The University of Western Australia
‘Hydrological Modelling of the 72 Keightly RoadGreywater Re-use Project’
David Rowlands
“This thesis is submitted in partial fulfillment for the degree ofBachelor of Engineering from the Department of Environmental
Engineering, at the University of Western Australia.”
November 2003
i
Acknowledgements
Throughout this year there have been many people who have generously given their time,
and support towards the completion of this project. I would like to thank all those who
offered help with the production of this thesis.
The first thank you goes to my supervisor Dr. Carolyn Oldham for her input of time,
advice and direction to the project.
Also thanks to Dr. David Horn and his wife Kay for providing the system design and
materials, garden and greywater required for this project to operate.
Thanks to Dr. Keith Smettem for sampling and analysis advice and providing the TDR
probe.
Thanks to Greg Holmes of Tanks West™ for construction of the sullage tank.
Lastly, thanks to Florence Verspecht and Melanie Jasper for their editing, help and advice
throughout the year.
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Abstract
The reuse of household greywater has the potential to significantly reduce Perth’s water
demand and consumption. However, the potential for adverse health and environmental
impacts cannot currently be eliminated. Low risk and viable methods of greywater
treatment and reuse need to be researched and trialled to further the development of
onsite greywater reuse beyond its infancy. While environmental impacts, processes
influencing rates of greywater decomposition and health risks are currently not well
quantified, the prevention of off-site greywater transport is a valuable precaution in
insuring that unwilling participants and locations are not placed at risk or degraded. This
thesis presents a greywater treatment and subsurface irrigation design accompanied by
the respective fittings and household modifications. With respect to this design, a field
analysis, box model and 1-D computer modelling approach have been applied to develop
a zero runoff and zero infiltration management strategy.
It is found that, despite the warm Mediterranean Perth climate, the highly permeable
Swan Coastal Plain sands allow deep infiltration throughout the year when vegetated with
shallow rooted turf. The quantity of deep infiltration to the groundwater is seasonally
accentuated, influenced by irrigation frequency and found to occur year-round. However,
surface pooling and surface runoff is of negligible risk. Warm season, C4, turf grasses
such as velvet buffalo can be sustained by a wide range of moisture availability, allowing
a simple and efficient irrigation regime to be devised.
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Table of Contents
ACKNOWLEDGEMENTS........................................................................................... I
ABSTRACT ................................................................................................................. II
TABLE OF CONTENTS............................................................................................ III
1.0 INTRODUCTION............................................................................................. 1
2.0 LITERATURE REVIEW ................................................................................. 2
2.1 CONCEPT OF GREYWATER RE-USE......................................................... 2
2.2 WHY REUSE GREYWATER? ...................................................................... 2
2.3 VOLUMES OF GREYWATER GENERATION. ........................................... 3
2.4 CONSTITUENCY OF GREYWATER ........................................................... 5
2.4.1 Boron ...................................................................................................... 6
2.4.2 Electrical Conductivity and Sodium......................................................... 6
2.4.3 Alkalinity (pH)......................................................................................... 8
2.4.4 Phosphorous and Nitrogen ...................................................................... 8
2.4.5 Microbial Contamination .......................................................................10
2.5 ADDITIONAL GREYWATER RE-USE RISKS ...........................................11
2.6 HYDROLOGICAL ASPECTS OF GREYWATER APPLICATION .............12
2.6.1 Interflow or Lateral flow.........................................................................13
2.6.2 Evapotranspiration.................................................................................14
2.6.3 Groundwater Recharge ..........................................................................18
2.6.4 Hydraulic Conductivity and unsaturated flow .........................................19
2.6.5 Subsurface drip irrigation.......................................................................22
2.6.6 Vegetation ..............................................................................................22
3.0 MATERIALS AND METHODS .....................................................................24
3.1 PHYSICAL SETTING...................................................................................24
3.2 GREYWATER RE-USE PROCESS DESIGN ...............................................25
3.3 SPLIT PLUMBING SYSTEM .......................................................................26
3.4 SYSTEM DESCRIPTION .............................................................................27
3.5 LAWN IRRIGATION NETWORK ...............................................................29
3.6 THE ‘TANK TEST’ EXPERIMENT..............................................................31
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3.6.1 Tank Test Materials ................................................................................31
3.6.2 Tank Test Setup ......................................................................................31
3.6.3 Tank Test Procedure...............................................................................33
3.7 ON-SITE MOISTURE CONTENT VS DEPTH MEASUREMENTS.............35
3.7.1 Preliminary Moisture measurements.......................................................35
3.7.2 Moisture versus depth data .....................................................................37
3.8 MATLAB BOX MODEL PROCEDURE.......................................................38
3.9 SOIL WATER INFILTRATION AND MOVEMENT MODEL (SWIM).......39
3.9.1 Water retention curve fit .........................................................................40
3.9.2 Saturated hydraulic conductivity.............................................................42
4.0 RESULTS.........................................................................................................45
4.1 LAWN IRRIGATION FINDINGS.................................................................45
4.2 TANK TEST RESULTS ................................................................................46
4.3 MOISTURE CONTENT FIELD RESULTS...................................................49
4.4 MATLAB BOX MODEL WATER BALANCE.............................................52
4.5 SWIM MODEL RESULTS............................................................................57
4.5.1 Water retention curve results ..................................................................57
4.5.2 Saturated hydraulic conductivity results .................................................58
4.5.3 Infiltration results...................................................................................59
5.0 DISCUSSION...................................................................................................62
5.1 GENERAL DESIGN......................................................................................62
5.2 WATER BALANCE......................................................................................63
6.0 CONCLUSIONS ..............................................................................................69
7.0 RECOMMENDATIONS .................................................................................70
8.0 REFERENCES.................................................................................................72
9.0 APPENDICES..................................................................................................77
1
1.0 Introduction
Historical epidemics of water-borne diseases, such as the famous cholera outbreak in
London 1849, have demonstrated the necessity for maintaining clean waterways and
water supplies in our population centers. Our ability to engineer solutions to this
population barrier, in the form of water treatment, sewerage and improved sanitation, has
enabled further expansion and development of our cities. However, new strains on
growth and development are beginning to appear in the form of resource shortages,
particularly water under-supply in arid regions such as the Middle East, parts of Africa
and Australia. In Australia water reuse has the potential to markedly relieve the burden
placed on potable water supply for irrigation and industrial purposes. The implementation
of household greywater reuse for irrigation purposes, in combination with a “water-wise”
garden plan, has the potential to reduce per-house water consumption by 38% (WAWA
1993). To minimize human exposure to virulent organisms and sustain a healthy
environment, research into the hydrological, chemical and microbiological processes
related to the various techniques of greywater treatment and application must be
performed. This will allow for cheap and safe methods of reuse to be devised and
approved.
This thesis focuses on on-site containment of irrigated greywater, through the derivation
of a hydrological balance, so as to reduce the risk of leaching of contaminants to the
environment. In addition, the sullage tank system (designed by Dr. David Horn) and the
subsurface drip irrigation network is evaluated.
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2.0 Literature Review
2.1 CONCEPT OF GREYWATER RE-USE
“Greywater” (“Graywater” in US literature), or “sullage”, is the term used to describe all
water discharged from a household that has not been soiled by toilet waste. This
incorporates shower, bath, kitchen and laundry wastes. In this study kitchen wastes have
been excluded from the greywater stream. Kitchen wastes generally have a high loading
of grease and organic solids, which cause blockages in greywater systems and can alter
hydraulic properties of receiving soils (DOH, WC & DEWCP 2002). Greywater is
distinct from heavily soiled toilet wastes, which are termed “blackwater”. In the average
household greywater and blackwater wastes are not partitioned but are jointly discharged
to the sewer as “wastewater”. Whilst both components of household wastewater have the
potential to be reused as a valuable resource, greywater is far easier, safer and cheaper to
recycle than blackwater (G. Marshall 1996). Excepting where kitchen wastes are
included, this is due partly to its characteristically lower BOD5, suspended solids and
thermotolerant coliform concentration (DEH 2001).
