f- ' CRES Monograph 5 V ■ / * * i . Environmental water quality
' # ■ * a systems stud^inTJggeranong Creek and Kambah Pool
Tom Beer, Peter C Ypung, Robert B Humphries and James S Burgess
UNCOCK )3 2 2 18 159 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 quality a 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 4 Canberra A.C.T. 2600.
library iii
PREFACE
Construction of an artificial Lake Tuggeranong comprises one of the possible options for the future development of the Tuggeranong region of the Australian Capital Territory. In order to provide scientific data as a basis for planning this structure and modelling its effects upon the down stream Murrumbidgee, the National Capital Development Commission contracted various studies. This monograph provides an account of the Centre for Resource and Environmental Studies (CRES) contribution to one of these known as the Murrumbidgee River Water Quality Study.
The raw data on which this work is based is available in a series of working papers prepared by the CRES Applied Systems group. We must, in fact, emphasise that the CRES research programme has been a complete team effort,with numerous individuals contributing in various ways. A list of CRES team personnel and their contribution is given below:
Tony Bayes computer programming, field assistance Ruth Bel in illustrations Julie Cathcart secretarial, typing June Harries secretarial, typing Alan Henderson research assistance, field assistance Tony Jakeman mathematics, modelling Pat Mitchel1 computer programming, data analysis, field assistance Barbara Piper secretarial, typing Christina Sirakoff data analysis, computer programming David (Dingle) Smith hydrology, dye tracer studies Paul Steele field assistance
In addition, the students enrolled in the program for the Master of Resource and Environmental Studies provided assistance with the field work.. iv
CONTENTS
Page
Preface i i i
Contents iv
CHAPTER 1 INTRODUCTION 1
1.1 Inland Australian Waters 1
1.2 Aim of the Study 5
1.3 Existing Information 6
1.4 The Character of the Tuggeranong Creek Catchment 7
1.5 Morphology 10
CHAPTER 2 QUIESCENT CONDITIONS 13
2.1 The Sampling Program 13
2.1.1 Fortnightly sampling program 14
2.1.2 Daily sampling program 15
2.2 Spatial Analysis of Nutrients 18
2.2.1 Phosphorus 18
2.2.2 Nitrogen 18
2.2.3 Chlorophylla and phaeophytin 20
2.2.4 Dissolved oxygen 22
2.2.5 Turbidity 22
2.3 Nutrient Behaviour in the Retention Pond 22
2.4 Conductivity 27
2.5 Estimation of Flows from Conductivity Measurements 29
2.6 Attached Algae 31
2.7 Bacterial Contamination of Tuggeranong Creek 32 V
CHAPTER 3 STORM EVENTS 41
3.1 Introduction 41
3.2 Gauging the Concrete Channel at S ite A 41
3.3 Flow-velocity Relations 42
3.4 Behaviour of the System During Storms 44
3.5 Flow-Duration-Concentration 46
3.6 The Storm of 4 January, 1980 49
3.7 Erosion in Tuggeranong Creek 52
3.8 Nutrient Loading and Land Use Characteristics 52
CHAPTER 4 KAMBAH POOL AND THE MURRUMBIDGEE 55
4.1 H is to ric a l Data 55
4.2 Longitudinal Variability 56
4.3 Biology and Water Q uality o f Kambah Pool 56
4.3.1 Survey methods and data analysis 58
4.3.2 Results and discussion 60
4.4 Diurnal Variation in Dissolved Oxygen 68
CHAPTER 5 DISPERSION AND MIXING
5.2 Tuggeranong Retention Pond 70
5.3 Tuggeranong Creek Concrete Channel 84
5.4 Downstream Tuggeranong Creek 85
5.5 Kambah Pool 87
5.6 Dispersion Modelling 91
CHAPTER 6 MATHEMATICAL MODELLING 95
6.1 A Flow Routing Model of the Murrumbidgee River 97 System Including Tuggeranong Creek
6.2 R ainfall-F low Model fo r Tuggeranong Creek 104
6.3 A Conservative Pollutant Dispersion and 119 Transportation Model vi
CHAPTER 6 MATHEMATICAL MODELLING (continued)
6.4 A Partial Steady State Model for 142 Non-conservative Pollutants
6.5 Recommendations on Future Modelling Studies 149
CHAPTER 7 ESTIMATION OF NUTRIENT LOADING AND TROPHIC STATUS 153 OF LAKE TUGGERANONG
7.1 The Prediction of Phosphorus and C hlorophylla 153 Concentration in Canberra's Urban Lakes
7.2 Estimation of the Trophic Status of Lake 155 Tuggeranong
7.3 The Trophic Status of Kambah Pool: Present 159 and Future
CHAPTER 8 PRINCIPAL FINDINGS 163
LIST OF ABBREVIATIONS USED IN REFERENCES 167
REFERENCES 169 vi i
CONTENTS
Appendices are provided on m ic ro fic h in the back of the book
Page N<
APPENDIX 1 ALGAL DATA 1
BATERIOLOGICAL DATA 3
APPENDIX 2 CHARACTERISATION OF LONGITUDINAL DISPERSION 1
1. Introduction 1
2. Dead Zone Processes 4
3. Problems in E stim ating the Dispersion Coefficient 7
4. D is c re te -tim e Models 11
5. The Identification and Estimation of Discrete-time Models 16
6. Comparison With the Routing Procedure 17
7. Discussion and Conclusions 2D
APPENDIX 3 Listing of the water quality and flow data used in p ro 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 predomin ate, 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 nor mal concentrations of sodium and chloride ions. However, it has been suggested that concentration of plant nutrients such as nitrogen and phos phorus, 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 situ ations experience seasonal variations that result from deciduous tree inputs. Finally, much of the fauna of Australian waters is endemic,with close relationships to marine life. 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 Austral ian 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 criteria. Similarly, the more recent studies by Cordery (1976a, b) reinforce Hart's conclusion. Cordery (1976b, p.3) notes that, 'very little published data are available on the quality of urban runoff in Australia. 2
The data that have been published relate only to low flow conditions and hence are not really representative of the total flow'.
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 this 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 ri ods of one year frequently being increased by up to three times the pre urbanised discharge level. Following the work of H ollis (1975) he suggests that urbanisation increased larger floods by smaller amounts and that very large floods are increased by insignificant amounts. Similar findings have been reported by Anderson (1970), da Costa (1970) and Leopold (1968).
Cordery (1976b) also reports that total runoff volumes from urban ised catchments can be increased by up to two times. This finding is supported by Anderson (1970) and by Cordery (1976a). Considerable v a ria b il ity in the size of the increase occurs largely as a result of highly vari able urban land uses and because of the numerous physiographic variables in the urban catchments.
The th ird major e ffe ct 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 suspend ed load,increase substantially in the early phases of urbanisation. Walling and Gregory (1970) demonstrated fo r Exeter that these patterns of high sedi ment load decrease following the construction phase, and fin a lly level o ff after a period of stabilisation.
The fourth set of major changes that occur in streams after urbani sation involve morphologic changes to the stream channel and the bed. Frequent ly channels are enlarged (Hammer, 1972) and bed sediment re -d istrib u te d .
Perhaps the most significant changes that occur following urbani sation are the changes in the chemical and bacteriological characteristics of the water that essentially determine the quality 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 Escherichia coli (Van Donsel e t a l . , 1967). Urban stormwater is frequently characterised by greater than normal biologi cal 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 treat ment 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 silica. Gutteridge, Haskins & Davey Pty. Ltd.,and the Environmental Protection Authority of Victoria (1981) studied pollution in urban Melbourne storm water runoff. They emphasise that the high pollution episodes represent an initial 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 coli and Streptococcus fa e c a lis indicated that levels could be several orders of magnitude higher in urban streams particularly at times of high flow.
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Numerical data are given of the changes in flood magnitude, sedi ment load and water quality as a result of urbanisation. However the lack of general understanding of the processes involved in these changes means that the published information really only provides qualitative indications of the changes that can be expected when changing the land use of an area from rural to urban conditions. The results described in Chapter 6 of this monograph are a preliminary attempt to provide a general methodological framework for modelling these effects. 1.2 Aim of the Study The overall aim of the Murrumbidgee River water quality study is to ensure that urban development in the Tuggeranong area does not have a deleterious impact on the recreational and aesthetic amenity of the Murrum bidgee River. The specific concern within this report is with the impact of pollution from Tuggeranong Creek and Village Creek on the immediate environ ment of the Murrumbidgee River and, in particular, on the uses of Kambah Pool. Within this overall framework, the Applied Systems Group of CRES was specifically requested to: (i) Monitor the quality and quantity of discharges to the Murrumbidgee River and the quality and flow of the Murrumbidgee River above Tuggeranong Creek and through the Kambah Pool, for a range of flows. ( ii) Undertake a programme of water quality monitoring within the Tugger anong Creek system for a range of existing urban development patterns, drain types, and water pollution abatement structures. (iii) Develop a rainfall/runoff model, to facilitate testing of a range of water pollution control options, and the computation of flow inputs for water quality studies. (iv) Analyse instream and inpool responses of Kambah Pool, and represent these processes in terms of a dynamic model. (v) Model bacterial and turbidity pollution and decay in this system. (vi) Analyse the water quality performance of Kambah Pool using the model, with and without a simulated Lake Tuggeranong in the system. 6 (vii) Analyse the water quality performance of Kambah Pool, using the model, for the specified range of urban development patterns, drain types, and pollution abatement structures. Our initial response to the above proposals was to mount an inten sive sampling programme. Initially it was intended to determine the optimum sampling interval for this program on the basis of the above-listed object ives but, in practice, the final sampling programme was completely determin ed by financial constraints. Out of a total budget allocation of $26,000 for CRES activities the maximum possible budget allocation for laboratory analysis was $12,000. However, as a full analysis of a single sample from a single sampling site cost $20.40, the nine station sampling programme originally approved was immediately found to cost more than the budget allocation. The final programme planned within these constraints was there fore, defined as follows: (i) Regular fortnightly water quality sampling was undertaken at nine sites in the Tuggeranong-Murrumbidgee system from 4 June 1979 until 17 June 1980. (ii) Daily water quality sampling was undertaken at the same nine sites in the Tuggeranong-Murrumbidgee system from 25 February 1980 until 10 March, 1980. (iii) Intensive sampling was undertaken during three storms on 8 August, 1979, 11 November, 1979 and 10 January, 1980. (iv) Dispersion, flow,and mixing characteristics 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 results of these investigations are presented in the subsequent chapters of this monograph and the final two chapters develop modelling methodologies based upon these results. 1.3 Existing Information The A.C.T. Region Water Quality Study (Department of Construction, 7 1978; hereafter referred to as the Basin Study) incorporated b acteriologi cal, hydrological and water quality sampling of Tuggeranong Creek and Kambah Pool on an approximately fortnightly basis. The existence of this data set - acquired before construction of either the Tuggeranong retention pond or the concrete channel - allowed us to analyse changes in catchment behaviour since these structures were b u ilt. In addition, the urban geology of Tuggeranong has been studied by the Bureau of Mineral Resources (Jacobson, et a l., 1975) who pointed out, in relation to the hydrology and drainage of the region, that groundwater extraction from bores in the region formerly took place for domestic and stock use. The water quality of this groundwater was quite variable with total dissolved solids ranging from 200 to 1100 parts per million and with bicarbonate as the dominant cation. Their results show little 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 criteria for the concrete channel that was built to guide Tuggeranong Creek. This concrete channel was constructed to completely contain the three year 3 flood, 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 3 produce 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 terrain patterns: ( i) F la t, a llu v ia l, deposits comprise the Isabella Plains, the centre of which was a natural swamp prior to the introduction of the concrete drainage channels that now comprise the upper portion of the Tuggeranong Creek system. (ii) Gently sloping colluvium deposits occur extensively in Kambah, much of Wanniassa and east of Gowrie. ( i i i ) Undulating S ilurian lands comprise the suburbs of Wanniassa, Monash and Gowrie. (iv) Strongly undulating Silurian rock outcrops compromise the h ill top reserves and lands upstream of the Tuggeranong pine plantation. 8 The characteristics of each of these terrain types is given by the CSIRO (1976) and, in terms of soil type and drainage may be summarised thus: (i) fla t alluvial deposits are gradational s ilty clay over heavy clay which is in turn over sand and gravel. 10% of the terrain has top soil 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; ( ii) colluvium deposits are sandy s ilt overlying heavy clay which is in turn over stratified material. 