond

In order to fu rther examine the data of Table 2.2 and the results of Figures 2.4 and 2.5, the h is to rica l load data from the Basin Study was com­pared to the data that CRES obtained during regular fo rtn ig h tly sampling and during storms. This was accomplished by p lo tting load-flow diagrams fo r to ta l phosphorus and fo r oxidised nitrogen and these diagrams are shown in Figures 2.12 and 2.13.

23

The main point to emerge from this is that the presence of theTuggeranong Creek retention pond has affected the load-flow characteristicsof phosphorus (as measured by total P) and there also appears to be aslight effect on oxidised nitrogen. As far as the phosphorus behaviour ofthe Tuggeranong Creek system is concerned, at high flows (greater than

30.1 m / s ) , the phosphorus loads were always greater before the retention pond was buil t than they are at present. At low flows the reverse seems to be true. By simple regression analysis we find that

P = 13.1 Q1’ (present study) ^(P - kg/day) (Q - nr/s)

P = 92.5 Q1' 8 (the Basin study)

which would indicate that the transition from phosphorus retention at high3

flows to phosphorus export at low flows occurs when Q = 0.0075 m /s . However this figure needs to be treated with caution. There is curious behaviour in the load-flow plots at low flows and low loads. We feel that the data from the Basin study at low flows are possibly unreliable as there is evidence that low flows and low concentrations have been assigned arbitrary values. This curious behaviour occurs below Q = 0.075 m /s and we feel that this bet ter represents the transitional flow value than the lower figure given above.

We can then tentatively interpret the huge difference in Tuggeranong Creek total phosphorus in Table 2.2 as arising primarily from flow differ ­ences, though i t is possible that the construction act ivity in the catchment during the Basin study led to temporarily raised levels of phosphorus. The regression analysis based on the load-flow curves indicates a systematic difference between pre-retention pond (1976-77) and post-retention pond (1979-80) characteristics of the system in terms of i ts phosphorus load.This also seems to be the case with oxidised nitrogen. Regression lines for NO /NO loads are

N = 61.1 Q1,06 (present study) ^(N - kg/day) (Q - m/ s )

N = 102.6 (the Basin study)

so that, in our study, all flows will give lower oxidised nitrogen readings. We should add here that the sparcity of the Basin study data means that in neither case would a s ta t i s t ical te st verify a null hypothesis that the two curves are different, but similarly one could not verify a null hypothesis

NT

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24

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LOG

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27

that the two curves are the same.

I t would appear then that, during storm periods, the retention pond acts as a phosphorus trap, but during low flow periods i t exports phosphorus, producing the elevated levels at Site B. The pond also seems to have a s l igh t trapping e ffect on oxidised nitrogen, but in this case, there is no evidence of re-release during low flows.

2.4 Conductivity

Conductivity is a measure of e le c tr ica l ly conducting dissolved substances in water. The ions responsible for oceanic conductivit ies and riverine conductivities are substantially d if fe ren t, as indicated by the typical world-wide values quoted in Table 2.3.

TABLE 2.3 Ionic Composition (by weight) in River and Sea Water

Ion Symbol Seawater River Water

Chloride Cl" 55.04% 5.68%Sodium Na+ 30.62 5.79Sulphate sor 7.68 12.14Magnesium Mg++ 3.69 3.41Calcium Ca++ 1.15 20.39Potassium K+ 1.10 2.12Carbonate c o r 0.41 35.15Silicates Si02 — 11.67

There is a high correlation between gravimetrically measured total dissolved solids (TDS) and conductivity. Provided the ra t io of salts always remains the same then th is correlation should be perfect. Conductivity is thus approximately conservative. Apparent non-conservation of conductivity generally arises from

( i ) changes in the ra t io of ions in the water;( i i ) temperature changes in the water;

( i i i ) changes in water tu rb id i ty . High sediment loads reduce theeffective volume of the sensor head of the conductivity probe and tend to lower the readings.

Nevertheless, owing to the lack of gauging fa c i l i t ie s on the upper reaches of Tuggeranong Creek and Village Creek, CRES was forced to assume that conductivity was indeed conservative and, as we shall see in Section 2.5,

28

Figure 2.14

Mm ho/cm Conductivity

400-

Figure 2.15

m g / I Total Organic Carbon

km

29

to then use the observed conductivity results as a means of apportioning flows in the system.

The longitudinal conductivity results of Figure 2.14 show va r i­ations sim ilar to that of oxidised nitrogen. The two drains in reach I to A, and Village Creek, which enters reach B - D, contribute s l ig h t ly to the conductivity of Tuggeranong Creek, presumably through groundwater inflow. There is a s l ig h t drop in mean conductivity in reach D - E which is hard to explain. I t may be due to uptake of Fe and Mg (HCO - is used as a source of C02 fo r photosynthesis by many aquatic plants) by algae and bacteria - presumably also partly the reason fo r the lowered conductivity at Site B.I t is unlikely to be a consequence of water intrusion via seepage into the reach since there are no inflowing streams in that area. Furthermore the drop is so s l ig h t that i t may be s ta t is t ic a l ly ins ign if ican t.

The Murrumbidgee shows no change of conductivity along i ts length.

2.5 Estimation of Flows from Conductivity Measurements

In the Tuggeranong Creek Study, we did not have measures of flow upstream of the gauging station because the retention pond gauge was inoper­ative (see also Chapter 6). I t is possible, however, to obtain a rough esti­mate of flows in the Village Creek and Tuggeranong Creek section jus t up­stream of the gauge by analysing the conductivity data collected during monitoring exercises under the assumption that conductivity is a measure of conservative substances, as detailed above.

Let us assume that the flows in Village Creek, Tuggeranong Creek upstream of the confluence with Village Creek, and downstream of the con­fluence ( i .e . at the present gauging s ite ) are Q y , Q^ , and Q ^ , respectively. I f the associated conductivities are, respectively, Cy, cQ, c^ then, assuming that conductivity is conservative,

QyCy + Qdcd = Qgcg (1)

Also, i f we assume that the flow at the gauge is the sum of the two upstream flows, then

V % = Qg (2)

Finally, fo r s im p lic ity , le t us suppose that the flow in Village Creek is a fixed proportion a of the gauge station flow, i .e . Qy = aQg. With this assumption, we have from (1) and (2)

30

so that

aQGcv + (1 - a) QgCd Qqcq

(3)

Since the conductiv ity measures are noisy, i t is c lea r ly necessary to obtain some estimate o f a on the basis o f equation (3). Two approaches are possible:

( i ) compute a from (3) fo r each sample and estimate by the sample average, ä, i . e .

where

a

a . 1

cGi ~ CDi cVi ' CDi

(4)

N is the number of samples and i indicates the i t h sample;

( i i ) obtain an estimate a computed from (3) w ith the concentration measures replaced by th e i r mean (average) values computed over the sample set, i .e .

a (5)

where, once again, the bar indicates sample average as in (4).

Using f i r s t equation (5) we f ind that fo r the N = 36 conductiv­i t y measures ( fo r tn ig h t ly + 14 da i ly )

~ _ 1013.3 - 706.4 a 1155.4 - 706.4 0.684 ( 6 )

in other words, the V il lage Creek flow appears, on the basis, to comprise 68% of the gauging sta tion flow and, therefore, the upstream Tuggeranong Creek comprises 32%.

On the other hand, i f we use equation (4), we f ind tha t a = 0.79, with V il lage Creek apparently contr ibuting a much larger 79% of the upstream flow. Upon fu r the r examination, however, we f ind tha t these higher values o f a are due almost e n t i re ly to three a-j values computed from (3) as greater

31

than unity. If these values are removed and the computation repeated for N = 33 measurements, therefore, then we obtain a = .68 as in (6).

Under the assumption that conductivity is a conservative measure, we can conclude that, on the average, the flow in Village Creek is 68% of the measured Tuggeranong gauge flow, while the flow in the 'upper' Tuggeranong Creek downstream of the retention pond is 32% of the measured gauge flow. Given the possible limitations of the "conservativity" assumption and the quite high variation in a computed from (3), these figures should be used with some caution. Nevertheless they appear to agree with visual observation of the system and seem, therefore, reasonable at this time, given the limi­tations of the gauging information on the Tuggeranong Creek system. Certain­ly they can be considered satisfactory a p rio ri figures until updated by flow model predictions or other information.

Clearly, similar computations can be carried out in order to e s t i ­mate flows of other sampling sites in the system on the basis of the measur­ed flows at the Tuggeranong and Pine Island gauging stat ions. On this basis, for example, the flow at the confluence of the Tuggeranong Creek and Murrum- bidgee is 1.06Q^; while the flows upstream and downstream of Kambah Pool seem about equal to Pine Island flows. The Tuggeranong and Murrumbidgeeflows provide a direct comparison since we know that over the study the mean

3 -1 3 -1flow at Site D was 0.05 m s and the mean flow at Pine Island was 2.8 m swhilst the mean conductivities were 1013 ymho/cm and 325 ymho/cm. The meanconductivity at Kambah Pool was 332.6 ymho/cm so that i f we assume that theflow at the si te D gauging station is a fixed proportion of the KambahPool flow Qk: i .e . = aQ then

* _ 332.6 - 325 _a 1013 - 325 0.011

whereas the flow ratio based on the mean flows is 0.018. This indicates that on average, Tuggeranong Creek provides from 1% to 2% of the water in Kambah pool, though in the short term the percentage can be a lot higher.

2.6 Attached Algae

During each fortnightly sampling period, colour photographs of each si te were taken in order to retain a record of the algal biomass at each s i te . These photographs are available from CRES, but their interpret­ation turns out to be rather subjective. In order to remove, as far as

32

possible, this sub jec t iv ity , the slides were presented to a group of six research workers who were asked to rank them from 0 to 5 with 0 representing a total absence of algae, and 5 representing a maximum.

Their results were used to construct the fo r tn igh t ly time series of attached algae given in Table 2.4. The salient points to emerge from this are:

( i ) there is a marked increase in attached algae as one progresses down Tuggeranong Creek. Of a l l the sampled sites, the algal content continually increased from Site A to B, B to D andD to E with Site E consistently registering the highest values.

( i i ) Detachment of algae by storm flushing is apparent. The exceed­ingly large runoff from the storm of 4 January 1980 (approxi­mately the 3 year flood) completely cleared Sites A, B, D andE of algae, and p a r t ia l ly cleared Sites C, F and G in Village Creek and the Murrumbidgee.

There is also evidence that the existing Tuggeranong Creek retention pond inh ib its this flushing for a l l but the most severe storms. Thus Site A was denuded by algae on two occasions - the samples of 27 August 1979 and 19 November 1979 - when there was no obvious effect at Site B. Note that because of the manner in which the time-series in Table 2.4 was obtained we have not attempted time-series analysis but rather have limited our discuss­ion to a descriptive evaluation, which parallels the results on the longi­tudinal v a r ia b i l i ty of tota l organic carbon shown in Figure 2.13.

A limited study of the attached algae during March and April 1980 has been completed by CCAE (and the data are given in Appendix 1). Their work includes quantitative assessment of algal biomass and chemical oxygen demand, and a qua lita tive assessment of the per cent algal cover and domi­nant taxa present. We attempted to relate our attached algal rating to these data, but the observations are too few and too variable to provide a calibration of the rating method.

2.7 Bacterial Contamination of Tuggeranong Creek

Regulations for the protection of Australian waterways frequently use faecal coliform as indicators of water quality . In the A.C.T. the standard set for contact recreation is a geometric mean of 200 faecal

33

TABLE 2.4 Attached Algae Ratings

Date A B C D E F G H

19/6 1.5 1.83 1.08 1.33 2.17 0.58 0.92 0.402/7 1.25 1.08 1.33 1.67 3.58 0.50 1.00 0.40

16/7 1.33 2.08 2.50 1.50 3.75 1.33 - -30/7 1.5 0.75 2.25 2.17 3.25 0.50 0.75 0.4013/8 1.25 0.67 0.83 2.17 3.00 0.83 0.92 0.1027/8 0 0.17 0.83 2.17 2.17 0.50 0.83 1.2010/9 2.58 0.83 2.25 1.67 2.50 0.33 1.33 0.4024/9 1.08 1.0 1.92 2.83 2.75 0.50 1.0 022/10 2.33 1.92 3.33 4.08 4.58 0.67 2.0 0.80

5/11 1.33 3.33 2.42 3.92 4.25 0,50 0.67 0.8019/11 0 2.83 2.08 2.58 4.50 1.25 0.17 1.903/12 0 1.67 2.58 3.67 4.58 1.33 1.58 1.70

17/12 0.5 1.50 3.00 4.17 4.00 1.33 0.67 3.102/1 0.58 1.0 1.33 4.25 4.00 1.83 1.17 2.10

14/1 0 0 1.50 0 0 2.33 1.0 0.9029/1 0.08 0 2.25 1.42 0.75 1.83 1.25 -11/2 0 0.75 1.08 0.5 1.50 1.75 2.42 -

25/2 0 0.67 2.50 1.67 2.33 2.67 2.42 -

24/3 1.0 0.17 1.25 0.75 1.17 2.92 2.08 -8/4 0.83 2.17 2.50 - - 3.10 - -

Mean 0.86 1.29 1.94 2.24 2.89 1.33 1.23 1.01

coliform/100 ml for data collected over a 30-day period provided not more than 10% of the samples have faecal coliform concentration of 400/100 ml. Faecal coliform (E scherichia c o l i ) is a non-pathogenic organism found in the digestive t ra c t of warm-blooded animals. E scherich ia c o l i is in i t s e l f a harmless bacteria and is only an indication that pathogenic bacteria may exis t . High levels of the bacteria usually indicate pollution from sewage works, urban runoff, or large populations of vertebrate animals.

Despite the reference to bacterial measurement, l i t t l e information has been published for Australian conditions (Bayly and Williams, 1973; Cordery, 1976b) and even when data are available, they are often misunder­stood (Russ and Tanner, 1978, p. 78). Data that have been published (Table 2.5) indicate that high and variable densit ies can frequently occur. Overseas

34

experience (Geldreich e t a l . 3 1968; Van Dönsel e t d l 1967; Weibel e t a l . y

1964, Wadleigh, 1968) indicate that high densities of bacteria are usually associated with times of increased flow. Variable discharge levels produce considerable varia tion in bacterial concentration. S im ila rly , Burgess and Olive (1975) have demonstrated that urban stormwater in the environs of Canberra can also have high densities of faecal coliform at times of increased flow.

The extreme v a r ia b ility of bacteria l levels in athalassic Australian waters is associated with and compounded by extreme v a r ia b ility of flow.This v a r ia b ility of bacteria l levels has encouraged workers to use the geo­metric mean (G = -----Xn) as a measure of central tendency (Burgess,1974; Environmental Protection Authority, 1974; Heath, 1967). The use of the geometric mean usually assumes that the data are log-normally d istributed.

Sample co llection

Bacterial data fo r th is study was collected over a period of nine months during 1979 and 1980. Data was collected weekly fo r the entire period and then more frequently during September and October of 1979 and during a large storm in early January 1980. Data collected are presented in Appendix 1. Location of the sample stations used (A, B, C, D, E, and I) are shown in Figure 2.1. Station Z was located where Ashley Drive crosses Tuggeranong Creek (Figure 2.1).

TABLE 2.5 Faecal Coliform Concentrations in Selected Waterways

Location Arithmetic Mean Geometric Mean

Queanbeyan River downstream of Queanbeyan* 6426 457

Queanbeyan River upstream of Queanbeyan* 816 55

Sullivans Creek A.C.T. near Lake Burley G r if f in * 4684 1410

Jerrabomberra Creek, A.C.T. 1672 93Dandenong Creek downstream of

Wells Road** 6370 3491Yarra River at Burke Rd.*** 4963 2729Kororit Creek, Forest Street

Bridge, Sunshine**** 94500 19361* Burgess, J.S. and Olive, L.J. of Vic. Rep. L3; **** E.P.A. of

(1975); ** E.P.A. of Vic. Vic. Rep. Western Suburbs

Rep. U4; *** E.P.A. Streams (undated).

35

Faecal co li form was determined using a membrane f i l t r a t io n tech­nique with the use of M-FC broth (Geldreich e t a l . , 1965). M illipo re prepared M-FC ampoules were used as the culture medium and the samples were f i lte re d through p re -s te r i1ised M illipo re HAWG 0.45 y f i l t e r papers. Incubation was by means of M il l i pore water bath incubators at 44.5° C fo r 24 hours. Normal procedure was to incubate two plates per sample, however, on occasions a greater number of plates were processed. Problems of sedi­ment interference at high flows were largely overcome by successive seria l d ilu tio n and then incubating a larger than normal number of plates. When zero counts were obtained a value of one was recorded.

Results

Figure 2.16 presents d is tr ib u tio n plots of the raw data fo r each of the sampling stations. Even from a cursory glance at the plots i t becomes obvious that extreme skewing occurs and that a problem with extreme values exists. In a ll cases the standard deviation (S) fo r each of the sample stations is larger than the arithm etic mean (X) and the geometric mean (G) is an order of magnitude lower than the arithm etic mean (Table 2.5).

A number of points emerge from Figure 2.17 which display the longi­tudinal varia tion of the data. F irs t there is an increase in levels between Stations I and Z. This change should be interpreted with care as the creek at Station I was not flowing on 11 of the 43 occasions sampled. In re la tion to th is point i t should be noted that the flow at Station Z on these occas­ions was pa rticu la rly low.

A marked drop in levels occurs between Stations A and B (above and below the retention pond) and th is could be interpreted as a re flec tion of bacterial d ie -o ff. Examination of the data in Appendix 1 demonstrates that the 'p u r if ic a tio n ' capacity of the retention pond is considerably lessened at times of high flow. On 5/10/79 Station A recorded a level of 620/100 ml, while Station B experienced only 80/100 ml. This lag e ffec t is further demonstrated in the data fo r 4/1/80, 6/1/80 and 7/1/80. On 4/1/80 a level of 19000/100 ml was recorded at Station A and 14500/100 ml at Station B. On 6/1/80 the level at A had dropped to 7000/100 ml then dropped further to 400/100 ml the next day. The decline in levels at Station B was less dram­a tic and on 6/1/80 was 10000/100 ml (3000/100 ml higher than A) and 2000/100 ml on 7/1/80 (an order of magnitude higher than A).

36

Figure 2.16

io3 io5

n3

rt

%*9

S'WCflrt

Faecal coliform/100 ml.

Figure 2.17

----- Arithmetic mean x----- Geometric mean G

- 3000

-2000

- 1000

►ncuo

oH*o'13

o3I—1

Station

37

Perhaps the most important change in bacterial densities occurs between Station B and Station D as a result of the addition of waters from Village Creek. Station C on Village Creek carried bacterial loads that are s ign if ican t ly higher than those encountered in Tuggeranong Creek. This trend is part icu la r ly obvious following periods of ra in fa l l . For example, on 29/9/79 (Appendix 1) a level of 2900/100 ml was recorded in Village Creek and 180/100 ml at Station B. S im ilar ly , on 6/10/79 levels of 2440/100 ml and 530/100 ml were recorded. Even more substantial differences occurred on 23/10/79 (14800/100 ml, 2040/100 ml) and on 3/3/80 (12800/100 ml and 750/100 ml). Under low flow conditions Village Creek does not exhibit such large differences. On a number of low flow occasions the levels in Village Creek were actually lower than those in Tuggeranong Creek.

Downstream of Village Creek Stations D and E have higher levels than the upstream Station B, and obviously carry greater loads of bacteria. The levels encountered are generally lower than in Village Creek and th is indicates mixing of the two creeks.

