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Temporal variations in water quality of farm dams: impacts of land use and water sources
Agricultural Water Management 70 (2004) 151–175
Temporal variations in water quality of farm dams: impacts of land use and water sources M.A. Brainwood, S. Burgin, B. Maheshwari∗ Centre for Integrated Catchment Management, University of Western Sydney, Hawkesbury Campus, Locked Bag 1797, Penrith South DC, NSW 1797, Australia Accepted 12 March 2004
Abstract Three farm dams near Raglan, New South Wales (Australia), were compared to investigate diurnal and seasonal patterns in water quality over a period of 1 year. The source of water in one dam was predominantly influenced by groundwater, another showed links with both groundwater and agricultural runoff, and the third collected runoff from urban and agricultural lands with no apparent groundwater input. Patterns in chemical profiles were compared to identify level of similarity in macro-trends of water quality. Within dams, micro-trends were contrasted with known chemical relationships in dam waters to explore links between land use and water quality. The three dams were shown to have quite distinct patterns of water chemistry. Within dams, trends were strongly linked with the differing water sources, evidenced by chemical patterns that matched those expected from the different dominant ion transfer pathways associated with surface water and groundwater flow processes. Phosphates were primarily linked with groundwater fluctuations, nitrogen as ammonium ions with urban runoff, and nitrates with storm events resulting in runoff from pastures. We conclude that, for farm dams, the combination of land use and preferential flow paths gives a more complete description of water quality impacts than land use alone. © 2004 Published by Elsevier B.V. Keywords: Farm dams; Water quality; Land use; Agricultural and urban runoff
1. Introduction Agriculture has both indirect and direct effects on the quality of surface and ground waters and is one of the key activities causing water quality degradation in many parts of Australia. The quality is affected by both macro- and micro-scale factors. Macro-scale ∗
Corresponding author. Tel.: +61-245-701-235; fax: +61-245-701-750. E-mail addresses: [email protected] (S. Burgin), [email protected] (B. Maheshwari). 0378-3774/$ – see front matter © 2004 Published by Elsevier B.V. doi:10.1016/j.agwat.2004.03.006
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factors include climate, landscape and parent material of the area, while micro-scale factors include land use and management at field or farm level. Past studies have indicated that there is a strong relationship between land use and quality of both surface and ground water in the area (Zalidis et al., 2002; Tong and Chen, 2002). This means that changes in land use and management practices can have considerable impact on water quality parameters. With the increased public concerns about water quality degradation, several water quality monitoring programs have been initiated in Australia in the recent years at local, state and national levels. A range of groups including water authorities, local government bodies, universities, communities, independent consultants and schools run the programs. The intensity and continuity of these programs vary considerably since data collection is often extremely time consuming and costly, especially if the monitoring is to be carried out over a period of many years. To make the monitoring more effective, a national framework has been developed for collecting and reporting of water quality data so that data collected from different locations can be compared and contrasted for developing an overall picture of the water quality situation within a region (ANZECC, 2000). Water quality investigations are carried out to provide information on the health of water bodies and for developing strategies that help in better management of catchment and water resources. In particular, they may assist in preparing an impact assessment, forecasting ‘what if’ scenarios and assessing the state of the ambient water environment and trends. The investigations may be a single study to tackle a particular water quality related issue, or they may be an ongoing program to monitor water quality and understand long-term impacts of land uses and other activities in the catchment. However, effective water quality monitoring requires the systematic collection of a range of water quality parameters within a carefully planned experimental design. Management of on-farm water supplies in Australia has always been an important issue. Increasing demands on water resources within catchments has led to the implementation of legislation that regulates the availability of water to individual users (Murray Darling Basin Ministerial Council, 2001). With the aim to reduce the amount of surface waters harvested by these dams in over-taxed catchments, one of the targets has been the erstwhile ubiquitous farm dam. A recent criticism of water allocation in Australia is the tendency for single usage of water (Ingram et al., 2000). The potential for contamination of dam water by sediment runoff or leaching of salts from the aquifer that make it unsuitable for stock or irrigation, iterates the need for an increased understanding of their chemical hydrology. The main objective of this study was to explore physical and chemical processes through a case study of three farm dams over diurnal and seasonal time scales and relate resulting chemical profiles to catchment land use.
2. Factors affecting water quality The distribution and cycling of chemical compounds in water bodies, such as farm dams, are closely related to water movement in the landscape and are influenced by processes in the hydrological and biological cycles. In Australia differences in the chemical composition of inland freshwaters occur across the vast extent of geographic and climatic conditions
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present. Significant quantities of these freshwaters are held in a large (>500,000) number of small, man-made reservoirs known colloquially as farm dams (Lewis, 2002). These dams provide drinking water for stock or irrigation waters for crops, and on many farm properties, hold the only fresh water directly available. Despite this, the impact of adjacent land usage on the quality of this water has remained largely unexplored. The major ionic components present in natural waters are generally considered to come from two main sources. One of these is atmospheric, with ions dissolving in rainwater as it forms, and the other is a result of the weathering of soils and base rocks in the catchment. In coastal parts of Australia saline groundwater of marine origin impacts on surface waters, as do fluctuations in water tables resulting in shallow water tables that can increase groundwater salinity in inland regions (Taniguchi, 1997). Particularly in shallow lakes and reservoirs, evaporation or precipitation of less-soluble salts can change the chemical composition of the water body. While considerable attention has been given to sediment sources and solute transport pathways in rural catchments (e.g. Croke et al., 1999; Gruszowski et al., 2003), little is known about the relative contribution of rain and the catchment geology to the chemical composition of farm dam waters. In farm dams the ionic composition is expected to closely reflect the composition of the inflowing waters. The two factors that most commonly lead to changes in the concentration and ionic composition of dam waters are evapo-concentration and the intrusion of groundwater. The final dam water quality is the result of a complex interaction between the composition of rainwater, weathering processes in the catchment, and groundwater inputs. For example, peaks in the introduction of dissolved and particulate materials can occur during storm event flushing from the catchment. Recently a number of studies have investigated land use impacts on water bodies, both in terms of macroinvertebrates and the algal communities supported and water quality parameters. These studies have been centred predominantly on rivers and creeks, with the main considerations being directed towards the presence/absence and density of riparian vegetation (e.g. Sponseller et al., 2001; Ometo et al., 2000; Stevens and Cummins, 1999). Variations in the density of riparian vegetation were observed to be affected by management practices that ranged from cropping, grazing, rotational cropping/grazing, through to undisturbed woodland vegetation (Weigel et al., 2000). Disturbance of riparian vegetation was seen to be a major factor resulting in increased sedimentation of rivers (Steiger et al., 2003). Sponseller et al. (2001) observed that stream water chemistry was related to catchment level characteristics, while water temperature and substrate composition were more closely related to riparian land cover patterns. Similarly macroinvertebrates were noted to respond more directly to larger scale watershed influences, with only minor variations reflecting localised land use (Weigel et al., 2000). Conversely, Stevens and Cummins (1999) found a significant relationship between stream chemistry and both land use and riparian vegetation. Despite the differences, there is general agreement that catchment land use and riparian vegetation affect aspects of water quality, but it is not clear at what hierarchical level these factors primarily impact. Ometo et al. (2000) explored the differential impacts of temperate and tropical climates and concurrent patterns of agriculture and land management practices and identified high levels of correlation for some chemical parameters, but not for others. Patterns of fluvial dynamics within stream systems create continua of environmental conditions that have inherently different characteristics to those found in drainage basins.
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While the effects of these conditions can be dispersed and diluted through a riverine system (Marchant and Hehir, 2002), they are more often compounded through continuing retention in water bodies such as farm dams. Perhaps because of this the relationship between land use and water chemistry in a lentic system could be expected to be more significant than for rivers and creeks. Groundwater seepage below the surface of the reservoir is commonly a major source of water. There is often a complex seepage hydrology with groundwater flow alternating between upwelling and downwelling in response to levels of precipitation and evapotranspiration (Wetzel, 1999). Modelling of groundwater flow dynamics suggests that up to 50% of input in many natural lakes is from groundwater, and up to 50% of water loss is by seepage (Lampert and Sommers, 1997). However, measurement of evaporation and evapo-transpiration is expensive and measurement of subsurface inputs and losses of water is difficult and demanding. A historical assessment of prairie lakes in Canada revealed the significance of the impacts of land use practices, and suggested regulation of cropping areas, livestock biomass, and urban nitrogenous wastes as a water quality management strategy (Hall et al., 1999). Ali et al. (2002) compared adjacent natural and man-made lakes in central Florida and observed how the variability in lake-specific combinations of water, sediment and algal variables was dependent upon season. This spatial and temporal variability of environmental conditions was reflected, directly or indirectly, in the distribution of organisms. Patterns of species distribution and abundance are frequently used to characterise ecosystem health. These patterns are often used as surrogate measures of fundamental ecological processes that contribute to essential life support systems. While environmental disturbance may affect these patterns, this does not prove the link between pattern and process (Bunn et al., 1999). Chemical profiling of farm dams, and consequent comparison to lake scenarios, has in the past been mainly limited to seasonal spot sampling (e.g. Timms, 1980), or more recently has been undertaken to provide a physicochemical background for a biodiversity survey (e.g. Hazell et al., 2001). This neglects the possibility that different chemical processes operate at different time scales in standing waters (Alvarez-Cobelas et al., 2002), resulting in a range of differential interactions that produce cycles and trends over diurnal, seasonal, annual and decadal scales. Contemporary philosophies relating to experimental design emphasise the need to design experiments that test a specific hypothesis, rather than on insights gained through inductive reasoning, based on large amounts of field data. On the largest scale, manipulation of ecosystems represents the least controlled of this type of ecological experiment. However, it has been proposed that small lakes and ponds are best suited because they form isolated systems (Lampert and Sommers, 1997).