62% of the area has topsoil of vari able depth, and the rest consists of soil of 2.5 m depth. There are discontinuous streams, and the area is liable to sheet flow; ( ii i) undulating Silurian lands consist of duplex sandy s ilt 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 remain ing 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 its e lf over decomposed rock. This region has a dendritic drain age type. The total surface of the Tuggeranong Creek - Village Creek catchment 7 2 is 6.4 x 10 m (6,442 ha) and, on the basis of land use characteristics, it would be possible to estimate total nutrient loadings. Table 1.2 gives estimates for these based on data obtained in Victoria. TABLE 1.2 Estimated Generation Parameters for Total Phosphorus Loadings (Source: Gutteridge, Haskins and Davey, 1979) Development Intensity Estimated Generation Land Use (average gross area/ Parameters for Total dwelling; ha/dw) Phosphorus (kg/ha/year) Forest >50 0.1 Grazing 15 0.1 Intensive C Agriculture D 1 - 3 Urban sewered 0.3 0.6 Urban unsewered . high density 0.3 12 . low density 1.0 3 9 PINE Sampling Site 2000 0 Metres Tuggeranong Creek - Murrumbidgee River System KAMBAH \ POOLS Figure 2.1 10 Because of the current building activity within the Tuggeranong Creek catchment, it is unclear whether it 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 its hydro- logical character. 1.5 Morphology The physical characteristics of stream channels govern the hydro dynamics 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 attach ed algae and emergent vegetation would be expected. During floods, veloc ities 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 it had been considered a large still 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 hilltop 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 Tugger anong 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 silt trap and conditions upstream and down stream 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 starts 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 t ion 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 this 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 immedi ately upstream of the concrete channel sometimes overflows a containment embankment and flows transiently down an old watercourse. Further evalu ation of this upstream area seems necessary and better matching of the flow patterns in the upstream natural creek and the concrete channel seems to be called for. 13 2. QUIESCENT CONDITIONS 2.1 The Sampling Program For the regular fortnightly water quality sampling, as well as for the daily sampling over the two week period, nine sites were chosen as follows: (see Figure 2.1). Site A: This site was at the end of Tuggeranong Creek concrete channel, and at the upstream end of the existing retention pond. Site B: Downstream of the retention pond, at the roadbridge over Erindale Drive. Site C: Village Creek, upstream from its confluence with Tuggeranong Creek. Site D: Tuggeranong Creek Gauging Station. Site E: Tuggeranong Creek upstream of its confluence with the Murrumbidgee River. Site F: Murrumbidgee River at 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 commence ment of the concrete channel. The distances between sites are given in Table 2.1. At each of these sites, the following water quality variables were monitored on a fortnightly 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 solids, i.e. salts) (ymho/cm) . Total Organic Carbon (mg/1) . Total Phosphorus (ug/1) . Total Nitrogen (ug/1) 14 . Nitrate and Nitrite (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 phos phorus 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 it is assumed that free ammonia is low in the system, then 'available1 nitrogen may be approximated by oxidised nitrogen and 'available' phosphorus by filterable 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 situ temperature and dissolved oxygen. The samples were then transported to the Canberra College of Advanced Education for subse quent analysis by Dr. R. Rosich and his staff. 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 it is apparent that there have been changes to the system over that period. Table 2.2, for example, lists 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 concen trations in the Tuggeranong system and a priori it 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 CREEK 0 km taken at Station 1, Monaro Highway crossing reach length, km cumulative distance, km * I to A 5.2 5.2 A to B 1.0 6.2 t B to D 1.7 7.9 D to E 1.0 8.9 E to Murrumbidgee confluence 0.4 9.3 VILLAGE CREEK C to D 0.7 - MURRUMBIDGEE RIVER F to Tuggeranong Creek 1.9 Tuggeranong Creek confluence to G 4.3 13.6 G to H 1.0 14.6 * Tuggeranong North Arm and the Wanniassa South Floodway enter this reach t Village Creek enters this reach 2.1.2 Daily sampling program In an attempt to obtain a better understanding of the shorter term variability of the system, it was decided to mount a daily sampling program over a two week period from February 25, 1980 until March 10, 1980. The water quality determinands detailed above were sampled and the data plotted in time series format. Unfortunately no rain occurred during this period and the consequent low flow conditions revealed very little about the short term behaviour of the system. On the basis of the daily and fortnightly sampling results and the shorter term storm sampling results (see Chapter 3), we are led to postulate that the Tuggeranong system has essentially two modes of behaviour: (i) a long term seasonal variability that can be adequately exam ined with a fortnightly sampling frequency, (ii) short term dynamics arising from storm conditions which, except for the Murrumbidgee River sites, are inadequately sampled even on a daily basis. 16 y g / l O r t h o P 103 ± 131 6 . 4 ± 6 . 7 7 . 1 ± 4 . 9 6 . 8 ± 6 . 4 y g / l T o t a l P 5 3 9 . 5 ± 2 2 . 3 Q 39.9 ± 3 5 . 19.8 2 ± 2 7 . 5 2 7 0 . 0 ± 2 1 9 . 0 ■ o "O C 00 -2 o GO § 6 7 3 ± 3 0 5 1 2 6 6 ± 6 0 7 1 7 . 2 ± 21 rc 4 6 . 6 ± 114 (£> OJ O) E y S /c m 163 ± 126 5 2 7 ± 154 2 3 1 7 ± 85 ea 1 0 1 3 ± 2 7 8 Conductivity >> O' s- Oj NTU 7 . 2 ± 6 . 4 4 . 1 ± 2 . 1 1 5 . 5 ± 3 1 . 4 T u r b i d i t y 108.9 ± 129.0 °C Temp 1 7 . 2 ± 5 . 5 1 5 . 0 ± 6 . 4 17.15 ± 5.5 1 7 . 2 + 6 . 8 ------1 •ä CU o r-. co cn cn (Xi r-H r H 2 2 i CXI cö cn LD 2 N r-~ LU cn cn £ r-H r-H 2 CQ E 5 17 Figure 2.2 Total Filterable Phosphorus , Mean & Standard Error p g /i 3 ° , 10 0 1 2 3 4 5 6 7 8 9 10 Ü 12 13 14 15 km Figure 2.3 mq/ i 14- Filterable Reactive Phosphorus 2 o 0 2 3 4 5 6 7 8 9 10 11 12 13 14 15 km Figure 2.4 M9/> Total 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 it has been assumed that the variations in mean concentrations are meaningful and the interpre tation 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) - PO^ Total filterable P (TFP) = organic P(0P) + FRP Total P(TP) = TFP + particulate P (PP). Particulate P is a complex fraction containing an unknown mixture of organ isms (e.g. algae, bacteria, protozoans), detritus and particle-bound inor ganic phosphorus, and may be estimated as follows: PP = TP - TFP. Examination of Figures 2.2 - 2.4 shows little evidence of strong variations in the concentration of any phosphorus fraction along the length of Tuggeranong Creek or the Murrumbidgee. There is a slight (non-signifi cant) 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 indi cation that the two streams entering reach I - A, or Village Creek which enters reach B - D, contribute substantial amounts of phosphorus to Tugger anong 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 possibilities. 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, virtually non-binding form of N readily available for use by plant and micro-organisms. The second fraction is 19 Figure 2.5 M9/I x 1 0 2 Oxidised Nitrogen 72 U Figure 2.6 Kjeldahl Nitrogen 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 its organic forms. Most particulate N (not measured in this study) is probably incor porated into organisms or detritus. Examination of Figures 2.5 and 2.6 reveals what are possibly signif icant 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 signifi cant amounts of inorganic nitrogen, or (ii) that the buildup of inorganic nitrogen is due to the intrusion of groundwater that contains a high nitrate content, and that the loss of this nitrogen is inhibited by the rapid flow along, for example, the concrete channel. It is difficult to choose between the two possibilities, especially since we believe (Beer, 1979) that the 'weepholes' along the concrete chann el appear to be highly effective groundwater interceptors during low-flow conditions. There is some evidence for denitrification or biological uptake of inorganic N within the Tuggeranong Creek retention pond - total Kjeldahl-N rises within the reach A - B, although perhaps not significantly, 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 site for phyto plankton growth is the Tuggeranong Creek retention pond although high turbid ity and short water residence times during large flows may lessen its suita bility. Examination of Figure 2.8 shows an anomalous pattern of longitudinal mean chlorophyl1 concentrations. The reach I - A shows slightly elevated chlorophyll, and concentrations decline thereafter. The decline within the dam (reach A - B) indicates that major phytoplankton growth does not occur 21 Figure 2.8 pg/l Chlorophylla 10 11 12 13 Figure 2.9 Mg/i 3 0-, Phaeophytin 2.5- 2 .0 - 1.5- 1.0 - .5- 0 - 0 1 2 3 4 5 6 7 1 9 11 12 13 "l4 15 km Figure 2.10 Dissolved Oxygen ppm 14- 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 virtually no longitudinal variation in chlorophylla in the Murrumbidgee. Phaeophytin, the primary decomposition product of chlorophyll, and indicative of algal death, shows little longitudinal variation at all (Figure 2.9). 2.2.4 Dissolved oxygen Mean dissolved oxygen concentrations (Figure 2.10) are slightly 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 ilitie s , and the results are given in Chapter 4. 2.2.5 Turbidity Turbidity is a composite variable, consisting of an unknown combin ation of suspended solids (e.g. clay particles), chlorophyll and dissolved colour due to tannic compounds resulting from the decomposition of terres tr 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 this area is usually suspended clay particles, but the turbidity difference upstream and downstream of the Tuggeranong retention pond is persistently v is ib le . The typical situation consists of clear, 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 this that water overtopping the spillway churns up the mud and earth at the foot of the spillway producing the observed turbidity peak at Site B. 2.3 Nutrient Behaviour in the Retention Pond In order to further examine the data of Table 2.2 and the results of Figures 2.4 and 2.5, the h isto rica l load data from the Basin Study was com pared to the data that CRES obtained during regular fo rtn ig h tly sampling and during storms. This was accomplished by p lo ttin g load-flow diagrams fo r total 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 the Tuggeranong Creek retention pond has affected the load-flow characteristics of phosphorus (as measured by total P) and there also appears to be a slight effect on oxidised nitrogen. As far as the phosphorus behaviour of the Tuggeranong Creek system is concerned, at high flows (greater than 3 0.1 m /s), the phosphorus loads were always greater before the retention pond was built 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 high 3 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 better 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 it is possible that the construction activity 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 its 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 statistical test verify a null hypothesis that the two curves are different, but similarly one could not verify a null hypothesis Figure 2.11 NTU Turbidity 24 CM - m - m iue 2.12 Figure Ln TUGDERRNONG CREEK LOG10 FLOW- P LOAD 1 • LO oo - r o - r O O) CO O CD — r"- r— CT> O) abp I I cn / b - h a u o i d 0 1001 0 d i o u a ix? \ r- r C\J « » Ln 25 O LH LO a E3 ca « a I LT? 1 f LOG10 FLOW iue 2.13 Figure TUGGERflNONG CREEK LOG10 FLOW- N LOAD e/^ N 1 0 0 1 0 N ! O H O Aep/ß^ ) O 5 0 05 05 26 1 1 1 I LD L O G !0 FLOW 27 that the two curves are the same. It would appear then that, during storm periods, the retention pond acts as a phosphorus trap, but during low flow periods it exports phosphorus, producing the elevated levels at Site B. The pond also seems to have a slight trapping effect 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 electrically conducting dissolved substances in water. The ions responsible for oceanic conductivities and riverine conductivities are substantially different, 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 5.79 Sulphate 7.68 12.14 sor Magnesium Mg++ 3.69 3.41 Calcium Ca++ 1.15 20.39 Potassium K+ 1.10 2.12 Carbonate c o r 0.41 35.15 Silicates Si02 — 11.67 There is a high correlation between gravimetrically measured total dissolved solids (TDS) and conductivity. Provided the ratio of salts always remains the same then this correlation should be perfect. Conductivity is thus approximately conservative. Apparent non-conservation of conductivity generally arises from (i) changes in the ratio of ions in the water; ( ii) temperature changes in the water; ( iii) changes in water turbidity. High sediment loads reduce the effective volume of the sensor head of the conductivity probe and tend to lower the readings. Nevertheless, owing to the lack of gauging facilitie 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 Mmho/cm Conductivity 400- Figure 2.15 mg/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 vari ations similar to that of oxidised nitrogen. The two drains in reach I to A, and Village Creek, which enters reach B - D, contribute slightly to the conductivity of Tuggeranong Creek, presumably through groundwater inflow. There is a slight drop in mean conductivity in reach D - E which is hard to explain. It may be due to uptake of Fe and Mg (HCO^- is used as a source of C02 for photosynthesis by many aquatic plants) by algae and bacteria - presumably also partly the reason for the lowered conductivity at Site B. It 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 slight that it may be statistically insignificant. The Murrumbidgee shows no change of conductivity along its 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 inoper ative (see also Chapter 6). It is possible, however, to obtain a rough esti mate of flows in the Village Creek and Tuggeranong Creek section just up stream 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 con fluence (i.e. at the present gauging site) are Qy, Q^, and Q^, respectively. If 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, for simplicity, let 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 aQGcv + (1 - a) QgCd Qqcq so that (3) Since the conductivity measures are noisy, i t is clearly necessary to obtain some estimate of a on the basis of equation (3). Two approaches are possible: (i) compute a from (3) for each sample and estimate by the sample average, ä, i.e . a (4) where cGi ~ CDi a . 