Figure 2.18 demonstrates the relationship between flow and bacterial levels for one of the periods that was sampled more intensively. Not sur­pr is ing ly , increases in flow are associated with increases in bacterial con­centration, however, the relationship is not simple nor does the data allow the relationship to be easily quantified. This d i f f i c u l ty is i l lu s t ra te d further by Figure 2.19. While concentrations of bacteria tend to increase with increase in flow, very high flows are not characterised by proportion­ately higher concentrations. I t appears that at very high flows the volume of water is su ff ic ien t to begin to d ilu te eff luent present and concentrations reach a maximum s l ig h t ly before these high flows begin.

Discussion

From the data presented i t is clear that urbanisation in the Tuggeranong Valley has substantially increased bacterial loads in the water­ways of the valley. I t is also clear that these higher levels are primarily expressed at times of increased flow. What is not clear is exactly what the increase in level has been. This is probably p a r t ia l ly a function of the complex data d is tr ibu tion being examined. From the standpoint of the a r i th ­metic mean (X) high levels are the norm throughout the waterway and levels at the urbanised Station C are twice those in non-urbanised Z and A. Levels of 3243/100 ml (Station C) and 1510/100 ml (Station A) would appear alarming, however, expressed in terms of the geometric mean (G) levels of 117/100 ml

38

(A) and 165/100 ml (C) appear re la t iv e ly low. The increase in level as expressed by th is measure (6) downstream o f V illage Creek is less spectacular and i t could be argued tha t the waterway complies w ith normally accepted bac te ria l standards.

I t could be fu rth e r argued (Table 2.6) tha t as the geometric mean fo r a l l data only reached a maximum of 165/100 ml fo r S tation C, then the waterway carried leve ls o f bacteria tha t permit recreationa l use. The means calculated from weekly data are su b s ta n tia lly less and a maximum o f 105/100 ml was recorded a t S tation C. However, i f i t is desirable tha t no more than 10% o f the samples exceed 400/100 ml then by almost any c r i te r ia the waters o f V illage Creek must be considered unsa tis facto ry from a contact sport po in t o f view.

TABLE 2.6

S tationMeasure

No. j Z A B C D E

1257 1359 1510 1166 3243 2111 24204660 4053 4012 3414 7599 5134 5872

Log G, 1.56 2.07 2.03 1.60 2.22 1.95 1.90

S 36 117 117 40 165 89 79Log G1 S1 1.24 1.16 1.10 1.18 1.31 1.38 1.49

X2 134 567 437 196 1542 942 998

S2 175 911 929 445 3516 2142 2249Log G2 1.54 2.10 2.01 1.47 2.02 1.75 1.56

« 235 126 102 30 105 57 37

Log G2 S2 0.92 1.01 0.80 0.91 1.15 1.21 1.41

G1 Geometric mean a ll data N = 43

x i Arithm etic mean a ll data N = 43

s , Standard devia tion a ll data N = 43Log Gj Log^ Geometric mean a l l data N = 43 Log GjSj Standard devia tion o f Log GX2 A rithm etic mean weekly data N = 23

Standard devia tion weekly data N = 23

Log G2 Log^g Geometric mean weekly data N = 23 G2 Geometric mean weekly data N = 23Log G2 S2 Standard devia tion o f Log G2 N = 23

39

Figure 2.18

D ischarge

Day No.

Figure 2 . IS

F low (mys)2 0 -

10- Key :★ 1976 - 1977• 1979 - 1980

.1 -

•01 * i 3 4 ^ i J M | 0 io^ 1 ? 7o5Col i fo rm B a c t e r i a

(count per 100ml)

40

Despite the diff icult ies with the data i t does seem obvious that, as urbanisation continues in the valley, bacterial levels will increase and that as i t is proposed to extend the urban area to include larger parts of the Tuggeranong catchment, higher levels throughout the waterway can be expected.

Increasing levels of bacterial pollution will have deleterious effects on downstream fac i l i t ie s . Exactly what these effects will be is uncertain. As yet die-off rates for bacteria have not been established, and so i t is not possible to predict the effect of the Tuggeranong urbani­sation on the waters of the Murrumbidgee River. If levels of 200 faecal coliform per 100 ml are seen as indicating a hazard for recreational use of waters, then perhaps the current practice of closing waters in and around Canberra to recreational use at time of high flow should be extended to the Murrumbidgee River.

Table 2.7 compares the bacteriological data with that given in the Basin Study for Tuggeranong Creek, Site D. Once again i t is not clear whether the lower values represent a real reduction in coliform bacteria or whether they merely represent lower flow conditions.

TABLE 2.7 Bacterial Count Escherichia coli (No./lOO ml)

Arithmetic Mean Geometric Mean 1976-77 4575 20701979-80 2111 89

Figure 2.19 presents the bacteria count versus flow plot of the two data sets. Except for the three ultra high flow points obtained during the large 4 January 1980 storm, the spread of data between the two time periods is indistinguishable. I t would appear then that, at low flows, the Tuggera­nong Creek retention pond has not altered the bacteriological characteristics of the creek, and that there are insufficient data to decide if the same is true at high flows.

41

3. STORM EVENTS

3.1 Introduction

On a number of occasions in the previous chapters we have had to consider the response of the hydrology and biology of Tuggeranong Creek to storm events. There is no doubt that these are very important in transport­ing large nutrient and sediment loads, and simultaneously flushing the system. Further, construction of the Tuggeranong Creek retention pond has altered the behaviour of the system and we wish to further elucidate the nature of these changes.

Unfortunately, this study took place during a particularly dry period. This enabled us to obtain representative results for low flow conditions, but further exacerbated the diff icult ies of understanding the potentially more important high flow dynamics of the system.

Our original intention was to intensively sample every storm that occurred during the study period. However i t transpired that the chemical analysts were unable to handle the large number of samples that a series of closely spaced storms of long duration would produce. A compromise was f inal ly effected by which three storms: those of 8 August 1979,11 November 1979 and 10 January 1980 were sampled as fully as possible.

The storm that produced the most severe runoff during this period(approximately the 3 year flood) occurred during a vacation period onJanuary 4 1980 when the flow at the Site D gauging station was of sufficientintensity to render the gauge inoperable. Estimates of the stage height,based on the maximum height of debris accumulation, indicated that the flow

3 3at Site D peaked between 120 m /s and 130 m /s . This event demonstrated the need for well maintained automatic sampling stations in any future study.

3.2 Gauging the Concrete Channel at Site A

In order to provide flow estimates upstream of the existing reten­tion pond, ORES had to gauge the flow at Site A. This was accomplished during a period of low flow, by painting a series of marks on the concrete channel, each of which represented a rise in water surface of 1.7 cm. Gauging could then be carried out by using Manning's formula relating the flow velocity to:

42

U = r 2/ 3 S^/n (S.I. units)

where n = 0.012 for a concrete channel and the channel slope S = .005.The hydraulic radius is related to the water depth, h, in a triangular channel by

r = (h cos e)/2

where 0 is the angle of depression of the sides of the channel. This then3

gives the flow, Q in in /s .

Q = 3.712 h8/3 (cos e)2/3/tan e

where tan e was measured to be .0632 so that

Q = 57.032 h8/3

Based on the above parameters we can estimate

U = a Qb

for the concrete channel: since

U = 3.71 h2/3

one finds that

U = 1.35 q3*.

This flow-velocity relationship will only apply for low flows. At3high flows (greater than about 4.5 m /s) the slope of the sides of the concrete channel is steeper, and this would need to be considered.

3.3 Flow-velocity Relations

In order to adequately model the system for representative flows outside of the range within which our data are based, i t was found necessary to find the flow-velocity relations between the sampling si tes . As a gener­al rule this is expressed as

U = a Qb (3.1)

where the parameter b is primarily determined by the morphology and shape of the stream cross-section whereas the parameter a is primarily determined by

43

the size of the cross-section.

Typical values for b range from 0.25, as given above for a triangu­lar cross-section, to 0.4 for a wide rectangular channel (Whitehead, Horn­berger and Black, 1979a). As an extreme example we may note that for a con­stant volume rectangular reservoir,

(3.2)

by definition so that in this case a = *//\ and b = 1.

In practice many data points obtained under widely differing flow conditions would be needed in order to adequately determine a and b. We do not have these data and thus our estimates of these coefficients must be considered with this in mind. On the basis of the turbidity results obtain­ed during the three storm events we estimate that from

Site C to Site D U = 0.31 Q0,52

whereas on the basis of our dye experiments on Kambah Pool we take

Kambah Pool U = 1.21 x 10"2 Q0,63

and these results were subsequently used in constructing our models (Chapter 6).

In the case of the Tuggeranong retention pond, the results of our dye experiments (see Chapter 5), along with i ts observed behaviour during storms indicates that a simple flow-velocity relationship is insufficient .On the basis of our experiments the relationship from Site X (at the up­stream turning point of the pond, Figure 5.1) to Site B would have been

U = 1.82 x 10"3 Q0-214.

However i t is diff icult to believe that the exponent would differ so much from that obtained on Kambah Pool.

I t seems that the anomalous low value of b arises from the curious behaviour of the retention pond. At low flows the incoming water seems to merely ref i l l the pond and the water does not actually travel downstream until the flow exceeds some threshold value. The attached algal results of Section 2.5 provide some evidence for this: at low flows there is l i t t l eor no algal detachment at SiteB, but at high flows complete detachment

44

occurs. The storm of 10 January 1980 also supports this idea: despite a32 m /s flow gauged at Site A, there was no rise in water level at Site B.

These results are curious because observation suggests that the water level is almost always at the level of the dam retaining wall, with slight spillover occurring on most occasions. Without a study of far greater detail than this one, however, the exact reason for this anomaly cannot be determined. At this time we would merely speculate that either:

(i) i t is possible that evaporation exceeds groundwater inflow over much of the year so that during summer the retention pond level is lowered;

( i i ) changes in the mean wind direction could play a significant role. If the wind blows downstream towards Site B, the sur­face stresses will push water towards, and over, the dam wall. When the wind dies down, or changes direction, this will result in an effective drop in the level of the lake.

For the above reasons, when modelling the retention pond behaviourin Chapter 6 of this report, i t was decided to use a two step flow-velocityrelationship in which the velocity stays constant at low flow (which onecould envisage as a wind effect) but, at high flow, the retention pond acts

3 3as a constant volume reservoir (equation 3.2) with a volume of 110 x 10 m4 2(110 ML), a surface area of 5 x 10 m (5 hectares) spread over 500 m (from

Site A to the retaining wall). This gives the retention pond an effective2depth of 2.2 m and an effective cross-sectional area A = 220 m . The choice

of transition flow was determined from the velocity obtained during the retention pond dye experiment of 27 June 1979.

3.4 Behaviour of the System During Storms

It has been previously mentioned that CRES undertook intensive sampling during three storms. The peak flows at Site D during these three storms were:

0.4 m'Vs on 8 August 19793

4.0 m /s on 11 November 19792.0 m /s on 10 January 1980.

In addition, there is a limited set of conductivity, turbidity and suspended sediment results obtained from the storm of 4 January 1980, and the subsequent

45

10 days.

The results o f the chemical analyses of these storms are given elsewhere (Henderson, 1980). On the f i r s t storm sampling exercise the peak flows were not fu l ly sampled. However, by u t i l is in g the experience gained in th is f i r s t August exercise, we were able to make sure that the peaks were sampled in November and January.

Although the gauging station at Site D continued to operate fo r a ll three storm events, the ORES gauging of Site A detailed in Section 3.2 was only operational fo r the November and January storm. I t is of in te res t to note that the water qua lity variables at Site A appear to peak on the ascending limb of the hydrograph, and have generally dropped to low concen­tra tions by the time tha t the hydrograph has peaked. This may be explained in terms of nu trien t runoff by postulating that the f i r s t ra in fa ll event washes nutrients in to the waterways, but the large quantity of water present at the hydrograph peak e ffe c tive ly d ilu tes the concentration. However, i f th is in te rpre ta tion is correct, i t is not obvious why the data from Site D appear to show simultaneous peaking of the flow and the water q ua lity variables.

The storm data confirm our contention that the Tuggeranong retention pond acts as a nu trien t trap during storm events. Table 3.1 gives peak con­centration values measured at the downstream s ite s , and i t is clear that in the short term ( i.e . during the storm) very l i t t l e nutrien t travels from Site A to Site B, and that most of the nutrien t load to Site D came from Site C. In other words the high nutrien t concentrations from S ite C were d ilu ted by water of lower nutrien t concentration from Site B.

One of the most surprising results during the storm sampling exercises was the fa ilu re of Tuggeranong Creek at Site B to respond to the storm of 10 January 1980. The creek did not r ise , and there was no evidence

3that Site B had in any way reacted to the 2 m /s flow input at A. Possible reasons fo r th is have already been discussed in Section 3.3, but i t is ins truc tive to consider the matter a l i t t l e fu rthe r. On the basis of the

3hydrograph at Site A, i t would seem that about 6000 m of water flowed in to the retention pond during the storm of January 10. Our estimate of the surface area of the retention pond, from Site A to the retaining wall is

9approximately 50,000 m so that the storm could have been expected to raise the water level in the retention pond by 10 cm, yet the evidence indicates

46

TABLE 3.1 Peak Nutrient Concentration During Storm Events

Site Total P (yg/1) N02/N03 (yg/1) Total N (yg/1)

Storm A 630 845 340511/11/79 B 120 345 1395

C 740 675 6285D 380 590 5910

Storm A 625 2560 713010/1/80 B No peak observed

C 265 2775 4575D 250 2625 3515

that this was insufficient to overtop the retaining wall. I t is clear from these calculations that furthers more comprehensive monitoring o f the retention pond is necessary before we can confidently describe i t s behavioural patterns.

3.5 FIow-Duration-Concentration

In Figure 2.14 and 2.15 we have plotted the nutrient loads of total phosphorus and oxidised nitrogen as a function of flow for the fortnightly, daily and storm data. I t is apparent that one can obtain an adequate power- law relationship between load and flow. Garman (1980) points out, however, that a simple plot of concentration (or load) against flow does not provide the analyst with enough information to assess whether or not a sufficiently wide range of flows has been sampled. He advocates a non-linear transform­ation of the flow axis by means of the flow-duration curve in order to

(i) check the adequacy of sampling;( i i ) assess concentrations under dry, average and high flow

conditions;( i i i ) check the range of concentration conditions found under

each flow regime;(iv) examine the data for any trends or change in concentration.

FLO

W

DU

RA

TIO

N

CU

RVE

TU

GG

ERAN

ON

G

CR

EEK

47

Figure 3.1

O

(sonnen MO I d

12.5

2

5.0

3

7.5

5

0.0

6

2.5

7

5.0

8

7-5

1

00

.P

ER

CE

NT

EX

CE

ED

EN

CE

FLO

W

DU

RA

TIO

N

CU

RVE

P

INE

IS

LAN

D48

Figure 3.2

o

to Lo ro C\l(S03Wn0) MO 13

12.5

2

5.0

3

7.5

5

0.0

6

2.5

7

5.0

8

7.5

10

0.PE

RC

ENT

EXC

EED

ENC

E

49

The flow duration curves fo r Tuggeranong Creek (S ite D) and theMurrumbidgee (Pine Island) are presented in Figures 3.1 and 3.2. We shouldemphasise that these are not quite the same as the flood-frequency curves since the la t te r plots only the return period of the highest flow in a given time period (usually a year), whereas we are considering here the duration of a ll flows - not ju s t floods - based on five years of average da ily flow.As a storm flow is un like ly to occupy more than a small fraction of a day,our curves w il l appear to over-emphasise low flows in comparison to flood- frequency curves.

Since in the 1979-1980 Study no instantaneous flows were recorded3 -1exceeding 3.8 cumecs,an a rb itra ry cu t-o ff was made at 5.0 m s fo r p lo tting

purposes. This encompasses 1807 of the 1826 data points.

A ll Site D (gauging station) water samples were combined, that is the fo rtn ig h tly data, 14-day data and the data from the three storms. This gave a maximum possible 175 data points. Each instantaneous flow from th is combined data set was given a cumulative percentage from the flow duration s ta t is t ic s . The cumulative percentage was then used as the X axis value and the Y axis values were flow and the chemical data. The flow , concentration, per cent exceedence graph is read as follows:

Reading Flow:At a given flow the creek exceeds that flow n per cent of the time (reading from per cent exceedence).

Reading Concentrations:At a given flow, where that flow intercepts the flow duration curve a ll the values of that determinand recorded are found when reading in the v e rtic a l, th e ir values are then read o ff the concentration scale.

Selected concentrations have been plotted on the flow-duration curves as suggested by Garman and, as an example, the flow-duration-concen­tra tio n curve fo r to ta l phosphorus at the Tuggeranong Creek gauging station is given in Figure 3.3.

3.6 The Storm of 4 January, 1980

The largest storm, about the 3 year flood (Q3), fo r Tuggeranong Creek occurred on 4 January, 1980. Although extensive sampling of a ll water qua lity variables could not be undertaken, a lim ited set of tu rb id ity ,

FLO

W

DU

RA

TIO

N/C

ON

CE

NT

RA

TIO

N

RE

LAT

ION

SH

IP50

Figure 3.3

r - O

— O

_o

__o

)£ SS2 OSn/on) d ivioi

I I I i i I I i I I I 1 IOS ’ fr s d * s o o * s s s - s o s * i s / - o o o * o

(sodwno) m o i d

PE

RC

EN

T E

XC

EE

DE

NC

E

51

co n d u c tiv ity , faecal c o li form and suspended sediment data was obtained.

Following the storm, the CRES team assessed i t s impact v is u a lly . The strength o f the re su ltin g runo ff can be judged from the fa c t tha t a car washed down channel from above S ite A, about 300 m in to the pool down­stream o f S ite A. The water in the re ten tion pond at the time was a m ilky brown co lour due to suspended sediment ru n o ff, and th is colour indicated tha t the water came from Tuggeranong Creek. At 1500 hours on 4 January, 1980 Tuggeranong Creek flow completely dominated Kambah Pool. This ind ica tes the e ffe c t tha t loca lised storms in the Tuggeranong area can have on Kambah Pool over short periods o f time. The Murrumbidgee was unaffected by th is p a r tic u la r ra in fa l l event, so tha t the water a t Pine Island remained c lea r. However, despite the low flow conditions in the Murrumbidgee, the tu rb id ity in Kambah Pool had e ffe c t iv e ly disappeared w ith in two to three days.

An exponential curve was f i t t e d to the suspended sediment data at S ite G, above Kambah Pool, and S ite H below Kambah Pool, g iv ing time constants (flu sh in g times) o f 0.5 days and 0.77 days respective ly . This confirms tha t the Kambah Pool system appears to have a quick response to sediment disturbances from Tuggeranong Creek, and th is is borne out by the dye tra ce r resu lts discussed in Chapter 5.

I f in form ation were ava ilab le on flow , i t would be possible to ca lcu la te the suspended sediment transport in to and out o f Kambah Pool. Unfortunately th is flow inform ation is not ava ilab le . Nevertheless, a rough assessment can be made i f we assume

( i ) th a t the peak in the suspended sediment d is tr ib u t io n wasobserved, and i t can be roughly modelled as S = SQexp(-t/T )where T is the time constant and S and S are in uq/1.o

( i i ) the flow peaked a t the same time as the suspended sediment concentration, and had the same time constant so tha t

3Q = QQexp (-t/T ) where Q is in m /s .