3. Site description The three dams selected for this study were located at Raglan (33◦ 25 S, 149◦ 39 E) near Bathurst in the Central Tablelands of New South Wales, Australia (Fig. 1). The dams were located in close proximity and in the same drainage line to eliminate distinct variations in
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Fig. 1. Field site at Raglan, New South Wales, with detail of the three dams and their immediate locality.
groundwater, catchment geology and dam substrate, and weather related variables including rainwater composition, and volume and evaporation rates. The area was located approximately 700 m above sea level and had a warm temperate climate, with mean maximum summer temperatures (January) about 30 ◦ C and minimum winter temperatures (September) of −3 ◦ C overnight during the study period (Fig. 2). Average daily variation in temperatures was around 15 ◦ C. Rainfall for the study period totalled 480 mm, with most rain falling during spring/summer. Peak rain months included October (34 mm), November (65 mm), December (80 mm), January (124 mm) and May (69 mm). Early spring and early autumn months were driest, each with monthly rainfall below 5 mm (Australian Bureau of Meteorology, 1995).
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Fig. 2. Rainfall and temperature for Raglan, New South Wales, during July 1994 to July 1995 (mean maximum temperature, mean minimum temperature, total monthly rainfall).
The dams were situated in a small hollow formed by a creek bed, in gently undulating to rolling low hills. The area immediately surrounding the dams included agricultural land with pasture, pet food production factory, several smaller industrial plants and a grain store. The soils at the dam sites and in the catchment area were mainly brown clay loam, slightly acidic and moderately fertile, placing them among the sodosols (Fitzpatrick et al., 2003; DLWC, 2003). These soils supported reasonable pasture for stock but generally required some improvement before cultivation. Due to the high clay content, the amount of infiltration into the soil profile during storm events was relatively low and runoff generated was high. This also meant that the area was susceptible to water erosion. 3.1. Dam 1 Dam 1 was the largest of three dams considered in this study. This dam covered an area of approximately 3.2 ha with a maximum depth of 2.2 m, and during the study period had an average storage volume of 38.1 ML. It was constructed by the building of a bank across a watercourse, although the creek was diverted at a later stage. There was minimal emergent aquatic vegetation, and a lack of vegetation in the area immediately surrounding the dam. Further up the bank tussock and other grasses grew, and along the top of the bank several established shrubs and small trees flourished, previously planted to stabilise the bank. When the site was first visited in November 1993, several reed beds were dying due to prolonged drought. Between this observation and the start of study in July 1994, the water level dropped by more than a metre (evidenced by the increased amount of bank exposed).
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Cattle and horses had ready access to the water and had made a substantial impact on the condition of the topsoil around the dam. Stock had presumably contributed to the lack of vegetation on the bank immediately adjacent to the water’s edge. This dam relied primarily on runoff from the surrounding hillsides, which included a combination of cultivated and stock paddocks. In the absence of effluent water channels and low seepage losses, loss of water from the dam was mainly due to evaporation or stock feeding. 3.2. Dam 2 Dam 2 covered an area of 0.3 ha with a maximum depth of 2.9 m and a constant storage volume of 5.7 ML. It was located in land owned by a nearby factory and was predominantly spring fed as runoff was excluded and channelled, via contour banks, away from the dam. This tank style dam had been built by excavating a hole in the ground, rather than by erecting banks. This resulted in a deeper dam with a smaller surface area, and thus reduced water loss due to evaporation. The banks of the dam were steep, making them unsuitable for stock use. Despite the relatively steep banks, the dam supported thriving Typha sp. and Juncus sp. beds that provided nesting sites for several species of native ducks. The adjacent factory regularly pumped water from the dam via a pump intake anchored approximately half a metre below water level on a float in the centre of the dam. Water was replenished from groundwater supplies via springs. 3.3. Dam 3 Dam 3 was located in the existing creek bed with the dam wall erected across the creek. It covered an area of 0.3 ha with a maximum depth of 1.0 m and a volume of 2.2 ML. Water sources for the dam included runoff from the hillside immediately adjacent to the dam, and from the creek bed. Water in the creek bed was composed of stormwater runoff from urban and light industrial areas of the nearby township of Raglan, with possible supplementation from underground sources. The result was a generally steady low-level flow of water into the dam. Except during exceptionally dry periods, there was a slow flow of water from the dam via an eroded channel at the side of the dam wall. Stock had access to approximately half of the dam’s perimeter. A slow overflow of water from the dam, coupled with a constant inflow, kept the water level in the dam consistent. As a result established reed beds of Typha sp. and Juncus sp. surrounded most of the dam, and while there had been some damage from stock trampling it was not sufficient to seriously affect growth. A canopy of Salix sp. and Cretaegus sp. surrounded part of the dam and reduced the level of evaporation. Together with the reed beds, they provided nesting sites for a variety of terrestrial and aquatic bird species. In summary, Dam 1 was largest, fed from agricultural runoff, had frequent stock access, and lacked vegetation around its edge. Dam 2 was smaller and deeper, spring fed with no stock access, and surrounded by reed beds. Dam 3 was smaller and shallow and creek fed from urban and light industrial areas, and supplemented with runoff from adjacent stock pastures, had stock access, and supported dense reed beds with reasonable canopy cover (Table 1).
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Table 1 Some physical aspects of three dams sampled at Raglan, New South Wales, between August 1994 and July 1995 Dam
Soil/substrate type
Relative stock use
Bank vegetated (%)
Relative canopy cover
Approximate depth sediment layer (cm)
1 2 3
Red and yellow sodolics on granite Red and yellow sodolics on granite Red and yellow sodolics on granite
Intensive None Moderate
2 85 98
Low Negligible Medium
30 5 90
4. Methodology The deepest point of each dam was located during preliminary survey and used as the point for surface and benthic sampling. The surface sampling point (30 cm below the water surface) was sampled every hour for 24 h using computer-controlled sampling equipment (Grant/YSI 3800 Water Quality Logging System). The benthos was also sampled (30 cm above the sediment surface) three times during the 24 h period, i.e. in the morning, late afternoon and the following morning, to collect information on diurnal mixing processes in the dam. Benthic sampling was not done in Dam 3, as the dam was too shallow. Parameters were measured monthly in situ using the Grant/YSI 3800 logger. Replicated water samples were collected from each dam for additional laboratory analysis using standard methods (Table 2). However, when inconsistencies in measured absorbance of standard solutions were observed for nitrates reduced over a copperised cadmium column before complexing with sulfanilamide, a second method based on UV absorbance was introduced. This involved elimination of interferences by heating and acidifying to pH 2 before reading absorbance of the solutions at 200 nm. This method provided more consistent results, was less resource intensive and showed strong correlation to the results from the standard method. Standard method for determining total nitrogen is the Kjeldahl method that is time consuming and complicated, with opportunity for errors in the chemical processing. Instead the method used was adapted from one discussed by Hosomi and Sudo (1986), which involved the simultaneous determination of total nitrogen and total phosphorus using persulfate digestion. Determination of chlorophyll-a concentrations closely followed the method outlined by Vollenweider (1974) in his manual on the measurement of primary production in freshwater aquatic environments. Water samples were filtered and chlorophyll-a extracted into acetone from the separated solids. The extract was acidified, denaturing the chlorophyll-a protein. The difference between absorbance before and after acidification was absorbance due to the presence of chlorophyll-a. 4.1. Data analysis Patterns in chemical profiles were compared to ascertain any similarity in macro-trends of water quality over a 12-month period between August 1994 and July 1995. Micro-trends within dams were contrasted with previously identified chemical relationships in farm dams and similar water bodies to further explore relationships between land use and water quality.
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Table 2 Physicochemical parameters recorded from dams at field sites during the study period and methods used Parameter
Method/instrument used
Water temperature pH Conductivity Salinity Dissolved oxygen (%) Dissolved oxygen (ppm) Turbidity Redox potential Air temperature Water level fluctuation Light penetration Productivity/biological oxygen demand Alkalinity Chlorophyll-a Reactive phosphates Total phosphates Nitrates (1) Nitrates (2) Nitrites Ammonium ions Total nitrogen Copper Zinc Magnesium Potassium
Water quality logging system Water quality logging system Water quality logging system Water quality logging system Water quality logging system Water quality logging system Water quality logging system Water quality logging system Thermometer Metre rule Secchi disk BOD bottles and DO metre Dual endpoint titration Extraction, absorbance Complex, absorbance Persulfate digest Acid hydrolysis UV absorbance Complex, absorbance Complex, absorbance Persulfate digest Atomic adsorption spectrometry Atomic adsorption spectrometry Atomic adsorption spectrometry Atomic adsorption spectrometry
Results were analysed using JMP software (SAS Institute, 2001). Six samples were randomly selected from each set of 24 h samples taken over 12 months for each dam and tested using a two-way ANOVA for repeated measures. Mean values from processing of parameters sampled once per month were tested using a two-way ANOVA for mean values (Sall et al., 2001). Specific parameters identified as indicative of chemical or thermal stratification were selected from the above data sets and replicate samples from the surface and benthos of the two deeper dams, Dam 1 and Dam 2, were tested for stratification using bivariate ANOVAs. Trends within dams were then examined with respect to the chemical processes that were interacting and defining the chemical profile of each dam. Inter-relationships between parameters were explored using regression analysis.
5. Results 5.1. Comparison of dams Trends from raw data indicated that there was a difference between the three dams on the basis of parameters commonly used to profile the chemistry of freshwaters (Table 3).