1 cVi ' CDi N is the number of samples and i indicates the ith sample; ( ii) obtain an estimate a computed from (3) with the concentration measures replaced by their mean (average) values computed over the sample set, i.e. a (5) where, once again, the bar indicates sample average as in (4). Using fir s t equation (5) we find that for the N = 36 conductiv ity measures (fortnightly + 14 daily) ~ _ 1013.3 - 706.4 0.684 a 1155.4 - 706.4 ( 6 ) in other words, the Village Creek flow appears, on the basis, to comprise 68% of the gauging station flow and, therefore, the upstream Tuggeranong Creek comprises 32%. On the other hand, i f we use equation (4), we find that a = 0.79, with Village Creek apparently contributing a much larger 79% of the upstream flow. Upon further examination, however, we find that these higher values of a are due almost entirely 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 limi tations of the gauging information on the Tuggeranong Creek system. Certain ly 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 esti mate flows of other sampling sites in the system on the basis of the measur ed flows at the Tuggeranong and Pine Island gauging stations. 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 Murrumbidgee flows provide a direct comparison since we know that over the study the mean flow at Site D was 0.05 m 3-1s and the mean flow at Pine Island was 2.8 m 3-1s whilst the mean conductivities were 1013 ymho/cm and 325 ymho/cm. The mean conductivity at Kambah Pool was 332.6 ymho/cm so that if we assume that the flow at the site D gauging station is a fixed proportion of the Kambah Pool 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 site were taken in order to retain a record of the algal biomass at each site. These photographs are available from CRES, but their interpret ation turns out to be rather subjective. In order to remove, as far as 32 possible, this subjectivity, 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 fortnightly 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 all the sampled sites, the algal content continually increased from Site A to B, B to D and D to E with Site E consistently registering the highest values. ( ii) Detachment of algae by storm flushing is apparent. The exceed ingly large runoff from the storm of 4 January 1980 (approxi mately the 3 year flood) completely cleared Sites A, B, D and E of algae, and partially cleared Sites C, F and G in Village Creek and the Murrumbidgee. There is also evidence that the existing Tuggeranong Creek retention pond inhibits this flushing for all 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 discuss ion to a descriptive evaluation, which parallels the results on the longi tudinal variability of total 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 qualitative assessment of the per cent algal cover and domi nant 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 0.40 2/7 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 0.40 13/8 1.25 0.67 0.83 2.17 3.00 0.83 0.92 0.10 27/8 0 0.17 0.83 2.17 2.17 0.50 0.83 1.20 10/9 2.58 0.83 2.25 1.67 2.50 0.33 1.33 0.40 24/9 1.08 1.0 1.92 2.83 2.75 0.50 1.0 0 22/10 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 0.80 19/11 0 2.83 2.08 2.58 4.50 1.25 0.17 1.90 3/12 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 3.10 2/1 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 0.90 29/1 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 (Escherichia coli ) is a non-pathogenic organism found in the digestive tract of warm-blooded animals. Escherichia coli is in itself a harmless bacteria and is only an indication that pathogenic bacteria may exist. 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, little information has been published for Australian conditions (Bayly and Williams, 1973; Cordery, 1976b) and even when data are available, they are often misunder stood (Russ and Tanner, 1978, p. 78). Data that have been published (Table 2.5) indicate that high and variable densities can frequently occur. Overseas 34 experience (Geldreich et a l. 3 1968; Van Dönsel et d l 1967; Weibel et 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 variation in bacterial concentration. Similarly, 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 variability of bacterial levels in athalassic Australian waters is associated with and compounded by extreme v a ria b ility of flow. This v a ria b ility of bacterial levels has encouraged workers to use the geo metric mean (G = -----Xn) as a measure of central tendency (Burgess, 1974; Environmental Protection A uthority, 1974; Heath, 1967). The use of the geometric mean usually assumes that the data are log-normally distributed. Sample collection Bacterial data for this 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 riffin * 4684 1410 Jerrabomberra Creek, A.C.T. 1672 93 Dandenong Creek downstream of Wells Road** 6370 3491 Yarra River at Burke Rd.*** 4963 2729 Kororit Creek, Forest Street Bridge, Sunshine**** 94500 19361 * Burgess, J.S. and Olive, L.J. (1975); ** E.P.A. of Vic. Rep. U4; *** E.P.A. of Vic. Rep. L3; **** E.P.A. of Vic. Rep. Western Suburbs Streams (undated). 35 Faecal co li form was determined using a membrane filtr a tio n tech nique with the use of M-FC broth (Geldreich et a l., 1965). M illipore prepared M-FC ampoules were used as the culture medium and the samples were filte re d through p re -s te ri1ised M illipore HAWG 0.45 y f ilt e r papers. Incubation was by means of M illi pore water bath incubators at 44.5° C for 24 hours. Normal procedure was to incubate two plates per sample, however, on occasions a greater number of plates were processed. Problems of sedi ment interference at high flows were largely overcome by successive serial 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 trib 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 all cases the standard deviation (S) for each of the sample stations is larger than the arithmetic 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 longi tudinal variation of the data. First 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 relation to this point i t should be noted that the flow at Station Z on these occas ions was p a rticu la rly low. A marked drop in levels occurs between Stations A and B (above and below the retention pond) and this could be interpreted as a reflection of bacterial d ie -o ff. Examination of the data in Appendix 1 demonstrates that the 'purification' 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 ffe ct 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 dram a 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 n 3 rt % *9 S' W Cfl rt io3 io5 Faecal coliform/100 ml. Figure 2.17 ----- Arithmetic mean x ----- Geometric mean G ►n cu o - 3000 o -2000 H* o' 1 3 - 1000 o 3 I—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 significantly higher than those encountered in Tuggeranong Creek. This trend is particularly obvious following periods of rainfall. 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. Similarly, 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 this 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 sur prisingly, increases in flow are associated with increases in bacterial con centration, however, the relationship is not simple nor does the data allow the relationship to be easily quantified. This difficulty is illustrated further by Figure 2.19. While concentrations of bacteria tend to increase with increase in flow, very high flows are not characterised by proportion ately higher concentrations. It appears that at very high flows the volume of water is sufficient to begin to dilute effluent present and concentrations reach a maximum slightly 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 water ways of the valley. It 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 partially a function of the complex data distribution being examined. From the standpoint of the a rith 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 tiv e ly low. The increase in level as expressed by th is measure (6) downstream of V illa g e Creek is less spectacular and i t could be argued th a t the waterway complies w ith normally accepted bacterial standards. It could be further argued (Table 2.6) that as the geometric mean fo r a ll data only reached a maximum of 165/100 ml fo r Station C, then the waterway carried levels of bacteria that permit recreational use. The means calculated from weekly data are substantially less and a maximum of 105/100 ml was recorded at Station C. However, i f i t is desirable th a t no more than 10% of the samples exceed 400/100 ml then by almost any criteria the waters of Village Creek must be considered unsatisfactory from a contact sport point of view. TABLE 2.6 S tation No. j ZAB C DE Measure 1257 1359 1510 1166 3243 2111 2420 4660 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 79 Log G1 S1 1.24 1.16 1.10 1.18 1.31 1.38 1.49 X2 134 567 437 196 1542 942 998 175 911 929 445 3516 2142 2249 S2 Log G2 1.54 2.10 2.01 1.47 2.02 1.75 1.56 35 126 102 30 105 57 37 « 2 Log G2 S2 0.92 1.01 0.80 0.91 1.15 1.21 1.41 Geometric mean a ll data N = 43 G1 x i A rithm etic mean a ll data N = 43 s, Standard deviation all data N = 43 Log Gj Log^ Geometric mean all data N = 43 Log GjSj Standard deviation of Log G^ X2 Arithmetic mean weekly data N = 23 Standard deviation weekly data N = 23 Log G2 Log^g Geometric mean weekly data N = 23 G2 Geometric mean weekly data N = 23 Log G2 S2 Standard deviation of 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 34^ iJM|0 io^ 1? 7o5 Coliform Bacteria (count per 100ml) 40 Despite the difficulties with the data it does seem obvious that, as urbanisation continues in the valley, bacterial levels will increase and that as it 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 facilities. Exactly what these effects will be is uncertain. As yet die-off rates for bacteria have not been established, and so it is not possible to predict the effect of the Tuggeranong urbani sation 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 it 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 2070 1979-80 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. It would appear then that, at low flows, the Tuggera nong 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 transport ing 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 difficulties 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 it 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 finally 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 on January 4 1980 when the flow at the Site D gauging station was of sufficient intensity to render the gauge inoperable. Estimates of the stage height, based on the maximum height of debris accumulation, indicated that the flow at Site D peaked between 120 m 3 /s and 130 m 3/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 reten tion 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 = r2/^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 then 3 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. At 3 high 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, it was found necessary to find the flow-velocity relations between the sampling sites. As a gener al 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 triangu lar cross-section, to 0.4 for a wide rectangular channel (Whitehead, Horn berger and Black, 1979a). As an extreme example we may note that for a con stant 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 obtain ed 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 its 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 up stream turning point of the pond, Figure 5.1) to Site B would have been U = 1.82 x 10"3 Q0-214. However it is difficult to believe that the exponent would differ so much from that obtained on Kambah Pool. It 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 refill 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 little or no algal detachment at SiteB, but at high flows complete detachment 44 occurs. The storm of 10 January 1980 also supports this idea: despite a 3 2 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) it is possible that evaporation exceeds groundwater inflow over much of the year so that during summer the retention pond level is lowered; (ii) changes in the mean wind direction could play a significant role. If the wind blows downstream towards Site B, the sur face 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 behaviour in Chapter 6 of this report, it was decided to use a two step flow-velocity relationship in which the velocity stays constant at low flow (which one could envisage as a wind effect) but, at high flow, the retention pond acts 3 3 as a constant volume reservoir (equation 3.2) with a volume of 110 x 10 m 4 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 effective 2 depth 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 1979 3 4.0 m /s on 11 November 1979 2.0 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 of the chemical analyses