This gives a to ta l sediment loading (TS) in grams of

TS = Q S T/2 yo o

when T is expressed in seconds. For the input we have Qq sQ = 500 ug/1 and T = 0.5 days so tha t

120 m3/s (say),

TS = 1,300 tonnes

52

while downstream o f Kambah Pool Qq = 120 m'Vs, SQ = 630 yg/1 and T = 0.77

days, so tha t

IS = 2,500 tonnes.

The discrepancy ( i . e . more calculated output than input) seems to arise from our fa i lu re to accurately locate the peak in suspended sediment.I t seems l i k e ly tha t the peak upstream of Kambah Pool was much higher than 500 yg/1. I t would thus appear that a sediment budget cannot be computed from our data. However we would estimate the sediment loading in to Kambah Pool from the 3 year flood in Tuggeranong Creek at 1900 ± 600 tonnes, with a strong caveat tha t these figures are based on very few data points. As in the case of the re tention pond, th is indicates the strong d e s i ra b i l i t y of more comprehensive short term monitoring o f Kambah Pool, i f possible using automatic monitoring devices.

3.7 Erosion in Tuggeranong Creek

Inspection a f te r the storm of 4 January 1980 revealed extensive

morphological changes in the pond reach between Site A and the main retention pond. Much of th is section had eroded, but the re tention pond i t s e l f showed evidence o f deposition, as did a l l the subsequent downstream Tuggeranong s i te s .

In order to fu r the r id e n t i fy the behaviour of the system i t was decided to in s ta l l erosion pins. These were in s ta l le d at various locations w ith in the ex is t ing re tention pond and downstream at Sites B, C and D.We have no measures to reveal whether the pins had been tampered w ith .

Given th is proviso, the general resu lts indicated that between 11 January, 1980 and 4 August, 1980 there was about 2 cm erosion along the southern side of the channel from Site A to the re tention pond; and that there was evid­ence of s l ig h t (1 cm to 1.5 cm) erosion w ith in the pond i t s e l f . The down­stream sites showed evidence o f s l ig h t deposition, once again of about 1 cm.

3.8 Nutr ient Loading and Land Use Characteristics

In Chapter 1 we presented V ictor ian data re la t in g the expected to ta l phosphorus loading over a year to the size of the catchment. Given a catch­ment area o f 6,400 ha, one would expect anywhere from 640 kg to 64,000 kg of to ta l P over one year. On the basis o f our re su lts , and the flow readings

53

estimate that the total phosphorus loadings are3

during quiescent condition (an average flow of 0.04 m /s3

which corresponds to a daily discharge of 3500 m ) there is a load of 0.18 ± 0.24 kg/day of total phosphorus; during storms the total loadings are as given in Table 3.2. In particular the regression of the total phosphorus loading (in grams) on the total discharge (in m ) is

PL = 0.228 Ql - 840

which can be directly compared with

PL = 0.33 Ql + 497

as given by Cullen e t a l . 3 (1978) for other A.C.T. catchments.

TABLE 3.2 Total Loadings (Site D) During Monitored Storms

at Site D, we

(i)

( i i )

Date Total Pkg

Total N kg

no2/ no3-nkg'3

TFPgm

Kjeldhal-Nkg

FRPgm

DischargeITT

8 Aug 79 1.22 16.23 8.27 12.4 7.96 6.38 1.02 x 10411 Nov 79 8.77 73.8 18.20 0.0 55.6 0.0 4.23 x 10410 Jan 80 3.18 42.7 22.3 0.0 20.4 0.0 1.61 x 104

We would make the following observations on the data in Table 3.2. Site D data was used because i t was the only continuously gauged si te . The table primarily reflects Village Creek characterist ics , because the Tuggera- nong retention pond affects loads (Table 3.1), often capturing most of an inflowing storm load down Tuggeranong Creek. Secondly, the low TFP and FRP values highlight the importance of particulate P. And thirdly, we wish to emphasise that the results were obtained by simultaneous integration of the measured concentrations with the observed hydrograph. Because the concen­tration time curves do not, in general, peak at the hydrograph peak - for example, total P always peaks on the ascending limb - i t would be incorrect to integrate the regression equations of page 15 through a representative hydrograph since that procedure would constrain both peaks to be contempor­aneous .

54

6 3If we then assume a total annual discharge of 16 x 10 m the annual phosphorus loading predicted by the regression equation would total 3650 kg which leads to a generation parameter of 0.57. This is in reasonable agree­ment with the Victorian data of Table 1.1.

55

4. KAMBAH POOL AND THE MURRUMBIDGEE

Kambah Pool is an important resource for aquatic recreation in the A.C.T., and a basic requirement for the further analysis of i t s behavi­our is the description of i t s bathymetry, biology and water chemistry. Accordingly, a survey was done, and the results compared with the limited historical data available.

4.1 Historical Data

As part of this study, sampling stations were established at Pine Island (Si te F), upstream of Kambah Pool (Si te G) and downstream of Kambah Pool (Site H). These s i te s do not correspond, however, with those of the Basin study, which sampled at Angle Crossing ( their Site 213) and Kambah Pool i t s e l f (Si te 209).

Comparisons with the present data set have already been made in Table 2.2. In the case of the Kambah Pool data, the differences in quanti­t i e s must arise completely as a result of the flow differences rather than from any changes in Murrumbidgee river i t s e l f .

The Basin study data was col lected in Murrumbidgee flow conditions 3 3that range from 1.4 m / s to 59.3 m / s , whereas the CRES data - taken during

3 3a very dry year - spans Murrumbidgee flow conditions from 0.1 m / s to 7.2nr/s There are, however, certain advantages to th i s . If interest i s centred upon the aes thet ic , chemical and bacteriological aspects of Kambah Pool, then the present study could be taken as representative of the 'worst-case' scenario with virtually no Murrumbidgee River flow to flush out the pool and with the occasional strong Tuggeranong flow depositing runoff from a partly urban catchment.

During the earl ier study in 1976-1977 the ratio of Murrumbidgee flow to Tuggeranong Creek flow during the regular sampling periods ranged from a low of 21 to a high of 193, with an average value of 83.5. For the 1979-80 study the ratio varied from 2.5 to 205 with an average value of 56.0 As we have already seen, there even appeared to be cases, such as the 4th January, 1980 storm, when the ratio was very much less than 1 - indicating that virtual ly all of the water in Kambah Pool during that period came from

56

the Tuggeranong Creek system.

We would re-emphasise the importance o f these flow resu lts fo r he o r ig ina l study ob jectives. With a ' t y p i c a l1 d i lu t io n fac to r ranging fror 50 to 80 parts of Murrumbidgee water to one part of Tuggeranong Creek waer, the po l lu t ion impact of Tuggeranong Creek upon Kambah Pool w i l l be s l igh t except under two conditions:

( i ) a loca lised storm in the Tuggeranong area which only a ffec ts the Tuggeranong Creek system; and

( i i ) extremely low flow conditions in the Murrumbidgee.

Both of these conditions were experienced during th is study. Tie previous chapter has already discussed the e ffec ts o f a loca lised storm <nd showed th a t , even when the storm occurred during Murrumbidgee low flow cm- d i t io n s , the flush ing time of Kambah Pool was less than one day. This Chapter w i l l examine the behaviour o f the Murrumbidgee during the low fl iw

conditions of December 1979 to May 1980.

4.2 Longitudinal V a r ia b i l i t y

In order to examine the low flow varia t ions in the Murrumbidgee we took the three days o f lowest flow from the fo r tn ig h t ly data set and avenged the water qua l i ty variables fo r those three days at each s i te . The resu'ts are given in Table 4 .1 , from which one notices a s l ig h t increase in disso'ved oxygen and tu rb id i ty as one trave ls downstream in the Murrumbidgee but 'ery l i t t l e var ia t ion in any of the other determinands.

The increased diurnal dissolved oxygen alona Kambah Pool probaby

arises from the growth w ith in the pool under low flow conditions. In Section 2.2.5 we have already commented upon the increased tu rb id i t y in Kambah Pool, and compared i t with the Tuggeranong Creek values; the tu rb id i ty readings o f Table 4.1 are so low tha t the s l ig h t downstream increase is un l ike ly to be s ig n i f ic a n t .

4.3 Biology and Water Quality of Kambah Pool

Kambah Pool is the f i r s t slow-moving section o f the Murrumbidgee River below i t s confluence with Tuggeranong Creek. Reduction of water f ow w ith in the increased width and depth o f Kambah Pool has created a deposition- al environment in which substantia l sedimentation of sand and f in e r part d e s has occurred. Low currents and shallow sediment banks provide a habitat

57

TABLE 4.1 Longitudinal Variations in the Murrumbidgee During Low Flow Conditions

Location

(ppm)DissolvedOxygen

(NTU)

Turbidity

r--------------------- (yg/1)Total Total N0?/N0

P N JFi 1terable Reactive P

Pine Island 7.9 2.3 20 593 17 4Upstream Kambah Pool 10.5 3.0 19 587 17 6

Downstream Kambah Pool 10.7 3.9 20 549 19 2.7

suitable for the development of macrophytes (= large plants), which may be large algae, or submergent and emergent higher plants.

Litt le was known of the biological or physical characteristics of Kambah Pool, so CRES mounted several brief surveys to investigate the morpho­metry and some aspects of the aquatic plant community present. These surveys provide a basis for a possible future analysis of plant growth, sediment and nutrient dynamics. The data set collected during this study has provided some information on the long term behaviour of nutrients and sediments within Kambah Pool , but there is an urgent requirement for a more detailed monitor­ing and analysis, so that the ef fects o f important short-term events, such as floods, may be understood. Floods, depending on their severity, are known to have several important consequences for attached water plants.

1. Direct removal and downstream transport of biomass (Basin study). This process may locally reduce the standing crop of aquatic plants, but also serves to transport viable plant fragments and seeds to points downstream, where establishment occurs in fav­ourable situations.

2. Elevated rates of sedimentation during high flows probably in­troduces the bulk of the nutrient inputs to habitats like Kam­bah Pool. Nutrient uptake and recycling within the Pool then releases nutrients, so that the biological and sediment systems gradually become depleted of nutrients in the absence of further nutrient input from upstream.

Macrophytes accelerate ageing of water bodies by collecting sediment around their root systems, thus f i l l ing in the pool. This process is less important in rivers, since very high flows probably cause a net removal of

58

both sediment and biomass, while low to intermediate flows result in net deposition.

Macrophytes are also viewed as a problem by many managers of water bodies (Mitchell, 1978), although only a few of the common problems pertain in any major way to Kambah Pool. These are:

(a) interference with flow;(b) occupation of space, and prevention of fish movement;(c) interference with access to water by people;(d) interference with recreation.

Point (b) above is of minor importance in Kambah Pool, but i t is a serious consequence of excessive attached algal growth (e.g. Cladophora, Hydrodiotyon) in the Murrumbidgee above Lake Burrinjuck, where water nutrient concentrations are higher. Interference with recreation is the most obvious problem in Kambah Pool, and this could change in character rapidly i f nutrient loads increase during the development of Tuggeranong.

Wise management of an important recreational resource like Kambah Pool requires knowledge of the system, and our ini t ial survey, reported below, provides such preliminary information.

4.3.1 Survey methods and data analysis

Kambah Pool was sampled along six transverse transects on March 27- 28, 1980 (see Figure 4.1). Graduated lines were stretched across the pool, and sampling carried out at approximately regular intervals, so that trans­verse patterns of variation were adequately sampled. Several variables of relevance to the measurement and interpretation of macrophyte distribution were measured by diving, and recorded immediately on data sheets. These variables were:

1. species composition - the species present within 1 m ei ther side of the sampling point on the transect line; visual estimate of species dominance was also made;

2. bottom cover - a visual estimate of vegetated bottom cover, expressed as a percentage;

3. vegetation height - measured with a graduated lead line, from the sediment surface to the top of the vegetation;

59

Figure 4.1

Transec t Number

Diurnal O bse rva t ion Sampling SiteDye Sampling Site

ChangirV

K ambah Pool

2 0 0 m

60

4. Sediment type-visually assessed into one of five classes;(Note: twelve representative sediment samples were collected on 2 April, 1980 from transects 2, 4 and 6, and have been stored frozen. These are available for chemical analysis, i f desired);

5. sediment depth - the depth of the s u p e r fic ia l sediment layer ( i f one existed) was directly measured with a steel rule;

6. water depth - measured with a graduated lead line.

The collected data were analysed to provide information on the spatial distributions of the sediment and vegetation characteristics l is ted above. A line printer contour mapping package (SYMAP) was used to produce Figures 4.2 and 4.3 in which the horizontal distributions of two of the sam­pled variables are shown. Our ini t ia l survey undersampled the pool over i ts whole surface area, even though the six transects were sampled in detai l. This undersampling leads to rather abrupt boundaries between contour levels, and could be simply corrected with some follow-up sampling in areas between the existing transects (Figure 4.1).

Simple visual analysis of the data was extended by plotting the variables against transect distance and by examining the relationship of the biological variables with depth (Figures 4.4 to 4.6).

4.3.2 Results and discussion

Kambah Pool has two major aquatic vegetation types. The emergent species such as rushes (Phragmites sp., Typka sp.) and sedges (Cyperus sp.) are not shown in the figures, but are patchily distributed along the l i t to ra l zone of the pool. These plants depend on the sediments for nutrients and water, and photosynthesize using l ight and atmospheric

The emergent l i t to ra l vegetation has an important stabilising function along shore edges, and provides a source of food and shelter for waterfowl, aquatic mammals and invertebrates.

The submergent macrophytic vegetation is dominated by seven species (see Table 4.2), four of which are rooted, higher plants with flowers and leaves (angiosperms); the other three are large green algae. Both the emergent and submergent vegetation support a diversity of microscopic plants and animals which grow directly on their surfaces. The microscopic plants include algae (particularly green algae and diatoms), bacteria and fungi.

61

TABLE 4.2 Annotated Listing of the Seven Dominant Species of Submergent Macrophytes Found in Kambah Pool

Green Algae (Chlorophyta)

Chara sp. (Stonewort) A complex branched alga usually found in s t i l l orslow moving water. This alga is often found entangled among the stems of other species, and penetrates more deeply into the pool than other macrophyte species.

N ite lla sp. (Stonewort) More delicately structured and smaller than the closely related Chara sp. In Kambah Pool this species is restr icted to rocky substrates.

Spirogyra sp. (Blanketweed) A filamentous green alga forming long, hair­like masses with a slippery texture. Variations in light avail­abil i ty cause marked changes in colour and appearance; ranging from small, l ight green tufts in shallow sandy areas to luxuriant, dark green masses in poorly-l i t, deeper water. Often associated with Chara.

Higher Plants (Angiosperms)

Potamogeton erispus (Curly Pondweed) This species has undulating leaf edges, and grows up to the water surface in suitable areas. Flowers protrude through the water surface.

Potamogeton ochreatus (Blunt Pondweed). This species has simple, bluntleaves, and has a similar form and l i fe history to P. orispus.

Myriophyllum sp. (Milfoil) A whorled, feathery-leaved plant, relatively rare in Kambah Pool. Some of the milfoils are able to produce toughen­ed, water-resistant leaves and grow in damp situations after a fall in water level .

Vallisneria sp ira lis (Ribbonweed, Eelweed) Probably the most importantmacrophyte in Kambah Pool. This species has f l a t , s trap-like leaves, and produces flowers and f ru i t on spiral tendri ls . Vallisneria colonises a variety of substrates, ranging from mud and sand to rock, and produces dense beds, which may inhibit flow.

GZ

Figure 4 .2

l OOm!i Sis

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9 ■■■(■((((1334 00 •o ■■■•■•■•:9 oo ♦ .• 0 •■■ ■ I'S SM I 9 00 ♦

Estimated Morphometry of Kambah Pool

26th March, 1980

63

Figure 4.3

l-:\Si?V .

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<20%+ + + + + 20% to 40%0 0 0 0 0 40% to 60%e 0 0 0 0 60% to 80%B B B B B 80% to 100%

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Estimated Distribution of Vegetation Cover in Kambah Pool

26th March, 1980

♦••• •-•'coot'• ♦ -or » ji♦l***CtwOC'(f

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64

Figure 4.4

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Figure 4.5

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66

Figure 4.6

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67

The microbiota of Kambah Pool was not studied further, but certainly plays an important role in the foodweb and nutrient cycles of the pool.

The dense vegetation of the pool is largely restr icted in inter­mediate depths, between about 0.5 and 3.0 m, in a maximum water depth of about 7 m (see Figures 4.2 to 4.4). Lack of light almost certainly res tr ic ts the penetration of most aquatic vegetation into the deepest parts of Kambah Pool (Mitchell, 1978; Wetzel, 1975; Welch, 1980). Damage by bathers seems a likely cause of the low standing crops of vegetation often found in the shallows of the pool.

The submergent species ut i l i se nutrients from both the water column and sediments, and dissolved CO (including HCO ). Photosynthesis is often temperature and light limited in situations such as Kambah Pool.

The present vegetation composition of Kambah Pool reflects a healthy ecosystem. However, i t seems likely that protracted periods of increased dissolved nutrient concentration could lead to a transition from rooted aquatic plants and large algae to a system dominated by planktonic algae (at low flows) with the possibili ty of massive choking growths of different green algae, such as Cladophova and Hydrodictyon. Such a transi tion was forced by sewage effluent discharge into the lower Murrumbidgee (cf. the Basin Study), and seems to have been successfully reversed by the nutrient removal oper­ation of the Lower Molongolo Water Quality Control Centre.

The high macrophyte densities in the Kambah Pool shallows are a mixed blessing. These plants are an important part of the riverine ecosys­tem; recycling nutrients, providing food and shelter for aquatic fauna, s tabilis ing sediments and improving water clari ty. Their tissues contain large amounts of nitrogen and phosphorus, which are ultimately transported downstream or mineralised into the Kambah Pool sediments. Photosynthesis oxygenates the water, and at night plant respiration consumes oxygen (see Section 4.4). The major detrimental effects of macrophytes in Kambah Pool are probably to interfere with swimming, and to add s i l t to otherwise coarse, sandy sediments, thus reducing i t s recreational amenity.

The growth cycle of the Kambah Pool macrophytes is strongly seasonal, with most growth occurring in spring and summer as light and temperature con­ditions improve. Heavy river flows probably reduce standing crops, but the importance of this mechanism is not known for Kambah Pool. We feel that limited mechanical harvesting of macrophytes during their growth period would have three benefits:

i

68

( i ) reduce the area of weed affecting recreation;( i i ) deplete Kambah Pool of stored tissue and sediment nutrients;( i i i ) encourage high plant productiv ity so that increased rates

of tissue nutrient incorporation (and hence sediment nutrient depletion) would result.

4.4 Diurnal Variation in Dissolved Oxygen

Dissolved oxygen concentration and temperature were monitored for 24 hours during March 1980 in Kambah Pool at three sites near the to i le ts and changing rooms (see Figure 4.1). S i te l was located over a sandy bottom, in about 0.5 m of water; Site 3 in about 6 m of water in the deepest section of the erosion meander; and Site 10 in about 1 m of water over a dense weed bank.

The resulting time series are shown in Figure 4.7. The sites over shallow, dense algal and macrophyte populations (Sites 1, 10) show continuous 02 saturation, with obvious supersaturation a fte r a few hours of photo­synthesis. The supersaturated 0 concentrations declined rapidly at dusk due to respiration and loss through the water surface. Site 3S (surface) exhib­ited quite stable saturated 0 concentrations, without a tendency to super­saturate. Site 3D (bottom, approx. 6 m) was chronically oxygen depleted, quite severely so during darkness, and was thermally stable, about 2.5° C colder than the surface water. All surface sites warmed between 1 - 2° C during daylight.