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Table 3 Some important physicochemical characteristics of the waters in three dams sampled at Raglan, New South Wales, between August 1994 and July 1995 (ranges indicate mean values of monthly measurements taken at 30 cm below the water surface) Parameter (◦ C)
Water temperature Dissolved oxygen (mg/L) pH Conductivity (S/cm) Salinity (parts per thousand, ‰) Redox potential (mV) Turbidity (NTU) Secchi disk transparency (cm) [HCO3 − ] alkalinity (mg/L) Nitrate (mg/L) Total nitrogen (mg/L) Total phosphate (mg/L) Chlorophyll-a (g/L)
Dam 1
Dam 2
Dam 3
7.3–28 4.7–11 7.7–9.3 0.26–0.43 0.2 90–350 9.0–63 60–130 43–84 0–0.84 0–1.6 0.01–0.55 0–22
6.7–28 2.5–14 7.6–9.1 0.49–0.80 0.3–0.4 13–360 9.0–90 20–230 79–170 0–1.60 0–2.5 0.04–0.71 0–130
5.4–28 0.06–27 6.6–9.1 0.25–0.87 0.1–0.4 −430–410 14–210 15–60 37–390 0–1.45 0–9.9 0.13–2.8 20–390
Waters in the three dams were identified as significantly different across both sets of physicochemical parameters tested at a 95% confidence level (Table 4). The only deviations from this outcome at a 99% confidence level were for temperature and chlorophyll-a levels. Dam 1 and Dam 2 both showed evidence of stratification at 99% confidence level across the majority of parameters examined (Table 5, Figs. 3 and 4). Stratification was most evident with temperature, pH and redox potential (Fig. 5). Dissolved oxygen, closely linked with redox potential, only showed clear stratification in both dams at 95% confidence level. It appeared that there were two periods of stratification during the 12-month study period in Dam 1. The first and most obvious of these was during summer (December/January) when Table 4 F values for two-way ANOVA tests on comparisons of data from three dams at Raglan, New South Wales, collected between August 1994 and July 1995 Test
Parameter
F-value
d.f.
Probability >F
Two-way ANOVA with repeated measures
Temperature pH Turbidity Salinity Conductivity Redox potential Dissolved oxygen
5.99 477 33.6 33500 34100 23.6 14.8
2 2 2 2 2 2 2
0.0122 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.0003
Two-way ANOVA with mean values
Total phosphorus Total nitrogen Alkalinity Chlorophyll-a Light penetration
31.3 9.40 32.9 5.38 6.05
2 2 2 2 2
<0.0001 0.0013 <0.0001 0.0125 0.0080
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Table 5 F values for bivariate ANOVA tests for stratification in Dams 1 and 2 at Raglan, New South Wales, for data collected between August 1994 and July 1995 Dam
Parameter
F-value
d.f.
Probability >F
Dam 1
Temperature pH Redox potential Dissolved oxygen
150 64.9 116 4.38
23 23 21 23
<0.0001 <0.0001 <0.0001 0.0481
Dam 2
Temperature pH Redox potential Dissolved oxygen
380 24.7 19.2 19.4
23 23 21 23
<0.0001 <0.0001 0.0003 0.0002
there was apparent chemical and thermal stratification followed by the common autumn overturn. A subsequent period of stratification then developed during winter (June/July) with a less common overturn in the spring (Fig. 3). In Dam 2 the period of summer stratification was longer and more distinct, and followed by a single annual overturn in late autumn (Fig. 4). Dam 3 was too shallow to develop any clearly identifiable layering using the available equipment. 5.2. Patterns of plant nutrient levels within dams Dams 1 and 2 showed similar trends across the year in concentrations of nutrients and the closely linked chlorophyll-a level (Fig. 6). However, the patterns for each of these parameters for Dam 3 were quite different. Trends for bicarbonate alkalinity were similar for Dam 1 and Dam 2, although the concentrations measured in Dam 3 were approximately double (Fig. 6). Again patterns of alkalinity for Dam 3 were different, indicating that water in this dam was exposed to a different set of chemical impacts. Comparison of fluctuations in concentration for nitrogen, phosphorus, chlorophyll-a and alkalinity from Dam 3 with the corresponding annual rainfall profiles showed a connection between peak rainfall events and subsequent reduction in concentration of total nitrogen and total phosphates (Fig. 6). Similarly, links between seasonal peaking of chlorophyll-a in spring (September/October) and reduced levels of nitrogen and phosphates were noted, with a similar reduction in levels of chlorophyll-a after significant rainfall events in December–January and May–July 1995. 5.3. Diurnal patterns within dams Diurnal turbidity levels in Dam 1 during autumn were consistent during daylight hours but rose during the hours between 10 p.m. and 4 a.m. (Fig. 7a). This peak coincided with the autumn mixing period, occurring concurrently with the disturbance of bottom sediments by the circulating waters. Patterns of pH in Dam 1 during summer and autumn indicated a response to a number of phenomena. In early summer daily pH levels were consistently very high, around pH
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Fig. 3. Variation of selected water quality parameters in Dam 1 between August 1994 and July 1995: (a) temperature; (b) pH; (c) dissolved oxygen ((×) surface, (䊐) benthic). Arrow indicates region of stratification. N.B. Area in between arrows indicate period of stratification.
9 (Fig. 7b), but following high rainfall in January 1995 dam waters were diluted with the mildly acidic rainfall and runoff, and subsequent diurnal pH ranges over the next few months were lower, between pH 8 and 8.5 (Fig. 7b and c). During this late summer and autumn period pH peaked in the late afternoon, immediately following the period of maximum
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Fig. 4. Variation of selected water quality parameters in Dam 2 between August 1994 and July 1995: (a) temperature; (b) pH; (c) dissolved oxygen ((×) surface, (䊐) benthic). Arrow indicates point of mixing. N.B. Area in between arrows indicate period of stratification.
photosynthetic activity. After dark respiration is dominant and pH dropped to a diurnal low overnight. This pattern was repeated in Dam 2 particularly during autumn (Fig. 8a) although during the drier months there was an increase in water use for irrigation, resulting in an unstable diurnal pH curve.
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Fig. 5. Variation of redox potential between August 1994 and July 1995 for (a) Dam 1 and (b) Dam 2 ((×) surface, (䊐) benthic) and (c) Dam 3.
A second parameter closely linked with photosynthesis is dissolved oxygen concentration, and in Dam 2 during summer and autumn this was closely tied to daily light availability, with peaks late in the afternoon following the extended period of photosynthetic activity (Fig. 8b and c). Corresponding lows in dissolved oxygen concentration were evident in the hours before dawn when respiration was again the dominant process.
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Fig. 6. Comparison of selected water quality parameters for three dams between August 1994 and July 1995: (a) chlorophyll-a, (b) bicarbonate alkalinity, (c) total nitrogen, (d) total phosphorus ((×) Dam 1, (䊐) Dam 2, (䉬) Dam 3).
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Fig. 7. Daily variation of selected water quality parameters in Dam 1, sampled at Raglan, New South Wales, for selected seasons between August 1994 and July 1995: (a) autumn 1995 turbidity, NTU ((䉬) February, (䊐) March, () April); (b) summer 1994/1995 pH ((䉬) November, (䊐) December, () January); (c) autumn 1995 pH ((䉬) February, (䊐) March, () April).
Measured levels of conductivity were higher in Dam 2 (Table 6; Fig. 8d). Daily patterns for conductivity had similar ranges throughout the year to those shown in Fig. 8d but patterns for autumn showed more erratic values during the period corresponding to constant water use for irrigation, pumped from the dam, coupled with replenishment from groundwater supplies. During autumn Dam 3 showed a similar trend to the other dams for pH with daily increases associated with photosynthetic activity, and decreasing after nightfall (Fig. 9a). Patterns for dissolved oxygen again followed a similar trend, but were erratic in Dam 3 during summer and autumn (Fig. 9b and c). Conditions in Dam 3 during the hours of darkness became quite anoxic, with dissolved oxygen levels generally reduced to zero, or very close to this. Concurrent redox potential changed from the values associated with oxygen richness of around 400–500 mV to those indicative of anaerobic conditions of 0 mV, and on occasions lower again to a reducing environment with values to as low as −400 mV (Fig. 9d).
Dam/season
Temperature (◦ C)
pH
Conductivity (mS/cm)
Salinity (‰)
DO2 (ppm)
Turbidity (NTU)
Dam 1 Spring, October 1994 Summer, January 1995 Autumn, April 1995 Winter, July 1995
16–19 24–28 11–12 7.3–7.9
8.4–8.6 8.4–8.7 8.2–8.2 8.2–8.4
0.36–0.37 0.35–0.37 0.41–0.42 0.40
0.2 0.2 0.2 0.2
7.5–8.8 4.7–6.4 7.4–8.1 10
14–22 18–39 21–41 32–41
170–210 160–190 280–350 300–320
Dam 2 Spring, October 1994 Summer, January 1995 Autumn, April 1995 Winter, July 1995
18–20 22–23 13–14 6.7–7.3
8.2–8.4 7.8–8.2 7.5–8.5 7.6–7.7
0.72–0.73 0.76–0.77 0.76–0.78 0.73–0.73
0.4 0.4 0.4 0.4
8.2–9.5 2.5–5.0 4.7–9.0 5.8–7.1
17–22 27–41 63–90 33–49
170–230 13–310 210–250 270–360
Dam 3 Spring, October 1994 Summer, January 1995 Autumn, April 1995 Winter, July 1995
13–16 21–23 9.7–13 5.4–8.6
6.8–8.6 6.8–8.0 7.5–8.5 6.9–7.8
0.25–0.33 0.35–0.42 0.84–0.87 0.35–0.37
0.1–0.2 0.2 0.4 0.2
3.2–17 0.06–9.6 0.22–12 0.20–5.2
35–205 36–94 35–71 57–94
230–370 −1.0–400 220–330 360–410
Redox potential (mV)
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Table 6 Seasonal diurnal ranges for chemical parameters measured hourly for 24 h from three dams at Raglan, New South Wales, sampled between August 1994 and July 1995
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Fig. 8. Daily variation of selected water quality parameters in Dam 2 between August 1994 and July 1995: (a) autumn 1995 pH ((䉬) February, (䊐) March, () April); (b) summer 1994/1995 dissolved oxygen, ppm ((䉬) November, (䊐) December, () January); (c) autumn 1995 dissolved oxygen, ppm ((䉬) February, (䊐) March, () April); (d) autumn 1995 conductivity, mS/cm ((䊐) February, () March, (×) April).