It is estimated that 18.4% (ABS 1998) - 20% (Stone 1996) of Perth householders illegally
reuse greywater, indicating a potentially hazardous legislative void and a demand for
practical suburban greywater technology. The risk and impact of this practice is currently
not well quantified.
2.2 WHY REUSE GREYWATER?
At present the cost of scheme water in Western Australia is very low relative to much of
the developed world. Ergo the incentive to conserve water and recycle wastewater is low
and often not economically beneficial. However, demand for greywater reuse is buoyed
by several factors of growing importance.
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Increased environmental awareness, due perhaps in part to school education programs
and corporate action, has spawned a desire among the public to reduce their ecological
footprint. Reduction in net household water consumption is one way in which people can
reduce the demand for new dams.
On a governmental level, the expected 5% per annum increase in wastewater ocean
outfall (WAWA 1995) cannot be sustained indefinitely without expense for new outfall
zones, increased capacity of treatment plants, potential for localized ocean eutrophication
and possible social objection to all such processes and developments. The possible 38%
reduction in household water consumption due to greywater reuse could effect similar
reductions in sewage flows, thus reducing the assimilative burden on our oceans and
treatment plants and reducing government expenditure. Additionally, this figure does not
incorporate the reduced irrigation requirement due to the increased efficiency of
subsurface drip irrigation as opposed to surface irrigation. This improved efficiency is
due largely to the reduced evaporative losses for subsurface irrigation employed by most
greywater reuse systems.
Less altruistic grounds for greywater reuse also exist. Recent water shortages in Perth
have lead to escalating restrictions on sprinkler-irrigation using potable scheme water.
During periods of water restriction a greywater reuse program provides a reliable source
of water for irrigation. Additionally, greywater contains many nutrients used by plants for
growth.
2.3 VOLUMES OF GREYWATER GENERATION.
Figure 1 illustrates the large proportion expenditure (47%) of potable water on garden
irrigation and the potential to supplement the irrigation by recycling other sections of the
pie chart, such as washing machine and bathroom derived wastewater, thus reducing
overall consumption.
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Figure 1. Water Corporation Domestic Water Usage 2002, taken from DOH, WC &
DEWCP (2002).
The chart partitions the 337kL per year, approximately 1000L per day, of water
consumed by the average 3.3 person household (DOH, WC & DEWCP 2002). It can be
deduced from Figure 1 that the summation of the greywater components, taps; washing
machine; and shower; represent a generation of approximately 125kL per year, or 340L
per day, of irrigable greywater for the average home. This result is approximately three
fifths of the garden irrigation requirement which is even greater than the 38% reduction
proposed by WAWA (1993). This reinforces the significant potential for reduced water
5
demand. Based on the average consumption figures, it is commonplace to linearly scale
the expected greywater generation for households greater or less than the average
(CDWR 1995), thus a 4 person home could produce 415L per day of greywater.
Californian standards recommend an estimate of 40Gal per person per day (CDWR
1995), which approximates to 605L per day for a 4 person house, however we may
expect differences in cultural practice from house to house and country to country.
2.4 CONSTITUENCY OF GREYWATER
In order to optimize the greywater irrigation rate, and assess the success of in-soil
treatment, it is important to understand the biological and chemical substances and
process that are to be contained by means of the hydrological balance, as they may affect
soil hydrological properties.
Bathroom and laundry greywater, 29-37% of total household water use depending on
contribution from taps (Figure 1), is generally contaminated with hair, lint and organic
particulates in addition to soaps, shampoos, hair dyes, toothpaste, body fats, oils,
disinfectants, nutrients (such as phosphorus and nitrogen), chemicals (such as sodium and
boron), and many other compounds that compose the Total Dissolved Solids (TDS)
loading of the water. Both bathroom and laundry greywater can also contain some faecal
contamination, and hence the potential for viruses and pathogenic bacteria.
Kitchen greywater, approximately 4% of total household water use or 11% of total
greywater volume (DOH, WC & DEWCP 2002), is generally heavily contaminated with
organic particulates, cooking oils, grease, detergents, and other cleaning products such as
dishwashing powders. Sporadic instances of very heavy faecal contamination have also
been recorded (NSW Health 2000). Some components of kitchen greywater may cause
soil to develop moisture repellent properties (DOH, WC & DEWCP 2002). Kitchen
greywater is omitted from many types of greywater systems due its moderately low water
contribution and to the high concentrations and low decomposition rates of the
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compounds mentioned above. Greywater systems which exclude kitchen wastes are free
from the impact of boron, super-phosphate and sodium containing kitchen cleaners, but
still vulnerable to these compounds in laundry products.
2.4.1 Boron
Boron is considered a plant micronutrient, required in only very small amounts, and is
found in adequate abundance in most soils (CDWR 1995). Boron is present in some
detergents and washing powders and possesses herbacidic properties when in
concentrations only slightly above those considered optimal for plant growth (CDWR
1995). Destruction of vegetation in the irrigation field reduces the potential for
transpirative water losses, thus increasing the likelihood of leaching and groundwater
recharge. Avoidance of boron containing cleaning agents is necessary to guarantee boron
accumulation does not occur within the soil. However some boron is acceptable (Table
1).
Table 1. US EPA and UNFAO boron risk levels to vegetation.
Boron Concentration C (mg/L) Risk Level
C < 0.75 Safe
0.75 < C < 2 Some risk
2 < C High risk
2.4.2 Electrical Conductivity and Sodium
Electrical conductivity is used as a measure of the concentration of dissolved salts and
minerals, including sodium, in greywater and soil. It is also empirically linearly related to
TDS. In general, the higher the conductivity, the higher the potential for adverse soil
effects (CDWR 1995). High soil conductivity reduces the ability of a plant to uptake
water by reducing its internal osmotic pressure (Short 2002), thus killing or seriously
inhibiting vegetation growth when available ions are in sufficiently high concentrations.
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High conductivities also imply an increased likelihood that specific ion toxicity levels
will be reached for the receiving vegetation.
Sodium ions are of particular importance due to their adverse effects on hydraulic
conductivity in soils containing clay. Large monovalent positively charged sodium ions
cause clay plates to become dispersed due the thick charge layer they create around clay
particles. The thickness of this adsorbed layer allows repulsive forces between particles
surrounded by their respective charge layers to dominate over attractive inter particle van
der Waals forces. Divalent cations, such as Mg2+ and Ca2+, create thinner adsorbed
charge layers around clay plates because of their higher charge densities, thus allowing
van der Waals attractive forces to bond clays together and remain stable (Whitlow 2001,
pp.11). Dispersed, sodium affected clay particles may move with pore water and clog soil
pore spaces, reducing the number of hydraulic pathways available to permeating fluids.
Soil water with low electrical conductivity and a high Sodium Adsorption Ratio (SAR) is
likely to result in a loss of hydraulic conductivity, as a result of clay dispersivity in clay
soils (Patterson 1996; DEH 2001). The SAR is a measurement of the exchangeable
sodium within the soil or the greywater and is characterized by
where the square brackets denote concentrations of the respective ions. However, the
ideal balance between SAR and conductivity depends on the soil type in the rootzone. A
lower boundary estimate for irrigation water is SAR < 3 to avoid increased soil sodicity
(ACT 1999). Water softeners affect a considerable negative influence on the SAR
because their purpose is to replace calcium and magnesium with sodium (Jeppesen &
Solley 1994). Thus water softening soaps and detergents are an undesirable greywater
constituent. Because of its reduction of the SAR, the periodic application of gypsum to
the irrigation zone is likely to aid in the long-term sustainability of greywater irrigation in
soils containing clay. For sandy, highly permeable soils with low clay content the
application of gypsum is likely to be an unnecessary precaution, but may be kept in
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reserve in the event of un-anticipated soil degradation and reduction of hydraulic
conductivity. Loss of hydraulic conductivity resulting from high sodium levels can lead
to soil water-logging, which in turn reduces the ability of vegetation to transpire and thus
process incoming greywater. Poor permeability and water-logging may cause greywater
to disperse laterally across property boundaries, thus breaching draft state health
department guidelines (DOH, WC & DEWCP 2002).