The measured curves indicate high levels of primary production in we ll- l ighted depths, part icu la r ly those supporting macrophytes. Oxygen demand does not appear very great, at least in shallow s ituations, and even the noticeable 0 depletion of Site 3D to about 1.5 mg/1 0 is not serious, provided that the whole pool does not develop such behaviour.

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Figure 4.7

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71

5. DISPERSION AND MIXING

During the study period, intensive surveys were made in Tuggeranong Creek and Murrumbidgee River in order to provide information about the times of travel of water through the rivers and the intensity of longitudinal mix­ing. Transit times and dispersion characteristics were examined by adding a 'slug' of fluorescent dye to the rivers to act as a tracer. The concentrat­ion of this dye was determined at intervals as i t passed a series of sites downstream.

Altogether six separate dye tracing experiments were conducted asfollows:

(a) two separate experiments were conducted on the Tuggeranong Creek retention pond. One of these was on 27 June,1979 and the other was on 10 January, 1980;

(b) the concrete channel was examined on 27 June, 1979;

(c) the portion of Tuggeranong Creek downstream of the retention pond was sampled on 14 November, 1978;

(d) two separate experiments were conducted on Kambah Pool. The f i r s t of these was on 24 October, 1978, prior to the s tart of the present study, and the second was on 10 March, 1980.

This chapter presents the results of these dye experiments together with in i t ia l analysis of the data. The dye experiments have also played an integral role in the formulation of the final CRES model for the system and, in the subsequent chapters which deal specifically with the modelling, we will delve more deeply into certain aspects of the interpretation of the resu l t s .

5.2 Tuggeranong Retention Pond

The aim of these experiments was to investigate the flow-through time for the retention pond and to establish the mixing characteristics with­in the pond. The answers to these queries are of basic importance to the likely performance of the pond, particularly in relation to i ts effects on water quality. The retention time gives an indication of the performance of the pond as regards the settl ing of particulate material while the 'velocity' through the pond can be used to indicate the likely size of material that will remain in suspension; e.g. Figure 5.1. Potentially, the residence

SA

ND

72

Figure 5.1

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73

time can also be used to assess the effects of the pond on nutrients in the r iv e r system, although in th is case the problem is more complex.

Note that the investigation of mixing with depth is also linked with the retention time. I f , fo r example, the input water moves only across the surface of the pond then the retention time w il l be shorter and the overall behaviour w il l be quite d iffe re n t from a s itua tion in which the waters were well mixed.

The input date was selected with the hope that major ra in fa ll would occur early in the experiment. Unfortunately th is was not the case, although ra in fa ll did occur subsequently in the experiment (Figure 5.2).

The fluorescent dye Rhodamine WT was used as the tracer material, with a Turner Designs F ilte r Fluorometer equipped with the appropriate f i l t e r s being used fo r the analysis o f the samples. The f i l t e r s and operat­ing procedure followed the instructions in the manufacturer's manual. The fluorometer is capable of detecting dye at a concentration of about 1 part in 10**, and i t can be read to about ± 0.005 yg/1. Samples were collected

from pre-selected sites marked with buoys. The background fluorescence fo r the pond ranged between 0.015 and 0.0135 yg/1. Twenty-five ml samples were collected and stored in small numbered phials. In the early part of the experiment subsurface samples were collected using a lig h t weight depth sampler suspended from a graduated lin e .

In addition to the sampling locations w ith in the pond, samples were also collected from Site B located on the creek below the dam wall and down­stream of the small pond that has formed immediately below the dam w all. An automatic water sampler was used at th is s ite fo r the f i r s t three weeks of the experiment.

Two l i t r e s o f dye (400 g of dry weight dye) were poured into the upstream end of the pond, immediately below the end of the concrete channel (S ite A on Figure 5.3), at 0730 hrs on the 27th June 1979. The input d is ­charge at that time was low and has been estimated to be about 15 litre s /se c

Samples were collected from the marked sites on Figure 5.3. The co llection of surface and subsurface samples was carried out each day fo r the f i r s t 7 days of the experiment from a boat. Subsequently the sampling in terval was increased and the number of sites sampled in the pond decreased Samples were collected on 27 occasions during the period from 27th June

30-1

TUG

GER

AN

ON

G C

REEK

RE

TEN

TIO

N

74

Figure 5.2

<u_Z<OC

QZoCL

u_z E< Ecc

lOCNJ

oCM

TIM

E,

afte

r D

ye

Inpu

t 19

79

75

u n t i l the experiment was concluded on 1st November. I t should be noted that dye was s t i l l detectable in the pond, at approximately 10 times the back­ground value, as la te as November 1st. Additional samples, mainly from the automatic sampler, were availab le fo r Site B, downstream of the dam.

Figure 5.3 shows the pattern of dye dispersion with time. The f i r s t a r r iv a l of dye at the l i p o f the dam is estimated to be between 0000 and 0600 on June 28th which is approximately 16 to 22 hours a f te r the dye input. By 1400 hrs on June 27th (some 7 hrs. a f te r input) the dye had only ju s t reached S ite 0. The f i r s t a r r iv a l at Site B, downstream of the dam, was at 1540 hrs on June 28th, some 32 hours a f te r input. I t should be noted, however, that the time lag between the dye concentration at the dam top and at the down­stream Site B was due to the e f fe c t o f the pool below the dam.

The most s t r ik in g feature o f the experiment was the degree to which the dye has mixed throughout the pond. This applies to mixing both ho r izon ta l ly

and v e r t ic a l ly . By 1200 hrs on Friday 29th March, the bulk of the pond had an even dye concentration, with the exception that the upstream sites in the re tention pond had s l ig h t ly higher dye concentrations. Mixing through the

water column was also even, although where concentrations were high there was a s l ig h t tendency fo r the bottom samples to have a s l ig h t ly higher concen­t ra t io n . This well mixed pattern was maintained throughout the period of sampling and was s t i l l apparent some 16 weeks a f te r input.

The degree of mixing is the more surpris ing because there was v i r t u a l l y no e f fe c t ive r a in fa l l fo r the f i r s t few weeks of the experiment (see Figure 5 .2). Thus only a very small quantity o f water was discharged over the dam wall and th is is re f lec ted by the lower dye concentrations recorded at Site B fo r the e a r l ie r phases (see Figure 5.4). Indeed there is l i t t l e doubt that much of the discharge in such periods o f low ra in fa l l input is due to wind fo rc ing water over the dam, ra ther than from discharge

from the concrete channel in to the dam.Wind mixing is c lea r ly important: the f i r s t few days o f the experiment weremarked by strong winds and there seems l i t t l e doubt tha t these were respons­ib le fo r the thorough la te ra l and ve r t ica l mixing of dye in the samples taken a f te r about 2 and 18 weeks, respective ly . By th is time one would have expected the upstream portions of the pond to e xh ib i t lower concentrations due to the input water from the inflow channel. Such e ffects were not present and again wind mixing is thought to be responsible.

76

Figure 5.3

77

Effects of dye decay

One potentia l l im i ta t io n o f f luorescent dye tracers is th e i r tendency to decay. The decay can be due to a va r ie ty o f causes and includes photo­chemical destruction and possible adsorption onto both organic and inorgan­ic p a r t ic le s . Rhodamine WT is known to be the most stable of the commonly used fluorescent dyes and, fo r periods of time measured in hours or days, i t is frequently regarded as f u l l y conservative. However fo r experiments in natural waters tha t la s t fo r periods o f weeks there is probably a decay fac to r present. The l i te ra tu re on th is topic is l im ited but a decay rate of about 1% per day would seem appropriate (see Smith 1978, and Warnerand Smith,

1979). In presenting figures o f various time-concentration plots th is decay fac to r should be borne in mind.

Time-concentration curves

Plots fo r a selection o f s ites are given in Figures 5.4 to 5.7. Figure 5.6 gives the data fo r the western edge o f Site 5 and Figure 5.7 gives the data fo r S ite B. The form of these curves is s im i la r but the time lag in the concentrations fo r Site B is evident. We would once again emphasise that the retention pond is exceedingly well mixed. The two curves of Figures 5.5 and 5.6, which were taken on the western edge of the pond, are identica l to those taken in the centre o f the pond when i t was sampled.

For each o f the s ites above the centre of g ra v ity , and the area under the curve is given in Table 5.1, and these results imply a mean d is ­charge during the experiment of between 24 1/s and 31 1/s.

TABLE 5.1

Site Area Linder Curve (ug - w eeks/ l i t re ) Centroid (weeks)

X 19.7 1.84

3 (west edge) 27.04 3.315 (west edge) 26.61 3.387 (west edge) 31.18 4.13B 23.32 3.8

DYE

CO

NC

EN

TRA

TIO

N

CU

RVE

FO

R S

ITE

X

(BO

AT

RAM

P)

73

Figure 5.4

■ I . ■ I I

1 / 0 0 N 0 I 1 U 3 1 N 3 O N 0 O 3 AO

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KS

AFTE

R DY

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AREA

U

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19

.70

C

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=

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DYE

CO

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FO

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ITE

3

SURF

ACE

(LE

FT

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Figure 5.5

<n i — —• — — —■

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AREA

UN

DER

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27

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RR

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SU

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(LE

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80

Figure 5.6

WEE

KS

AFTE

R DY

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DYE

C0N

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F0R

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B

(BEL

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Figure 5.7

WEE

KS

RETE

R DY

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PUT

82

The lower value for the curve area at Site X indicates that complete transverse mixing of the dye had not taken place for the whole experiment at this particular s i te because of i t s proximity to the injection point. The lower value for the area under the curve at Site B most probably results fromi the decay of dye. The 'centre of gravity' for the observed data is close to four weeks, and with allowance for the decay rate is close to eight weeks. These values, which can be regarded as the mean residence times, are of value; in modelling the water quality effects of the retention pond.

Discharge

Clearly, the form of time-concentration curves will be related to the input discharge conditions. No continuous discharge record is available for the input at Site A but the rainfall record for the period is available as shown in Figure 5.2. However, no effective rainfall occurred during the f i r s t 6 weeks of the experiment and by that stage the dye concentration values had declined. With the sampling interval employed, the discharge effects did not noticeably affect the dye concentrations.

The rainfall occurring in the catchment upstream of Site A fromJune 27 to November 2 was 118.6 mm which volumetrically is approximately4,900 megalitres (4.9 x 106 m^). Only a fraction of this is likely to bedischarged at Site A. The volume of the retention pond is estimated to be

5 3110 megalitres (1.1 x 10 m ). Thus, even allowing only a 10% runoff for the catchment, the input flows during the period of the experiment exceed the volume of the pond by a factor close to 5.

These speculative figures are of interest in relation to the dye concentrations, as the major rainfall events do not appear to have displaced the dyed waters but to have mixed with them so that measurable dye concen­trations remain in the retention pond even after major rainfall events. This, further reinforces the earl ier conclusion regarding the mixing characteris­t ics .

The results gleaned from this experiment may be summarised thus:

1. even under conditions of very low input the waters in the retention pond are well mixed both horizontally and vertically by wind;

2. the retention times are lengthy so that some dye, and therefore the solutes i t simulates, could remain in the retention pond for long periods;

83

3. the information gained from the dye experiment can be used to measure the effectiveness of the pond with respect to the deposition of particu la te material in the pond, provided a decay factor fo r such material is available. (See Chapter 6.)

A second dye experiment on the retention pond was conducted in order to examine the e ffec t o f the small storm of 10 January, 1980. Two lit re s (400 gram) of dye was injected at Site A at 1500 hrs and samples were collected by canoe from various stations and depths on the afternoon of 11 January, 1980. These indicated, as with the previous dye experiment, that the lake was re la tive ly well mixed. The dye rapidly mixed la te ra lly and v e rt ic a lly in less than 24 hours.

An automatic sampler was placed at Site B and its results (Figure 5.8) indicate the time from input to dam overflow as about 18 hours.Since by 1740 hrs on 12 January, the sampler dye value was only 0.85 ug/1 compared to 3.50 yg/1 fo r the dam l ip , i t would appear that very l i t t l e water had sp ille d over. Thus the mixing in the lake must be dominantly wind generated. The winds on the afternoon of .11 January were strong but not exceptional.

The sampler at Site B ran fo r about 120 hours and was then removed. This raises problems in in terpreting the data since only the rise in dye con­centration and the peak appear to have been measured. In such cases of sparse data, i t is possible to f i t a concentration-time curve based on a solution to Taylor's d iffus ion equation fo r an impulse input

c (x ,t) = exp [ - ( x- u t>2] (5.1)/4nDt 4Dt

where A is the channel cross-sectional area, M is the mass of dye in jected,U is the mean travel time and D the dispersion coe ffic ien t.

Transformation of th is equation in to a p lo t of t In ( c / t j against t produces a parabola, and i f Taylor's hypothesis is correct, the coeffic ients A (which give Q), D and U may be evaluated by a parabolic least squares f i t . However, i t has been noted previously (Beer, 1979) that in order to obtain sens­ib le resu lts , each transformed data point needs to be weighted according to some power of its concentration. For th is case the best re su lt, as depicted in Figure 5.11, was obtained by a weighting to the sixth power which produced the follow ing coeffic ien ts :

TUG

GER

AN

ON

G

POND

DY

E EX

PER

IMEN

T 1

0/0

1/1

98

0S

ITE

B

84

FIGURE 5 . 8

Id Ld

CD OO 3

_o

_o

r o r o c \ j < \ j - - * - o on/OH) NO I 1 Vd 1 N30N00

120

160

200

240

280

320

360

40

0TI

ME

(HR

S)

85

Centre of gravity = 103 hours Mean cross-sectional area = 165 Mean Q = 0.39 m'Vs Mean Velocity = 0.0024 m/s D = 0.142 m^/s.

I t may be noted that the mean cross-sectional area is in fai r agreement with 2the 220 m calculated in Chapter 3. Further comments on this method of analy­

sis are given later in this chapter.

5.3 Tuggeranong Creek Concrete Channel

This experiment was conducted along the concrete-lined channel that contains Tuggeranong Creek from the Tharwa Road to the Tuggeranong Retention Pond. Eight s ites along this channel provided usable results: the time-series graphs, together with a preliminary interpretation of the results based on the cubic weighted solution to Taylor's equation as discussed above, are given by Beer (1979). Table 5.2 summarises these results. We shall show la ter in this chapter and in Appendix 2 that a superior description of the dispersive effects can be obtained from lumped parameter estimation techniques provided that there are sufficient data.

TABLE 5.2 Mean Hydrological Characteristics from Start of Tuggeranong Creek Drain to Sampling Site

Site Q(l/s) U(m/s) D(m^/s)

1 3.3 0.35 3.32 3.4 0.30 ro

4 4.3 0.28 8.45 8.3 0.28 8.26 10.0 0.29 7.87 11.9 0.23 9.08 14.7 0.30 7.2

The most noticeable effect in Table 5.2 is the steady increase in the mean discharge along the channel. This is almost certainly due to ground- water discharge through the weepholes set in the bottom of the channel. Normally increased discharge would be accompanied, in a channel of uniform cross-section, by increased flow velocities but this was not evident.

i

86

This was due to the gradual downstream widening of the channel.

I t is also noteworthy that the discharge in to the re tention pond of 15 1/s on th is day (27 June, 1979) does not appear representative of the

mean discharge over the subsequent twenty week period. The results summar­ised in Table 5.1 ind ica te that the e f fe c t ive flow through the retention pond was in the range 24 1/s to 31 1/s.

5.4 Downstream Tuggeranong Creek

At 0926 on 14 November, 1978, 20 ml (4 grams dry weight) of Rhoda­mine WT were in jected at the road bridge on Tuggeranong Creek below Site B. Four sampling s ites were chosen.

Site 1: On Tuggeranong Creek ju s t above the confluence with V i l lage Creek,a distance o f 1170 m from the in je c t io n point.

S ite 2: The Gauging Station at Site D, a distance of 506 m from Site 1.

Site 3: Lower Tuggeranong Creek a t S ite E, a distance of 1228 m from Site 2.

Site 4: Just above the confluence (about 10 m upstream) with MurrumbidgeeRiver below the las t pool on Tuggeranong Creek, a distance of 253 m from S ite 3.

The resu lts are summarised in Table 5.3.

TABLE 5.3 Mean Hydrological Characteris tics from Road Bridge to Sampling Si te

Site Area (yg-hr/1) Q(m3/s ) Centroid (hrs) U(m/s)

1 3.03 0.37 1.41 0.232 2.70 0.41 2.23 0.213 2.78 0.40 4.68 0.174 2.30 0.48 6.47 0.14

There is evidence that S ite 4 was affected by backflow from the

Murrumbidgee River. The resu lts from Sites 1, 2 and 3 display the character­i s t i c r is e , peak and decaying t a i l o f dye dispersion results under well-mixed conditions, whereas the behaviour observed at S ite 4 (Figure 5.9) is quite d i f fe re n t . The dye concentration rises and then v i r t u a l ly plateaus, as i f i t

DYE

C

ON

C.

TUG

GER

ANO

NG

CK

S

ITE

87

FIGURE 5 .9

O

^ ( M O O O C D ^ T C X J O

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14

.0

15

.0

16

.0

17

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DYE

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88

was constrained w ith in the area o f the sampling s ite , presumably by the main

stream flow .

5.5 Kambah Pool

Two separate experiments were conducted in order to assess the mix­ing and dispersive ch a ra c te ris tics o f Kambah Pool. These experiments took advantage o f the large Murrumbidgee flow va ria tions between 1978 and 1980: the e a r lie r one was conducted p r io r to the formal commencement o f the study under 'normal' flow cond itions, whereas the second one took place under

unusually low flow cond itions.

At 0800 on 24 October, 1978, 3 l i t r e (600 grams dry weight) of Rhodamine WT was put in to the Murrumbidgee River 10 metres downstream of i ts confluence w ith Tuggeranong Creek. Samples were co llected at S ite 6, S ite H

and a t three traverse lines across Kambah Pool (Figure 4 .1 ).

Transect 2 - across Kambah Pool a t the changing sheds near the sandy beach at the upstream end of the Pool;

Transect 4 - downstream of A, approximately halfway down the length

o f the Pool;Transect 6 - near the downstream end o f the Pool near the sandy bank

below the end o f the roadway.

Figures 5.10 and 5.11 show the dye concentration-tim e curves up­stream and downstream o f Kambah Pool. Within the l im its o f accuracy o f the

experiment, there appears to be no dye re ten tion w ith in the pool, and the3area under the curves implies a flow o f 16 m /s a t an average ve lo c ity

through Kambah Pool o f 0.06 m/s. We may note from the curve o f Figure 5.11 the re la t iv e ly rapid flush ing o f the Pool; in the space o f 10 hours v i r tu ­a l ly a l l o f the dye had passed downstream o f the pool.

Figure 5.12 depicts the dye concentration-tim e curves at surface and depth w ith in Kambah Pool. The main feature to note is th a t, a t these flow cond itions, the pool was very well mixed and could be considered as being ju s t another reach o f the Murrumbidgee R iver, ra the r than a d is t in c t hydro- log ica l e n t ity e xh ib itin g lacus trine ch a ra c te r is tic s . A s im ila r s itu a tio n

prevailed during the second dye experiment: Figure 5.13 depicts theseresu lts taken under p a r t ic u la r ly low flow conditions and the graphs show the high degree o f transverse and la te ra l m ixing.