Diurnal turbidity patterns in Dam 3 showed some interesting variations during spring and autumn (Fig. 10a and b). In October 1994, there was a brief period of elevated turbidity between 10 and 2 a.m. that could be associated with a flushing event although this was not a storm surge. Late afternoon peaks evident from Dam 3 during spring through to autumn were associated with stock watering and cooling behaviours, and were absent during winter (Fig. 10c).
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Fig. 9. Daily variation of selected water quality parameters in Dam 3 between August 1994 and July 1995: (a) autumn 1995 pH ((䉬) February, (䊐) March, () April); (b) summer 1994/1995 dissolved oxygen, ppm ((䉬) November, (䊐) December, () January); (c) autumn 1995 dissolved oxygen, ppm ((䉬) February, (䊐) March, () April); (d) summer 1994/1995 redox potential, mV ((䊐) December, () January, (×) March).
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Fig. 10. Daily variation of selected water quality parameters in Dam 3 between August 1994 and July 1995: (a) spring 1994 turbidity, NTU ((䉬) August, (䊐) September, () October); (b) autumn 1995 turbidity, NTU ((䉬) February, (䊐) March, () April); (c) winter 1995 turbidity, NTU ((䉬) May, (䊐) June, () July); (d) annual 1994/1995 salinity, ‰.
Of the three dams, Dam 3 was the only dam that showed any notable variation in salinity during the entire study period. In general, lower values corresponded with peak rainfall periods and higher values with drier periods, indicating a link with runoff flushing through the dam and evapo-concentration (Fig. 10d).
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6. Discussion 6.1. Water sources for the dams The hydrology and water quality of farm dams are controlled by the exchange of water and solutes with adjacent uplands. Mechanisms of water and solute transfers include precipitation, runoff, evapo-transpiration and subsurface flows. Of these, direct precipitation generally comprises less than one-tenth of the total water input, while surface waters as runoff from the drainage basin can comprise nearly all of the water input into a reservoir (Wetzel, 1999). Each of the dams showed variations in water chemistry that corresponded to a different set of inputs. Groundwater can also enter farm dams as discrete springs. This happens frequently in hard water reservoirs such as in the study area in the Bathurst district, or where the basin is effectively sealed from groundwater seepage by sediment deposits. Of the three dams in Raglan, Dam 2 is known to be spring fed. However it is not clear whether the only input into Dam 2 is via springs or also via a seepage pathway. Contour banks constructed around the dam channel runoff away, limiting input to direct precipitation and groundwater. Comparison of this dam with the other dams provides some kind of benchmark for groundwater input. Dam 1, the largest dam, showed some similarity in trends of water quality, indicating some input in the form of groundwater to this dam. Additional input from runoff explains the differences in water quality between the two dams. The adjacent pasture provided a runoff catchment for Dam 1, along with a concurrent input of particulate matter and dissolved chemical species. Transportation of sediments into the dam is influenced by rainfall intensity, temperature, soil moisture and discharge conditions, catchment shape, variations in surface condition and vegetation cover, and sediment supply (Webb et al., 1995; Basnyat et al., 2000). Trends of chemical patterns in Dam 3 show little similarity to either of the other two dams, indicating that this dam relies primarily on waters from a different source. This dam collected runoff from the nearby urban and industrial areas via a creek, as well as from adjacent agricultural lands. While Dam 1 collected agricultural runoff from grassland, Dam 3 collected runoff from a range of urban and rural land use areas. 6.2. Water quality influences Low-intensity rainfall in general mobilises less nutrient laden sediment than high-intensity storm events, although soil moisture and permeability also contribute to sediment movement (Basnyat et al., 2000). The resulting nonpoint source pollution is more difficult to quantify than pollution from a single source. Runoff sediment transport capacity is dictated by the shear stress relationship that develops between the dominant flow shear of the soil and the critical stress from rainfall events (Leon et al., 2001). Raglan is situated on impermeable bedrock of granite, with gully soils comprising mainly sodolics (sodosols), which have low permeability and a resulting higher erosive potential. Thus dams that are exposed to runoff input are also exposed to a potentially high sediment load from the soils. Areas of impervious cover associated with urbanisation have important impacts on storm surges and concentration of pollutants (Wear et al., 1998), impacts that affect Dam 3. Soil
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surface crusting associated with sodolics was noted on the hillside above Dam 1. This crusting can contribute to storm flow by reducing the infiltration of rainwater into soils (Zhu et al., 1999). The soil water balance dictates whether waters and associated sediment and nutrient loads will be transported as runoff or via a longer pathway as groundwater (Bellot et al., 2001). The principal pathway for the transport of a particular compound is determined by a number of factors. The first and most important of these is the chemistry of the compound, followed by the hydrology of the region, which together determine the relative roles of groundwater leaching and runoff transport pathways. The final factor is land use (Blanchard and Lerch, 2000). Most contaminants affecting water quality in rural areas comprise simple inorganic ions, more complex organic molecules or particulates. Among other sources, including soils and decomposing vegetation, each of these can result from animal manure (Goss et al., 2000). Each of these sources is known to impact both Dam 1 and Dam 3, and not Dam 2. Animal manure potentially provides a source of nitrate, phosphate, toxic metals and bacteria. The organic matter in manure alters the physicochemical properties of the soil, increasing the mobility of contaminants and resulting in movement through the soil in a wider range of conditions. Preferential flow paths can develop due to structures present in the surface soil or in the subsurface across soil horizon boundaries. This preferential flow can carry water and contaminants to depth very rapidly (Goss et al., 2000). This can result in contamination of groundwater with higher than expected levels of nitrates and phosphates, and may explain the high levels of each of these in Dam 2. 6.3. Links with adjacent land use There is considerable agreement in recent studies that amounts of nitrogen and phosphorus in surface waters are significantly influenced by anthropogenic inputs associated with land cover, land use and point sources (e.g. Castillo et al., 2000; Ferrier et al., 2001; Valiela and Bowen, 2002). However, there is less agreement on the exact nature of these relationships. Once mobilised from surficial clay complexes, phosphorus is transported in solution via groundwater aquifers (Cox and Ashley, 2000). Phosphates tend to show little seasonal variation, although concentrations may increase slightly during periods of low runoff flow (Castillo et al., 2000). In both Dam 1 and Dam 2, phosphate levels showed this slight increase after the long dry period in autumn. In Dam 3 the relationship was more apparent as a decrease in phosphate levels in conjunction with the high rainfall events during summer. Thus evapo-concentration and dilution following storm surges are important regulators of phosphate concentration in farm dams. Nitrates can potentially be leached or transported in runoff (Blanchard and Lerch, 2000). Nitrates are strongly associated with agricultural land and grasslands (Ferrier et al., 2001), and concentrations are highest in spring and in conjunction with high runoff events. Each of the three dams studied reflected this spring increase to some degree. Dam 3 demonstrated a relationship between nitrogen and runoff events with peaks in concentration evident concurrent with high rainfall periods. Ferrier et al. (2001) found that urban catchments were highly correlated with ammonium ions, reactive phosphates and suspended solids. This dominance of ammonium ions in the
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total nitrogen, and reactive phosphates in the total phosphorus was also identified in Dam 3, suggesting that there was a significant impact from runoff from the urban areas that outweighed the input from the agricultural areas. In contrast, Dam 1 and Dam 2 showed a dominance of nitrogen as nitrate ions. In summary, with the current reduction in resource availability in eastern Australia due to ongoing drought and increasing competition for resources on an already stressed system, there is a need to maintain optimal water quality in the available water resources. A significant portion of this is reserved in farm dams, either for domestic supply, stock or irrigation. If potable water is to continue to be available from these dams they need to be managed in a way that promotes this aim either by planting trees to retain water and nutrients away from the dams, or wetland plants to remove excessive nutrients from the dam, and management of cropping and grazing in the adjacent basin catchment. If dams are to be managed as nutrient/sediment traps for the protection of nearby stream systems this needs to be conducted in a manner that minimises nutrient leaching by groundwater pathways, again by incorporating appropriate vegetation strategies in the management strategy. 7. Conclusions The presence of important plant nutrients, such as nitrates and phosphates has clearly influenced the development of photosynthetic algae in normal seasonal patterns. Dams with higher levels of nutrients tended to have higher levels of chlorophyll-a, leading to higher oxygen production, with linked fluctuations in pH, and redox potential. Particulate sediment inputs affected levels of turbidity, light penetration and the ratio of photosynthetic activity to respiration. Dissolved inorganic ions similarly affected levels of salinity and conductivity. Thus many of the chemical processes examined in the dams can be linked to the input waters, which in turn reflect their origins. For Dam 2 this was almost entirely groundwater, while for Dam 1 the groundwater input was tempered with pasture runoff. For Dam 3, it was the runoff from a landscape mosaic of urban, industrial and pasture lands that affected the water quality most and the influence due to groundwater input was probably negligible. This suggests that, in these dams at least, land use forms only part of the impact on water quality. A more complete picture would include water sources, with accompanying ion transfer pathways and attendant aquifer recharge and discharge patterns, rather than merely a linking to immediate land surface characteristics. References Ali, A., Frouz, J., Lobinske, R.J., 2002. Spatio-temporal effects of selected physico-chemical variables of water, algae and sediment chemistry on the larval community of nuisance Chironomidae (Diptera) in a natural and a man-made lake in central Florida. Hydrobiologia 470, 181–193. Alvarez-Cobelas, M., Baltanas, A., Velasco, J.L., Rojo, C., 2002. Daily variations in the optical properties of a small lake. Freshwater Biol. 47, 1051–1063. ANZECC, 2000. An Introduction to the Australian and New Zealand Guidelines for Fresh and Marine Water Quality. Australian and New Zealand Environment and Conservation Council and Agriculture and Resource Management Council of Australia and New Zealand. http://www.ea.gov.au/water/quality/nwqms/ introduction/index.html.