Sodium sulphate can compose up to 40% of laundry compounds and functions merely as
a bulking agent. Concentrates do not require bulking agents and thus contain less sodium.
Some laundry compounds contain potassium salts as an alternative bulking agent.
Potassium salts do not display deleterious effects on soil chemical or physical properties
(Patterson 1996). Potassium is also a readily utilized plant nutrient and hence less likely
to accumulate within the soil as it can be removed from the root-zone via vegetation
uptake followed by harvesting, mowing or pruning.
2.4.3 Alkalinity (pH)
Soil pH affects the availability of nutrients to plants. Effluent within the range of 6.5-8.5
is acceptable for irrigation (ACT 1999) however suitably tolerant vegetation must still be
considered (Section 2.6.6 & Appendix 1). The presence of hydroxides, potassium,
sodium, calcium and other alkali’s from soaps, toothpaste and cleaning compounds cause
greywater to be generally alkaline, thus greywater pH may range from 6.5-9 (Water
Corporation 2003). pH also effects the type, health and efficiency of soil microbes which
aid in greywater decomposition, thus making extreme pH’s even more undesirable.
Gypsum can be applied to lower pH in soils suffering from high alkalinity.
2.4.4 Phosphorous and Nitrogen
Phosphate is an essential plant nutrient added to fertilizers to enhance growth.
The weathered alluvial sands of the coastal plain are often low in phosphate due to their
highly permeable and leached nature. Phosphates present in greywater from detergents
and washing compounds may be of benefit to garden plants, if not overly concentrated.
9
However, not all forms of phosphate are readily usable by plants and soils (CDWR
1995), thus highlighting the need for containment until proper decomposition and
biological uptake has occurred. The potential for rapid leaching of phosphates and
nitrogenous compounds without decomposition or biological uptake is of concern in
highly permeable soils. Nitrogen and phosphorus pose eutrophication risks to waterways
and contamination risks to groundwater if biochemical degradation timescales
significantly exceed transport timescales. However, phosphorus input to greywater may
be reduced by using low phosphorus detergents. Soil-based nutrient removal processes
can invoke substantial levels of denitrification in the presence of sufficient quantities of
labile carbon (EPRI 2001), implying a periodic organic top dressing of the irrigation zone
may be beneficial. The addition of clays to highly permeable soils will allow for some N
and P adsorption, slow leaching rates and increase effluent residence time within the
microbially active surface layer, the top 300 mm of soil where most of the nutrient
decomposition occurs (Farwell 1993, cited in Jeppesen & Solley 1994). Many of the
nutrient removal processes associated with turf vegetation itself also occur within the
microbially active layer, at the top 200mm of soil containing much of the root network
(Barton & Colmer 2001). However, the addition of clay poses the risk of soil
degeneration through sodium damage (Section 2.4.2). Iron, calcium and aluminium
convert soluble phosphorous to insoluble precipitates and thus may aid in immobilization.
If greywater irrigation and rainfall is not properly balanced with garden
evapotranspiration (ET) rates then, in the event of insufficient biological uptake and
decomposition, leaching of nutrients to the groundwater and waterways may occur.
“Human health is primarily at risk from high nitrate-N concentrations in groundwater
used as drinking water, although in some cases (i.e. surface reservoirs) potentially
carcinogenic by-products of algal blooms are also of concern” (EPRI 2001).
Methemoglobinemia in infants, or “blue baby” syndrome, is one such health risk. Unlike
nitrogen, phosphorous is not directly toxic to humans (EPRI 2001), however it does serve
as the primary limiting nutrient for eutrophication in fresh waterways. In the event of
groundwater extraction for drinking purposes additional expenditure would be required
for N and P reduction if significant seepage of nutrients was allowed to occur.
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2.4.5 Microbial Contamination
Microbial contamination of fluids is commonly estimated as the number of viable colony
forming thermotolerant coliforms per 100mL of sample (cfu/100mL). Thermotolerant
coliforms are bacteria that live in the intestines of mammals and are used as indicator
organisms for the likelihood of human pathogenic contamination. Greywater is more
dilute than blackwater, but may still contain coliform densities well above the
Department of Health guidelines judged safe for human contact of 10 cfu/100mL (DOH,
WC & DEWCP 2002). Typical raw sewage effluent levels of 106 to 108 cfu/100mL help
contextualize greywater coliform densities of 10 to 107 cfu/100mL , with rare
occurrences of up to 2x109 cfu/100mL in kitchen wastes (NSW Health 2000).
Predominant factors which lead to such great variation in microbial contamination
include; the exposure of greywater to faeces such as in houses containing children using
recyclable nappies; and the storage time of effluent. Storage can lead to a 10-100 fold
increase in coliform density in the first 24-48 hours (NSW Health 2000). Duration of
storage of organic effluent such as greywater also increases the likelihood of anoxia
which may lead to the evolution of noxious hydrogen sulphide gas from sulphur reducing
bacteria (Hemond & Fechner-Levy 2000, pp.129). Hydrogen sulphide gas is a major
cause of odour in wastewater treatment and swampland.
Subsurface irrigation of effluent allows the negation of the 10cfu/100mL constraint,
providing there is no risk of human exposure. Irrigation of greywater in the top 300mm of
the soil column incurs a greater pathogenic mortality rate than that of surface irrigation
(ACT Environment 2003; Jeppesen 1996). With the exception of such pathogens as
Campylobacter, Legionella and Vibrio, most pathogenic bacteria are rapidly digested in
the aerobic soil environment (Prescott, Harley & Klein 1999) without their mammalian
hosts. However, survival of the order of months cannot be discounted for some
organisms. The general rapid mortality of pathogens in the soil is possibly due to
predation by protozoa, parasitism by Bdellovibrio and other organisms, lack of space,
lack of certain required nutrients, and the presence of certain microbial toxins (Prescott,
Harley & Klein 1999), such as phenols secreted by wood. Soil appears to act as a highly
effective medium for pathogen inactivation and immobilization, retaining most foreign
11
bacteria in the upper few centimetres (Frankenberger 1992). The huge historical success
of sand filtration of drinking water for prevention of cholera transmission is testimony to
the unlikelihood of groundwater microbial contamination in any but the shallowest of
water tables. Microbial health risks are far more likely to occur in soils of low
permeability where surface pooling or runoff may occur.
2.5 ADDITIONAL GREYWATER RE-USE RISKS
Diversion of greywater from the sewage mains may decrease the velocity and increase
the density of the flow through the pipes. This has the potential to increase blockage
risks. Additionally, wastewater treatment plants are designed to process sewage that has
been diluted with greywater. Increased organic loading and higher fluid density may not
be conducive to the efficiency of the aerobic treatment process of most wastewater
facilities, implying a possible need for increased residence times in aeration ponds or
some other design upgrade. Acute highly concentrated bursts of illegally disposed
industrial chemicals, such as hydroxide, are occasionally detected at wastewater
treatment plant inflows. These chemicals have highly deleterious effects on the aerobic
micro-flora central to the treatment process. Weak acids and bases, such as those present
in greywater, dilute and buffer the pH of concentrated chemical pulses (Atkins 1996, pp.
166). In the event that gradual wide scale greywater reuse was to be adopted, solutions to
the obstacles mentioned above would need to be engineered and integrated as required.
On the household to household scale, the significance of health risks associated with
greywater reuse is uncertain. The general approach of the regulatory bodies in Australia
has been to err on the side of caution, disallowing direct land surface application of non
secondary treated and disinfected greywater. Limits on untreated greywater sullage tank
residence times have also been recommended due to the known rapid multiplication of
stored thermotolerant coliforms.
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Chemical fate and transport of greywater constituents is governed by soil type,
temperature, rainfall, on-site vegetation types, humidity, soil microbes and many other
factors. The long term fate and transport is not well understood due to the great potential
for case-by-case variability of the above-mentioned parameters.