of these storms are given elsewhere (Henderson, 1980). On the f ir s t storm sampling exercise the peak flows were not fu lly sampled. However, by u tilis in g the experience gained in this 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 for the November and January storm. It is of interest to note that the water q ua lity variables at Site A appear to peak on the ascending limb of the hydrograph, and have generally dropped to low concen trations by the time that the hydrograph has peaked. This may be explained in terms of nutrient runoff by postulating that the firs t rainfall event washes nutrients into the waterways, but the large quantity of water present at the hydrograph peak e ffe c tiv e ly dilutes the concentration. However, i f this interpretation 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 u a lity variables. The storm data confirm our contention that the Tuggeranong retention pond acts as a nutrient trap during storm events. Table 3.1 gives peak con centration values measured at the downstream sites, and it is clear that in the short term ( i.e . during the storm) very l i t t l e nutrient travels from Site A to Site B, and that most of the nutrient load to Site D came from Site C. In other words the high nutrient concentrations from Site C were diluted by water of lower nutrient 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 ris e , and there was no evidence 3 that Site B had in any way reacted to the 2 m /s flow input at A. Possible reasons for this have already been discussed in Section 3.3, but it is instructive to consider the matter a little further. On the basis of the 3 hydrograph at Site A, i t would seem that about 6000 m of water flowed into 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 9 approximately 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 3405 11/11/79 B 120 345 1395 C 740 675 6285 D 380 590 5910 Storm A 625 2560 7130 10/1/80 B No peak observed C 265 2775 4575 D 250 2625 3515 that this was insufficient to overtop the retaining wall. I t is clear from these calculations that furthers more comprehensive monitoring of the retention pond is necessary before we can confidently describe its 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. It 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 transform ation of the flow axis by means of the flow-duration curve in order to (i) check the adequacy of sampling; (ii) assess concentrations under dry, average and high flow conditions; (iii) check the range of concentration conditions found under each flow regime; (iv) examine the data for any trends or change in concentration. iue 3.1 Figure FLOW DURATION CURVE TUGGERANONG CREEK (sonnen 47 MO Id 12.5 25.0 37.5 50.0 62.5 75.0 87-5 100. O PERCENT EXCEEDENCE iue 3.2 Figure FLOW DURATION CURVE PINE ISLAND o o o C\l ro Lo to (S03Wn0) MO 13 48 o 12.5 25.0 37.5 50.0 62.5 75.0 87.5 100. PERCENT EXCEEDENCE 49 The flow duration curves fo r Tuggeranong Creek (Site D) and the Murrumbidgee (Pine Island) are presented in Figures 3.1 and 3.2. We should emphasise that these are not quite the same as the flood-frequency curves since the latter 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 all flows - not just floods - based on five years of average daily flow. As a storm flow is unlikely to occupy more than a small fraction of a day, our curves w ill appear to over-emphasise low flows in comparison to flood- frequency curves. Since in the 1979-1980 Study no instantaneous flows were recorded 3 -1 exceeding 3.8 cumecs,an a rb itra ry c u t-o ff was made at 5.0 m s fo r p lo ttin g 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 this combined data set was given a cumulative percentage from the flow duration s ta tis tic 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-concen tra tio n curve for total 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 quality variables could not be undertaken, a limited set of turbidity, S r ds os ss si /o oo*o s/-o os*i ss-s oo*s sd*s frOS’ iue 3.3 Figure I i I i I 1 I 1 I I I i I I i i I I I FLOW DURATION/CONCENTRATION RELATIONSHIP £ S OS SS2 )£ /n d ivioi dn/on) (sodwno) 50 mo id r-O — O — __o _o PERCENT EXCEEDENCE 51 conductivity, faecal coli form and suspended sediment data was obtained. Following the storm, the CRES team assessed its impact v is u a lly . The strength of the resulting runoff can be judged from the fact that a car washed down channel from above S ite A, about 300 m in to the pool down stream of Site A. The water in the retention pond at the time was a milky brown colour due to suspended sediment runoff, and this colour indicated th a t the water came from Tuggeranong Creek. At 1500 hours on 4 January, 1980 Tuggeranong Creek flow completely dominated Kambah Pool. This indicates the e ffe c t th a t localised storms in the Tuggeranong area can have on Kambah Pool over short periods o f time. The Murrumbidgee was unaffected by this particular rainfall event, so that the water at Pine Island remained cle a r. However, despite the low flow conditions in the Murrumbidgee, the turbidity in Kambah Pool had effectively disappeared within two to three days. An exponential curve was fitte d to the suspended sediment data at Site G, above Kambah Pool, and S ite H below Kambah Pool, giving time constants (flushing times) of 0.5 days and 0.77 days respectively. This confirms th a 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 tracer results discussed in Chapter 5. If information were available on flow, it would be possible to calculate the suspended sediment transport into and out of Kambah Pool. Unfortunately this flow information is not available. Nevertheless, a rough assessment can be made i f we assume (i) that the peak in the suspended sediment distribution was observed, and it can be roughly modelled as S = SQexp(-t/T) where T is the time constant and S and S are in uq/1. o (ii) the flow peaked at the same time as the suspended sediment concentration, and had the same time constant so that 3 Q = QQexp(-t/T) where Q is in m /s. This gives a total 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 120 m3/s (sa y), sQ = 500 ug/1 and T = 0.5 days so that 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 that IS = 2,500 tonnes. The discrepancy (i.e . more calculated output than input) seems to arise from our failure to accurately locate the peak in suspended sediment. It seems lik e ly that 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 into Kambah Pool from the 3 year flood in Tuggeranong Creek at 1900 ± 600 tonnes, with a strong caveat that these figures are based on very few data points. As in the case of the retention pond, this indicates the strong desirability of more comprehensive short term monitoring of Kambah Pool, i f possible using automatic monitoring devices. 3.7 Erosion in Tuggeranong Creek Inspection after the storm of 4 January 1980 revealed extensive morphological changes in the pond reach between Site A and the main retention pond. Much of this section had eroded, but the retention pond its e lf showed evidence of deposition, as did all the subsequent downstream Tuggeranong sites. In order to further identify the behaviour of the system i t was decided to in sta ll erosion pins. These were installed at various locations within the existing retention pond and downstream at Sites B, C and D. We have no measures to reveal whether the pins had been tampered with. Given this proviso, the general results 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 retention pond; and that there was evid ence of slight (1 cm to 1.5 cm) erosion within the pond its e lf. The down stream sites showed evidence of slight deposition, once again of about 1 cm. 3.8 Nutrient Loading and Land Use Characteristics In Chapter 1 we presented Victorian data relating the expected total phosphorus loading over a year to the size of the catchment. Given a catch ment area of 6,400 ha, one would expect anywhere from 640 kg to 64,000 kg of total P over one year. On the basis of our results, and the flow readings 53 at Site D, we estimate that the total phosphorus loadings are 3 (i) during quiescent condition (an average flow of 0.04 m /s 3 which corresponds to a daily discharge of 3500 m ) there is a load of 0.18 ± 0.24 kg/day of total phosphorus; (ii) 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 et al.3 (1978) for other A.C.T. catchments. TABLE 3.2 Total Loadings (Site D) During Monitored Storms Date Total P Total N no2/no3-n TFP Kjeldhal-N FRP Discharge kg kg kg'3 gm kg gm ITT 8 Aug 79 1.22 16.23 8.27 12.4 7.96 6.38 1.02 x 104 11 Nov 79 8.77 73.8 18.20 0.0 55.6 0.0 4.23 x 104 10 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 it was the only continuously gauged site. The table primarily reflects Village Creek characteristics, 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 concen tration time curves do not, in general, peak at the hydrograph peak - for example, total P always peaks on the ascending limb - it would be incorrect to integrate the regression equations of page 15 through a representative hydrograph since that procedure would constrain both peaks to be contempor aneous . 54 6 3 If 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 agree ment 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 its behavi our is the description of its 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 (Site F), upstream of Kambah Pool (Site G) and downstream of Kambah Pool (Site H). These sites do not correspond, however, with those of the Basin study, which sampled at Angle Crossing (their Site 213) and Kambah Pool itself (Site 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 quanti ties must arise completely as a result of the flow differences rather than from any changes in Murrumbidgee river itself. The Basin study data was collected in Murrumbidgee flow conditions 3 3 that range from 1.4 m /s to 59.3 m /s, whereas the CRES data - taken during 3 3 a very dry year - spans Murrumbidgee flow conditions from 0.1 m /s to 7.2nr/s There are, however, certain advantages to this. If interest is centred upon the aesthetic, 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 earlier 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 virtually all of the water in Kambah Pool during that period came from 56 the Tuggeranong Creek system. We would re-emphasise the importance of these flow results for he original study objectives. With a 'ty p ic a l1 dilution factor ranging fror 50 to 80 parts of Murrumbidgee water to one part of Tuggeranong Creek waer, the pollution impact of Tuggeranong Creek upon Kambah Pool w ill be slight except under two conditions: (i) a localised storm in the Tuggeranong area which only affects the Tuggeranong Creek system; and ( ii) extremely low flow conditions in the Murrumbidgee. Both of these conditions were experienced during this study. Tie previous chapter has already discussed the effects of a localised storm 4.2 Longitudinal V ariability In order to examine the low flow variations in the Murrumbidgee we took the three days of lowest flow from the fortnightly data set and avenged the water quality variables for those three days at each site. The resu'ts are given in Table 4.1,from which one notices a slight increase in disso'ved oxygen and turbidity as one travels downstream in the Murrumbidgee but 'ery l i t t l e variation in any of the other determinands. The increased diurnal dissolved oxygen alona Kambah Pool probaby arises from the growth within the pool under low flow conditions. In Section 2.2.5 we have already commented upon the increased turbidity in Kambah Pool, and compared i t with the Tuggeranong Creek values; the turbidity readings of Table 4.1 are so low that the slight downstream increase is unlikely to be significant. 4.3 Biology and Water Quality of Kambah Pool Kambah Pool is the fir s t slow-moving section of the Murrumbidgee River below its confluence with Tuggeranong Creek. Reduction of water f ow within the increased width and depth of Kambah Pool has created a deposition- al environment in which substantial sedimentation of sand and finer part de 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 (ppm) (NTU) r------(yg/1) Dissolved Total Total N0?/N0^ Fi 1terable Location Oxygen Turbidity P N ^ J Reactive P Pine Island 7.9 2.3 20 593 17 4 Upstream 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. Little was known of the biological or physical characteristics of Kambah Pool, so CRES mounted several brief surveys to investigate the morpho metry 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 monitor ing and analysis, so that the effects of 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 fav ourable situations. 2. Elevated rates of sedimentation during high flows probably in troduces the bulk of the nutrient inputs to habitats like Kam bah 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 filling 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 it 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 if 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 initial 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 trans verse 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 either 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 Transect Number Diurnal Observation Sampling Site Dye Sampling Site Changir V Kambah 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, if desired); 5. sediment depth - the depth of the superficial sediment layer (if 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 listed 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 sam pled variables are shown. Our initial survey undersampled the pool over its whole surface area, even though the six transects were sampled in detail. 