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Temporal variations in water quality of farm dams: impacts of land use and water sources M.A. Brainwood, S. Burgin, B. Maheshwari∗ Centre for Integrated Catchment Management, University of Western Sydney, Hawkesbury Campus, Locked Bag 1797, Penrith South DC, NSW 1797, Australia Accepted 12 March 2004
Abstract Three farm dams near Raglan, New South Wales (Australia), were compared to investigate diurnal and seasonal patterns in water quality over a period of 1 year. The source of water in one dam was predominantly influenced by groundwater, another showed links with both groundwater and agricultural runoff, and the third collected runoff from urban and agricultural lands with no apparent groundwater input. Patterns in chemical profiles were compared to identify level of similarity in macro-trends of water quality. Within dams, micro-trends were contrasted with known chemical relationships in dam waters to explore links between land use and water quality. The three dams were shown to have quite distinct patterns of water chemistry. Within dams, trends were strongly linked with the differing water sources, evidenced by chemical patterns that matched those expected from the different dominant ion transfer pathways associated with surface water and groundwater flow processes. Phosphates were primarily linked with groundwater fluctuations, nitrogen as ammonium ions with urban runoff, and nitrates with storm events resulting in runoff from pastures. We conclude that, for farm dams, the combination of land use and preferential flow paths gives a more complete description of water quality impacts than land use alone. © 2004 Published by Elsevier B.V. Keywords: Farm dams; Water quality; Land use; Agricultural and urban runoff
1. Introduction Agriculture has both indirect and direct effects on the quality of surface and ground waters and is one of the key activities causing water quality degradation in many parts of Australia. The quality is affected by both macro- and micro-scale factors. Macro-scale ∗
Corresponding author. Tel.: +61-245-701-235; fax: +61-245-701-750. E-mail addresses: [email protected] (S. Burgin), [email protected] (B. Maheshwari). 0378-3774/$ – see front matter © 2004 Published by Elsevier B.V. doi:10.1016/j.agwat.2004.03.006
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factors include climate, landscape and parent material of the area, while micro-scale factors include land use and management at field or farm level. Past studies have indicated that there is a strong relationship between land use and quality of both surface and ground water in the area (Zalidis et al., 2002; Tong and Chen, 2002). This means that changes in land use and management practices can have considerable impact on water quality parameters. With the increased public concerns about water quality degradation, several water quality monitoring programs have been initiated in Australia in the recent years at local, state and national levels. A range of groups including water authorities, local government bodies, universities, communities, independent consultants and schools run the programs. The intensity and continuity of these programs vary considerably since data collection is often extremely time consuming and costly, especially if the monitoring is to be carried out over a period of many years. To make the monitoring more effective, a national framework has been developed for collecting and reporting of water quality data so that data collected from different locations can be compared and contrasted for developing an overall picture of the water quality situation within a region (ANZECC, 2000). Water quality investigations are carried out to provide information on the health of water bodies and for developing strategies that help in better management of catchment and water resources. In particular, they may assist in preparing an impact assessment, forecasting ‘what if’ scenarios and assessing the state of the ambient water environment and trends. The investigations may be a single study to tackle a particular water quality related issue, or they may be an ongoing program to monitor water quality and understand long-term impacts of land uses and other activities in the catchment. However, effective water quality monitoring requires the systematic collection of a range of water quality parameters within a carefully planned experimental design. Management of on-farm water supplies in Australia has always been an important issue. Increasing demands on water resources within catchments has led to the implementation of legislation that regulates the availability of water to individual users (Murray Darling Basin Ministerial Council, 2001). With the aim to reduce the amount of surface waters harvested by these dams in over-taxed catchments, one of the targets has been the erstwhile ubiquitous farm dam. A recent criticism of water allocation in Australia is the tendency for single usage of water (Ingram et al., 2000). The potential for contamination of dam water by sediment runoff or leaching of salts from the aquifer that make it unsuitable for stock or irrigation, iterates the need for an increased understanding of their chemical hydrology. The main objective of this study was to explore physical and chemical processes through a case study of three farm dams over diurnal and seasonal time scales and relate resulting chemical profiles to catchment land use.
2. Factors affecting water quality The distribution and cycling of chemical compounds in water bodies, such as farm dams, are closely related to water movement in the landscape and are influenced by processes in the hydrological and biological cycles. In Australia differences in the chemical composition of inland freshwaters occur across the vast extent of geographic and climatic conditions
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present. Significant quantities of these freshwaters are held in a large (>500,000) number of small, man-made reservoirs known colloquially as farm dams (Lewis, 2002). These dams provide drinking water for stock or irrigation waters for crops, and on many farm properties, hold the only fresh water directly available. Despite this, the impact of adjacent land usage on the quality of this water has remained largely unexplored. The major ionic components present in natural waters are generally considered to come from two main sources. One of these is atmospheric, with ions dissolving in rainwater as it forms, and the other is a result of the weathering of soils and base rocks in the catchment. In coastal parts of Australia saline groundwater of marine origin impacts on surface waters, as do fluctuations in water tables resulting in shallow water tables that can increase groundwater salinity in inland regions (Taniguchi, 1997). Particularly in shallow lakes and reservoirs, evaporation or precipitation of less-soluble salts can change the chemical composition of the water body. While considerable attention has been given to sediment sources and solute transport pathways in rural catchments (e.g. Croke et al., 1999; Gruszowski et al., 2003), little is known about the relative contribution of rain and the catchment geology to the chemical composition of farm dam waters. In farm dams the ionic composition is expected to closely reflect the composition of the inflowing waters. The two factors that most commonly lead to changes in the concentration and ionic composition of dam waters are evapo-concentration and the intrusion of groundwater. The final dam water quality is the result of a complex interaction between the composition of rainwater, weathering processes in the catchment, and groundwater inputs. For example, peaks in the introduction of dissolved and particulate materials can occur during storm event flushing from the catchment. Recently a number of studies have investigated land use impacts on water bodies, both in terms of macroinvertebrates and the algal communities supported and water quality parameters. These studies have been centred predominantly on rivers and creeks, with the main considerations being directed towards the presence/absence and density of riparian vegetation (e.g. Sponseller et al., 2001; Ometo et al., 2000; Stevens and Cummins, 1999). Variations in the density of riparian vegetation were observed to be affected by management practices that ranged from cropping, grazing, rotational cropping/grazing, through to undisturbed woodland vegetation (Weigel et al., 2000). Disturbance of riparian vegetation was seen to be a major factor resulting in increased sedimentation of rivers (Steiger et al., 2003). Sponseller et al. (2001) observed that stream water chemistry was related to catchment level characteristics, while water temperature and substrate composition were more closely related to riparian land cover patterns. Similarly macroinvertebrates were noted to respond more directly to larger scale watershed influences, with only minor variations reflecting localised land use (Weigel et al., 2000). Conversely, Stevens and Cummins (1999) found a significant relationship between stream chemistry and both land use and riparian vegetation. Despite the differences, there is general agreement that catchment land use and riparian vegetation affect aspects of water quality, but it is not clear at what hierarchical level these factors primarily impact. Ometo et al. (2000) explored the differential impacts of temperate and tropical climates and concurrent patterns of agriculture and land management practices and identified high levels of correlation for some chemical parameters, but not for others. Patterns of fluvial dynamics within stream systems create continua of environmental conditions that have inherently different characteristics to those found in drainage basins.
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While the effects of these conditions can be dispersed and diluted through a riverine system (Marchant and Hehir, 2002), they are more often compounded through continuing retention in water bodies such as farm dams. Perhaps because of this the relationship between land use and water chemistry in a lentic system could be expected to be more significant than for rivers and creeks. Groundwater seepage below the surface of the reservoir is commonly a major source of water. There is often a complex seepage hydrology with groundwater flow alternating between upwelling and downwelling in response to levels of precipitation and evapotranspiration (Wetzel, 1999). Modelling of groundwater flow dynamics suggests that up to 50% of input in many natural lakes is from groundwater, and up to 50% of water loss is by seepage (Lampert and Sommers, 1997). However, measurement of evaporation and evapo-transpiration is expensive and measurement of subsurface inputs and losses of water is difficult and demanding. A historical assessment of prairie lakes in Canada revealed the significance of the impacts of land use practices, and suggested regulation of cropping areas, livestock biomass, and urban nitrogenous wastes as a water quality management strategy (Hall et al., 1999). Ali et al. (2002) compared adjacent natural and man-made lakes in central Florida and observed how the variability in lake-specific combinations of water, sediment and algal variables was dependent upon season. This spatial and temporal variability of environmental conditions was reflected, directly or indirectly, in the distribution of organisms. Patterns of species distribution and abundance are frequently used to characterise ecosystem health. These patterns are often used as surrogate measures of fundamental ecological processes that contribute to essential life support systems. While environmental disturbance may affect these patterns, this does not prove the link between pattern and process (Bunn et al., 1999). Chemical profiling of farm dams, and consequent comparison to lake scenarios, has in the past been mainly limited to seasonal spot sampling (e.g. Timms, 1980), or more recently has been undertaken to provide a physicochemical background for a biodiversity survey (e.g. Hazell et al., 2001). This neglects the possibility that different chemical processes operate at different time scales in standing waters (Alvarez-Cobelas et al., 2002), resulting in a range of differential interactions that produce cycles and trends over diurnal, seasonal, annual and decadal scales. Contemporary philosophies relating to experimental design emphasise the need to design experiments that test a specific hypothesis, rather than on insights gained through inductive reasoning, based on large amounts of field data. On the largest scale, manipulation of ecosystems represents the least controlled of this type of ecological experiment. However, it has been proposed that small lakes and ponds are best suited because they form isolated systems (Lampert and Sommers, 1997).