2.6 HYDROLOGICAL ASPECTS OF GREYWATER APPLICATION
When water falls on the land surface it may be partitioned into overland flow, or runoff,
and infiltration, water that is absorbed into the soil storage. Overland flow results when
ET and soil infiltration rates are insufficient to prevent surface pooling of water. Surface
pooling and overland flow are undesirable with respect to greywater irrigation because
they imply the potential for off-site transport of greywater contaminants and increased
possibility for human contact. Over-irrigation and heavy rainfall increases soil saturation
and reduces soil infiltration capacity, the ability for soil to absorb more water. Soil
hydrological suitability for greywater irrigation with respect to its ability to conduct flow
is tabulated below (Table 2). The highly permeable alluvial nature of the sandy soils of
the Swan Coastal Plain, which encompasses most of the Perth metropolitan area, means
that infiltration capacities will remain generally high under most conditions. This poses a
low risk of surface pooling. However, the resultant high rate of gravity drainage, vertical
gravity-driven seepage, with its potential for groundwater recharge is of prime interest in
this thesis, as groundwater recharge represents a possibility for contaminant transport. Of
secondary interest is the risk potential for lateral subsurface flow, or interflow.
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Table 2. Five Soil type descriptions with effluent irrigation suitability.
Based on Patterson (1996).
Soil Type Suitability for land effluent disposal
Alluvial Sand - surface soil from a coastal
river or floodplain. Dominantly sand with
small amounts of clay and organic matter. pH -
variable. (Similar to most Perth metropolitan
soils)
Yes, with caution.
Black Earth – medium clay, clay content 40-
50%, high shrink-swell capacity, high fertility,
pH around 6.5.
No. Poor initial percolation loss.
Red Brown Earth – clay loam, red color due
to iron oxides, poor organic matter content,
sets very hard on drying. pH – variable.
No. Rapid loss of percolation.
Krasnozem – red loam, high in iron oxides,
extremely water stable aggregates, pH 5.4.
Yes. Suitable for short term irrigation.
Yellow Solodic – medium clay, high sodium
content, extremely dispersible, erodible, poor
wet strength. pH – variable.
No. High SAR and soil degradation
risk.
2.6.1 Interflow or Lateral flow
The occurrence of one type of lateral flow, interflow, is favoured by layered or stratified
soils (Fetter 2001, pp. 39) where a hydraulically conductive soil layer is underlain by a
low permeability layer. Interflow poses the potential for transport of greywater to
adjacent properties and the possibility of re-surfacing if land elevation falls below the
depth of the low permeability bounding layer (Figure 2).
14
Figure 2. Interflow schematic.
Drilling logs (Table 4 & Appendix 2) indicate no significant soil stratification. Tthe
homogeneity of the sand supports the unlikelihood of interflow.
Lateral flow may also be a direct result of steeply sloping soil profiles where gravitational
and surface tension forces acting on the water become larger than the attraction of water
to the soil (Frank et al 2001).
2.6.2 Evapotranspiration
Evapotranspiration is the process by which water is conveyed to the atmosphere from
vegetative surfaces (Augustin 1983). ET (mm H2O) comprises two components,
evaporation and transpiration. Evaporation is a purely physical process which may take
place on vegetative or moist abiotic surfaces. Transpiration is the uptake of liquid water
by plants, usually through the roots, and expulsion to the atmosphere as a vapour,
generally through the leaf stomata. The term evapotranspiration was coined due to the
virtual impossibility of separating evaporation from transpiration in plants without the
means of measurement having adverse effects on the processes themselves. Factors
which govern the rate of ET are wind, temperature, irradiance, humidity, vegetation type,
and soil moisture (Rosenberg 1974). It is hoped evapotranspiration will represent the
15
dominant water loss term in the irrigation water balance. Thus an accurate estimation of
either ET or infiltration is highly desirable, so as the missing term can be deduced.
For warm season turf-grasses, the type of grass and how it is managed effects only small
changes to the ET if the grass is actively growing and is not moisture limited (Biran et al
1981; Short 2002). Minimal ET occurs during dark cloudy days with high humidity, low
temperatures and little wind (Augustin 1983), thus boding poorly for wintertime
greywater irrigation of warm season turf grasses.
Potential Evapotranspiration (ETp) is often used as an estimate of actual transpiration.
ETp is the ET expected for a spatially continuous turf which completely covers its
substrate, is not moisture limited and exerts little resistance to the flow of moisture from
the soil to the atmosphere (Augustin 1983). ETp generally ignores specific plant ET
capabilities. Actual ET is generally less than ETp because one or more of the factors
mentioned is limiting. Most of the empirical ET equations compute ETp rather than ET
and thus provide an upper bound for the actual field ET. One such equation is the
commonly used Penman equation (Penman 1948)
γγ
γ +∆
−+
+∆
−∆=
))(()( eeufGRET sn
p
where _ is the slope of the saturation water vapor pressure (mbar) vs temperature curve
(°C), Rn is the net radiation (cal cm-2 day-1), G is the soil heat flux, _ is the psychometric
constant (0.65 mbar °C-1), f(u) is Penman’s empirical wind function, e is the mean vapor
pressure at temperature T (mbar) and es is the saturated vapor pressure at temperature T
(mbar). Penman’s model tends to slightly underestimate ETp, but can provide good
correlation to actual ET for arid regions (Haque 2002). There are many other empirical
formulas for the estimation of ETp, including the Morton, McCloud and the Thornthwaite
models.
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16
ET estimation for a vegetated area is often assumed proportional to Epan according to the
following relationship
panEpcropcrop kk ET =
pancrop kE ET =
where Epan (mm) is the evaporation from a US ‘Class A’ pan, kp is a dimensionless
constant for the conversion of Epan to actual field evaporation, kcrop is a dimensionless
crop coefficient for the conversion of evaporation to a specific crop ET estimate ETcrop
(mm) and k is the combined coefficient of kp kcrop. This process of ET estimation is
termed the “crop coefficient” or “crop factor” method. By this method Epan is scaled by a
pan specific coefficient (kp) and known reference crop coefficient (kcrop) for a similar
plant type to calibrate the relationship of Epan to ET (Bevan 2001, pp. 61). The result is an
estimate of ET based on that of the reference species for which kcrop, or k, is known. As
pan evaporation will often exceed surrounding evaporation, due to heating and high
exposure of the pan to wind and sun, the coefficient kp must be applied to the pan data to
reduce the evaporation estimate. In some cases screens are applied to pans to prevent
interference from animals and accumulation of leaves. Evaporation results from these
pans sometimes need to be scaled up rather than down. kp coefficients are typically
around 0.7 for a non-screened Class A pan (Bevan 2001, pp. 61). kcrop may be
determined empirically via field based irrigation experiments (Short 2002).
Although the crop coefficient method is cheap and simple, one drawback is that kcrop is
not a true constant; it may vary depending on the season. Warm weather (C4) turf grasses
trialled at the UWA Turf Research Centre in Shenton Park displayed ET rates of 52-68%
of Epan (Short 2002), implying a k value (Equation 4) of 0.52-0.68 for C4 turf grasses
grown in the local climate. Considerably higher k values of up to1.3, for cool weather
(C3) turf grasses, are also recorded (Short 2002). k values of 0.6-1.0 for C4 turf grasses
represent the only other recent local study (Parish 1987).
(3)
(4)
17
The simplicity of Crop Coefficient ET estimation is an advantage over the Penman
model, which is better suited to large scales where a variety of vegetation types may
exist. The Crop Coefficient method is well suited to a small scale mono-species
environment such as a turf patch, as unique turf coefficients can be calibrated to the
particular species. For instances where mean evaporation data is used to estimate ET, the
Crop Coefficient method does not account for localised meteorological variation such as
high wind events, wind shielding or localized cloud which influence ET on small
timescales. This represents one advantage of the Penman model, whereby wind input may
be varied using the empirical wind function f(u) allowing greater ET temporal variation
to be captured. Improvements to the accuracy of the Crop Coefficient method can be
implemented by using seasonally varied coefficients, thus taking into consideration the
species seasonal growth cycles.