During the second experiment 200 grams o f dye was in jected at the

DYE

CO

NC

. AB

OVE

KA

MBA

H

POO

L 2

4/1

0/7

889

FIGURE 5 .1 0

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4

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20

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Figure 5.11

O

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r o r o c N O v j — » - o ol / 0 n NO 11V31N30N00 3AQ

15

.0

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27

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91

Figure 5.12(a)

K A M B A H POOL DYE EXP E RIM E NT, 24.10 1978 SURFACE READIN GS

M fl'143-

2

5

TR AN SEC T 6

6 7 8 9 10 11 12HOURS AFTER DYE INPUT

Figure 5.12(b)K A M B A H POOL DYE E XPERIMENT, 24.10.1978 DEPTH RE ADIN GS

92

old pumping sta tion on the Murrumbidgee River upstream from Kambah Pool at 1645 on 10 March, 1980 and, because of the extremely low flow, only morning and afternoon sampling was carried out. The only noteworthy feature of the results of Figure 5.13 is the rise in concentration in the ta i l of the samples taken at depth along traverse 6. The reason fo r th is remains unclear.

5.6 Dispersion Modelling

As we have seen, during the present study the dispersion behaviour of Tuggeranong Creek and Kambah Pool were extensively evaluated using the dye Rhodamine WT. In order to describe th is behaviour in mathematical terms, i t is standard practice to define two parameters - a ve locity U and a disper­sion co e ffic ie n t D - obtained from the measured f i r s t and second moments of the observed concentration versus time curves.

The simplest method of determining D is the method of moments (Dept, of Construction, 1978) but in practice there are problems associated with i t . Fischer et a l . } (1979) point out that dye is slowly released from pockets and causes measurable concentrations of dye to be observed long a fte r the main portion of the dye cloud has passed. The method of moments weights the concentrations in the ta i l heavily, so that i f the ta i l is not ignored the variance increases unreasonably and the dispersion coe ffic ien t can become unconscionably large. Various methods to overcome th is include:

( i ) the routing procedure of Fischer (1968);( i i ) Chatwin's (1971) transformation;( i i i ) a transformation to the concentration data that applies a

power-law weighting to the data (Beer, 1979); and( iv ) analysis using a time-series model of the data in order to

obtain a dynamic description of the reach characte ris tics; th is is then used to compute the ve loc ities and dispersion co e ffic ie n ts .

When one has a sparse data set, or the points w ith in i t are not uniformly d is tribu ted in time, then good results can be obtained from the power-law weighting method (Beer, 1979). With a more comprehensive data set, sampled at reasonably uniform in tervals o f time, the model results obtained by using the time-series analysis technique appear fa r superior to those obtained by other methods. In fa c t, the consistently superior data representation obtained by the time-series model has important implications regarding the physical nature of the dispersive process and

93

FIGURE 5 .13 (a )

K A M B A H POOL E XP E R IM E N T

Dy* lnpu,*ri 12 13 14 15 16 17 1»MARCH 1980

FIGURE 5.13(b)

K A M B A H POO L DYE E X P E R IM E N T 1 0 .3 .1 980

T R A N S E C T 2 - S I T E S 1 , 2 * 3

4 4 . 5 * 6

6 7 , 8 * 9

DEPTH R E A D IN G S

94

suggest that i t is not reasonable to use the coefficient D as a measure of dispersion in rivers. The characterisation of longitudinal dispersion in natural streams is discussed in detail in Appendix 2.

95

6. MATHEMATICAL MODELLING

The primary objectives o f the CRES con tribu tion to the Tuggeranong Study have been to c o lle c t data from regular monitoring and spec ia lly planned experiments, and to u t i l is e these data fo r the construction o f data-based and ob jective hydrological and water q u a lity models o f both the Tuggeranong Creek and the associated Murrumbidgee River system.In previous chapters we described the major a c t iv it ie s as regards data c o lle c t io n , and in the present chapter we discuss how these data have been u t i l is e d in the development o f the mathematical models.

Unfortunate ly, th is model bu ild ing programme was not as compre­hensive as tha t envisaged during the p re lim inary planning stages o f the study. I t was only possible to develop the fo llow ing models, which cons titu te a sub-set o f those o r ig in a lly planned:

(1) A streamflow rou ting model between the Lobb's Hole and Mount MacDonald gauges inc lud ing , as a special case, a smaller model between Pine Island and Mount MacDonald.

(2) A ra in fa ll- ru n o f f model fo r Tuggeranong Creek re la tin g ra in fa ll to gauged flow a t the Tuggeranong Gauge.

(3) A conservative p o llu ta n t transport and dispersion modelo f the Tuggeranong Creek-Murrumbidgee River System between the Monaro Highway Crossing and downstream o f Kambah Pool, based on dye trace r experiment da ta .+

(4) A p a rtia l 'steady s ta te ' p o llu tio n model o f the same system as in (3) describ ing only the long term behaviour o f the major water q u a lity determinands, but w ith each determinand treated as a separate, non-in te racting va riab le .

Non-conservative simulations are possible given appropriate decay rate inform ation.

i

96

Full development of dynamic-stochastic models of water quality for the system was not feasible and hence it is impossible to provide an adequate description of the short term water quality variations of non­conservative pollutants. Limited evaluation of short term or transient loading and nutrient balances, except in relation to the limited data available from the storm monitoring exercises, is discussed in Chapter 3.It should be noted that the rainfall-runoff model (1) is not as extensive as originally intended due to unanticipated deficiences in both rainfall and flow data.

Despite these limitations, it is felt that the computer-based, mathematical models that have been developed provide a reasonable description of the Tuggeranong Creek-Murrumbidgee River System and consider­ably enhance the information on this part of the A.C.T. River System avail­able from the A.C.T. Water Quality Study Report (Department of Construction, 1978). In all cases, the models have been developed on the ANÜ UNIVAC 1100 Computer System in Fortran V language and include extensive visual-inter­active facilities, including graphical data output to VDU hard copier or X-Y plotter. Transfer of these models to the NCDC Computer System will be accomplished after the completion of the main study.

The overall philosophy of modelling used by the team has been described fully elsewhere (e.g., Young, 1978; Humphries, Young and Beer, 1980) and will not be repeated here. Suffice it to say that the modelling is, first and foremost, 'data-based', in the sense that all mathematical descriptions are holistic and are obtained directly from the analysis of in situ data, usually by resort to some form of time-series analysis. Speculative simulation modelling based on reductionist principles is not utilised by the Applied Systems Group in CRES unless it is carried out with­in a stochastic setting, usually as the basis for generating initial hypo­theses about system behaviour (see Humphries, et al., 1980; Chapter 5).No such stochastic simulation modelling has been attempted in the present study.

97

Also the modelling is 'ob jective orientated' in the sense that the model form and type are chosen to sa tis fy the objectives of the study; i.e . the model is not normally intended to describe the system in great deta il unless such deta il is essential to achieving these objectives and a sa tis ­factory data base is available to allow i t . This is a most important aspect of applied systems analysis and can be misunderstood. A large and detailed model is not necessarily a 'b e tte r ' model of a dynamic system, pa rticu la rly i f the data base is lim ited (as is usually the case in environmental systems analysis). And such a large model may well contain surplus, unvalidated con­tent whose presence is d i f f ic u l t to ju s t ify i f the study objectives only demand description at a less detailed level (see Young, 1978). There are, in other words, dangers in relying on speculative simulation models and a concentration on the use of data based, objective orientated models, when­ever th is is possible, tends to avoid such dangers.

6.1 A Flow Routing Model of the Murrumbidgee River System Including Tuggeranong Creek

The flow routing model developed fo r the present study is s im ila r in concept and structure to previous models constructed fo r the Bedford-Ouse River System in Eastern England (Whitehead and Young, 1975; Whitehead,Young and Hornberger, 1979b) and the Murray River of Western Australia (Humphries, Young and Beer, 1980). I t has been implemented in purely deter­m in is tic form, although stochastic extensions such as those discussed in the above references can be incorporated fa ir ly stra ight-fo rw ard ly i f required.

The riv e r system is subdivided into N reaches, each described by the follow ing ordinary d iffe re n tia l equation

f = i(I-Q) (6.1)

where3

Q = riv e r flow (m /u n it time)3I = inflow from upstream reach (m )

K = time constant, 'time of t ra v e l', or 'residence time' of reach.

As K is a 'residence time' parameter, i t is a function of flow and is defined in the normal manner, i.e .

K VQ

98

where V is the changing volume of the reach. Taking note o f the fact that

V = Aax; Q = AU

where A is the changing cross sectional reach area, Ax the reach length and U the mean flow ve lo c ity , i t is clear that K can be defined a lte rna tive ly as

K = ^ (6.2)

Since U is not d ire c tly available fo r measurement, i t must be estimated from Q and a well known empirical re lationship is used here of the form

U = aQb (6.3)

where the coe ffic ien ts a and b can be evaluated e ither by theoretical analy­sis based on the hydraulic characteristics of the system or by empirical methods based on the results of dye tracer experiments carried out under d iffe re n t flow conditions.

In the present study values of a = 0.046 and b = 0.57 were obtained from dye tracer studies carried out on the Murrumbidgee System during previ­ous studies (WATERCRES, 1978).

I t should be noted here that there is an im p lic it assumption of mass conservation in the reach model (6.1) to (6 .3 ); in other words, add it­ional mass flow is neither added nor lo s t between upstream and downstream sites at each reach. This becomes apparent i f we consider 'steady sta te ' or 'equ ilib rium ' conditions: then dQ/dt = 0 and we see from (6.1) that I = Q.In systems terms, we say that the steady state gain (SSG) between I and Q is un ity : i f mass is added by ra in fa l1-runo ff processes between upstream anddownstream location , then we would expect the SSG to be greater than un ity ; i f water is lo s t by evaporation or to the groundwater, however, SSG would be less than un ity. For s im p lic ity , such effects are introduced at 'node points' between reaches so tha t, fo r instance, Tuggeranong Creek enters the main Murrumbidgee routing model at the nearest convenient node point to the geographical position of the actual confluence.

The detailed structure o f the model including the number of reaches between gauging stations and confluence points is determined by a combin­ation of time-series analysis and in teractive simulation modelling. Time- series analysis can easily and quickly indicate the overall dynamic behaviour

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Figure 6.

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between upstream and downstream gauge points and can provide an i n i t i a l idea of the reach s t ru ct u re appropriate to describing such behaviour. In ter ac t ive simulation modelling then allows for the modification of th is i n i t i a l model to allow for b e t t e r explanation of the data and more appropriate f ine s t r u c ­tu re , usual ly in re la t io n to the object ives of the model building exercise.

Typical of the r e su l t s obtained in the i n i t i a l t ime-ser ies analys is are those given in Figure 6.1 which shows the output xk of a t ime-ser ies model for dai ly flow var ia t ions between Pine Island and Mount MacDonald for dai ly data over al l of 1971. This model is in d iscre te- t ime terms and takes

*f*the form of a sta tic , or steady s t a t e re la t io nsh ip ,

xk = 1.1819uk ( i ) (6.4)

yk = \ + 5k (11)

here xk denotes the modelled flow a t the downstream or 'o u t p u t ' , Mount Mac­Donald gauge; while uk is the upstream of ' inpu t ' flow at Pine Island. The measured ( i . e . gauged) output flow a t Mount MacDonald i s represented by y k , and £k denotes the s tochas t i c or 'noise ' e f fec ts not explained by the d e t e r ­minis t ic re la t ionsh ip between xk and uk in ( 6 . 4 ) ( i i ) . I t i s c lea r fromFigure 6.1 tha t the model adequately describes the data: in f a c t , the

2co e ff i c i en t of determination Ry for the model, i . e .

RT2 ^ 2

is 0.9825; in other words, the percentage of the variance of y k not explain­ed by the model i s only 1.75%. This unexplained s tochas t i c e f f ec t is em­bodied in the s tochas t i c var iable £k and fu r the r t ime-ser ies analysis (see e .g. Young and Jakeman, 1979) could y ie ld an autoregress ive , moving average (ARMA) model for £k which would then allow for s t a t i s t i c a l forecast ing of y k on a recursive bas is . However, in the present context , we are concerned not with fo recas t ing, as such, but with the re la t ionsh ip between xk and uk> since t h i s represents the major ch a rac te r i s t i e s of the r i v e r system between Pine Island and Mount MacDonald which need to be represented by the flow routing model .

This a r is e s because the dynamic behaviour a l l takes place within the sampling period of one day.

101

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£>a:0 )0)o>

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a;

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Note that the model 6.4 is a purely sta t ic or equilibrium model, with no apparent dynamics. This arises because all dynamic act ivity in the system between the two gauging points takes place well within the daily sampling interval (as indicated by the dye tracer results) and so is not apparent from the daily sampled data. Hourly sampling would provide infor­mation on this short term behaviour and could be used for time-series analy­s is , but this was not carried out in the present exercise since i t was fe l t that a daily model of the Murrumbidgee was adequate, given the lack of short term water quality data.

From equation (6.4) we see that, on the average, the flow at Mount MacDonald is 1.18 times greater than that forecast by a 'unity gain' determ­inist ic model on the basis of upstream gauged flow at Pine Island alone.And i t implies that 0.18 of this flow is contributed by rainfall-runoff processes occurring between the two gauging stations including, most import­antly, that arising from the Tuggeranong Creek system.+

A schematic diagram of the daily flow routing model is given in Figure 6.2, where i t can be seen that the 20.3 km length of river is decom­posed into eight reaches, the f i r s t of 2.8 km and the rest of 2.5 km, with Tuggeranong Creek entering after the f i r s t reach. Note also that the model has been extended further downstream from Mount MacDonald to Burrinjuck Dam including the effects of Paddy's River, Cotter River, Molonglo River below Lake Burley Griffin and Yarralumla Creek. All t ributaries enter the model as simple additive inputs.

An alternative version of this model is shown in Figure 6.3. Here the model has been extended upstream to include the Lobbs Hole and Gudgenby gauges, so avoiding the need for Pine Island gauge data. This may be advantageous to the NCDC since Pine Island and Gudgenby gauge data are avail­able directly from the Department of Construction while Pine Island data has to be obtained from the N.S.W. Water Resources Commission.

A typical example of the output of the second model is shown in Figure 6.4, which compares the model output x with the observed flow ob­tained from the Mount MacDonald gauge for the year 1977. The f i r s t model also reproduces the flow behaviour at Mount MacDonald quite well and i t has been the main vehicle for the estimation of flows at Kambah Pool over the 1979-80 study year, where only data from Pine Island is so far available.

Note that this was for 1971 which was dominated by the early high flow periods of some 850 cumecs around day 40.

GAUG

ING

STA

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103

Figire 6.4

_ CD— m

CD CD CD CD CD CDO CD ID CvJ CsJ•— ' I

> -GZQ

104

6.2 Rainfall-Flow Model fo r Tuggeranong Creek

When modelling the ra in fa ll/ru n o ff characteristics of Tuggeranong Creek, i t is important to recognise that the catchment area is part urtan and part ru ra l. The hydrology of urban and rural catchments may be expected to d if fe r considerably. The rural areas consist mainly of non-irrigated pas­tures and woodlands. Rainfall in these areas may be absorbed by the ground, i f dry,and produce no runoff. I f the ground is saturated, however, runoff w il l occur slowly with water f i l te r in g through vegetation and passing down natural water courses. By contrast urban areas consist, in part, of imperm­eable surfaces such as roads, house roofs and compacted s o il. Rainfall on these surfaces w il l pass quickly into storm-water drains or concrete culverts, and w il l reach the creek quite rap id ly . Urban areas consist also of gardens, playing fie ld s and the lik e , which are frequently irr ig a te d . A storm on irr iga ted so il w il l be more lik e ly to produce saturated conditions than is the case fo r rural s o il. When the water drains o f f , i t soon reaches a drain, and runoff is , therefore, quite rapid.

The purpose of th is section is to develop a prelim inary uethodology fo r evaluating separately the urban and rural runoff. The methodclogy is then applied to ra in fa l1/runo ff measurements fo r the Tuggeranong area fo r June to December, 1977.

Rural so il in the Tuggeranong area may be characterised as an upper layer of permeable top so il, covering a re la tive ly impermeable subsoil. Run­o ff characteristics are largely unaffected by the condition of the subsoil, and depend mainly on the moisture content of the top layer of so il and on the quantity of surface vegetation. When conditions have been very dry, topsoil can absorb 50-70 mm of water per hour, and subsoil can absorb 5 mm per hour, up to saturation point, with very l i t t l e runoff. On an improved pasture at the end of a dry summer, a ra in fa ll of 40-60 mm may be absorbed almost en tire ly (Talsma 1976 and Costin 1980). In other words, based on studies in s im ila r areas, i t would appear that a constant ra in fa ll of 70 mm/ hour could fa l l in the Tuggeranong area fo r 50 minutes with minimal re su lt­ant runoff.

Once the so il is wet, i t can s ta rt to lose water by evaporation and by plant transp ira tion . With well vegetated s o il, most of the moisture loss is through plant transp ira tion . Dunin (CSIR0, D ivision of Plant Industry) has performed some measurements on improved pasture at Krawarree on the upper Shoalhaven catchment area. Quoting so il moisture as cc. of water per

105

cc. of soi l , the figures show that saturated topsoil has a moisture content of 0.25. From 0.25 down to 0.15 the moisture loss rate appears to be about 0.8 pan evaporation rate. Below 0.15 plants s ta r t to wilt , and their trans­piration rate decreases. Moisture loss appears to reduce linearly from 0.8 pan evaporation at moisture = 0.15 to zero at moisture = 0.1. Below 0.1 the plant cover has wilted and no transpiration seems to occur.

We can construct a preliminary speculative model of soil moisture by assuming that

(a) most rainfalls are absorbed by unsaturated, well vegetated top soi l , and very l i t t l e by the sub-soil which is assumed in this model to be impervious;

(b) moisture loss follows the pattern described above;(c) the depth of topsoil is known.

Clearly, the depth of topsoil is not known accurately for Tuggera- nong. For Ginninderra (Costin, 1980) if 40 mm of rain can be absorbed by soil with a moisture range of 0.1 to .25, the depth must be at least 40/.15 = 260 mm. Three random topsoil depths were measured in the Tuggeranong catchment on 8.5.79 giving an average depth of 290 mm.

To test the method, a soil moisture simulation was run, assuming f i r s t ly 200 mm depth of topsoil, then 300 mm. Evaporation figures used were monthly figures for Canberra Airport, supplied by the Bureau of Meteorology. For the seven months June to December, 1977, these were 65.7, 53.7, 88.3, 108.5, 206.9, 258.9 and 325.5 mm respectively. Daily evaporation figures are available but i t was fe l t that monthly figures are sufficiently accurate for this purpose. The evaporation was averaged over the days in the month, and no account taken of the likelihood of lower evaporation on rainy days. The soil was assumed to be saturated at the s ta r t of the period so that the 'worst' or most moist case could be examined. Using the model, soil moist­ure and runoff were calculated for each 12 hour period in the seven months. The results are plotted in Figure 6.5(a) (taking topsoil depth as 200 mm) and Figure 6.5(b) (taking topsoil as 300 mm). I t can be seen that in both cases the soil moisture never exceeded saturation (.25) and therefore i t seems highly likely that no rural runoff at all occurred during this period.

The reader should note here that this modelling is purely specu­lative and reported here to give some idea of the possible soil moisture be­haviour of the system. Future work should carry out this analysis on a stochastic basis, with parameters specified as probability distributions

TU&G

ERRN

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S0IL

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1977

(2

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106

Figure 6.5(a)

a

1BI0W 1 1 0 5

12 H

RLY

ORTH

TUGGERHN0NG AREA

S0IL H

0ISTURE

JUN

T0 D

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977

(300MN D

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107

Figure 6.5(b)

co

- o

- U - l i l l 1 l.U-1 I t t t 1 t 1 1 1 U i l l 1.11-1 ii-l

1S10W ~110S

108

rather than point estimates and simulation carried out using stochastic

(Monte Carlo) methods.