3. Site description The three dams selected for this study were located at Raglan (33◦ 25 S, 149◦ 39 E) near Bathurst in the Central Tablelands of New South Wales, Australia (Fig. 1). The dams were located in close proximity and in the same drainage line to eliminate distinct variations in
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Fig. 1. Field site at Raglan, New South Wales, with detail of the three dams and their immediate locality.
groundwater, catchment geology and dam substrate, and weather related variables including rainwater composition, and volume and evaporation rates. The area was located approximately 700 m above sea level and had a warm temperate climate, with mean maximum summer temperatures (January) about 30 ◦ C and minimum winter temperatures (September) of −3 ◦ C overnight during the study period (Fig. 2). Average daily variation in temperatures was around 15 ◦ C. Rainfall for the study period totalled 480 mm, with most rain falling during spring/summer. Peak rain months included October (34 mm), November (65 mm), December (80 mm), January (124 mm) and May (69 mm). Early spring and early autumn months were driest, each with monthly rainfall below 5 mm (Australian Bureau of Meteorology, 1995).
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Fig. 2. Rainfall and temperature for Raglan, New South Wales, during July 1994 to July 1995 (mean maximum temperature, mean minimum temperature, total monthly rainfall).
The dams were situated in a small hollow formed by a creek bed, in gently undulating to rolling low hills. The area immediately surrounding the dams included agricultural land with pasture, pet food production factory, several smaller industrial plants and a grain store. The soils at the dam sites and in the catchment area were mainly brown clay loam, slightly acidic and moderately fertile, placing them among the sodosols (Fitzpatrick et al., 2003; DLWC, 2003). These soils supported reasonable pasture for stock but generally required some improvement before cultivation. Due to the high clay content, the amount of infiltration into the soil profile during storm events was relatively low and runoff generated was high. This also meant that the area was susceptible to water erosion. 3.1. Dam 1 Dam 1 was the largest of three dams considered in this study. This dam covered an area of approximately 3.2 ha with a maximum depth of 2.2 m, and during the study period had an average storage volume of 38.1 ML. It was constructed by the building of a bank across a watercourse, although the creek was diverted at a later stage. There was minimal emergent aquatic vegetation, and a lack of vegetation in the area immediately surrounding the dam. Further up the bank tussock and other grasses grew, and along the top of the bank several established shrubs and small trees flourished, previously planted to stabilise the bank. When the site was first visited in November 1993, several reed beds were dying due to prolonged drought. Between this observation and the start of study in July 1994, the water level dropped by more than a metre (evidenced by the increased amount of bank exposed).
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Cattle and horses had ready access to the water and had made a substantial impact on the condition of the topsoil around the dam. Stock had presumably contributed to the lack of vegetation on the bank immediately adjacent to the water’s edge. This dam relied primarily on runoff from the surrounding hillsides, which included a combination of cultivated and stock paddocks. In the absence of effluent water channels and low seepage losses, loss of water from the dam was mainly due to evaporation or stock feeding. 3.2. Dam 2 Dam 2 covered an area of 0.3 ha with a maximum depth of 2.9 m and a constant storage volume of 5.7 ML. It was located in land owned by a nearby factory and was predominantly spring fed as runoff was excluded and channelled, via contour banks, away from the dam. This tank style dam had been built by excavating a hole in the ground, rather than by erecting banks. This resulted in a deeper dam with a smaller surface area, and thus reduced water loss due to evaporation. The banks of the dam were steep, making them unsuitable for stock use. Despite the relatively steep banks, the dam supported thriving Typha sp. and Juncus sp. beds that provided nesting sites for several species of native ducks. The adjacent factory regularly pumped water from the dam via a pump intake anchored approximately half a metre below water level on a float in the centre of the dam. Water was replenished from groundwater supplies via springs. 3.3. Dam 3 Dam 3 was located in the existing creek bed with the dam wall erected across the creek. It covered an area of 0.3 ha with a maximum depth of 1.0 m and a volume of 2.2 ML. Water sources for the dam included runoff from the hillside immediately adjacent to the dam, and from the creek bed. Water in the creek bed was composed of stormwater runoff from urban and light industrial areas of the nearby township of Raglan, with possible supplementation from underground sources. The result was a generally steady low-level flow of water into the dam. Except during exceptionally dry periods, there was a slow flow of water from the dam via an eroded channel at the side of the dam wall. Stock had access to approximately half of the dam’s perimeter. A slow overflow of water from the dam, coupled with a constant inflow, kept the water level in the dam consistent. As a result established reed beds of Typha sp. and Juncus sp. surrounded most of the dam, and while there had been some damage from stock trampling it was not sufficient to seriously affect growth. A canopy of Salix sp. and Cretaegus sp. surrounded part of the dam and reduced the level of evaporation. Together with the reed beds, they provided nesting sites for a variety of terrestrial and aquatic bird species. In summary, Dam 1 was largest, fed from agricultural runoff, had frequent stock access, and lacked vegetation around its edge. Dam 2 was smaller and deeper, spring fed with no stock access, and surrounded by reed beds. Dam 3 was smaller and shallow and creek fed from urban and light industrial areas, and supplemented with runoff from adjacent stock pastures, had stock access, and supported dense reed beds with reasonable canopy cover (Table 1).
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Table 1 Some physical aspects of three dams sampled at Raglan, New South Wales, between August 1994 and July 1995 Dam
Soil/substrate type
Relative stock use
Bank vegetated (%)
Relative canopy cover
Approximate depth sediment layer (cm)
1 2 3
Red and yellow sodolics on granite Red and yellow sodolics on granite Red and yellow sodolics on granite
Intensive None Moderate
2 85 98
Low Negligible Medium
30 5 90
4. Methodology The deepest point of each dam was located during preliminary survey and used as the point for surface and benthic sampling. The surface sampling point (30 cm below the water surface) was sampled every hour for 24 h using computer-controlled sampling equipment (Grant/YSI 3800 Water Quality Logging System). The benthos was also sampled (30 cm above the sediment surface) three times during the 24 h period, i.e. in the morning, late afternoon and the following morning, to collect information on diurnal mixing processes in the dam. Benthic sampling was not done in Dam 3, as the dam was too shallow. Parameters were measured monthly in situ using the Grant/YSI 3800 logger. Replicated water samples were collected from each dam for additional laboratory analysis using standard methods (Table 2). However, when inconsistencies in measured absorbance of standard solutions were observed for nitrates reduced over a copperised cadmium column before complexing with sulfanilamide, a second method based on UV absorbance was introduced. This involved elimination of interferences by heating and acidifying to pH 2 before reading absorbance of the solutions at 200 nm. This method provided more consistent results, was less resource intensive and showed strong correlation to the results from the standard method. Standard method for determining total nitrogen is the Kjeldahl method that is time consuming and complicated, with opportunity for errors in the chemical processing. Instead the method used was adapted from one discussed by Hosomi and Sudo (1986), which involved the simultaneous determination of total nitrogen and total phosphorus using persulfate digestion. Determination of chlorophyll-a concentrations closely followed the method outlined by Vollenweider (1974) in his manual on the measurement of primary production in freshwater aquatic environments. Water samples were filtered and chlorophyll-a extracted into acetone from the separated solids. The extract was acidified, denaturing the chlorophyll-a protein. The difference between absorbance before and after acidification was absorbance due to the presence of chlorophyll-a. 4.1. Data analysis Patterns in chemical profiles were compared to ascertain any similarity in macro-trends of water quality over a 12-month period between August 1994 and July 1995. Micro-trends within dams were contrasted with previously identified chemical relationships in farm dams and similar water bodies to further explore relationships between land use and water quality.
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Table 2 Physicochemical parameters recorded from dams at field sites during the study period and methods used Parameter
Method/instrument used
Water temperature pH Conductivity Salinity Dissolved oxygen (%) Dissolved oxygen (ppm) Turbidity Redox potential Air temperature Water level fluctuation Light penetration Productivity/biological oxygen demand Alkalinity Chlorophyll-a Reactive phosphates Total phosphates Nitrates (1) Nitrates (2) Nitrites Ammonium ions Total nitrogen Copper Zinc Magnesium Potassium
Water quality logging system Water quality logging system Water quality logging system Water quality logging system Water quality logging system Water quality logging system Water quality logging system Water quality logging system Thermometer Metre rule Secchi disk BOD bottles and DO metre Dual endpoint titration Extraction, absorbance Complex, absorbance Persulfate digest Acid hydrolysis UV absorbance Complex, absorbance Complex, absorbance Persulfate digest Atomic adsorption spectrometry Atomic adsorption spectrometry Atomic adsorption spectrometry Atomic adsorption spectrometry
Results were analysed using JMP software (SAS Institute, 2001). Six samples were randomly selected from each set of 24 h samples taken over 12 months for each dam and tested using a two-way ANOVA for repeated measures. Mean values from processing of parameters sampled once per month were tested using a two-way ANOVA for mean values (Sall et al., 2001). Specific parameters identified as indicative of chemical or thermal stratification were selected from the above data sets and replicate samples from the surface and benthos of the two deeper dams, Dam 1 and Dam 2, were tested for stratification using bivariate ANOVAs. Trends within dams were then examined with respect to the chemical processes that were interacting and defining the chemical profile of each dam. Inter-relationships between parameters were explored using regression analysis.
5. Results 5.1. Comparison of dams Trends from raw data indicated that there was a difference between the three dams on the basis of parameters commonly used to profile the chemistry of freshwaters (Table 3).