Table 3. Lysimeter ET values with standard error for turf grown at the Shenton Park Turf
research Centre, categorized under two separate Epan intensity ranges (Short 2002).
(days with 5-7.9mm of Epan) (days with 8-11mm of Epan)
Genotype ET (mm day-1) (%Epan) ET (mm day-1) (%Epan)
Wintergreen (C4) 3.89 (0.14) 59.8 (2.1) 4.92 (0.17) 51.9 (1.6)
Saltene (C4) 4.15 (0.15) 63.9 (2.4) 5.08 (0.09) 53.8 (1.5)
Buffalo (C4) 4.40 (0.16) 67.8 (2.4) 5.24 (0.15) 55.4 (1.6)
Kikuyu (C4) 4.28 (0.19) 65.8 (2.8) 5.26 (0.17) 55.4 (1.0)
Zoysia (C4) 4.30 (0.18) 66.5 (3.2) 4.93 (0.16) 52.3 (1.9)
Ryegrass (C3) 6.68 (0.35) 102.1 (4.4) 8.37 (0.52) 90.0 (5.8)
Bare ground 3.24 (0.25) 51.0 (4.6) 3.18 (0.3) 33.6 (3.3)
There is only a small degree of ET variation amongst C4 turf grass species. Differences
between the % Epan results for particular species exposed to 5-7.9mm Epan and 8-11mm
Epan highlights the potential for kcrop to change seasonally (Table 3).
18
The minimum summer irrigation requirement for warm season turf-grasses grown at the
Shenton Park Turf Research Centre, is between 50-60% of the daily Epan, with Buffalo
grass only requiring 50% of daily Epan to survive indefinitely (Short & Colmer 2001).
Additionally, warm season turf-grasses can be sustained at a daily irrigation of 33% of
Epan for up to 10 weeks, with some loss of colour (59.7% for Buffalo) (Short & Colmer
2001). This displays the ability of warm season turf-grasses to buffer against periodic
water shortage that may result from less than ideal irrigation volumes.
2.6.3 Groundwater Recharge
With the assumption that runoff, interflow and changes in long term soil storage equal
zero, prevention of groundwater recharge is achieved by balancing greywater irrigation
and rainfall infiltration with ET losses (Figure 3). The homogeneity and sandy nature of
the soils in question dictates that vertical transport is likely to dominate the water balance
(Fetter 2001, pp. 39).
Figure 3. Ideal water balance.
As 0-300mm is stated as the biologically/microbially active zone (section 2.4.4), where
most of the turf ET and nutrient removal is expected to occur, it is assumed that water
19
seeping below this zone will eventually recharge the groundwater. This assumption is
only appropriate due to the shallow rooted nature of turf grasses. It is not applicable for
deep rooted vegetation, where considerable water uptake may occur beyond the
microbially active zone. The assumption is conservative because although the greatest
densities of buffalo grass roots exist within the biologically active zone, roots of warm
season turf grasses such as buffalo may exceed depths of 1.5m (Passmore 1999)
providing a larger however less active area from which moisture may be drawn for ET.
The high permeability of the sandy soils on the Swan Coastal Plain poses a potential
problem for direct greywater irrigation, as seepage velocities may be excessive and
effluent residence times within the biologically active zone may be too brief to allow a
significant degree of ET uptake and nutrient decomposition. This may mean that frequent
low volume irrigation bursts are preferable to infrequent heavy bursts, thus reducing the
likelihood of moisture levels exceeding the field capacity for the soil, the maximum
moisture content a soil can have before gravitational drainage forces exceed surface
tension forces (Fetter 2001, pp. 226). This practise maximises the volume of water
available for ET and reduces the risk of drainage beyond the biologically active zone.
2.6.4 Hydraulic Conductivity and unsaturated flow
To construct a water balance for greywater irrigated to soil, knowledge on the rate of
infiltration and flow must be determinable. These factors govern the dispersion and
volume of moisture transport with respect to soil depth. This relationship is vital in
determining contaminant transport and groundwater recharge.
The nature of fluid flow through a porous media, such as soil, was defined by Henry
Darcy in 1856 as
⎟⎠
⎞⎜⎝
⎛∂
∂−=
l
hKAQ
where Q is the volume of flow (units L3/T), A is the cross sectional area over which flow
may occur (units L2), ∂h/∂l is the change of head pressure over the length of porous
(5)
20
media (units L/L) and K is an intrinsic property of the porous media known as the
hydraulic conductivity (units L/T). The hydraulic conductivity, or soil permeability, is a
measure of the ability of a porous media to conduct fluid and is a critical parameter
regarding the feasibility of a particular greywater irrigation project. It can be seen from
Equation 5 that low permeability clay soils will permit a lower volumetric flow rate, Q,
which may prevent the leaching of salts, harm plants that require good drainage, increase
the possibility of surface pooling and runoff and cause further soil permeability
degradation due to the effects of sodium. Overly permeable soils, on the other hand, may
allow effluent to seep away before significant microbiological treatment has occurred
(AWA 2003).
Infiltration of water into a soil is dependent on gravitational forces and the attraction
forces between soil and water known as the moisture potential (_) which is measured as a
negative pressure. If soil is dry, attractive forces overwhelm gravitational forces and
water is held within soil pores preventing drainage. Conversely, if the field capacity is
exceeded then gravity drainage dominates. Moisture is conducted through interconnected
soil pores called voids. The ease with which moisture flows through these voids (K) is
related to soil water content (_) (Fetter 2001), because water flows more readily through
already saturated voids. K is constant for saturated porous media, simplifying flow
calculations considerably. However, Darcy’s Law may still be applied for unsaturated
flows although K becomes a function of _, with its maximum value being attained at total
soil saturation. The resultant relationship is characterized by the Richards equation
(Richards 1931)
z
K
z
K
zt ∂
∂−⎟
⎠
⎞⎜⎝
⎛∂
∂
∂
∂=
∂
∂ ψθ
where _ is the soil water content (Dimensionless), z is soil depth (L), _ is the moisture
potential (L), K or K(_) is the variable unsaturated hydraulic conductivity (L/T). Equation
6 is highly non-linear and generally requires numerical solutions for soils displaying
varying hydraulic properties with respect to depth. To calculate K(_), and thus
(6)
21
unsaturated flow through a soil, the relationship between _ and K can be determined
experimentally via means of a water retention graph and a known saturated hydraulic
conductivity value. Saturated hydraulic conductivity (Ksat) can be determined
experimentally using a constant head (Section 3.9.2) or falling head permeability test.
Water retention analysis involves exposing a saturated soil sample to increasing suction
pressures and measuring the resultant water content, thus a _ versus _ relationship is
determined. From this relationship the function K(_) may be determined. The general
numerical relationship between these measured parameters and K(_) is presented by
Campbell (1974), based on Brooks and Corey (1966) (Equations 7 & 8), where the two
exponents are empirically related by m = 2b + 3 (Smettem & Ross 1992). The
relationship is as such
b
se
−
⎟⎟⎠
⎞⎜⎜⎝
⎛=
θθ
ψψ
m
ssatKK ⎟⎟
⎠
⎞⎜⎜⎝
⎛=
θθ
where _e is the air entry potential, _s is the saturated soil water content, b is the slope of
the water retention curve (Equation 7), Ksat (L/T) is the saturated hydraulic conductivity
and m is a constant related to the water retention curve slope.
Water retention plots are represented with suction pressure, _, increasing up the vertical
axis, and normalised water content, _/_s, increasing along the horizontal axis to a
maximum value 1. Inflection occurs at points on the water retention graph close to
_/_s=1, however the remainder of the relationship is log-linear with a decreasing slope
(–b) thus allowing K to be determined. The air entry potential (_e) is the pressure required
for drainage to occur, and thus denotes the vertical coordinate for the water retention
curve point of inflection.
The concept of soil hydraulic conductivity represents a “catch twenty two” with regards
to greywater irrigation. On one hand we want highly permeable soil, to allow leaching of
(7)
(8)
22
highly soluble sodium salts. However, on the other hand we want low permeability soil,
to minimise or eliminate deep infiltration so as to prevent the transport of nutrients.