In order to obtain some idea of the Tuggeranong Creek catchment character is t ics i t is necessary to re la te r a in fa l l on the catchment to flow measured at the Tuggeranong Creek gauging s ta t ion . O r ig ina l ly we were led to believe that there were gauge records available at two points on the Creek: one at the dam (retention pond) s i te and one downstream of theVil lage Creek confluence. Such gauging would have allowed fo r quite detailed modelling of the catchment, w ith t ime-series ra in fa l 1-runo ff models supple­mented by flow routing between gauges, including e x p l ic i t id e n t i f ic a t io n of the V il lage Creek con tr ibu tion . In the event, the somewhat misnamed 'dam- s i te ' gauge did not, in fa c t , e x is t p r io r to re tention pond construction and d i f f i c u l t i e s in in te rp re t ing the data obtained since i t s establishment have meant that they could not be used in model development.

In th is s i tu a t io n , there are two a l te rna t ive approaches to the mod­e l l in g problem: f i r s t a simple t ime-series representation o f ra in fa l l - ru n o f fat the Tuggeranong Creek gauge can y ie ld information on the aggregate catch­ment dynamics; second, some form of dynamic simulation model based on both catchment data and the l im ited r a in fa l l - f lo w records can be constructed to allow fo r greater descrip t ive deta il than is possible from the time-series model.

The r a in fa l l - r u n o f f model is obtained by d ire c t analysis of the time-series, again using the CAPTAIN computer program package (e.g. Young and Jakeman, 1979). A diagram of the model is shown in Figure 6.6 where we see that i t consists o f a series connection o f two sub-models: the f i r s t is a non-linear so i l moisture - evapotranspiration sub-model which y ie lds an 'e f fe c t iv e ' ra in fa l l input to the second sub-model, which is simply a l inea r trans fe r function model o f the type used in the previous section fo r stream- flow time-series analysis. The use of the CAPTAIN package fo r th is kind of analysis has been discussed by Young (1974), Whitehead and Young (1975) and Whitehead et a l . y (1979b). Consequently we w i l l r e s t r i c t the present description to the main aspects o f the model bu ild ing .

The ra in fa l l r^ is f i r s t processed by a 's o i l moisture' f i l t e r ofthe form

c-1 + f <r* sk - l* ( 6 . 6 )

109

Figure 6.6

_ J

LU

O

Li_

O

<cll_

I—•

2u _

§sLUOOW§oro<

sC

Q

no

where is a measure o f s o i l moisture and T is the dominant t im e-constant

associated w ith the s o i l w e tt ing and dry ing c h a ra c te r is t ic s . The 'e f f e c t i v e '

r a i n f a l l u^ is then obtained as the product

uk*k

sk^max(6.7)

where ( s . ) mav is the maximum value o f s. over the data record and ß is a

se lected power law, in the present case u n i ty . The longer term (seasonal)

evapo transp ira t ion m o d if ic a t io n to the r a i n f a l l measure is usua lly app lied to

Uj obtained from (6 .7 ) . In the present case, however, ce rta in d i f f i c u l t i e s

were encountered w ith the in te rp re ta t io n o f the t im e-ser ies in the long term

and so, as we sha l l see, s a t is fa c to ry evapo transp ira t ion e f fe c ts proved ex­

tremely d i f f i c u l t to id e n t i f y from the t im e-se r ies data.

The eva lua t ion o f T in (6.6) is ca rr ie d out by reso r t to recu rs ive

e s t im a t ion . The t ra n s fe r fu nc t io n model in Figure 6.6 is estimated f i r s t

using the unmodified r k ser ies as a d i r e c t in p u t ( i . e . by-passing completely

the non linea r block A): th is y ie ld s recu rs ive estimates o f the c o e f f ic ie n ts

in the B(z~1) polynomial w ith pronounced shor t term temporal v a r ia t io n (non-

s t a t i o n a r i t y ) over the data i n t e r v a l . In t ro d u c t io n o f the s o i l moisture f i l ­

t e r tends to remove th is temporal v a r ia t io n and the T value is selected so

th a t the c o e f f ic ie n ts are as close to s t a t io n a r i t y ( t im e - inva r iance ) as poss­

ib le in the short term. Longer term v a r i a b i l i t y may s t i l l be present, how­

ever, because th is w i l l be re la ted to the longer term e f fe c ts - such as

evapo transp ira t ion .

In the present case, we found no d i f f i c u l t y in modelling the short

term behaviour and id e n t i f y in g a s u i ta b le T va lue. Figures 6.7(a) and 6.8(a)

show the model f i t obtained over two periods o f 125 hours; the f i r s t s t a r t ­

ing 0000 hours on 22nd February, 1977 and the second a t 1500 hours on 31st

August, 1977. In each case, the s o i l moisture time constant T was se t a t

5 hours ( the sampling in te rv a l was 0.5 hours so th is represents 10 sampling

in t e r v a ls ) . Also the data were analysed in both cases w ith base f low e f fe c ts

present ( t h i s is p e r fe c t ly a l lowable when using the CAPTAIN package and

represents a s ig n i f i c a n t advantage o f the program). As a r e s u l t , the model

f i t is somewhat d is to r te d and Figures 6 .7 (b) and 6 .8 (b ) show the improved

model f i t when base f low e f fe c ts have been added to the model using an

estimate obtained by frequency s e le c t iv e smoothing o f the data. We now see

TUG

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Figure 6J (a)

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100

125

150

175

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25

250

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(0.5

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112

Figure 6.7 (b)

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100

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150

175

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Figure 6.8 (a)

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114

Figure 6.8 (b)

O Q_

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(SOBHnO) M 0 1 J

100

125

150

175

200

225

250

TIM

E

(0.5

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115

that the model is adequately modelling the recession part of the response in both cases .

The t ransfer functions of the two models to generate Figures 6.7 and 6.8 are as follows:

(i) 22/02/77:

( i i ) 31/08/77:

1.21 + 0.98z'1 - 0.69z •1 Uk + 5k

0.36 + 1.27z“1 ..y k = ------------------

1 - 0.79z -1 k + ?k

( 6 . 8 )

and thei r impulse response character is t ics are shown in Figure 6.9. This im­pulse response can be interpreted directly in hydrological terms as the unit hydrograph response of the catchment to a unit impulse of e f fe c t iv e r a in fa l l . We see that the two responses are quite similar; indeed, they are identical to within the standard errors on the parameter estimates.

The SSG’s for each model are given as follows (see Section 6.1)

( i ) SSG = 1.21 + 0.98 _ 1 - 0.69 7.0

( i i ) SSG 0.36 + 1.27 _ o 1 = 0.79 7,8

In other words, for the 22nd February data, 1 mm of e f fe c t iv e ra infal l yield­ed 7.0 cumecs of flow; while for the 31st August data, the yield was 7.8 cumecs. The closeness of these figures for widely separated data sets sug­gests that the model description is adequate. This is confirmed in Figures 6.10(a) and (b) which show the model f i t to the 31st August data using the 22nd February model, with and without base flow: this can be considered asan in i t ia l validation stage in the analysis and the f i t is certainly good enough to conclude that the short term models are ent i re ly adequate.

Unfortunately these sat isfactory short term resul ts are not repro­duced by long term analysis. In i t i a l evaluation of the data on a longer term basis confirm the short term analysis, with time-series models based on a daily sampling interval providing good short term ( i . e . over a few days) f i t to the observed gauge data.

TUG

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C

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KIM

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R

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31

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T I M

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116

F ig u re 6 .9

O

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c\ J *— *— »— o o o o(so3nno) moi j

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TUG

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117

Figure 6.10(a)

o o_

to 2QD OO O

(S03ND0) MOld

100

125

150

175

200

225

250

TIM

E

(0.5

H

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TUG

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1500

H

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31

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ITH

B

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W

INC

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TED

U

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R 2

2/

02

/77

118

Figure 6.10(b)

C S C G W n O ) M 0 1 J

100

125

150

175

20

0

225

250

TIM

E

(0.5

H

OU

RS)

119

Figure 6.11 shows the plots o f daily ra in fa ll and flow fo r the whole of 1977. A typ ical e ffo r t at modelling is shown in Figure 6.12 where the da ily model output over the whole o f 1977 is compared with the gauged flow data over the same period. Clearly the model reproduces transient patterns of behaviour quite well but the prediction of flow magnitude is quite often in considerable e rro r, making the model v ir tu a lly useless as a predictive to o l.

The problem appears to be one of data deficiency. F irs t i t seems tha t, in the long term, no one rain gauge is s u ff ic ie n t to describe the very heterogenous ra in fa ll patterns. Furthermore, use of a ll available ra in fa ll gauge data in the general area (Farrer, Torrens, Kambah, and Tuggeranong Creek) does not s ig n ific a n tly a ffect th is descriptive a b i l i ty : in otherwords, i t seems impossible to adequately explain the flow variations indicat­ed by the Tuggeranong gauge in re la tion to the measured ra in fa ll in the area. Secondly, the gauge data i t s e l f may well be inadequate and th is could ex­plain the lack of long term corre la tion between the magnitude of the measur­ed ra in fa ll and resultant flow. Indeed, we have observed during regular water q ua lity monitoring that the pipe leading from the Creek to the gauging hut is quite often p a r tia lly blocked with sand and we believe tha t th is could, at times, lead to erroneous flow measures. This is ce rta in ly consist­ent with our in te rpre ta tion of the data, and a re-examination of the 1977gauge data indicates that there was indeed a malfunction which prevented any

3 -1flows of greater than 18 m s being recorded.

We feel that there is no short term solution to th is problem. We can only recommend that some improvement o f the Tuggeranong Creek gauging station is carried out and that an investigation of the adequacy of ra in fa ll monitoring in the area is undertaken subsequent to th is (since i t may be that more accurate gauging could, in i t s e l f , s u ff ic ie n tly improve the s itu a tio n ).

6.3 A Conservative Pollutant Dispersion and Transportation Model

During the study CRES has devoted considerable e ffo r t to the plann­ing and execution of several dye d ilu tio n gauging and dispersion experiments covering the whole of the study area from the Monaro Highway crossing to Kambah Pool. The results of these exercises have been discussed in Chapter 5. In th is section, we w il l show how these results can be used: f i r s t , todevelop a model fo r transportation and dispersion of conservative pollutants

56

.0-4

D

AIL

Y

TUG

GER

ANO

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RA

INFA

LL

1977

120

Figure 6.11(a)

O00

O

O

00

i— i— ro cm r

ro c\ j

(AIAI) 11VJN I V8

oCD

o

oooO

120

160

200

240

280

320

360

400

TIM

E

(DA

YS

)

DAIL

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1977

121

Figure 6.11(b)

_o

_o

(SOdHPlO) MO Id

120

160

200

240

280

320

360

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in the system under the flow conditions prevailing at the time of the exer­cises; and second to extend this model in order to obtain some idea of the behaviour under varying flow conditions. This second part of the modelling exercise can be considered as an i n i t i a l extrapolation of the basic model using physically reasonable principles. As such, i t will need to be val i­dated by later dye tracer exercises i f i t is to be entirely adequate in a predictive sense. At present, however, we feel that i t represents the best evaluation of the system behaviour available from the analysis of existing data.

The dye experiment data has been processed using the CAPTAIN package. Typical examples of the analysis are shown in Figures 6.13 to 6.17 which com­pare the output of a time-series model for dye concentration at various points in the system with the temporal changes in dye concentrations measured during the experiments.

Figure 6.13, shows the results obtained for the length of concrete channel between Sites 6 and 7 (see Chapter 5). The model, based on a sampl­ing interval of 2 minutes, takes the form

where x ^ denotes the estimated dye concentration at Site 7 and x ^ the measured concentration at Site 6 , both at the kth sampling instant. The in­put term x 7 indicates that the effect of changes in dye concentration at Site 6 is not observed at Site 7 until af ter a pure time (transportation) delay of 7 sampling intervals; in this case 14 minutes. I t can be shown (e.g. Young 1980; Takahashi et a l . , 1970) that the discrete-time (difference equation or sampled data) model (6.9) is approximately equivalent to a con­tinuous-time (differential equation) model of the form,

where here i = 7, 6 = 14 mins, bQ = 0.83 and = 4.5.

In dynamic systems terms (6.10) is a f i r s t order dynamic system with a time constant of 4.5 minutes, a steady state gain (SSG) of 0.83 and a pure time delay of 14 minutes; in other words, i t indicates that an impulse (gulp) input of dye at Site 6 will not be detectable at Site 7 until 14

x7k 0,64 x7, k-1 + ° 430 x6 , k-7 (6.9)

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minutes after injection (the transportation time delay; i .e . the time taken for the dye front to travel from Site 6 to Site 7); the concentration at Site 7 will then quickly rise to a peak value within 2 minutes (as the data were obtained from discrete sampling at a 2 minute interval, any continuous time extrapolation is only able to locate the peak to within this accuracy), and will thereafter decay exponentially to background levels with an expon­ential time constant of 4.5 minutes. A plot of this unit impulse response is given in Figure 6.14. For convenience, Figure 6.14 is a plot of the discrete­time model (6.9) impulse response, as the reader may verify by straight­forward recursive solution of (6.9) with u ^ defined as zero for 0>k>1.0 and unity for k = 1.0.

Note that the SSG of 0.83 is an indication of an apparent lack of conservativeness (an SSG of unity defines a completely conservative system) caused ei ther by decay of dye or by dilution, caused by additional inflow along the section of the channel. This has been discussed in Chapter 5 where we conclude that, since SSG values are normally unity on all other parts of the system, i t is unlikely that the dye is i t se l f non-conservative. Rather the nature of the channel and the Isabella Plains through which i t passes probably allow water inflow and consequent dilution effects (see Chapter 5).

In Figures 6.15, 6.16 and 6.17 are the plots of typical modelling results obtained from the other three dye tracer experiments: that on the retention pond, the section of Tuggeranong Creek below the retention pond and the Murrumbidgee River between the Tuggeranong Creek con­fluence and below Kambah Pool. Figure 6.15 shows the model f i t for the main part of the retention pond between Sites X and B, below the dam wall: here, as expected, we see very slow response characteristics with a pure time delay (TD) of 0.25 weeks and an exponential decay time, or time constant (TC) of 2.6 weeks, with l i t t l e indication that the flow variations occurring over the experimental period had any significant effect on these dynamic charac­te r i s t ics (see Chapter 5).

Figure 6.16 supplies the model f i t over the lower reaches of Tugger­anong Creek prior to the final reach at the Murrumbidgee River confluence: note the quite rapid r ise (TD = 160 mins; TC = 44 mins) and the fact that the model was of second order.

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The second order model is

( 0.1220 0.1454z"1 + 0,0582z~2)(1 - 1.624z“1 + 0.66z"2) Uk-6 +

where TD equals 6 multiplied by the sampling interval ; u is the upstream input a t time k and y^ is the downstream output. A second order model of this form can be broken up into two f i r s t order models:

Wk- y 1)

(1 - ajZ- 1 )uk-D

(ß.*k

so that(1 - aj z A)

B.z '1)— T T Wk - A + e k

so bo - (eo bl + el ho» z' ‘ + el bl z‘ 2 n-1 -2 1 - (a^ + a^) Z + a^ z V d- a + ?k

Factorisation of the observed model indicates that two identical f i r s t order models in series are suitable , within the errors on the parameter estimates, each with TD = 80 minutes and TC = 22 minutes. This i l l u s t r a t e s one advan­tage of the present modelling approach: a p r io r i specification of reachlengths is not essen t ia l ; i f a reach length is chosen too large, as in this case, then the analysis indicates the need to model as two reaches of shorter length. This can be extremely useful in the planning of further dye t racer experiments (see Jakeman and Young, 1980).

Finally Figure 6.17 shows the model f i t obtained over the Kambah Pool ( i . e . between the 'upstream' and 'downstream' Kambah Pool sampling s ta t ions ) . Here the analysis indicates a total TD of 160 minutes and total TC of 96 minutes but, again, indicates the need to model in terms of two separate f i r s t order reaches, each with TD = 80 minutes and TC = 48 minutes.

These time-series models can be considered in more conventional ' retention time' terms. For example, in the Kambah Pool case the retention time T is simply the sum of the total pure time delay and the two time constants i . e .

T = 2 x 80 + 2 x 48 = 256 mins. = 4.26 hrs.

131

If we now define T in the normal manner i .e .

where V is the effective volume of the pool which will be less than or equalto the actual volume and Q is the flow rate, then an estimate of V can beobtained from this expression by substituting for the flow rate Q as obtainedfrom the dye tracer experimental analysis (Chapter 5). In this case Q =

3 - 116.0 m s so an estimate V of V is obtained as

i .e .V = 4.26 x 16 x 3600

V = 245,700 m3

It is now possible to compute approximate T values at other flow rates usingthis value of V under the assumption that the effective volume remains con-

+stant over the range of flow rates being considered. Typical examples are

3 - 1 3 - 1given in Table 6.1 for the flow values of 16 m s , and 0.3 m s respec­tively. Also the table shows T values for these storms alone, i .e . with zero Murrumbidgee flow ('worst case' examples).

TABLE 6.1 Mean Retention Times in Kambah Pool for Various Flow Rates

Flow (cumecs) Mean Retention Time, T (hours)

16.0 4.260.3 227.6

0.3 + 2.153 27.80.3 + 3.33 18.8

16 + 2.153 3.7516 + 3.33 3.53

2.153 31.73.33 20.4

The dynamic model of the entire system is shown in block diagram form in Figure 6.18. We see that i t is composed of 23 reaches each described

The validity of this extrapolation is d iff icult to check using the present data, but i t seems a reasonable assumption.

MU

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133

by a f i r s t order dynamic system such as (6.10) with specified reach number ( i ) , pure time delay {&) and time constant (a^). This model provides a very accurate description of the transportation and dispersion characteristics of the system for the flow conditions pertaining a t the time of the experiment. Nominally, however, i t does not allow for the prediction of such character­istics under other flow conditions.

In order to introduce such an extrapolative potential to the model, we have considered a physical interpretation of the dynamic model (6.10) in terms of a continuous sti rred tank reactor (CSTR) mechanism, well known in chemical engineering applications and introduced into water quality modelling studies by Beck and Young (1975). Here a simple mass conservation analysis of a short reach under the assumption of complete mixing ( i . e . the output concentration is representative of the average concentration in the reach) yields a differential equation model of the form

mass exchange = mass in mass out

i .e.dx.(t)

VE dt = Qxi _1(t) Qx.(t)1

where Q is the flow rate and is the 'effect ive' volume, i . e . the volume of the reach 'effect ive' in producing the observed dynamic behaviour; V^isnot, in other words, the actual volume of the reach discussed above. Note that in (6.11) both Q and V£ are nominally functions of time.

If we consider a number of such reaches in series, then i t is well known (e.g. Marshall, 1980) that the overall dynamic equation can be approxi­mated by series connection of a differential equation of low order (in com­parison with the number of reaches) and a pure (transportation) time delay.In the f i r s t order case, for example, this model can be written

Ve ^Q dt xi - l (t_6) - x.( t) ( 6 . 12)

where 6 is the pure time delay and Vg is again an 'effect ive' volume. Note that, in this situation, the effective volume is appropriate to the reduced order description; which wil l , of course, be different from V .