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Table 3 Some important physicochemical characteristics of the waters in three dams sampled at Raglan, New South Wales, between August 1994 and July 1995 (ranges indicate mean values of monthly measurements taken at 30 cm below the water surface) Parameter (◦ C)
Water temperature Dissolved oxygen (mg/L) pH Conductivity (S/cm) Salinity (parts per thousand, ‰) Redox potential (mV) Turbidity (NTU) Secchi disk transparency (cm) [HCO3 − ] alkalinity (mg/L) Nitrate (mg/L) Total nitrogen (mg/L) Total phosphate (mg/L) Chlorophyll-a (g/L)
Dam 1
Dam 2
Dam 3
7.3–28 4.7–11 7.7–9.3 0.26–0.43 0.2 90–350 9.0–63 60–130 43–84 0–0.84 0–1.6 0.01–0.55 0–22
6.7–28 2.5–14 7.6–9.1 0.49–0.80 0.3–0.4 13–360 9.0–90 20–230 79–170 0–1.60 0–2.5 0.04–0.71 0–130
5.4–28 0.06–27 6.6–9.1 0.25–0.87 0.1–0.4 −430–410 14–210 15–60 37–390 0–1.45 0–9.9 0.13–2.8 20–390
Waters in the three dams were identified as significantly different across both sets of physicochemical parameters tested at a 95% confidence level (Table 4). The only deviations from this outcome at a 99% confidence level were for temperature and chlorophyll-a levels. Dam 1 and Dam 2 both showed evidence of stratification at 99% confidence level across the majority of parameters examined (Table 5, Figs. 3 and 4). Stratification was most evident with temperature, pH and redox potential (Fig. 5). Dissolved oxygen, closely linked with redox potential, only showed clear stratification in both dams at 95% confidence level. It appeared that there were two periods of stratification during the 12-month study period in Dam 1. The first and most obvious of these was during summer (December/January) when Table 4 F values for two-way ANOVA tests on comparisons of data from three dams at Raglan, New South Wales, collected between August 1994 and July 1995 Test
Parameter
F-value
d.f.
Probability >F
Two-way ANOVA with repeated measures
Temperature pH Turbidity Salinity Conductivity Redox potential Dissolved oxygen
5.99 477 33.6 33500 34100 23.6 14.8
2 2 2 2 2 2 2
0.0122 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.0003
Two-way ANOVA with mean values
Total phosphorus Total nitrogen Alkalinity Chlorophyll-a Light penetration
31.3 9.40 32.9 5.38 6.05
2 2 2 2 2
<0.0001 0.0013 <0.0001 0.0125 0.0080
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Table 5 F values for bivariate ANOVA tests for stratification in Dams 1 and 2 at Raglan, New South Wales, for data collected between August 1994 and July 1995 Dam
Parameter
F-value
d.f.
Probability >F
Dam 1
Temperature pH Redox potential Dissolved oxygen
150 64.9 116 4.38
23 23 21 23
<0.0001 <0.0001 <0.0001 0.0481
Dam 2
Temperature pH Redox potential Dissolved oxygen
380 24.7 19.2 19.4
23 23 21 23
<0.0001 <0.0001 0.0003 0.0002
there was apparent chemical and thermal stratification followed by the common autumn overturn. A subsequent period of stratification then developed during winter (June/July) with a less common overturn in the spring (Fig. 3). In Dam 2 the period of summer stratification was longer and more distinct, and followed by a single annual overturn in late autumn (Fig. 4). Dam 3 was too shallow to develop any clearly identifiable layering using the available equipment. 5.2. Patterns of plant nutrient levels within dams Dams 1 and 2 showed similar trends across the year in concentrations of nutrients and the closely linked chlorophyll-a level (Fig. 6). However, the patterns for each of these parameters for Dam 3 were quite different. Trends for bicarbonate alkalinity were similar for Dam 1 and Dam 2, although the concentrations measured in Dam 3 were approximately double (Fig. 6). Again patterns of alkalinity for Dam 3 were different, indicating that water in this dam was exposed to a different set of chemical impacts. Comparison of fluctuations in concentration for nitrogen, phosphorus, chlorophyll-a and alkalinity from Dam 3 with the corresponding annual rainfall profiles showed a connection between peak rainfall events and subsequent reduction in concentration of total nitrogen and total phosphates (Fig. 6). Similarly, links between seasonal peaking of chlorophyll-a in spring (September/October) and reduced levels of nitrogen and phosphates were noted, with a similar reduction in levels of chlorophyll-a after significant rainfall events in December–January and May–July 1995. 5.3. Diurnal patterns within dams Diurnal turbidity levels in Dam 1 during autumn were consistent during daylight hours but rose during the hours between 10 p.m. and 4 a.m. (Fig. 7a). This peak coincided with the autumn mixing period, occurring concurrently with the disturbance of bottom sediments by the circulating waters. Patterns of pH in Dam 1 during summer and autumn indicated a response to a number of phenomena. In early summer daily pH levels were consistently very high, around pH
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Fig. 3. Variation of selected water quality parameters in Dam 1 between August 1994 and July 1995: (a) temperature; (b) pH; (c) dissolved oxygen ((×) surface, (䊐) benthic). Arrow indicates region of stratification. N.B. Area in between arrows indicate period of stratification.
9 (Fig. 7b), but following high rainfall in January 1995 dam waters were diluted with the mildly acidic rainfall and runoff, and subsequent diurnal pH ranges over the next few months were lower, between pH 8 and 8.5 (Fig. 7b and c). During this late summer and autumn period pH peaked in the late afternoon, immediately following the period of maximum
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Fig. 4. Variation of selected water quality parameters in Dam 2 between August 1994 and July 1995: (a) temperature; (b) pH; (c) dissolved oxygen ((×) surface, (䊐) benthic). Arrow indicates point of mixing. N.B. Area in between arrows indicate period of stratification.
photosynthetic activity. After dark respiration is dominant and pH dropped to a diurnal low overnight. This pattern was repeated in Dam 2 particularly during autumn (Fig. 8a) although during the drier months there was an increase in water use for irrigation, resulting in an unstable diurnal pH curve.
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Fig. 5. Variation of redox potential between August 1994 and July 1995 for (a) Dam 1 and (b) Dam 2 ((×) surface, (䊐) benthic) and (c) Dam 3.
A second parameter closely linked with photosynthesis is dissolved oxygen concentration, and in Dam 2 during summer and autumn this was closely tied to daily light availability, with peaks late in the afternoon following the extended period of photosynthetic activity (Fig. 8b and c). Corresponding lows in dissolved oxygen concentration were evident in the hours before dawn when respiration was again the dominant process.
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Fig. 6. Comparison of selected water quality parameters for three dams between August 1994 and July 1995: (a) chlorophyll-a, (b) bicarbonate alkalinity, (c) total nitrogen, (d) total phosphorus ((×) Dam 1, (䊐) Dam 2, (䉬) Dam 3).
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Fig. 7. Daily variation of selected water quality parameters in Dam 1, sampled at Raglan, New South Wales, for selected seasons between August 1994 and July 1995: (a) autumn 1995 turbidity, NTU ((䉬) February, (䊐) March, () April); (b) summer 1994/1995 pH ((䉬) November, (䊐) December, () January); (c) autumn 1995 pH ((䉬) February, (䊐) March, () April).
Measured levels of conductivity were higher in Dam 2 (Table 6; Fig. 8d). Daily patterns for conductivity had similar ranges throughout the year to those shown in Fig. 8d but patterns for autumn showed more erratic values during the period corresponding to constant water use for irrigation, pumped from the dam, coupled with replenishment from groundwater supplies. During autumn Dam 3 showed a similar trend to the other dams for pH with daily increases associated with photosynthetic activity, and decreasing after nightfall (Fig. 9a). Patterns for dissolved oxygen again followed a similar trend, but were erratic in Dam 3 during summer and autumn (Fig. 9b and c). Conditions in Dam 3 during the hours of darkness became quite anoxic, with dissolved oxygen levels generally reduced to zero, or very close to this. Concurrent redox potential changed from the values associated with oxygen richness of around 400–500 mV to those indicative of anaerobic conditions of 0 mV, and on occasions lower again to a reducing environment with values to as low as −400 mV (Fig. 9d).
Dam/season
Temperature (◦ C)
pH
Conductivity (mS/cm)
Salinity (‰)
DO2 (ppm)
Turbidity (NTU)
Dam 1 Spring, October 1994 Summer, January 1995 Autumn, April 1995 Winter, July 1995
16–19 24–28 11–12 7.3–7.9
8.4–8.6 8.4–8.7 8.2–8.2 8.2–8.4
0.36–0.37 0.35–0.37 0.41–0.42 0.40
0.2 0.2 0.2 0.2
7.5–8.8 4.7–6.4 7.4–8.1 10
14–22 18–39 21–41 32–41
170–210 160–190 280–350 300–320
Dam 2 Spring, October 1994 Summer, January 1995 Autumn, April 1995 Winter, July 1995
18–20 22–23 13–14 6.7–7.3
8.2–8.4 7.8–8.2 7.5–8.5 7.6–7.7
0.72–0.73 0.76–0.77 0.76–0.78 0.73–0.73
0.4 0.4 0.4 0.4
8.2–9.5 2.5–5.0 4.7–9.0 5.8–7.1
17–22 27–41 63–90 33–49
170–230 13–310 210–250 270–360
Dam 3 Spring, October 1994 Summer, January 1995 Autumn, April 1995 Winter, July 1995
13–16 21–23 9.7–13 5.4–8.6
6.8–8.6 6.8–8.0 7.5–8.5 6.9–7.8
0.25–0.33 0.35–0.42 0.84–0.87 0.35–0.37
0.1–0.2 0.2 0.4 0.2
3.2–17 0.06–9.6 0.22–12 0.20–5.2
35–205 36–94 35–71 57–94
230–370 −1.0–400 220–330 360–410
Redox potential (mV)
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Table 6 Seasonal diurnal ranges for chemical parameters measured hourly for 24 h from three dams at Raglan, New South Wales, sampled between August 1994 and July 1995
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Fig. 8. Daily variation of selected water quality parameters in Dam 2 between August 1994 and July 1995: (a) autumn 1995 pH ((䉬) February, (䊐) March, () April); (b) summer 1994/1995 dissolved oxygen, ppm ((䉬) November, (䊐) December, () January); (c) autumn 1995 dissolved oxygen, ppm ((䉬) February, (䊐) March, () April); (d) autumn 1995 conductivity, mS/cm ((䊐) February, () March, (×) April).