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 littoral zone of the pool. These plants depend on the sediments for nutrients and water, and photosynthesize using light and atmospheric The emergent littoral 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 still or slow 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 itella sp. (Stonewort) More delicately structured and smaller than the closely related Chara sp. In Kambah Pool this species is restricted to rocky substrates. Spirogyra sp. (Blanketweed) A filamentous green alga forming long, hair like masses with a slippery texture. Variations in light avail ability cause marked changes in colour and appearance; ranging from small, light green tufts in shallow sandy areas to luxuriant, dark green masses in poorly-lit, 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, blunt leaves, and has a similar form and life 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 toughen ed, water-resistant leaves and grow in damp situations after a fall in water level. Vallisneria spiralis (Ribbonweed, Eelweed) Probably the most important macrophyte in Kambah Pool. This species has flat, strap-like leaves, and produces flowers and fruit on spiral tendrils. 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 lOOm !i Sis I * 0 t 0 ...... « • ■ •■ •((■ M l 9 ...... 9 iiKiiiim ...... • ■■■■•■■■■■■ 9 S 3 ♦ . . . 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 i ü i . .. <20% iW + + + + + 20% to 40% :: . 0 0 0 0 0 40% to 60% e 0 0 0 0 60% to 80% i i t h , BBBB B 80% to 100% l-:\ S i?V . I ' i l t o 1 Seal e T W -S r CT ri »M:!:!:ü : 2 ■ii:ni|l!!ili.:i: III i $ l iiSiiiiiiiSiii.*. °r : ::::: 100 m * t* jooo ♦ • •• ...... If • *•» ' * COOC )üo-jooejO 0 •• .... 'U«UOO(c ♦ < • . •••• cooccoooo ♦ *° ^ nO •••• .. t' OC wC C C ^ <00 V:::.-:.*::• •• Ö t.;*.*. 00 I So • !• • • . i, 0» OC o wO • • C • c 0 (COCO ♦ ... ■Y"'"'"' • EOC 0 ♦ • • •t • ( ?SSS.rc-c-c?o c*c coo ;i£ ... r-i-liiiiii&lk i?o : is. " S ä V B A ‘S:K::Y:h : : : w S 8 .. Y o:: . j i r i & s s s X ' * m * a m * . W s K a p t u 08«.‘‘,::"\:.V88888,88800,,88.j| T o ; . , : ’.: l«A»-StCT ? * ^0 ♦ ♦ h Ü s s i;...... • 0 • • • ...... 'K ♦ ♦ 0 0 • 0 * . CC0** ::!:Y88i8888 88?888f«M;85f8Tc8ffi ♦l***CtwOC'(f ♦•••• ♦ -or » •-•'coot' ji Estimated Distribution of Vegetation Cover in Kambah Pool 26th March, 1980 Figure 4.4 VEGETATION COVER - DEPTH 7 . AOO NO I 1 V1303 A NO V1303 I 1 AOO 7. 64 DEPTH iue 4.5 Figure IO ro VEGETATION HEIGHT - DEPTH o ro in CM 1 n 4 1H0I3H i > i■ 4 4 4 4 o CM 65 4 4 4 4 NO 1303 1I V A 4 m o m i 1 1 1 1 i 1 4 * 4 4 4 4 4 3 4 4 4 4 4 4 4 4 4 : 4 4 4 4 4 o 4 4 4 4 4 4 4 4 4 4 l 4 o o DEPTH iue 4.6Figure O O O C LO O c\j LO ro O ro LO SEDIMENT DEPTH - DEPTH i r i i O l3 1N3HIQ3S WO Hld30 c \ j 66 4 I *4 4 * 4 ä 4 4 4 4 4 4 4 4 : « < 4 < 4 4 3 I — C\J — 2 _ __ N- C\J ro LO ^r CD 00 I I i I I I I DEPTH 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 restricted in inter mediate 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 restricts 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 utilise 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, it 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 possibility of massive choking growths of different green algae, such as Cladophova and Hydrodictyon. Such a transition 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 oper ation 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 ecosys tem; recycling nutrients, providing food and shelter for aquatic fauna, stabilising sediments and improving water clarity. 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 silt to otherwise coarse, sandy sediments, thus reducing its 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 con ditions 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; ( ii) deplete Kambah Pool of stored tissue and sediment nutrients; ( ii i) encourage high plant productivity 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 toilets and changing rooms (see Figure 4.1). S itel 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 after a few hours of photo synthesis. The supersaturated 0^ concentrations declined rapidly at dusk due to respiration and loss through the water surface. Site 3S (surface) exhib ited quite stable saturated 0^ concentrations, without a tendency to super saturate. 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 well-lighted depths, particularly those supporting macrophytes. Oxygen demand does not appear very great, at least in shallow situations, 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. i Figure 4.7 Dissolved Oxygen - Kambah Pool 69 0 ) Time 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 mix ing. Transit times and dispersion characteristics were examined by adding a 'slug' of fluorescent dye to the rivers to act as a tracer. The concentrat ion of this dye was determined at intervals as it passed a series of sites downstream. Altogether six separate dye tracing experiments were conducted as follows: (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 first of these was on 24 October, 1978, prior to the start of the present study, and the second was on 10 March, 1980. This chapter presents the results of these dye experiments together with initial 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 results. 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 with in the pond. The answers to these queries are of basic importance to the likely performance of the pond, particularly in relation to its 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 iue 5.1 Figure SAND ; w ü LU < ? n / E (/) E © I I I II 72 © 5 _ .© © TIME, HOURS 73 time can also be used to assess the effects of the pond on nutrients in the riv e r system, although in this case the problem is more complex. Note that the investigation of mixing with depth is also linked with the retention time. If, for example, the input water moves only across the surface of the pond then the retention time w ill be shorter and the overall behaviour w ill be quite d iffe re n t from a situation in which the waters were well mixed. The input date was selected with the hope that major rainfall would occur early in the experiment. Unfortunately this was not the case, although rainfall did occur subsequently in the experiment (Figure 5.2). The fluorescent dye Rhodamine WT was used as the tracer m aterial, with a Turner Designs F ilte r Fluorometer equipped with the appropriate f ilt e r s being used fo r the analysis of the samples. The filte r s and operat ing 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 light weight depth sampler suspended from a graduated lin e . In addition to the sampling locations within the pond, samples were also collected from Site B located on the creek below the dam wall and down stream of the small pond that has formed immediately below the dam w all. An automatic water sampler was used at this s ite fo r the f ir s t three weeks of the experiment. Two litr e s of dye (400 g of dry weight dye) were poured into the upstream end of the pond, immediately below the end of the concrete channel (Site A on Figure 5.3), at 0730 hrs on the 27th June 1979. The input dis 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 collection of surface and subsurface samples was carried out each day for the f ir s t 7 days of the experiment from a boat. Subsequently the sampling interval was increased and the number of sites sampled in the pond decreased Samples were collected on 27 occasions during the period from 27th June cc E z u_ E < Figure 5.2 30-1 TUGGERANONG CREEK RETENTION CL Z Q u_ o Z < OC < CNJ lO CM o 74 TIME, after Dye Input 1979 75 until the experiment was concluded on 1st November. I t should be noted that dye was s t ill detectable in the pond, at approximately 10 times the back ground value, as late as November 1st. Additional samples, mainly from the automatic sampler, were available for Site B, downstream of the dam. Figure 5.3 shows the pattern of dye dispersion with time. The f ir s t arrival of dye at the lip of the dam is estimated to be between 0000 and 0600 on June 28th which is approximately 16 to 22 hours after the dye input. By 1400 hrs on June 27th (some 7 hrs. after input) the dye had only just reached Site 0. The fir s t arrival at Site B, downstream of the dam, was at 1540 hrs on June 28th, some 32 hours after input. I t should be noted, however, that the time lag between the dye concentration at the dam top and at the down stream Site B was due to the effect of the pool below the dam. The most striking feature of the experiment was the degree to which the dye has mixed throughout the pond. This applies to mixing both horizontally and ve rtica lly. 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 retention pond had slig h tly higher dye concentrations. Mixing through the water column was also even, although where concentrations were high there was a slight tendency for the bottom samples to have a slig h tly higher concen tration. This well mixed pattern was maintained throughout the period of sampling and was s t ill apparent some 16 weeks after input. The degree of mixing is the more surprising because there was virtually no effective rainfall for the first few weeks of the experiment (see Figure 5.2). Thus only a very small quantity of water was discharged over the dam wall and this is reflected by the lower dye concentrations recorded at Site B for the earlier phases (see Figure 5.4). Indeed there is l i t t l e doubt that much of the discharge in such periods of low rainfall input is due to wind forcing water over the dam, rather than from discharge from the concrete channel into the dam. Wind mixing is clearly important: the f ir s t few days of the experiment were marked by strong winds and there seems li t t l e doubt that these were respons ible for the thorough lateral and vertical mixing of dye in the samples taken after about 2 and 18 weeks, respectively. By this time one would have expected the upstream portions of the pond to exhibit lower concentrations due to the input water from the inflow channel. Such effects were not present and again wind mixing is thought to be responsible. 76 Figure 5.3 77 Effects of dye decay One potential limitation of fluorescent dye tracers is their tendency to decay. The decay can be due to a variety of causes and includes photo chemical destruction and possible adsorption onto both organic and inorgan ic particles. Rhodamine WT is known to be the most stable of the commonly used fluorescent dyes and, for periods of time measured in hours or days, i t is frequently regarded as fu lly conservative. However for experiments in natural waters that last for periods of weeks there is probably a decay factor present. The literature on this topic is limited but a decay rate of about 1% per day would seem appropriate (see Smith 1978, and Warnerand Smith, 1979). In presenting figures of various time-concentration plots this decay factor should be borne in mind. Time-concentration curves Plots for a selection of sites are given in Figures 5.4 to 5.7. Figure 5.6 gives the data for the western edge of Site 5 and Figure 5.7 gives the data for Site B. The form of these curves is similar but the time lag in the concentrations for 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 identical to those taken in the centre of the pond when i t was sampled. For each of the sites above the centre of gravity, and the area under the curve is given in Table 5.1, and these results imply a mean dis charge during the experiment of between 24 1/s and 31 1/s. TABLE 5.1 Site Area Linder Curve Centroid (weeks) (ug - weeks/litre) X 19.7 1.84 3 (west edge) 27.04 3.31 5 (west edge) 26.61 3.38 7 (west edge) 31.18 4.13 B 23.32 3.8 iue 5.4Figure DYE CONCENTRATION CURVE FOR SITE X (BOAT RAMP) I . I ■ 00 NIU13NO AO 3 N0I1U31N3ON0O 0 /0 1 73 ■ I I WEEKS AFTER DYE INPUT AREA UNDER CURVE = 19.70 CENTRE BF BRAV ITY= 1.84 Figure 5.5 DYE CONCENTRATION CURVE FOR SITE 3 SURFACE (LEFT EDGE) < i n • —■ — — —• — /n 0bi3N3 3AO N0UbyiN33N03 1/On 79 WEEKS AFTER DYE INPUT AREA UNDER CURVE = 27.04 CENTRE 0F GRAVITY= 3.31 iue 5.6 Figure .6□ YE C0NCENTRRTI0N CURVE E0R SITE 5 SURFACE (LEFT EDGE) 80 WEEKS AFTER DYE INPUT Figure 5.7 DYE C0NCENTRRTI0N CURVE F0R SITE B ( BEL0W RETENTION P0ND 81 WEEKS RETER DYE INPUT 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 site because of its 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 first 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 from June 27 to November 2 was 118.6 mm which volumetrically is approximately 4,900 megalitres (4.9 x 106 m^). Only a fraction of this is likely to be discharged at Site A. The volume of the retention pond is estimated to be 110 megalitres (1.1 x 10 5 m 3). 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 concen trations remain in the retention pond even after major rainfall events. This, further reinforces the earlier conclusion regarding the mixing characteris tics. 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 it 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 particulate material in the pond, provided a decay factor for such material is available. (See Chapter 6.) A second dye experiment on the retention pond was conducted in order to examine the e ffe ct of the small storm of 10 January, 1980. Two litre 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 tiv e ly well mixed. The dye rapidly mixed la te ra lly and v e rtic 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 lip , i t would appear that very l i t t l e water had spilled 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 interpreting the data since only the rise in dye con centration and the peak appear to have been measured. In such cases of sparse data, it is possible to fit a concentration-time curve based on a solution to Taylor's d iffu sio n equation fo r an impulse input c(x,t) = exp [-(x-ut>2] (5.1) /4nDt 4Dt where A is the channel cross-sectional area, M is the mass of dye injected, U is the mean travel time and D the dispersion coefficient. Transformation of this equation into a plot of t In (c/tj against t produces a parabola, and if Taylor's hypothesis is correct, the coefficients A (which give Q), D and U may be evaluated by a parabolic least squares fit. However, i t has been noted previously (Beer, 1979) that in order to obtain sens ible re su lts, each transformed data point needs to be weighted according to some power of its concentration. For this case the best result, as depicted in Figure 5.11, was obtained by a weighting to the sixth power which produced the following coefficients: IUE 8 . 