I t is clear on comparison that equation (6.12) is identical to (6.10) with a = Vg/Q and bQ = 1.0 (as expected,since we have assumed mass conser­vation). Furthermore, we can argue that i f the flow velocity is U, then the sum cf the time delay 6 and the time constant a^, represents the travel time

134

T = L/U, where L is the reach length. As a re su lt, we can ca lib ra te the model (6.12) by reference to the time-series model of the tracer data. Know­ing the reach length L the flow Q and ve locity U measured at the time of the experiments and u ti l is in g the estimated values of a- and 6, we can f i r s t estimate the e ffective volume Ve from the equation

Ve = axQ (6.13)

I f i t is then assumed that the usual empirical re lationship (6.3) between U and Q applies (see Section 6.1 and Chapter 3) i.e .

U = aQb

where a and b need to be estimated in the manner discussed in Section 6.1, then an estimate 5 of 6 can be evaluated fo r any flow Q from

<5 = j j - (6-14)

where a is the appropriate estimate of a- in (6.12) obtained from (6.13) as

with Vg estimated from the time-series analysis resu lts . Thus, given a time- series of changing flow values we can update the estimates and 6 from (6.14) and (6.15) fo r each reach, and solve the resu lting model equations, with each reach represented by an equation of the form

. d x .(t)xi ( t ) + dt = bQX1_1( t -6 ) (6.16)

where bQ is set to the time-series estimate (normally unity except in the concrete channel).

Unfortunately, certain problems are encountered i f 6 from (6.14) and Q are updated on a continuous basis since th is can resu lt in lack of mass con-

•4*

servation in the solution. As a simple solution to th is problem, we have

+ Solutions to th is problem involving Pade type representations (m ultip le CSTR) of the time delay are being considered.

135

chosen to keep 6 and Q fixed for any simulation run at an average value appropriate to the flow varia tion s over th is run. Whilst this implies some inaccuracy in dynamic terms, i t will be small for normal storm events and the errors are likely to be well within the uncertainty associated with the model when used in the extrapolative mode (see later). Further evaluation of this aspect of the model is called for, however, but will require further dye tracer experimentation during storms. Note that i t is possible to introduce transient effects resulting from flow variations by defining the input concentration time-series so that i t is associated with the flow event: for example, i t should be possible to estimate the relation­ship between storm flow and pollutant concentration and use this relationship to define an input pollutant concentration time-series for any defined storm flow event.

In the above manner, i t is possible to predict the perturbations in concentration resulting from the injection of a conservative pollutant any­where in the system under any prescribed flow conditions. The nature of injection (pulse, continuous and constant, continuous but changing over time etc.) can be specified by the user and supplied as an input time-series at the appropriate reach or reaches.

Figures 6.19 to 6.23 show the output of the model in various sectors for an impulse input at the head of the f i r s t reach of the sector involved. In reading these figures, i t should be noted that the scale of the vertical axis is arbitrary. In those figures showing several curves, the x-axis for some of the curves has been shifted upwards. This has been done in an attempt to clarify the presentation. In each case, the height at which a curve intersects the y-axis indicates the true origin for that curve. Figure 6.19 presents the results for the concrete channel; Figure 6.20 for the retention pond; Figure 6.21 for Tuggeranong Creek downstream of the retention pond; and Figure 6.22 for the Murrumbidgee to below Kambah Pool.In all cases, constant flow is maintained. Figure 6.23 is a similar plot to Figure 6.22 but with the flow increased by a factor of five. The effect of this change is to increase the speed of travel by a factor of at least two, and to reduce the dispersion by a similar proportion.

It is necessary to introduce certain caveats with regard to the use of the transport and dispersion model.

CON

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136

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160

200

240

280

320

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Figure 6.20

CONSERVATIVE

NON CONSERVATIVE

~ ~ l ------------ ------

8000 16000 24000 32000 40000 48000 56000 64000MINUTES

SITE 13

8000 16000 24000 32000 40000 48000 56000 64000MINUTES

SITE 12

8000 16000 24000 32000 40000 48000 56000 57000MINUTES

1 1SITE

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138

Figure 6.21

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200

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400

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Figure 6.23

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400

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141

F irs t, while the model w il l be extremely accurate fo r flow conditions pertaining at the time o f the 'c a lib ra tio n ' dye experiments, its accuracy has not been assessed at other flow conditions where the physically motivated extrapolations (6.14) and (6.15) come into e ffe c t. We stress, therefore, tha t further dye tracer studies at d iffe re n t flow conditions w il l be required both to validate the extrapolations and to reassess the value of the a and b coeffic ien ts in the ve loc ity-flow re la tionship 6.3 fo r each of the major model sectors.

Second, as mentioned in Chapter 3, the behaviour of the retention pond under d iffe re n t flow conditions is rather d i f f i c u l t to assess. On the basis o f the dye experiments in the pond, which covered a range of low to medium flow conditions, we have con­strained 6 and a in (6.14) and (6.15) to be constant at the calibrated values of 0.25 weeks and 3.5 weeks, respective ly, up to a flow of 0.16 cumecs and only use the extrapolative predic­tion of a fo r flows greater than th is . Further evaluation of th is assumption is also required before the v a lid ity o f the retention pond model at higher flows can be assessed.

F ina lly , in order to permit speculative simulation model runs with non-conservative po llu tan ts , we have programmed each reach equation in the form

dx.U ) b— dt = - (4-+ k1)xi ( t ) + ( ^ + k2)xi _1(t- f i) (6.17)

al al

with k^ and k2 to be specified by the user. For ^ = k2 = 0 the model represents the basic conservative response; i f k is set appropriate to some decay rate (time "*) fo r a pa rticu la r pollu tant (with k2 = 0 ), then the model w il l provide an estimate of the loss of that po llu tan t down the system: with k2 other than zero, the user can introduce other 'non­conservative' factors (such as d ilu tio n ) in a simple manner. We would stress, however, that unless the estimates of k and k2 have been obtained in some rigorous manner in re la tion to the short term behaviour of pollutants in th is pa rticu la r catchment, then such model results would have to be treated with caution.

142

Some information on decay rates is available from the NCDC (Curtis, pers. comm., 1980), who have produced a graph of percentage reten­tion against retention (residence) time for phosphorus (Figure 6.24). Using an appropriate value of k obtained by reference to the phosphorus graph, we have re-run the simulations in Figure 6.20 and the results are shown by dotted lines on Figure 6.20. The effects of the decay factor are clearly indicated and the difference between the full line and dotted curves indi­cates the estimated loss of nutrient to the retention pond based on the NCDC figures (the retention time for the lower part of the pond during the dye tracer exercise was 2.56 weeks (0.049 years) and the percentage retention of total phosphorus is given by the NCDC graph as 47%, which corresponds to a k = 2.45 x 10 5 min"^). By using data collected during an earlier study on the Murrumbidgee river i t is possible to produce a similar graph for sediment retention. This is done in the appendix.

6.4 A Partial Steady State Model for Non-conservative Pollutants

Limitation of the data base only allows an evaluation of the long term or 'average' characteristics of the system in relation to non­conservative pollutants. Such an evaluation does not necessarily involve modelling. For example, the non-conservative pollutant data are analysed and discussed in previous chapters. Modelling can only encapsulate this interpretation in a concise numerical manner and is , therefore, of relatively limited additional use, particularly in a predictive sense.

All that we have been able to do is analyse an assumed instantaneous linear relationship between the concentration of determinands at consecutive sampling sites, with each determinand treated as a separate variable not interacting with other variables. In other words, we have assumed that the value of a determinand concentration x at the ith reach is related to the concentration of the determinand at the previous (i- l)th reach by a steady- state or equilibrium relationship of the simple form

143

Figure 6.24

O-L-r-

2 7Ö 20 50 100 200 400 600

Residence Time, days

144

xik = bxi - i ,k + h (6-18)

when the subscript k again denotes the value of the variable at the kth sam­pling instant and is indicative of noise (uncertainty) in the relation­ships. If b < 1.0 then such a simple model, which can be evaluated in the CAPTAIN package to provide an estimate b of b, is indicative of an 'expon­ential ' type decay of determinand concentration down the system. This be­comes clear i f we look at the relationship between and x^_n over n reaches for constant b value at each reach: which takes the form:

xik = b" xi-n,k + 5ck

where £ is the cumulative uncertainty. A plot of concentration against reach number for b = 0.7 and n = 5 and = 1-0, is given in Figure 6.25 where we see that the concentration has decayed from unity at the f i r s t (i-5) reach to 0.17 at the 6th (ith) reach.

Nominally, i t might be better to consider relationships such as (6.18) between loads at sampling points rather than concentrations. However, the difficulty in obtaining good indications of flow at each sampling point over the 1979-80 study year have made the accurate assessment of loads almost impossible at the time of writing. Nevertheless, we have tried to take flow factors into account wherever this has proved necessary for consistency. For example, downstream of the retention pond Tuggeranong Creek is joined by Village Creek and i t is essential to account for the combined effect of the two streams in some manner. Utilising the simple flow apportionment calcu­lation based on conductivity measurements discussed in Chapter 2, we can assume that, in the long term,

QG xik = b [QDxi- l ,k + V i - 1 , k] + 5k

where (L, Qn and Q.. and the flows at the Tuggeranong gauge, below the reten- b U V

tion pond and in Village Creek respectively; while x. is the concentrationD 1 Vat the gauge, x. the concentration below the retention pond, and x _- the

concentration in Village Creek. We see therefore, that

145

Figure 6.25

Ozoo

REAC

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146

xik = b D + ^ x V ]1-1 ,k Qg i -1 , k j + qG?k (6.19)

We computed the sum in parentheses from the observed concentrations at the two upstream stations with the ra tios Op/QG = Qy/QG = 0-68, calculated from the conductivity re lationship in Chapter 2.

Table 6.2 shows the estimated values of the b parameters fo r each sampled section of the system in the case of to ta l phosphorus. Sim ilar values can be determined fo r the other parameters. Typical examples of the model f i t s obtained are shown in Figures 6.26 and 6.27: Figure 6.26 showsto ta l phosphorus at the Tuggeranong gauging station obtained from the model (6.19); while Figure 6.27 shows to ta l nitrogen results at the same s ite . I t is clear that to ta l nitrogen is predicted well in th is manner but to ta l phosphorus is not predicted quite so w e ll. These results are typ ical fo r most reaches.

In a number of cases, the estimate b is found to be greater than un ity , which indicates tha t, on the average (as indicated by the fo r t ­n igh tly , and 14 d a ily , exercises) the concentration at the output of the reach is higher than at input, thus implying a continuing export of material from the reach. For instance, a typical and important example is Kambah Pool where b = 1.11 fo r to ta l phosphorus and b = 1.09 fo r to ta l f i lte ra b le phosphorus. In other words, there appears to be a long-term net export of

11% from the pool.

I t is d i f f ic u l t to explain these phenomena with the lim ited data available since the data are ambiguous and a number of d iffe re n t explan­ations are possible, a ll apparently consistent with the observed concentration measures. For example, we could hypothesise tha t, during short term high flow transients (not monitored s u ff ic ie n tly in the study) there is a net accretion of material in the pool and th is material is then los t slowly during the subsequent period o f lower and steadier flows. A lte rna tive ly , since in th is case the estimated net export is quite small, i t could be that b is biased upwards a small amount because the fo r tn ig h tly sampling in terval is c learly inappropriate fo r the flow dynamics of Australian rivers lik e the Murrumbidgee.

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Figure 6.27

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149

In systems terms, we would say that the inappropriately low sampling frequency makes the true dynamic behaviour of the system 'unidentifiable' from the available data base. The obvious procedure to adopt to solve this problem of identi f iabi l i ty is to plan more sustained monitoring exercises with higher sampling frequencies than in the present study. For example, our original suggestion of a 6 week daily monitoring program should provide a solution to this problem, provided storms occurred during the monitoring period.

TABLE 6.2 Values of the b Parameter for Total Filterable Phosphorus

Si tes

I to A

A to B

B to D

C to D

D to E

F to G

G to H

Value

0.7799 ± 0.0822

0.8285 ± 0.0817

0.8061 ± 0.0621

0.4860 ± 0.0607

0.9598 ± 0.0525

1.0583 ± 0.0497

1.0933 ± 0.0439

Degree of Fit

Poor

Good (RT 0.83)

Good <rt 0.5234)

Poor

Good <rt = 0.96)

Good <rt = 0.89)

Good <rt = 0.91)

6.5 Recommendations on Future Modelling Studies

Our main recommendations on future modelling studies are to urge the NCDC to f i l l the gaps outlined in present study as soon as possible.We believe that this will require action on two fronts:

(1) The ini t iat ion of a research program aimed at the acquisition of good quality short term data on the main variables of importance in the Tuggeranong-Murrumbidgee system (i .e .

150

strategically measured, short term ( hourly) flow data, turbidity, suspended sediments, conductivity, nitrogen, phosphorus (a comprehensive breakdown with their various forms is necessary i f processes are to be understood), and possibly various measures of biological act ivity.

(2) Extension of the modelling studies described in the present report to (a) fully u t i l i se the data obtained in (1), above; and (b) construct speculative stochastic simulation models based on the pollutant dispersion and transportation model described in Section 6.3, as extended to include descriptions of biological activity resulting from retained dissolved and particulate nutrients, particularly in Kambah Pool and the proposed Lake Tuggeranong.

Because of the diff icult ies in the manual collection of storm data, recommendation (1) will require the establishment of automatic sampling stations at relevant locations in the system. In relation to current object­ives, the minimum number of locations would be six: upstream of the retent­ion pond; on the Village and Tuggeranong Creeks upstream of their confluence; at the gauging station on Tuggeranong Creek; and both upstream and downstream of Kambah Pool. An additional automatic station at Pine Island would greatly assist data interpretation as would stations within Tuggeranong Creek retent­ion pond and Kambah Pool. The establishment of such automatic stations would need to be coordinated with planned programmes of manual monitoring (particularly those based on extensive daily sampling over several 8 week (mini- mum)periods); together with at least two years of weekly sampling. The intensive daily sampling should attempt to cover ' typ ica l1 winter and summer periods and should include weekend sampling to ensure continuity of time-series data. I t is important that these exercises should, i f at all possible, include the effects of storms in the Tuggeranong Creek catchment area.

Such a programme of monitoring would require considerable funding, but we believe i t is essential to fully understand water quality behaviour in this important urban area. Other less intensive approaches are, of course, possible but they will always be open to the criticism that they are speculative: there is no alternative to hard datain the area of water quality planning and, as we have seen in this report, the biological mechanisms associated with water quality are not amenable to description on the basis of long term data and steady-state models.

151

Recommendation (2) is much less costly since i t is a 'desk study1 which could be carried out on the basis of the data obtained during the current study. I t is a modelling exercise which is overtly speculative, but we feel i t could provide a much better basis for assessing behaviour in the Tuggeranong-Murrumbidgee System than current deterministic modelling approaches, (such as the Boughton model in a purely hydrological context) which are no less speculative and, additionally, fail to allow sat isfactorily for the uncertainty in the speculative content of the model (e.g. model para­meters such as decay coefficients, biological growth rates etc. ) .

The approach we suggest is based on the modelling methods used by the Applied Systems Group in the Peel-Harvey Study, as described in Chapter 9 ofthat Study Report (Humphries et a l . , 1980). I t is not appropriate to describe the methodology here except to say that i t requires the following three steps:-

(a) The construction of a 's tate-of-the-art ' dynamic simulation model which is based on all current information available on the system, including local data (as collected in the present study) and information gleaned from the technical li terature.I t can also include mechanisms based on engineering or scienti­fic judgement, provided good account is taken of the uncertain­ty associated with such judgement.

(b) The specification of the uncertainty associated with the para­meters which characterise the model, as well as the model form i t se l f . For example, this could require that the parameter values are not specified as given numerical values (say a decay rate kj of 0.9) but rather as a probability distribution. Such a distribution can be complex or simple depending upon the circumstances; in one of the simplest cases, for example, i t could be a rectangular distribution with reasonable upper and lower bounds on the parameter value providing the extremes, and with all values between these values having equal probabil­ity; or again, i t could be Gaussian normal with the 'most likely' value specified as having maximum probability.

(c) Use of the model obtained in (a) and (b) for stochastic simu­lation exercises based on Monte-Carlo methodology, in which the model is repeatedly solved on a digital computer with the model parameters for each run (as well as any other stochastic inputs

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such as climatic factors) specified by random selection from the chosen probability distributions. The 'average behaviour' of the model can then be evaluated by computation of ensemble averages based on the complete set of random simulations gen­erated by the computer: this could provide simple results,such as mean and standard deviation of water quality variables at a given location for each time-increment over the simulat­ion period; or i t could result in complete probability dis­tributions for specified variables (see e.g. Whitehead and Young, 1979). Additionally, the Monte-Carlo approach can be used very effectively as a form of stochastic sensitivity analysis or hypothesis generating device which helps to identify the most important parameters for a certain specified problem behaviour (see e.g. Humphries e t a l . , 1980; Spear and Hornberger, 1978). In the Tuggeranong-Murrumbidgee case, for example, i t could provide an indication of what might be the most important contributions to a specified problem such as eutrophication of the proposed Lake Tuggeranong or Kambah Pool.

This kind of stochastic simulation study is fairly straight-forward and, in the Tuggeranong-Murrumbidgee case, the model in (a), above, could be based on the transportation and dispersion model described in 6.3, expanded to include nutrient-biological interaction and any other factors thought to be important in planning terms. I t could be seen as a valuable prelude to the planning of further monitoring exercises while, at the same time, provid­ing a more objective basis for system evaluation than more conventional deterministic simulation models.

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7. ESTIMATION OF NUTRIENT LOADING AND TROPHIC STATUS OF LAKE TUGGERANONG

7.1 The Predict ion of Phosphorus and Chlorophyll Concentration in Canberra's Urban Lakes

Canberra's urban lakes have a l l experienced nuisance growths of phytoplankton and rooted aquatic macrophytes a t various t imes, and in all cases the problem seems to be get t ing worse. Several s tudies of exis t ing and proposed urban lakes have attempted to e lucida te the causes of eut rophi­ca t ion , and to determine plans to manage these lakes (Cullen e t a l . , 1978a, b; Hillman 1974; Rosich e t a l 1978).

All of these studies have drawn on the work of Vollenweider (1968, 1976), who establ ished empirical re la t ionsh ips between the hydrology, nu t r i en t loading and re su l t ing summer phytoplankton standing crop, using data from a large number of European and North American lakes . Vollenweider has developed a ser ies of simple mass balance and export models for nitrogen and phosphorus and has shown, for the group of northern hemisphere lakes, th a t phosphorus loading ra tes may be re la t ed to the r a t i o 'mean depth/ hydraulic residence time' (Z/x), and th a t mean maximum summer chlorophyll

aconcentrat ions may be predicted. (See below fo r more d e t a i l . )

Application of Vollenweider's models to Austra lian lakes has been less successful (Cullen e t a l . s 1978a, b; Lawrence 1980). Among the reasons for the d i f f i c u l t i e s experienced by these workers are:

( i ) tha t Austra lian inland waters are general ly tu rb id , and hence l i g h t f requent ly l imi ts p lant growth, despi te high nu tr ien t avai1ab i1i t y ;

( i i ) Aust ralian stream flows show extreme v a r i a b i l i t y (Lawrence 1980) which in turn causes great v a r i a b i l i t y in annual n u t r i ­ent loadings to receiving water bodies;

( i i i ) most phosphorus i s t ranspor ted in pa r t i c u la te form during storm flows. Much of the p a r t i c u la te phosphorus e i th e r sed i ­ments quickly, or may be l o s t in storm outflows from small lakes. In e i t h e r case, a large f r ac t ion of the incoming p a r t i cu la te phosphorus i s not avai lable d i r ec t ly for phyto­plankton growth.