2.6.5 Subsurface drip irrigation
Subsurface drip irrigation consists of rows of buried perforated pipe through which
greywater is pumped or gravity fed. In this way greywater is distributed to the root-zone
of vegetation, but remains below the soil surface where human contact is most likely to
occur. Regulations specify that the pipe be purple for identification purposes.
NETAFIM™ is the current major supplier of subsurface drip irrigation piping. Piping
includes chemical and/or mechanical root intrusion inhibitors to prevent blockages, and
may be purchased at 1.6, 2.3 and 3.5Lhr-1 flow rates (per perforation).
Subsurface drip irrigation is currently considered to be the safest method of greywater
application. Increased irrigation efficiency due to reduced evaporation, and reduced risk
of human contact resulting in a less stringent treatment requirement are some major
benefits of this process. However, recommended irrigation depths of 200-300mm
(Jeppesen & Solley 1994) bypass the soil microbially active zone and most of the active
root-zone, posing and increased nutrient leaching threat. The Department of Health
recommended depths of 150mm (DOH, WC & DEWCP 2002) are a slight improvement
on this, but may require secondary treatment. The reduced evaporation of subsurface
irrigation may require that ET estimates be reduced, so as to avoid over watering.
2.6.6 Vegetation
Draft regulations state that greywater may only be irrigated to ornamental plants and not
to species grown for consumptive purposes. Many types of vegetation are acceptable for
greywater reuse, however species preferring acidic soils, shade or low nutrient levels are
not recommended for receiving typically high nutrient alkaline greywater (DOH, WC &
DEWCP 2002). Many Australian native plants, such as members of the Proteaceae
family, are accustomed to highly leached low nutrient soils. A list of unsuitable plants for
receiving greywater is given in Appendix 1.
23
“Limited evidence from trials and existing greywater systems suggest that there are no
apparent adverse effects on lawns and ornamental gardens from chemicals occurring in
greywater” (Emmerson 1998). A cultivar of Stenotaphrum secundatum, Velvet Buffalo,
was chosen as the greywater test species for this thesis. Velvet Buffalo grass is a warm
weather, C4, turf type. The Evergreen Turf Farm™ describes Velvet Buffalo as deep
rooted, hardy, salt tolerant, shade tolerant, suited to sandy soil, but herbicide sensitive.
The deep rooted nature of Velvet Buffalo may aid with transpiration capability and hence
soil moisture reduction between irrigation bursts, when surface moisture levels begin to
decline.
24
3.0 Materials and Methods
To construct and calibrate a water balance for the irrigation of greywater to the study site,
laboratory simulations and a computer model were developed. Field data was collected to
validate the findings. The following sections outline the study site, greywater re-use
design and the analytical and computational methods used to construct the water balance.
3.1 PHYSICAL SETTING
The study site, 74 Keightly Road, Shenton Park, Western Australia, is a family residence
situated 20.2m - 19.2m above sea level (Australian Height Datum) on a medium/coarse
Tamala limestone, leached yellow sand and Bassendean sand blend of high permeability
and low nutrient retention. The drilling logs imply that the local soil is sandy, largely
unstratified and homogeneous. The depth to groundwater of 13.9m ± 3m-seasonal
variation, computed from the Water and Rivers Commission Groundwater Atlas
(Appendix 3), is sufficiently deep that despite seasonal variation the water table will
remain at a significant depth below the biologically active zone. Relative to the land
surface the water table slopes from 0m depth at Shenton Park Lake to the east, to well in
excess of 20m deep at Kings park to the west (Appendix 5). Soil analysis from the
Western Australian Chemistry Centre indicates a very low clay content (~2%) supporting
good drainage and the unlikelihood of soil degradation through clay dispersion
(Appendix 4).
The land surface has a slight slope of 1:15 from the south-east corner to minimum
elevation at the north-west corner. This slope is not sufficient to promote lateral flow.
The lawn area is situated to the rear of the house on the north-west side (Appendix 6).
The 3mx13m lawn contains some surface traces of limestone rubble within the soil, likely
to be from the pre-existing shed. The greywater primary treatment unit is partially
submerged and located at the southern end of the lawn area. The sewer main runs closely
down the length of the western boundary at a depth of approximately 2.5m. The eastern
25
half of the garden contains several large shrubs and trees. Morning shading of the
northern half of the lawn is a result of the site’s gum and olive tree, and the neighboring
northern residence. Gradual progressive total shading of the lawn occurs in the late
afternoon as a result of the western property fence.
Table 4. Summaries of the two closest Water and Rivers Commission (WRC) soil
stratigraphy logs; taken during installation of bores on nearby Rosalie St (Appendix 3).
Feature Location Description
Bore Cnr. of Rosalie St.
and Nicholson Rd.
Sand all the way; yellow to water then becoming
paler until at 3m below water table where sand
became white and remained so. Sand varied from
fine to coarse grains.
Bore Near cnr. of Rosalie
St. and Maxwell St..
Sand.
Shenton Park lies on the western side of the central Perth metropolitan area and is
governed by the characteristic Mediterranean climate of hot dry summers and mild wet
winters. Thus the water demand at the site will not be seasonally consistent.
3.2 GREYWATER RE-USE PROCESS DESIGN
The overall treatment process consisted of 3 major components:
• A split plumbing system to separate reusable greywater from heavily soiled
greywater and blackwater. This plumbing system directs reusable greywater to a
sullage tank, and other household wastewater to the sewer.
• A greywater sullage tank, with coarse screening and primary treatment, and an
electric Davey™ 350 rotary pump. The purpose of these components was to allow
irrigation to be delivered in controlled bursts of known volume (~200L). The
primary treatment was intended to prevent blockages within the irrigation
26
network. The system incorporates the necessary overflows and sewer diversions
in case of failure or maintenance.
• A distribution network of subsurface drip irrigation piping to deliver greywater to
the root-zone of the designated garden lawn.
3.3 SPLIT PLUMBING SYSTEM
The greywater plumbing system receives water from the baths, showers, wash-basins and
washing machine/laundry trough in the 3-bedroom, 2-bathroom house. The blackwater
and greywater plumbing streams run in parallel along the western property boundary
underneath the pedestrian walkway until diverging near the sullage tank, at the north-
west corner of the verandah. Both plumbing systems were installed by a licensed
plumber, are separately vented (Appendix 7) and conform to the current regulations. The
plumbing system is expected to divert a mean of 415kL per day, based on Water
Corporation figures (Section 2.3), of greywater through the sullage tank. However, only
200L may be stored and irrigated at any one time, as the excess overflows to the sewer.
27
3.4 SYSTEM DESCRIPTION
The sullage tank used for greywater storage at the study site is moulded from the inside
of a 44 gallon drum (Figures 4, 5 & 6) using low density polyethylene. The maximum
capacity of the tank is just over 204L. The vertical tank, or “chimney”, houses a high
level overflow so that when the tank reaches capacity the flow cascades into the sewer
diversion pipe, seen exiting the bottom of the chimney. Similarly, there is a bypass valve
near the top of the chimney that diverts all flow directly to the sewer so that the tank may
be brought offline for maintenance. The tank meters out a maximum of just over 204L
per irrigation unless there is greywater inflow during irrigation pumping, in this event the
tank may empty after more than 204L has been pumped. Flow entering the tank is
initially screened for hair and lint by a filter mesh overlying the tank inlet. Flow is drawn
from the bottom of the tank for irrigation and pumped through a filter, flow metre and
slow release chemical root intrusion cartridge (Figure 7). This chemical is supplied by
NETAFIM ™ for the purpose of inhibiting turf root growth into the irrigation drippers.
Figure 4. Greywater sullage tank and fittings.
28
Figure 5. Photograph of primary treatment unit (side view), with pump on top.
Figure 6. Photograph of primary treatment unit (front view).
29
Figure 7. From right to left: pump; filter; flow meter; sampling tap; slow release root
intrusion inhibitor; air release valve.