5 FIGURE TUGGERANONG POND DYE EXPERIMENT 10/01/1980 r o r o c \ j < \ j - - * - o o SITE B n/OH) d Ld Id 3 O O CD NO I1 Vd 1N30N00 84 _o _o 120 160 200 240 280 320 360 400 TIME (HRS) 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. It may be noted that the mean cross-sectional area is in fair agreement with 2 the 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 sites 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 later 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 3.3 2 3.4 0.30 ro 4 4.3 0.28 8.4 5 8.3 0.28 8.2 6 10.0 0.29 7.8 7 11.9 0.23 9.0 8 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. It is also noteworthy that the discharge into the retention pond of 15 1/s on this day (27 June, 1979) does not appear representative of the mean discharge over the subsequent twenty week period. The results summar ised in Table 5.1 indicate that the effective 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 Rhoda mine WT were injected at the road bridge on Tuggeranong Creek below Site B. Four sampling sites were chosen. Site 1: On Tuggeranong Creek just above the confluence with Village Creek, a distance of 1170 m from the injection point. Site 2: The Gauging Station at Site D, a distance of 506 m from Site 1. Site 3: Lower Tuggeranong Creek at Site E, a distance of 1228 m from Site 2. Site 4: Just above the confluence (about 10 m upstream) with Murrumbidgee River below the last pool on Tuggeranong Creek, a distance of 253 m from Site 3. The results are summarised in Table 5.3. TABLE 5.3 Mean Hydrological Characteristics 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 0.23 2 2.70 0.41 2.23 0.21 3 2.78 0.40 4.68 0.17 4 2.30 0.48 6.47 0.14 There is evidence that Site 4 was affected by backflow from the Murrumbidgee River. The results from Sites 1, 2 and 3 display the character is tic rise, peak and decaying ta il of dye dispersion results under well-mixed conditions, whereas the behaviour observed at Site 4 (Figure 5.9) is quite different. The dye concentration rises and then virtually plateaus, as if it IUE 5.9 FIGURE *- — ^-00000 O J X C T ^ D C O O O M ( ^ DYE CONC. TUGGERANONG CK SITE O 1V31N30N00 3 AO 0 0 N 0 3 N 1 3 V NO I 1 n o / 1 87 O 14.0 15.0 16.0 17. HOURS WRT DYE INPUT TIME 88 was constrained within the area of the sampling site, presumably by the main stream flow. 5.5 Kambah Pool Two separate experiments were conducted in order to assess the mix ing and dispersive characteristics of Kambah Pool. These experiments took advantage of the large Murrumbidgee flow varia tio n s between 1978 and 1980: the earlier one was conducted prior to the formal commencement of the study under 'normal' flow conditions, whereas the second one took place under unusually low flow conditions. 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 its confluence w ith Tuggeranong Creek. Samples were collected at S ite 6, S ite H and at three traverse lines across Kambah Pool (Figure 4.1). Transect 2 - across Kambah Pool at the changing sheds near the sandy beach at the upstream end of the Pool; Transect 4 - downstream of A, approximately halfway down the length of 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-time curves up stream and downstream of Kambah Pool. Within the lim its of accuracy of the experiment, there appears to be no dye retention within the pool, and the 3 area under the curves implies a flow of 16 m /s at an average velocity through Kambah Pool of 0.06 m/s. We may note from the curve of Figure 5.11 the relatively rapid flushing of the Pool; in the space of 10 hours virtu a lly a ll of the dye had passed downstream of the pool. Figure 5.12 depicts the dye concentration-time curves at surface and depth within Kambah Pool. The main feature to note is that, at these flow conditions, the pool was very well mixed and could be considered as being ju s t another reach of the Murrumbidgee River, rather than a d is tin c t hydro- logical entity exhibiting lacustrine characteristics. A similar situation prevailed during the second dye experiment: Figure 5.13 depicts these results taken under particularly low flow conditions and the graphs show the high degree of transverse and lateral mixing. During the second experiment 200 grams of dye was injected at the IUE 5.10 FIGURE o N- DYE CONC. ABOVE KAMBAH POOL 2 4 / 1 0 / 7 8 O O C l/on l/on o o 14.0 17.0 20.0 23.0 26. HOURS WRT DYE INPUT TIME iue 5.11 Figure r o r o c N O v— j LOOLOOLOOLOO ■ DYE CONC. BELOW KAMBAH POOL 24/10/73 •••••.. / NO n l/0 1 V13N0 3AQ1V31N30N00 90 »-oo PO 15.0 19.0 23.0 27. O HOURS WRT DYE INPUT TIME 91 Figure 5.12(a) K AM B A H POOL DYE EXPERIMENT, 24.10 1978 SURFACE READINGS TR A N S E C T 6 M fl'14 3- 2 5 6 7 8 9 10 11 12 HOURS AFTER DYE INPUT Figure 5.12(b) KAMBAH POOL DYE EXPERIMENT, 24.10.1978 DEPTH READINGS 92 old pumping station 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 il of the samples taken at depth along traverse 6. The reason fo r this 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 this behaviour in mathematical terms, i t is standard practice to define two parameters - a velocity U and a disper sion co e fficie n t D - obtained from the measured f ir 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 it. Fischer et al.} (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 tail heavily, so that if the tail is not ignored the variance increases unreasonably and the dispersion co e fficie n t can become unconscionably large. Various methods to overcome this include: ( i) the routing procedure of Fischer (1968); (ii) Chatwin's (1971) transformation; ( iii) 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 characteristics; this is then used to compute the velocities and dispersion coefficients. When one has a sparse data set, or the points w ithin i t are not uniformly distrib ute d 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 intervals of time, the model results obtained by using the time-series analysis technique appear far superior to those obtained by other methods. In fact, 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 AM BA H POOL EXPERIMENT Dy* lnpu,*ri 12 13 14 15 16 17 1» MARCH 1980 FIGURE 5.13(b) KAMBAH POOL DYE EXPERIMENT 10.3.1980 DEPTH READINGS TRANSECT 2 - SITES 1,2*3 4 4 .5 *6 6 7 ,8 *9 94 suggest that it 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 of the CRES contribution to the Tuggeranong Study have been to collect data from regular monitoring and specially planned experiments, and to utilise these data for the construction of data-based and objective hydrological and water quality models of both the Tuggeranong Creek and the associated Murrumbidgee River system. In previous chapters we described the major activities as regards data collection, and in the present chapter we discuss how these data have been utilised in the development of the mathematical models. U nfortunately, th is model b u ild in g programme was not as compre hensive as that envisaged during the preliminary planning stages of the study. It was only possible to develop the following models, which constitute a sub-set of those originally planned: (1) A streamflow routing model between the Lobb's Hole and Mount MacDonald gauges in clu d in g , as a special case, a sm aller model between Pine Island and Mount MacDonald. (2) A r a in fa ll-ru n o ff model fo r Tuggeranong Creek re la tin g r a in fa ll to gauged flow at the Tuggeranong Gauge. (3) A conservative pollutant transport and dispersion model of the Tuggeranong Creek-Murrumbidgee River System between the Monaro Highway Crossing and downstream o f Kambah Pool, based on dye tracer experiment data.+ (4) A p a rtia l 'steady s ta te ' p o llu tio n model o f the same system as in (3) describing only the long term behaviour of the major water quality determinands, but with each determinand treated as a separate, non-interacting variable. Non-conservative simulations are possible given appropriate decay rate information. 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 non conservative 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 consider ably enhance the information on this part of the A.C.T. River System avail able 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-inter active 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 with in a stochastic setting, usually as the basis for generating initial hypo theses 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 'objective orientated' in the sense that the model form and type are chosen to satisfy the objectives of the study; i.e. the model is not normally intended to describe the system in great detail unless such detail is essential to achieving these objectives and a satis 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, p a rticu la rly if the data base is limited (as is usually the case in environmental systems analysis). And such a large model may well contain surplus, unvalidated con tent whose presence is d ifficult to justify if 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, when ever 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 sim ilar 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 deter m inistic form, although stochastic extensions such as those discussed in the above references can be incorporated fairly straight-forwardly if required. The river system is subdivided into N reaches, each described by the following ordinary differential equation f = i(I-Q) (6.1) where 3 Q = river flow (m /unit time) 3 I = inflow from upstream reach (m ) K = time constant, 'time of travel', or 'residence time' of reach. As K is a 'residence time' parameter, it is a function of flow and is defined in the normal manner, i.e . K V Q 98 where V is the changing volume of the reach. Taking note of 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 velocity, it is clear that K can be defined alternatively as K = ^ (6.2) Since U is not d ire c tly available for measurement, i t must be estimated from Q and a well known empirical relationship is used here of the form U = aQb (6.3) where the coefficients a and b can be evaluated either by theoretical analy sis based on the hydraulic characteristics of the system or by empirical methods based on the results of dye tracer experiments carried out under different 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 previ ous 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, addit ional mass flow is neither added nor lo s t between upstream and downstream sites at each reach. This becomes apparent if we consider 'steady state' or 'equilibrium ' 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 unity: i f mass is added by ra in fa l1-runoff processes between upstream and downstream location, then we would expect the SSG to be greater than unity; if water is lost by evaporation or to the groundwater, however, SSG would be less than unity. For s im p lic ity , such effects are introduced at 'node points' between reaches so that, 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 of the model including the number of reaches between gauging stations and confluence points is determined by a combin ation of time-series analysis and interactive simulation modelling. Time- series analysis can easily and quickly indicate the overall dynamic behaviour iue 6. Figure MODEL PREDICTION OF MOUNT MACDONALD FLOW 1 OOO —1 FROM PINE ISLAND FLOW USING 1971 DAILY RECORDS LxJ cc (S03Wn0) 99 MO d I CM 0 o 1 0 o NT 1 r*o —■ o ■ c I— o ; h L —O O F— o j I—■ co i o o i r o _ o ro ro C\J o C\J oo o o CM C\J T 's CM o 00 o TIME (DAYS) 100 between upstream and downstream gauge points and can provide an initial idea of the reach structure appropriate to describing such behaviour. Interactive simulation modelling then allows for the modification of this initial model to allow for better explanation of the data and more appropriate fine struc ture, usually in relation to the objectives of the model building exercise. Typical of the results obtained in the initial time-series analysis are those given in Figure 6.1 which shows the output xk of a time-series model for daily flow variations between Pine Island and Mount MacDonald for daily data over all of 1971. This model is in discrete-time terms and takes *f* the form of a static, or steady state relationship, xk = 1.1819uk (i) (6.4) yk = \ + 5k (11) here xk denotes the modelled flow at the downstream or 'output', Mount Mac Donald gauge; while uk is the upstream of 'input' flow at Pine Island. The measured (i.e. gauged) output flow at Mount MacDonald is represented by yk, and £k denotes the stochastic or 'noise' effects not explained by the deter ministic relationship between xk and uk in (6.4)(ii). It is clear from Figure 6.1 that the model adequately describes the data: in fact, the 2 coefficient of determination Ry for the model, i.e. ^ 2 2 R T is 0.9825; in other words, the percentage of the variance of yk not explain ed by the model is only 1.75%. This unexplained stochastic effect is em bodied in the stochastic variable £k and further time-series analysis (see e.g. Young and Jakeman, 1979) could yield an autoregressive, moving average (ARMA) model for £k which would then allow for statistical forecasting of yk on a recursive basis. However, in the present context, we are concerned not with forecasting, as such, but with the relationship between xk and uk> since this represents the major characteristies of the river system between Pine Island and Mount MacDonald which need to be represented by the flow routing model . This arises because the dynamic behaviour all takes place within the sampling period of one day. 101 ■g I 3 u. £ > a: 0) o> 1 3 i o g a) < a; •I—I i 102 Note that the model 6.4 is a purely static or equilibrium model, with no apparent dynamics. This arises because all dynamic activity 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 infor mation on this short term behaviour and could be used for time-series analy sis, but this was not carried out in the present exercise since it was felt 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' determ inistic model on the basis of upstream gauged flow at Pine Island alone. And it implies that 0.18 of this flow is contributed by rainfall-runoff processes occurring between the two gauging stations including, most import antly, that arising from the Tuggeranong Creek system.