Lawrence (1980) has approached these problems by estimating the phosphorus loading ra tes for Canberra region lakes from urban runoff a t low

154

stream flows and sewage loadings only. Using Vollenweider's one box model

[Plake^L/q

l+/z7q(7.1)

where,

[Plake l = average summer concentration of total phosphorus in lake water (mgP m

-2 -1L = lake areal phosphorus loading (mgP m year )Z = mean depth (m)q = lake hydraulic loading (m year "*)

Note that ,

q = — and

_ V T " Q

where,t = water (hydraulic) residence time (years), which is the

time necessary, a t the annual rate of water outflow (Q) for the volume of the lake (V) to be replaced.

Lawrence (1980), then applied Vollenweider's (1976) empirical relationship

[chlorophyll^] = 0.367 [Plakel ° ' 91 (7.2)

to predict mean summer chlorophylla concentrations for various lakes in the Canberra region. He obtained a correlat ion coeff ic ient (r) of 0.93, with a sample size of eight.

Cullen et a l (1978b) attempted to apply Vol1enweider' s equations (7.1 and 7.2 above) to predict both summer mean total P concentration and surface summer mean chlorophylla concentrations for the 1976-77 and 1977-78 summers in Lake Ginninderra and Lake Burley Griff in . Equation 7.1 predicted

_3a 1977-78 total P concentration of 136 mg P m for Lake Ginninderra; a

_3value of 21 mg P m was observed. Substitution of e i ther predicted or observed values of total P into equation 7.2 resulted in poor predictions of chlorophyll , which was also over-estimated.

a

The main reasons for the over-estimation of total P concentrations (and hence over-estimated chlorophyll concentrations) appears to be the

aunder-estimation of P loss by sedimentation, and probable suppression of

155

phytoplankton growth by turbidity. A possible improvement might come from the use of dissolved , rather than total nutrient loadings in the Vollen- weider models. This is because most of Vollenweider's original data are from large to very large lakes, which are loaded mostly by sewage and urban runoff. A greater fraction of the phosphorus load would be dissolved under such circumstances, and hence most sedimentation loss of P would occur via biological uptake and subsequent sedimentation. Insufficient data exist to test this suggestion for Canberra's urban lakes.7.2 Estimation of the Trophic Status of Lake Tuggeranong

Lawrence (1980, 1981) has estimated the trophic status of the proposed Lake Tuggeranong by accounting for urban phosphorus loadings only. Gutteridge, Haskins and Davey (1980) have estimated both total P and PO -P loadings under various assumptions of runoff, urban development and catch­ment P yield, and conclude that the lake will be highly eutrophic. These estimates, and others, are discussed below, and a reassessment of Lake Tuggeranong1s future trophic status made. I t should be emphasised that the following dimension uses Gutteridge, Haskins and Davey (1980) estimates for mean annual flow and rainfall runoff. Lawrence (1982, pers. comm.) has demonstrated that the data for this study were drawn from years when rain­fall was above the 'average'. Nutrient export figures discussed here are therefore above what could be expected in a 'dr ier ' year.

Table 1 contains data necessary for the computation of P loading for the Tuggeranong ponds and lake. The proposed Tuggeranong lake and pond system will consist of the existing Tuggeranong Creek retention pond, Village Creek retention pond, and Lake Tuggeranong i t se l f . All may be classified as wet, on-line ponds.

TABLE 7.1 Dimensions of Existing or Proposed Ponds in the Tuggeranong Creek Catchment

Structure Area (A) (m3 x 10°)

Mean depth (Z) (m)

Volume (V) (m3 x 106)

Tuggeranong retention pond 0.048 2.3 0.11Village Creek retention pond 0.041 0.73 0.03Lake Tuggeranong 0.70 3.14 2.2

From the data in Table 7.1, and making assumptions on total catch­ment runoff in median, wet and dry years, and i t s partitioning between Tugger­anong and Village Creeks, i t is possible to estimate the hydraulic residence characteristics for the ponds, given in Table 2.

156

TABLE 7.2 Computation of Hydraulic Residence Times (x or Z/q) fo r Ponds in the Tuggeranong Creek Catchment(the bracketed numbers are approximate retention time in days)

Total annual discharge-*- (m3 x 106)

TCRP VCRP LT

t (years) = l

Median 16 0.022 ( 8) 0.003 (1.1) 0.156 ( 57)Dry 9 0.039 (14) 0.005 (1.8) 0.278 (101)Wet 24 0.015 ( 6) 0.002 (0.7) 0.104 ( 38)

Assumptions:1. Estimated median (50 percen tile ), 90 percentile and 10 percentile to ta l

annual discharge, from whole catchment partitioned as flow x 0.316 to TCRP, flow x 0.684 to VCRP and flow x 1.0 to LT.For the purposes of th is ca lcu la tion , i t is assumed that inflow = outflow from each pond. Cullen e t a l . , (1978b) found that the ra tio outflow: in flow fo r Lake Ginniderra was 0.857 in the 1977-78 water year.

I t is not known whether the re lationship between P retention and hydraulic residence time based on data fo r Lake Burley G r if f in (Figure 6.24) can be extrapolated to the Tuggeranong ponds. Assuming th is extrapolation, under the dry, wet and median conditions considered in Table 7.2, Village Creek RP would retain in s ig n ifican t amounts of P, while the Tuggeranong Creek retention pond and Lake Tuggeranong would retain between about 30-40% and 55-70% of inflowing P, respectively. This pattern of apparent retention is unfortunate, since V illage Creek w il l contribute most of the nutrien t load in to Lake Tuggeranong, and the Village Creek RP appears to be an ine ffec tive nu trien t trap.

The behaviour of the Tuggeranong catchment is changing with increas­ing urbanisation, and both annual discharge and catchment P export rates are d i f f i c u l t to estimate precisely. However, i t is possible to estimate annual P loading to Lake Tuggeranong under a variety of assumptions and, by using Vollenweider's model in a conservative fashion, antic ipate the like lihood of excessive phytoplankton growth. Macrophyte growth is probably not strongly related to simple nutrien t loadings. The major requirement fo r macrophyte colonisation is shallow (<3 m deep) water, with a suitable sediment fo r root attachment. Relatively good lig h t is also necessary, and prolonged algal blooms or periods of high abiogenic tu rb id ity may prevent colonisation. Lake Tuggeranong w i11 be shallow (Z = 3.14), and should provide an excellent habitat

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-2 -1TABLE 7.3 Projected Areal Total P or PO -P Loading (g m yr ) to Lake Tuggeranong, Under the Various Assumptions Detailed Below (any reduction of P loading by the retention ponds is ignored)

Total export (kg y r - 1)

Catchment export rate (kg ha-1 y r -1)

Areal loading (g n r2 y r -1)

:GHD (a) 2490 0.39 3.56(b) 980 0.15 1.40

2GHD (a) 2820 0.44 4.03(b) 1110 0.17 1.59

3GHD (a) 3270 0.51 4.67(b) 1290 0.20 1.84

4Lawrence 735 -0.30 1.05

750

5LBG 3792 0.59 5.42

^Ginninderra 779 0.12 1.11

7GHD (a) 2046 0.32 2.92(b) 860 0.13 1.23

8GHD (a) 2243 0.35 3.20(b) 884 0.14 1.26

Notes and Assumptions:1. Total P (a) and PO.-P (b) exports and areal loading, 1978 r a i n f a l l ,

exist ing development. Source: Gutteridge, Haskins and Davey (1980).2. As above, 1978 r a in f a l l , full development of serviced area.

Source: GHD (1980).3. As above, 1978 r a in f a l l , ultimate development of Tuggeranong Valley.

Source: GHD (1980).2 6 34. Current urban loading only (25 km urban area generating 4.9 x 10 m

runoff containing 0.15 gP m“3). Source: Lawrence (1981).5. Assuming Lake Burley Griffin urban (0.91 kg ha- -*- yr -•*■) and rural (0.3 kg

ha- l y r -1 ) P export ra tes , applied to urban (3050 ha) and rural (3390 ha) Tuggeranong. Source: Cullen, Greenham, Rosich and Toshach (1978).

7. Assuming East Doncaster Urban storm runoff - total P export regression(Total P kg knr2 = 0.22 R.O.mm + 0.15), 1978 Tuggeranong rainfal l (734mm) and rural exports (rural = urban x 0.3) . Source: GHD (1980).

8. As above, except with ultimate development and 34.03% catchment e f f i c i ­ency. Source: GHD (1980).

To

tal

Ph

osph

orus

Lo

adin

g

(gP

/m2/

yr)

158

F i g . 7.1

TROPHIC STATUS OF PROPOSED LAKE TUGGERANONG

J Eutroph ic

I.;:.... i Mesotrophic

O ligo troph ic

Mean Depth

Hydraulic ResidenceTime( m / y r )

159

fo r aquatic weeds. Table 7.3 contains estimates of possible areal phosphorus loadings to Lake Tuggeranong. These should be compared with Figure 7.1.

The data in Tables 7.1, 7.2 and 7.3 can now be combined to produce ranges of areal P loading rates and hydraulic residence times fo r Lake Tugg- erenong. These combined data are given in Table 7.4.

TAELE 7.4 Variation in Estimates of Areal Total P and PO^-P Loading Rates, the Ratio of Mean Depth/Hydraulic Residence Time fo r Lake Tuggeranong

Areal loading gP m“ 2 y r - l

Areal loading gPO^-P m-2 y r _l

Hydraulic Loading Z / t = (q ) m y r - 1

Total catchment 0.64 - 4.67 0.25 - 1.84 12.59 - 33.65Urtan catchment (a) 1.05 ~0.42 7.0only, median (b) 1.05 -0.42 10.6r a in fa l1 (Lewrence 1981)

(c) 0.74 -0.30 4.9

Notes: (a) Current proposal fo r Lake Tuggeranong.(b) Current proposal, w ith 50% d i lu t io n due to Murrumbidgee River

make-up water (assumes no addit ional nu tr ien t loading from th is source).

(c) A larger Lake Tuggeranong (area 100 ha, volume 4 x 10 n r ,Z=4 m).

The l i k e ly ranges o f areal to ta l P and P04~P loading rates, and these of possible hydraulic loading rates from Table 7.4 are p lotted in Fig­ure 7.1. The graph suggests tha t , on the basis of e ithe r projected to ta l P or PO^-P loading rates, Lake Tuggeranong w i l l range from mesotrophic to eutrophic, and w i l l probably experience nuisance phytoplankton blooms in spring through to la te summer.

This conclusion is based on the s im p l is t ic assumptions of Vollen- weider's model, but nevertheless indicates that water q u a l i ty problems are l ik e ly to occur in the new lake.

7.3 The Trophic Status o f Kambah Pool: Present and Future

Kambah Pool, as discussed e a r l ie r in th is monograph, is r ive r ine in natjre, w ith short hydraulic residence times (<3 days), and is currently dominated by various genera o f rooted angiosperms and some large algae.

In such r ive r ine s i tua t ions , primary p ro d u c t iv i ty , and the types of

160

primary producers present, tend to be a function of

( i ) the frequency, duration and in tens ity of high flows; Moderate to high flows, up to some unspecified threshold, transport and deposit sediments (and nutrients) into reaches lik e that of Kambah Pool. At s t i l l higher flows, scouring of both sedi­ments and plants w il l occur. Regrowth and recolonisation of macrophytes then occurs, depending on season, u n til another large flow.

( i i ) the a v a ila b il ity of suitable habitat fo r macrophyte co loni­sation (see Chapter 4);

( i i i ) the concentration (rather than load) of nitrogen and phosphor­us in the flowing water; There are data fo r the Murrumbidgee reaches downstream of the LMWQCC which show large algal(Hydrodictyon, Cladophora) domination during summer, when Canberra's secondary sewage e ffluen t constituted a large pro­portion of the r iv e r 's flow. A fte r the successful commission­ing of the LMWQCC, ambient nutrien t concentrations f e l l , and rooted macrophytes reinvaded th is section of the r iv e r. A l­though these data have not been fu l ly analysed, they contain the nu trien t concentration ranges over which both types of aquatic f lo ra occur, and should be used to define nutrien t water qua lity c r ite r ia fo r the Murrumbidgee.

The above points are, of course, an over-s im p lifica tion of the plant ecological processes operating in the Murrumbidgee, and fu rthe r c la s s if ic a t­ion of many processes is needed. For example, some macrophytes (e.g. Potam- ogeton spp.) die o ff in autumn, releasing nutrients to the water column on decomposition. Under conditions of low flow, phytoplankton blooms may occur at these times. Speculative simulation modelling of r iv e r and lake macro­phyte growth, as done fo r an estuarine Cladophora species by Hornberger and Spear (1980), Spear and Hornberger (1980) and Humphries et al . 3 (1980), would provide a sound basis on which to research the growth mechanisms of local macrophyte species in deta il (see Chapter 6, Section 6.5).

As a general po in t, i t should be noted that rooted aquatic plants gain most of th e ir mineral n u tr itio n from the sediments, rather than the water, and can colonise quite nutrient-poor waters. Phytoplankton and larger algae, on the other hand, lack roots and absorb nutrients from the water. A prolonged increase in dissolved, inorganic forms of N and P w il l lead to a

161

shift from rooted water plants to phytoplankton or attached algae, depending on rates of flow and water residence times.

163

8. PRINCIPAL FINDINGS

1. The Tuggeranong retention pond has modified the phosphorus load-flow characterist ics of Tuggeranong Creek by trapping part of the phosphorus load during storms. Part of the trapped phosphorus load is subsequently re-released downstream on a longer time scale under con­ditions of low flow.

2. The retention pond and associated spillway increases turbidity of Tuggeranong Creek downstream of these structures. This is believed to be due to sediment.disturbance by spillway water.

3. On the basis of limited conductivity data, and assuming conductivity to be conservative, approximately 70% of Tuggeranong Creek flow into the Murrumbidgee emanates from Village Creek under normal conditions. Total discharge from the Tuggeranong Creek system comprises only between 0.02 and 0.01 of the Murrumbidgee flow.

4. At present, attached algal populations are significant only within the lower reach of Tuggeranong Creek, af ter i ts confluence with Village Creek.

5. Large storm flows are the major deleterious influence on water quality in the Tuggeranong Creek system. Elevated nutrient and sediment loads are transported downstream during these flows, which also scour the stream channel of algae. Storm-flow nutrient and sediment loads are rapidly flushed from the Tuggeranong Creek system into the Murrumbidgee.

6. Kambah Pool appears to effectively trap suspended, but not dissolved, matter. The pool is relatively well-mixed, with riverine, rather than lacustrine hydraulic characterist ics , and even during low flows in the Murrumbidgee, has a residence time of less than one day during storm run-off from the Tuggeranong catchment.

7. The water quality of Kambah Pool is generally satisfactory, even under conditions of low flow. Although not well documented, i t appears that most nutrient input to Kambah Pool occurs during sedimentation from storm inflow, and that subsequent sediment nutrient uptake and recycling by aquatic macrophytes releases nutrients to the water column, some of which are lost downstream. Kambah Pool is of sufficiently low flow energy to permit heavy macrophyte growth during spring and summer, which reduces the recreational amenity of the pool. The pool is sensitive

164

to chronic elevation of dissolved inorganic nutrient concentrations, and under such conditions, the flora would change to one dominated by attach­ed algae. This emphasises the need for good water quality management in the Tuggeranong catchment.

8. There is no evidence for prolonged vertical or horizontal s trat if ica t ion in the retention pond or Kambah Pool. All dye studies indicated rapid mixing throughout both water bodies. The mixing process is probably dominated by wind and water inflow.

9. I t is considered that construction of Lake Tuggeranong would improve water quality downstream of the lake, although there are insufficient data for quantitative conclusions. Estimates of eutrophication potent­ia l , using Vol1enweider' s model, have been made, indicating that the lake will be eutrophic, and will probably experience nuisance phytoplank­ton blooms. Depending on design, the lake could support a large macro­phyte population, as do Canberra's other urban lakes.

10. Our simple steady-state models appear to adequately characterise low flow conditions in most parts of the Tuggeranong Creek system. Behaviour of the system during short-term, high flow periods is not adequately understood. The short-term model constructed from dye study results appears to simulate conservative pollutant behaviour adequately, but is speculative for non-conservative substances.

11. Coliform bacterial concentrations are consistently above recommended levels for water contact act ivit ies in Village Creek, and intermittently so in Tuggeranong Creek, particularly during periods of higher discharge. I t is predicted that bacterial contamination will increase with catch­ment development.

12. It was not possible during the present study to obtain sufficient short term water quality data. We strongly recommend the establishment of six (or more) automatic monitoring stations on the Tuggeranong-Murrumbidgee system to enable such data to be obtained during future studies. Such monitoring, which should be very well planned and executed, is normalin other developed countries (e.g. the United Kingdom), and would appear particularly important in the Canberra area, which represents one of the most important inland urban developments in Australia.

13. I t is recommended that two modelling exercises should be considered in future projects:

165

(a) construction of a speculative stochastic (Monte-Carlo) simu­la tion model based on the po llu tan t dispersion and transport­ation model developed during the present study, as extended to include nutrien t and b io logical behavioural mechanisms;

(b) on the basis of the results obtained in (a) and with access to additional short term data as obtained in 12., above, con­struction and va lidation of a short term, dynamic model of nu trien t-b io log ica l behaviour in the Tuggeranong Creek- Murrumbidgee River System, as fa r as Kambah Pool.

167

LIST OF ABBREVIATIONS USED IN REFERENCES

ANU A u s t ra l ia n N a t iona l U n iv e r s i t y

ANZAAS - A u s t r a l i a and New Zealand A s s o c ia t io n f o r the Advancement o f Science

ASCE American S o c ie ty o f C i v i l Engineers

AWRC A u s t ra l ia n Water Resources Commission

BMR Bureau o f M inera l Resources

CRES Centre f o r Resource and Environmental S tud ies

EPA Environmental P ro te c t io n A u th o r i t y

OECD O rg a n iza t io n f o r Economic C o-ope ra t ion and Development

169

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Anderson, D.G. (1970) E f fe c ts o f urban development on f lo o d s in Northern V i r g i n i a . Ü.S. Geo log ica l Survey W ater-Supply Paper, No. 2001-C, 22 pp.

Angino, E .E . , Magnuson, L.M. and S te w a r t , G.F. (1972) E f fe c ts o f u rb a n i ­z a t io n on storm w ate r r u n o f f q u a l i t y : a l im i t e d experim ent, Naism ith D i t c h , Lawrence, Kansas. Wat. Resources Res., 8: 135-140.

A r i s , R. (1959) The l o n g i t u d in a l d i f f u s i o n c o e f f i c i e n t in f lo w through a tube w i th s tagnan t pocke ts . Chem. Eng. S e i . , _11: 194-198.

A u s t r a l i a . Department o f C o n s tru c t io n (1977) Tuggeranong Creek Stormwater Channel through I s a b e l la P la in s Design Review. A Report to the N a t iona l C a p ita l Development Commission.

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Beer, T. and Young, P.C. (1980) Systems methods in the c h a ra c te r is a t io n o f lo n g i t u d in a l d is p e rs io n in n a tu ra l streams. Canberra: CRES, ANU. (ANU. Centre f o r Resource and Environmental S tu d ie s .CRES Report AS/42.)

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