3.5 LAWN IRRIGATION NETWORK
The irrigation network consists of 10 north-south rows of NETAFIM™ 1.6 litres/hour
drip irrigation piping buried at approximately 5cm depth below lawn surface. Piping rows
were 30cm apart and dripper outlets on the piping were at 40cm spacing, resulting in 32-
33 drippers per row of piping (Figure 8). This approximates to 325 total dripper outlets
over the area of the lawn. The volumes of water pumped to the lawn were read from the
meter and recorded for each irrigation (Appendix 8). Several pumping durations, the time
taken to irrigate a full greywater sullage tank to the turf, were measured and recorded for
the determination of the field flow rates. Thus the flow volume and flow rate through
each dripper could be calculated as such
DrippersofNumber
VolumeIrrigationTotalDripperperVolumeFlow = (9)
30
TimePumpingxDripperperVolumeFlowRateFlowDripper
60=
where the flow volume was measured in litres, “Pumping Time” was recorded in minutes
and flow rate determined in litres per hour.
As most of the study was conducted over the wet season where irrigation was not
expected to be required, irrigation was performed on a once per 3-4 day basis. This was
to allow a sufficient number of pre and post-irrigation moisture measurements to be taken
in the soil moisture analysis.
Figure 8. Oblique lawn irrigation schematic (Not to scale).
(10)
31
3.6 THE ‘TANK TEST’ EXPERIMENT.
The Tank Test experiment was devised to assist in the determination of the dispersion
behavior of water when irrigated on the turf site at 72 Keightly Road, Shenton Park. It
was a concern that moisture diffusion from the irrigation drippers might not occur evenly
or be homogeneous, and thus defy attempts to be modelled reliably. This experiment was
intended to determine the rates of vertical and lateral moisture diffusion, and thus act as a
test of the homogeneity of the soil moisture movement.
3.6.1 Tank Test Materials
• A clear Perspex cube of inner dimensions 29cm x 28.2cm x 28.3cm (height x
width x length), with a gauze covered perforated base.
• A 30cm long 102.5cm diameter PVC pipe, ‘soil corer’.
• Approximately 30kg of soil from a representative part of the study site.
• Low heat oven.
• Standard diameter garden hosing with corresponding fittings: One PVC “L-
shaped connector”; one PVC “T-shaped connector”; 2 adjustable-flow taps; two
PVC stoppers; eleven ring clips; a short length of NETAFIM ™ subsurface
irrigation tubing with a single central dripper.
• Constant pressure head apparatus.
• 200mL graduated cylinder.
• Stopwatch and ruler.
• Vegetable dye and syringe.
• Digital camera
3.6.2 Tank Test Setup
The in-situ bulk density was determined by pushing the 30cm PVC soil corer into a
section of soil where the turf was later to be laid. The depth, 20cm, was recorded and
32
marked on the PVC cylinder. The area around the pipe was then excavated and a plastic
disk was slid across the base of the pipe to seal it. The soil sample was taken to the lab
and dried at 60ºC for 2 days. The bulk density was calculated according to
4
2DxDepth
WeightDrySampleb
πρ =
where _b is the in-situ bilk density (g cm-3), “Sample Dry Weight” is the mass (g) of the
soil core after 2 days of oven drying at 60ºC, “Depth” is the length of the soil core taken
(cm) and D is the soil corer inside diameter (cm).
The total mass of soil (kg) required to fill the tank at the in-situ density was calculated,
according to
1000bxVolumeFilledSoilTank
MassSoilTankρ
=
where the “Tank Soil Filled Volume” was equal to the inner tank dimensions subtract 2
cm from the height dimension, 27cm x 28.2cm x 28.3cm (height x width x length), to
accommodate space for the dripper apparatus and any surface pooling during the
experiment.
Soil was added to the tank in 10 equal increments, each one tenth of the total Tank Soil
Mass. Each incremental layer was levelled and compacted with a wooden block to a
thickness one tenth of the tank soil filled height (2.7cm), thus a moderately uniform
density could be maintained throughout the tank depth. The water delivery mechanism
was constructed according to Figure 9, and flow was supplied from constant head
apparatus. The length of NETAFIM™ tubing and single dripper were situated parallel to,
and directly against the front wall of the tank at 5mm soil depth.
(11)
(12)
33
Figure 9. Water delivery for the tank apparatus.
A is rubber hosing; B is a ring clip; C1 and C2 are adjustable taps; D is a PVC “L-shaped
connector”; E is a PVC stopper; F is a length of NETAFIM ™ drip tubing; G is a solitary
dripper; H is the tank soil surface; I is a PVC “T-shaped connector”.
3.6.3 Tank Test Procedure
Firstly the dripper flow rate was calibrated. For this, flow from the constant head tank
was activated and taps C1 and C2 opened. Flow through the dripper (G) was collected in
a 200mL graduated cylinder for a duration of 1 minute, then tap C1 was closed. The flow
rate (L/hr) was determined according to
DurationxVolumeRateFlow
60= (13)
34
where “Volume” (L) is the quantity of water collected in the graduated cylinder over the
selected “Duration” (min). Tap C2 was adjusted and the process repeated until the flow
rate was close to half that of the field flow rate, determined according to Section 3.5. A
duration of five minutes was then used to fine tune the flow rate. Once the flow rate was
calibrated to half of the field flow rate, ±5% error, tap C1 was closed and tap C2 left
untouched. Half the field flow rate was used in the experiment because of the effect of
the tank wall blocking half of the possible dispersion field.
With the tap C1 firmly closed, the stopper near the T-connector (I) was removed and the
connecting section of tubing, which serves as a reservoir, was filled with vegetable dye
and re-stoppered. The dripper was positioned at 5mm depth against the front Perspex wall
of the tank.
To begin the Tank Test for the completely dry soil, the tap C1 was opened and the
stopwatch is started. The dispersion field, viewed through the front Perspex tank wall,
was photographed when the stopwatch reached times of one third, two thirds and three
thirds the field pumping time. Measurements of vertical and lateral dispersion (cm) were
also taken. At each time interval the stopwatch was halted, tap C1 was closed and the dye
reservoir quickly refilled before proceeding. Once the field pumping time was reached
the experiment was complete.
To measure moisture dispersion in damp soil the process above was repeated, however, a
hose was run at the surface of the tank until uniform wetting could be observed
throughout the soil sample. The soil was allowed to gravity drain for three days before
experimentation. Estimations of the field wetted area (m), corrected for non-uniform
irrigation based on the tank test lateral dispersion lengths, were made according to
2
1002325 ⎟
⎠
⎞⎜⎝
⎛=xD
AreaWetted π (14)
35
where D (cm) is the tank test lateral dispersion length. Note that there are 325 drippers
across irrigation area.
The effective irrigation depth (mm) for the wetted area, corrected for non-uniform
irrigation, was calculated according to
AreaWetted
VolumeIrrigationDepthIrrigation =
where “Irrigation Volume” (L) is the quantity of water pumped from the tank (~ 200L).
3.7 ON-SITE MOISTURE CONTENT VS DEPTH MEASUREMENTS
Soil moisture content with respect to depth was measured using a hand held Time
Domain Reflectometer (TDR) probe. This method was used to produce a field data based
water balance for comparison to the MATLAB climatic box model and the SWIM model.
With the input quantities of rainfall and irrigation to the soil known, soil moisture was
measured with the aim of determining the water retained within the surface 45 cm. The
water loss 1 hour after irrigation was assumed to be deep infiltration, as ET over 1 hour is
small.
3.7.1 Preliminary Moisture measurements
A preliminary “before” and “after” irrigation soil-moisture data set was obtained to give
an idea of the spatial variation in soil moisture as a result of the point-source dripper
network. This involved taking a series of 0-10cm depth moisture measurements with the
TDR probe at various distances from, and along, the drip lines (Figure 10). Due to slight
irregularities in the linearity of the irrigation network most of the 325 dripper locations
were not known exactly.
(15)
36
To obtain moisture readings 10cm electrodes were inserted into the TDR. The TDR probe
was then pushed into the soil at the desired location and the moisture percentage and
location of the sample, relative to the turf boundaries, were recorded.