Diurnal turbidity patterns in Dam 3 showed some interesting variations during spring and autumn (Fig. 10a and b). In October 1994, there was a brief period of elevated turbidity between 10 and 2 a.m. that could be associated with a flushing event although this was not a storm surge. Late afternoon peaks evident from Dam 3 during spring through to autumn were associated with stock watering and cooling behaviours, and were absent during winter (Fig. 10c).
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Fig. 9. Daily variation of selected water quality parameters in Dam 3 between August 1994 and July 1995: (a) autumn 1995 pH ((䉬) February, (䊐) March, () April); (b) summer 1994/1995 dissolved oxygen, ppm ((䉬) November, (䊐) December, () January); (c) autumn 1995 dissolved oxygen, ppm ((䉬) February, (䊐) March, () April); (d) summer 1994/1995 redox potential, mV ((䊐) December, () January, (×) March).
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Fig. 10. Daily variation of selected water quality parameters in Dam 3 between August 1994 and July 1995: (a) spring 1994 turbidity, NTU ((䉬) August, (䊐) September, () October); (b) autumn 1995 turbidity, NTU ((䉬) February, (䊐) March, () April); (c) winter 1995 turbidity, NTU ((䉬) May, (䊐) June, () July); (d) annual 1994/1995 salinity, ‰.
Of the three dams, Dam 3 was the only dam that showed any notable variation in salinity during the entire study period. In general, lower values corresponded with peak rainfall periods and higher values with drier periods, indicating a link with runoff flushing through the dam and evapo-concentration (Fig. 10d).
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6. Discussion 6.1. Water sources for the dams The hydrology and water quality of farm dams are controlled by the exchange of water and solutes with adjacent uplands. Mechanisms of water and solute transfers include precipitation, runoff, evapo-transpiration and subsurface flows. Of these, direct precipitation generally comprises less than one-tenth of the total water input, while surface waters as runoff from the drainage basin can comprise nearly all of the water input into a reservoir (Wetzel, 1999). Each of the dams showed variations in water chemistry that corresponded to a different set of inputs. Groundwater can also enter farm dams as discrete springs. This happens frequently in hard water reservoirs such as in the study area in the Bathurst district, or where the basin is effectively sealed from groundwater seepage by sediment deposits. Of the three dams in Raglan, Dam 2 is known to be spring fed. However it is not clear whether the only input into Dam 2 is via springs or also via a seepage pathway. Contour banks constructed around the dam channel runoff away, limiting input to direct precipitation and groundwater. Comparison of this dam with the other dams provides some kind of benchmark for groundwater input. Dam 1, the largest dam, showed some similarity in trends of water quality, indicating some input in the form of groundwater to this dam. Additional input from runoff explains the differences in water quality between the two dams. The adjacent pasture provided a runoff catchment for Dam 1, along with a concurrent input of particulate matter and dissolved chemical species. Transportation of sediments into the dam is influenced by rainfall intensity, temperature, soil moisture and discharge conditions, catchment shape, variations in surface condition and vegetation cover, and sediment supply (Webb et al., 1995; Basnyat et al., 2000). Trends of chemical patterns in Dam 3 show little similarity to either of the other two dams, indicating that this dam relies primarily on waters from a different source. This dam collected runoff from the nearby urban and industrial areas via a creek, as well as from adjacent agricultural lands. While Dam 1 collected agricultural runoff from grassland, Dam 3 collected runoff from a range of urban and rural land use areas. 6.2. Water quality influences Low-intensity rainfall in general mobilises less nutrient laden sediment than high-intensity storm events, although soil moisture and permeability also contribute to sediment movement (Basnyat et al., 2000). The resulting nonpoint source pollution is more difficult to quantify than pollution from a single source. Runoff sediment transport capacity is dictated by the shear stress relationship that develops between the dominant flow shear of the soil and the critical stress from rainfall events (Leon et al., 2001). Raglan is situated on impermeable bedrock of granite, with gully soils comprising mainly sodolics (sodosols), which have low permeability and a resulting higher erosive potential. Thus dams that are exposed to runoff input are also exposed to a potentially high sediment load from the soils. Areas of impervious cover associated with urbanisation have important impacts on storm surges and concentration of pollutants (Wear et al., 1998), impacts that affect Dam 3. Soil
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surface crusting associated with sodolics was noted on the hillside above Dam 1. This crusting can contribute to storm flow by reducing the infiltration of rainwater into soils (Zhu et al., 1999). The soil water balance dictates whether waters and associated sediment and nutrient loads will be transported as runoff or via a longer pathway as groundwater (Bellot et al., 2001). The principal pathway for the transport of a particular compound is determined by a number of factors. The first and most important of these is the chemistry of the compound, followed by the hydrology of the region, which together determine the relative roles of groundwater leaching and runoff transport pathways. The final factor is land use (Blanchard and Lerch, 2000). Most contaminants affecting water quality in rural areas comprise simple inorganic ions, more complex organic molecules or particulates. Among other sources, including soils and decomposing vegetation, each of these can result from animal manure (Goss et al., 2000). Each of these sources is known to impact both Dam 1 and Dam 3, and not Dam 2. Animal manure potentially provides a source of nitrate, phosphate, toxic metals and bacteria. The organic matter in manure alters the physicochemical properties of the soil, increasing the mobility of contaminants and resulting in movement through the soil in a wider range of conditions. Preferential flow paths can develop due to structures present in the surface soil or in the subsurface across soil horizon boundaries. This preferential flow can carry water and contaminants to depth very rapidly (Goss et al., 2000). This can result in contamination of groundwater with higher than expected levels of nitrates and phosphates, and may explain the high levels of each of these in Dam 2. 6.3. Links with adjacent land use There is considerable agreement in recent studies that amounts of nitrogen and phosphorus in surface waters are significantly influenced by anthropogenic inputs associated with land cover, land use and point sources (e.g. Castillo et al., 2000; Ferrier et al., 2001; Valiela and Bowen, 2002). However, there is less agreement on the exact nature of these relationships. Once mobilised from surficial clay complexes, phosphorus is transported in solution via groundwater aquifers (Cox and Ashley, 2000). Phosphates tend to show little seasonal variation, although concentrations may increase slightly during periods of low runoff flow (Castillo et al., 2000). In both Dam 1 and Dam 2, phosphate levels showed this slight increase after the long dry period in autumn. In Dam 3 the relationship was more apparent as a decrease in phosphate levels in conjunction with the high rainfall events during summer. Thus evapo-concentration and dilution following storm surges are important regulators of phosphate concentration in farm dams. Nitrates can potentially be leached or transported in runoff (Blanchard and Lerch, 2000). Nitrates are strongly associated with agricultural land and grasslands (Ferrier et al., 2001), and concentrations are highest in spring and in conjunction with high runoff events. Each of the three dams studied reflected this spring increase to some degree. Dam 3 demonstrated a relationship between nitrogen and runoff events with peaks in concentration evident concurrent with high rainfall periods. Ferrier et al. (2001) found that urban catchments were highly correlated with ammonium ions, reactive phosphates and suspended solids. This dominance of ammonium ions in the
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total nitrogen, and reactive phosphates in the total phosphorus was also identified in Dam 3, suggesting that there was a significant impact from runoff from the urban areas that outweighed the input from the agricultural areas. In contrast, Dam 1 and Dam 2 showed a dominance of nitrogen as nitrate ions. In summary, with the current reduction in resource availability in eastern Australia due to ongoing drought and increasing competition for resources on an already stressed system, there is a need to maintain optimal water quality in the available water resources. A significant portion of this is reserved in farm dams, either for domestic supply, stock or irrigation. If potable water is to continue to be available from these dams they need to be managed in a way that promotes this aim either by planting trees to retain water and nutrients away from the dams, or wetland plants to remove excessive nutrients from the dam, and management of cropping and grazing in the adjacent basin catchment. If dams are to be managed as nutrient/sediment traps for the protection of nearby stream systems this needs to be conducted in a manner that minimises nutrient leaching by groundwater pathways, again by incorporating appropriate vegetation strategies in the management strategy. 7. Conclusions The presence of important plant nutrients, such as nitrates and phosphates has clearly influenced the development of photosynthetic algae in normal seasonal patterns. Dams with higher levels of nutrients tended to have higher levels of chlorophyll-a, leading to higher oxygen production, with linked fluctuations in pH, and redox potential. Particulate sediment inputs affected levels of turbidity, light penetration and the ratio of photosynthetic activity to respiration. Dissolved inorganic ions similarly affected levels of salinity and conductivity. Thus many of the chemical processes examined in the dams can be linked to the input waters, which in turn reflect their origins. For Dam 2 this was almost entirely groundwater, while for Dam 1 the groundwater input was tempered with pasture runoff. For Dam 3, it was the runoff from a landscape mosaic of urban, industrial and pasture lands that affected the water quality most and the influence due to groundwater input was probably negligible. This suggests that, in these dams at least, land use forms only part of the impact on water quality. A more complete picture would include water sources, with accompanying ion transfer pathways and attendant aquifer recharge and discharge patterns, rather than merely a linking to immediate land surface characteristics. References Ali, A., Frouz, J., Lobinske, R.J., 2002. Spatio-temporal effects of selected physico-chemical variables of water, algae and sediment chemistry on the larval community of nuisance Chironomidae (Diptera) in a natural and a man-made lake in central Florida. Hydrobiologia 470, 181–193. Alvarez-Cobelas, M., Baltanas, A., Velasco, J.L., Rojo, C., 2002. Daily variations in the optical properties of a small lake. Freshwater Biol. 47, 1051–1063. ANZECC, 2000. An Introduction to the Australian and New Zealand Guidelines for Fresh and Marine Water Quality. Australian and New Zealand Environment and Conservation Council and Agriculture and Resource Management Council of Australia and New Zealand. http://www.ea.gov.au/water/quality/nwqms/ introduction/index.html.
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