+ A schematic diagram of the daily flow routing model is given in Figure 6.2, where it can be seen that the 20.3 km length of river is decom posed into eight reaches, the first of 2.8 km and the rest of 2.5 km, with Tuggeranong Creek entering after the first 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 tributaries 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 avail able 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 ob tained from the Mount MacDonald gauge for the year 1977. The first model also reproduces the flow behaviour at Mount MacDonald quite well and it 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. Figire 6.4 GAUGING STATI0N D D v CsJ I CD CvJ CD CD ID CD CD CD ' •— O CD 103 m — _ CD - > Q GZ 104 6.2 Rainfall-Flow Model fo r Tuggeranong Creek When modelling the rainfall/runoff 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 differ considerably. The rural areas consist mainly of non-irrigated pas tures and woodlands. Rainfall in these areas may be absorbed by the ground, if dry,and produce no runoff. If the ground is saturated, however, runoff w ill occur slowly with water filte r in g through vegetation and passing down natural water courses. By contrast urban areas consist, in part, of imperm eable surfaces such as roads, house roofs and compacted s o il. Rainfall on these surfaces w ill pass quickly into storm-water drains or concrete culverts, and w ill reach the creek quite rapidly. Urban areas consist also of gardens, playing fie ld s and the lik e , which are frequently irrig a te d . A storm on irrigated soil w ill be more likely to produce saturated conditions than is the case for rural soil. When the water drains off, it soon reaches a drain, and runoff is, therefore, quite rapid. The purpose of this section is to develop a preliminary uethodology for evaluating separately the urban and rural runoff. The methodclogy is then applied to ra in fa l1/ru n o ff measurements fo r the Tuggeranong area for June to December, 1977. Rural soil in the Tuggeranong area may be characterised as an upper layer of permeable topsoil, covering a relatively impermeable subsoil. Run off characteristics are largely unaffected by the condition of the subsoil, and depend mainly on the moisture content of the top layer of soil 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 little 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 e n tire ly (Talsma 1976 and Costin 1980). In other words, based on studies in similar areas, it would appear that a constant rainfall of 70 mm/ hour could fa ll in the Tuggeranong area fo r 50 minutes with minimal re s u lt ant runoff. Once the soil is wet, it can start to lose water by evaporation and by plant transpiration. With well vegetated soil, most of the moisture loss is through plant transpiration. Dunin (CSIR0, Division of Plant Industry) has performed some measurements on improved pasture at Krawarree on the upper Shoalhaven catchment area. Quoting soil moisture as cc. of water per 105 cc. of soil, 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 start to wilt, and their trans piration 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 soil, and very little 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 firstly 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 it was felt 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 start of the period so that the 'worst' or most moist case could be examined. Using the model, soil moist ure 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). It can be seen that in both cases the soil moisture never exceeded saturation (.25) and therefore it seems highly likely that no rural runoff at all occurred during this period. The reader should note here that this modelling is purely specu lative and reported here to give some idea of the possible soil moisture be haviour of the system. Future work should carry out this analysis on a stochastic basis, with parameters specified as probability distributions Figure 6.5(a) TU&GERRN0NG flRER S0IL MOISTURE JUN T0 DEC 1977 (200011 DEPTH) 1BI0W 1105 106 a 12 HRLY ORTH Figure 6.5(b) TUGGERHN0NG AREA S0IL H0ISTURE JUN T0 DEC 1977 (300MN DEPTH) ll l.U-1 t tt 1 1I t 1 U 1 - U . l 1 l l i l - U - S0 ~110S 1S10W 107 i l l 1.11-1 ii-l 1.11-1 l l i o - co 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 characteristics i t is necessary to relate rainfall on the catchment to flow measured at the Tuggeranong Creek gauging station. Originally we were led to believe that there were gauge records available at two points on the Creek: one at the dam (retention pond) site and one downstream of the Village Creek confluence. Such gauging would have allowed for quite detailed modelling of the catchment, with time-series rainfal 1-runoff models supple mented by flow routing between gauges, including explicit identification of the Village Creek contribution. In the event, the somewhat misnamed 'dam- site' gauge did not, in fact, exist prior to retention pond construction and d iffic u ltie s in interpreting the data obtained since its establishment have meant that they could not be used in model development. In this situation, there are two alternative approaches to the mod elling problem: first a simple time-series representation of rainfall-runoff at the Tuggeranong Creek gauge can yield information on the aggregate catch ment dynamics; second, some form of dynamic simulation model based on both catchment data and the limited rainfall-flow records can be constructed to allow for greater descriptive detail than is possible from the time-series model. The rainfall-runoff model is obtained by direct 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 of a series connection of two sub-models: the fir s t is a non-linear soil moisture - evapotranspiration sub-model which yields an 'effective' rainfall input to the second sub-model, which is simply a linear transfer function model of the type used in the previous section for stream- flow time-series analysis. The use of the CAPTAIN package for this kind of analysis has been discussed by Young (1974), Whitehead and Young (1975) and Whitehead et al.y (1979b). Consequently we w ill re s tric t the present description to the main aspects of the model building. The rainfall r^ is first processed by a 'soil moisture' filte r of the form ( 6 . 6 ) c-1 + f Figure 6.6 _J LU O Li_ O or§ o < Cs Q no where is a measure of soil moisture and T is the dominant time-constant associated with the soil wetting and drying characteristics. The 'effective' ra in fa ll u^ is then obtained as the product *k u (6.7) k ^ sk^max where (s .)mav is the maximum value of s. over the data record and ß is a selected power law, in the present case unity. The longer term (seasonal) evapotranspiration modification to the rainfall measure is usually applied to Uj^ obtained from (6.7). In the present case, however, certain d iffic u ltie s were encountered with the interpretation of the time-series in the long term and so, as we shall see, satisfactory evapotranspiration effects proved ex tremely d if f ic u lt to id e n tify from the time-series data. The evaluation of T in (6.6) is carried out by resort to recursive estimation. The transfer function model in Figure 6.6 is estimated firs t using the unmodified rk series as a direct input (i.e. by-passing completely the nonlinear block A): this yields recursive estimates of the coefficients in the B(z~1) polynomial with pronounced short term temporal variation (non- stationarity) over the data interval. Introduction of the soil moisture f il te r tends to remove this temporal variation and the T value is selected so that the coefficients are as close to stationarity (time-invariance) as poss ib le in the short term. Longer term v a ria b ility may s t i l l be present, how ever, because this w ill be related to the longer term effects - such as evapotranspiration. In the present case, we found no d iffic u lty in modelling the short term behaviour and identifying a suitable T value. Figures 6.7(a) and 6.8(a) show the model fit obtained over two periods of 125hours; the firs t start ing 0000 hours on 22nd February, 1977 and the second at 1500 hours on 31st August, 1977. In each case, the soil moisture time constant T was set at 5 hours (the sampling interval was 0.5 hours so this represents 10 sampling in te rv a ls ). Also the data were analysed in both cases with base flow effects present (this is perfectly allowable when using the CAPTAIN package and represents a sig n ifica n t advantage of the program). As a resu lt, the model f i t is somewhat distorted and Figures 6.7(b) and 6.8(b) show the improved model f i t when base flow effects have been added to the model using an estimate obtained by frequency selective smoothing of the data. We now see i Figure 6 TUGGERANONG CREEK FLOW FORECAST FROM OOOO HRS 22/02/77 NO BASE FLOW CORRECTION J (a) CL O co o co z co UJ o o o S3n) M01J (S03Wn0) 111 l 100 125 150 175 200 225 250 TIME (0.5 HOURS) iue . (b)Figure 6.7 TUGGERANONG CREEK D C O O O O O D C ^ M C O r < I ro 100 125 150 175 200 225 250 TIME (0.5 HOURS) i iue . (a) 6.8 Figure TUGGERANONG CREEK O FLOW FORECAST FROM 1500 HRS 3 1 / 0 8 / 7 7 NO BASE FLOW CORRECTION oo CL. O u COLul i - l CE o o o cno D M O CM CD d l O M ) O l P N G C S C 113 CM I I N_ m o m cm o 100 125 150 175 200 225 250 TIME (0.5 HOURS) TUGGERANONG CREEK (b) 6.8 Figure FLOW FORECAST FROM 1500 HRS 31/08/77 BASE +FLOW INCORPORATED * O O OD O Q_ O SBn) M01J (SOBHnO) 114 _o 100 125 150 175 200 225 250 TIME (0.5 HOURS) 115 that the model is adequately modelling the recession part of the response in both cases. The transfer functions of the two models to generate Figures 6.7 and 6.8 are as follows: (i) 22/02/77: 1.21 + 0.98z' 1 - 0.69z •1 Uk + 5k ( 6 . 8) 0.36 + 1.27z“1 .. (ii) 31/08/77: yk = ------1 - 0.79z-1 k + ?k and their impulse response characteristics are shown in Figure 6.9. This im pulse response can be interpreted directly in hydrological terms as the unit hydrograph response of the catchment to a unit impulse of effective rainfall. 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) 1.21 + 0.98 _ (i) SSG = 1 - 0.69 7.0 (ii) 0.36 + 1.27 _ o SSG 1 = 0.79 7,8 In other words, for the 22nd February data, 1 mm of effective rainfall yield ed 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 sug gests that the model description is adequate. This is confirmed in Figures 6.10(a) and (b) which show the model fit to the 31st August data using the 22nd February model, with and without base flow: this can be considered as an initial validation stage in the analysis and the fit is certainly good enough to conclude that the short term models are entirely adequate. Unfortunately these satisfactory short term results are not repro duced by long term analysis. Initial 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) fit to the observed gauge data. iue 6.9 Figure \ * * » oooo o o o »— *— *—c\J TUGGERANONG CREEK IMPULSE RESPONSES FOR 22/02/77 AND 31/08/77 T I ME PERIODS (so3nno) 116 mo i j o _ — ro — CD— \J _C O L _ 0 0 _ O TI ME (0.5 HOURS) iue 6.10(a) Figure TUGGERANONG CREEK FLOW FORECAST FROM 1500 HRS 31/08/77 WITH NO BASE FLOW CORRECTION USING MODEL FOR 22/02/77 o_ o to D O QD O O 2 S3D) MOld (S03ND0) 117 100 125 150 175 200 225 250 TIME (0.5 HOURS) TUGGERANONG CREEK Figure 6.10(b) FLOW FORECAST FROM 1500 HRS 31/08/77 WITH BASE FLOW INCORPORATED USING MODEL FOR 22/ 02/77 J 1 0 M ) O n W G C S C 118 100 125 150 175 200 225 250 TIME (0.5 HOURS) 119 Figure 6.11 shows the plots of daily ra in fa ll and flow fo r the whole of 1977. A typical effort at modelling is shown in Figure 6.12 where the daily model output over the whole of 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 error, making the model virtually useless as a predictive to o l. The problem appears to be one of data deficiency. F irs t i t seems that, in the long term, no one rain gauge is sufficient 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 significantly affect this descriptive ability: in other words, it seems impossible to adequately explain the flow variations indicat ed by the Tuggeranong gauge in relation to the measured ra in fa ll in the area. Secondly, the gauge data it s e lf may well be inadequate and this could ex plain the lack of long term correlation between the magnitude of the measur ed ra in fa ll and resultant flow. Indeed, we have observed during regular water quality monitoring that the pipe leading from the Creek to the gauging hut is quite often partially blocked with sand and we believe that this could, at times, lead to erroneous flow measures. This is ce rtainly consist ent with our interpretation of the data, and a re-examination of the 1977 gauge data indicates that there was indeed a malfunction which prevented any 3 -1 flows of greater than 18 m s being recorded. We feel that there is no short term solution to this problem. We can only recommend that some improvement of the Tuggeranong Creek gauging station is carried out and that an investigation of the adequacy of rainfall monitoring in the area is undertaken subsequent to th is (since i t may be that more accurate gauging could, in it s e lf , s u ffic ie n tly improve the situation). 6.3 A Conservative Pollutant Dispersion and Transportation Model During the study CRES has devoted considerable e ffo rt to the plann ing 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 this section, we w ill show how these results can be used: firs t, to develop a model for transportation and dispersion of conservative pollutants iue 6.11(a) Figure 56.0-4 DAILY TUGGERANONG RAINFALL 1977 00 O o o (AIAI) 11VJN I V8 ro cm 120 c ^r —i r i— i— \ j CD o oo o O o O 00 O 120 160 200 240 280 320 360 400 TIME (DAYS) Figure 6.11(b) DAILY TUGGERANONG FLOW 1977 (SOdHPlO) MO Id 121 _o _o 120 160 200 240 280 320 360 400 TIME (DAYS) iue 6.12 Figure TUGGERANONG CREEK C \ ] C \ J *— - 0 0 «•«••*** FLOW FORECAST 1977 Q_ o er O Z CO CO LÜ Z < o o o O CD , - I SBO) Id O M (SOBWOO) 122 I I I I I = = C\JC\I _o _o 120 160 200 240 280 320 360 400 TIME (DAYS) 123 in the system under the flow conditions prevailing at the time of the exer cises; 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 in itia l extrapolation of the basic model using physically reasonable principles. As such, it will need to be vali dated by later dye tracer exercises if it is to be entirely adequate in a predictive sense. At present, however, we feel that it 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 com pare 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 sampl ing interval of 2 minutes, takes the form x7k 0,64 x7, k-1 + °430 x6, k-7 (6.9) 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 in put term x^ ^ 7 indicates that the effect of changes in dye concentration at Site 6 is not observed at Site 7 until after a pure time (transportation) delay of 7 sampling intervals; in this case 14 minutes. It can be shown (e.g. Young 1980; Takahashi et al., 1970) that the discrete-time (difference equation or sampled data) model (6.9) is approximately equivalent to a con tinuous-time (differential equation) model of the form, dx^(t) (6 .10) where here i = 7, 6 = 14 mins, bQ = 0.83 and = 4.5. In dynamic systems terms (6.10) is a first 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, it indicates that an impulse (gulp) input of dye at Site 6 will not be detectable at Site 7 until 14 Figure CONCRETE CHANNEL 4 0 .0 — SITE 6 TO SITE 7 .13 ro C\J O co J CO UJ Q_ O z -c -< > O O O CQ z CO C C < Z -< + + + — t— UJ (— UJ QL cn s. «C n/om C\J o ^r NO I 1Vd1N30N00 CD o 124 o oo o o 0 CD 00 o o O TIME (2 MI NS) 125 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 expon ential 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 discrete time model (6.9) impulse response, as the reader may verify by straight forward 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 either 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, it is unlikely that the dye is itself non-conservative. Rather the nature of the channel and the Isabella Plains through which it 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 con fluence and below Kambah Pool. Figure 6.15 shows the model fit 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 little indication that the flow variations occurring over the experimental period had any significant effect on these dynamic charac teristics (see Chapter 5). Figure 6.16 supplies the model fit over the lower reaches of Tugger anong Creek prior to the final reach at the Murrumbidgee River confluence: note the quite rapid rise (TD = 160 mins; TC = 44 mins) and the fact that the model was of second order. iue 6.14 Figure Concentrati Q 126 « Time, minutes 127 Figure 6.15 CC UJ UJ o o. _ 0 0 UJ CO QQ O O O _C\J _o CO.25 WEEKS) TIME _ 0 0 _ < \ J CD LO ro cm o n/om NO I 1 VyiN30N00 TUGGERANONG CREEK Figure 6.16 O O L O O L O O L O O l C\J CM SITE B TO MURRUMBIDGEE RIVER CONFLUENCE LÜ c a o_ o O O O CD CO z *— CO n/on) NO I VdlN30N03 1 128 o o 0 1 _o __o 80 100 120 140 160 180 200 TIME (2 M I NS) I iue 6.17 Figure LU OC < o CL o < OQ «< X < IS O M M- CM o r CONSTANT PARAMETER 1o) NO 1Vd1N30I N00 (1/on) cm 129 0 o 00 o o 00 0 1 CD _ o _ o O O _ _o _o _o _ o _ o 00 N_ LO CD CM xr TIME (1 0 M I NS) 130 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 at time k and y^ is the downstream output. A second order model of this form can be broken up into two first order models: - y 1) Wk u (1 - ajZ-1) k-D (ß. B.z'1) *k (1 - aj— z TT A) Wk-A + ek so that so bo - (eo bl + el ho» z' ‘ + el bl z‘2 n -1 -2 V d-a + ?k 1 - (a^ + a^) Z + a^ z Factorisation of the observed model indicates that two identical first order models in series are suitable, within the errors on the parameter estimates, each with TD = 80 minutes and TC = 22 minutes. This illustrates one advan tage of the present modelling approach: a p rio ri specification of reach lengths is not essential; if 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 tracer experiments (see Jakeman and Young, 1980). Finally Figure 6.17 shows the model fit obtained over the Kambah Pool (i.e. between the 'upstream' and 'downstream' Kambah Pool sampling stations). 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 first 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 = 2x 80 + 2x 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 equal to the actual volume and Q is the flow rate, then an estimate of V can be obtained from this expression by substituting for the flow rate Q as obtained from the dye tracer experimental analysis (Chapter 5). In this case Q = 16.0 m3 s - 1 so an estimate V of V is obtained as V = 4.26 x 16 x 3600 i.e. V = 245,700 m3 It is now possible to compute approximate T values at other flow rates using this 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 - 1 given in Table 6.1 for the flow values of 16 m s , and 0.3 m s respec tively. 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 4.26 0.3 227.6 0.3 + 2.153 27.8 0.3 + 3.33 18.8 16 + 2.153 3.75 16 + 3.33 3.53 2.153 31.7 3.33 20.4 The dynamic model of the entire system is shown in block diagram form in Figure 6.18. We see that it is composed of 23 reaches each described The validity of this extrapolation is difficult to check using the present data, but it seems a reasonable assumption. MURRUMBIDGEE RIVE Figure 6.18 132 133 by a first 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 at the time of the experiment. Nominally, however, it does not allow for the prediction of such character istics 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 stirred 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 dx.(t) i.e. = VE dt Qxi_1(t) Qx.(t)1 where Q is the flow rate and is the 'effective' volume, i.e. the volume of the reach 'effective' 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 it is well known (e.g. Marshall, 1980) that the overall dynamic equation can be approxi mated by series connection of a differential equation of low order (in com parison with the number of reaches) and a pure (transportation) time delay. In the first 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 'effective' volume. Note that, in this situation, the effective volume is appropriate to the reduced order description; which will, of course, be different from V^. It 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 conser vation). Furthermore, we can argue that if 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 result, we can calibrate the model (6.12) by reference to the time-series model of the tracer data. Know ing the reach length L the flow Q and velocity U measured at the time of the experiments and u tilis in g the estimated values of a-^ and 6, we can f ir s t estimate the effective volume Ve from the equation Ve = axQ (6.13) If it is then assumed that the usual empirical relationship (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 for any flow Q from <5 = jj - (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 results. Thus, given a time- series of changing flow values we can update the estimates and 6 from (6.14) and (6.15) for each reach, and solve the resulting 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 this can result in lack of mass con- •4* servation in the solution. As a simple solution to this problem, we have + Solutions to this problem involving Pade type representations (multiple 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 variations over this run. Whilst this implies some inaccuracy in dynamic terms, it 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 it is possible to introduce transient effects resulting from flow variations by defining the input concentration time-series so that it is associated with the flow event: for example, it should be possible to estimate the relation ship 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, it is possible to predict the perturbations in concentration resulting from the injection of a conservative pollutant any where 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 first reach of the sector involved. In reading these figures, it 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. Figure 6.19 CONCRETE CHANNEL N T 0 r i U y i N 3 3 N ' 0 3 136 120 160 200 240 280 320 MINUTES iue 6.20 Figure CONCENTRATION CONCENTRATION CONCENTRATION 8000 00 60 200 20 400 80 500 64000 56000 48000 40000 32000 24000 16000 8000 00 60 200 20 400 80 500 57000 56000 48000 40000 32000 24000 16000 8000 60 200 20 400 80 500 64000 56000 48000 40000 32000 24000 16000 IE 12 SITE SITE IE 13 SITE O CONSERVATIVE NON CONSERVATIVE MINUTES MINUTES MINUTES 1 1 137 l ~ ~ ------TUGG CK BELOW POND Figure 6.21 NO I lbiyiN33N03 138 100 200 300 400 500 600 700 800 MINUTES Figure 6.22 ' B I D G E E R I V E R N0UdyiN33N03 139 (3 MINUTES iue 6.23Figure BIDGEE RIVER (FLOOD) NO 11U31.N33N03 140 100 200 300 400 500 600 700 800 MINUTES 141 First, while the model w ill be extremely accurate for flow conditions pertaining at the time of the 'calibration' dye experiments, its accuracy has not been assessed at other flow conditions where the physically motivated extrapolations (6.14) and (6.15) come into effect. We stress, therefore, that further dye tracer studies at different flow conditions w ill be required both to validate the extrapolations and to reassess the value of the a and b coefficients in the ve locity-flow relationship 6.3 fo r each of the major model sectors. Second, as mentioned in Chapter 3, the behaviour of the retention pond under different flow conditions is rather d ifficu lt to assess. On the basis of the dye experiments in the pond, which covered a range of low to medium flow conditions, we have con strained 6 and a^ in (6.14) and (6.15) to be constant at the calibrated values of 0.25 weeks and 3.5 weeks, respectively, up to a flow of 0.16 cumecs and only use the extrapolative predic tion of a^ for flows greater than this. Further evaluation of this assumption is also required before the v a lid ity of the retention pond model at higher flows can be assessed. Finally, in order to permit speculative simulation model runs with non-conservative pollutants, we have programmed each reach equation in the form dx.U ) b —dt = - (4-+ k1)xi ( t) + ( ^ + k2)xi _1(t-fi) (6.17) al al with k^ and k2 to be specified by the user. For ^ = k2 = 0 the model represents the basic conservative response; if k^ is set appropriate to some decay rate (time "*) for a particular pollutant (with k2 = 0), then the model w ill provide an estimate of the loss of that pollutant down the system: with k2 other than zero, the user can introduce other 'non conservative' factors (such as dilution) in a simple manner. We would stress, however, that unless the estimates of k^ and k2 have been obtained in some rigorous manner in relation to the short term behaviour of pollutants in this p a rticula 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 reten tion 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 indi cates 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 it 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 non conservative 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 sam pling instant and is indicative of noise (uncertainty) in the relation ships. 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 'expon ential' type decay of determinand concentration down the system. This be comes clear if 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 first (i-5) reach to 0.17 at the 6th (ith) reach. Nominally, it 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 it is essential to account for the combined effect of the two streams in some manner. Utilising the simple flow apportionment calcu lation 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 concentration at the gauge, x.D ^ the concentration below the retention 1 pond, and x^_-^ V the concentration in Village Creek. We see therefore, that 145 Figure 6.25 REACH REACH NUMBER O z o o 146 D + ^ x V ] (6.19) xik = b 1-1,k Qg i -1, k j + qG?k We computed the sum in parentheses from the observed concentrations at the two upstream stations with the ratios Op/QG = Qy/QG = 0-68, calculated from the conductivity relationship 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 for the other parameters. Typical examples of the model f it s obtained are shown in Figures 6.26 and 6.27: Figure 6.26 shows total phosphorus at the Tuggeranong gauging station obtained from the model (6.19); while Figure 6.27 shows total nitrogen results at the same site. It is clear that total nitrogen is predicted well in this manner but total phosphorus is not predicted quite so well. These results are typical for most reaches. In a number of cases, the estimate b is found to be greater than unity, which indicates tha t, on the average (as indicated by the fo r t nightly, and 14 daily, 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 for tota l phosphorus and b = 1.09 fo r tota l filte 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 if fic u lt to explain these phenomena with the lim ited data available since the data are ambiguous and a number of d iffe re n t explan ations 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 ffic ie n tly in the study) there is a net accretion of material in the pool and this material is then lo st slowly during the subsequent period of lower and steadier flows. Alternatively, since in this case the estimated net export is quite small, i t could be that b is biased upwards a small amount because the fo rtn ig h tly sampling interval is clearly inappropriate fo r the flow dynamics of Australian rivers lik e the Murrumbidgee. iue 6.26 Figure TUGGERANONG STEADY STATE MODEL o o CM B+ C TO D « PHOSPHORUS GO o Z I I I + C\J O O C O Ld QL L L < " . s l I n/on) NO I 1 N30N00 Vd 1 O 'sT O 00 O 147 0 1 O 00 I O TIME (FORTNIGHTLY) TUGGERANONG STEADY STATE MODEL Figure 6.27 4 0 0 0 - B+C T O D ■ N ! TROGEN 148 TI ME (FORTNIGHTLY) 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 identifiability 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 Value Degree of Fit I to A 0.7799 ± 0.0822 Poor A to B 0.8285 ± 0.0817 Good (RT 0.83) B to D 0.8061 ± 0.0621 Good 0.5234)