Figure 10. Preliminary sampling for moisture homogeneity.
Figure is a schematic of the sampling locations relative to dripper columns. Numbers
denote sample points. Note the six known dripper locations marked with red X’s.
37
3.7.2 Moisture versus depth data
Sites 1, 4 and 8 were used for measuring variation in soil moisture with respect to depth.
Each site was located adjacent to an irrigation dripper. 2 x 10cm electrodes were inserted
into the TDR and pushed into the soil at each site, where they were disconnected from the
TDR, left in the soil and marked with red pegs. This was also done with 45cm electrodes
at each site. The locations of the electrodes were marked with yellow pegs. 30cm
electrodes were similarly inserted and marked with green pegs at sites 1 and 2. Site 3 did
not possess a 30cm set of electrodes due to their short supply. Due to the bulky nature of
the TDR probe head, the part of the probe into which the ends of the electrodes are
inserted, the electrodes needed to be spaced 5cm apart within the soil. This meant that the
0-10cm, 0-30cm and 0-45cm moisture measurements could not be taken from exactly the
same position at each site. It was desirable to leave the electrodes in the soil rather than
alter the soil porosity and soil packing by repetitive re-insertion, as continual re-insertion
would have influenced the moisture readings. It should be noted that the moisture
electrodes were inserted into the soil in a linear north-south fashion from short to long,
thus the 0-30cm electrodes were at a slightly lower radial distance (5cm) from the known
dripper locations relative to the 0-10cm and 0-45 cm electrodes (7.5cm). The area of lawn
containing these three sites was marked off with construction tape so that the soil probe
electrodes were not disturbed. Data was collected immediately before and 1 hour after
irrigation for 5 irrigation days. Each greywater irrigation event was approximately 3-4
days apart.
Data collection involved connecting the TDR probe to the 10cm soil electrodes. Care was
taken to insure that the electrodes were in firm contact with and fully housed within the
probe electrode sockets. The probe was manually set to read at 10cm depth. Readings
were taken several times for each electrode set to insure a consistent output was obtained.
If the readings fluctuated by more than 1% or a reading of 0 was obtained, the position of
the electrodes within the probe socket was adjusted and/or the electrodes were cleaned to
insure good contact with the probe. The process was repeated for the 30cm and 45cm
electrodes. After the initial moisture readings were obtained, the greywater pump was
switched on until the sullage tank had emptied. The reading on the sullage tank flow
38
meter was recorded so that the volume of water irrigated could be determined. One hour
after the irrigation had finished the moisture readings were re-taken at each depth and the
results were tabulated.
Rainfall data was collected and tabulated at 7.30am each morning using an on-site rain
gauge (Appendix 9). With a known volume of water inputted to the soil it was expected
that infiltration could be accounted for as the difference between the known moisture
loading due to irrigation and the measured moisture increase in the top 45cm of soil. As
almost all of the water uptake and biological degradation of nutrients occurs shallower
than 45cm depth, it was assumed that losses below 45cm would result in groundwater
recharge.
3.8 MATLAB BOX MODEL PROCEDURE
A MATLAB code was written to analyse and display local average climate data and
estimate the climatological interaction with the irrigation regime. This approach results in
a water balance that assumes infiltration is sufficiently slow to make evapotranspirative
uptake of irrigated water the dominant sink. Evapotranspiration is modelled via the crop
coefficient method. The result is a series of graphs that indicate the turf water demand,
indicating surplus or deficit of water supply. At the end of each day, water surplus is
assumed to become deep infiltration. Code for the MATLAB program can be viewed in
Appendix 10. The main function of the program is to convert monthly evaporation and
rainfall averages to a mean daily time series. The MATLAB program takes the monthly
rainfall averages as the centre-point for each month, and constructs an 11th order
polynomial to curve fit the March-November data. The January-March data and
November-January data are each curve fitted with 5th order polynomials. This eliminated
the polynomial wiggle error which occurs from using one polynomial curve fit.
Bureau of Meteorology (BOM) rainfall information from the Nedlands (UWA) data
station (Appendix 11) was used in conjunction with BOM Epan data from the Perth
39
Regional Office data station (Appendix 12). As reliable Epan data sets are not available for
most climate stations, the Regional Office evaporation data was assumed to be
compatible with the Nedlands climate data. A crop coefficient (kcrop) of 0.678 for buffalo
grass, based on the %Epan values (Table 3), was used to determine an ET estimate from
the Epan data. The 0.678 kcrop value was chosen, instead of the alternative 0.554 value, due
to the unlikeliness of moisture limitation on ET in winter. The raw Epan data is scaled up
by 7%, as recommended (Kowald B. pers. comm.), due to the shading effect of the bird
guards used. The inputs of rainfall and irrigation are balanced with the output of ET to
determine the likelihood of moisture accumulation, and thus groundwater recharge. The
results are plotted to display where expected water losses exceed water inputs, thus
representing a low risk of deep infiltration and groundwater recharge. The Epan and
rainfall output from the MATLAB script were then used to construct a new irrigation
regime based on adjusting the irrigation frequency to keep average expected water supply
within the upper 67.8%Epan, and lower 33%Epan boundary water requirements for Buffalo
turf.
3.9 SOIL WATER INFILTRATION AND MOVEMENT MODEL (SWIM)
SWIMv.1.1 was applied to the turf environment to approximate ET and deep infiltration
based on soil and vegetation properties. Central to the SWIM model is the Richards
equation for unsaturated fluid flow through soil. The SWIM model required the onsite
rainfall data, the regional evaporation data, the soil saturated hydraulic conductivity and a
water retention curve as inputs.
Fluid flow through soil in the SWIM model is calculated according to the Richards
equation and its relationship to water retention parameter (b) and Ksat (Section 2.6.4). Ksat
and b were determined from soil samples analysed in the laboratory according to the
respective test methods (Sections 3.9.1 & 3.9.2). “Transpiration rates are calculated from
steady-state radial flow to the roots” (Ross 1990) and incorporated as a loss term into the
Richards equation.
40
SWIM assumes that ETp is equal to evaporation. To obtain ET, the ETp is scaled by a
growth factor (f) and a root-length density factor (dz). The root length density factor
(cm/cm3) is determined as a function of depth according to
⎟⎟⎠
⎞⎜⎜⎝
⎛=
csz z
zdd exp
where ds (cm/cm3) is the maximum surface root-length density, z (cm) is the depth from
the surface, zc (cm) is called the root depth constant and is the depth to which root length
density falls to 37% of its maximum.
The sigmoid shaped growth curve for f accounts for growth and establishment of crop
species as they proceed towards their maximum ET capacity. However, the turf at the
study site is assumed to be fully established and completely cover the soil surface, thus
the growth factor is assumed to be equal to 1. The effect of root density with respect to
depth is however assumed to have significant influence over ET. The transpiration loss
term is determined incrementally over depth as the factor dz changes. Typical ds and zc
values for turf are 1cm/cm3 and 8cm respectively (Smettem K. pers. comm.). These
recommended values were used in the SWIM model. Due to the high hydraulic
conductivity of the soil the model was run over hourly rather than daily time-steps to
capture the pulses of irrigation. The model was run over 1m depth so as to encompass
virtually all of the ET. The 1m depth was modelled as a free-draining boundary.
3.9.1 Water retention curve fit
A water retention curve is useful in describing the ability of a certain soil to “hold on” to
moisture. It is a measure of the surface tension, adhesion and capillary forces that resist
drainage within a particular soil. In a water retention experiment a saturated soil sample
is exposed to a series of increasing air pressures which replace some of the water filled
(16)
41
voids, the reduction in soil water content is measured for each pressure increment. The
water retention procedure was as follows:
A porous ceramic disc was placed in a water bath and kept in a vacuum until all air was
removed from the voids. A sample of the oven dried soil from Section 3.6 was packed to
the in-situ density inside a short metal cylinder and plugged at the base with a dry
ceramic disc. The sample and the wet ceramic disc were then placed in the soil capsule
apparatus shown (Figure 11 A, B & C). It was important to insure that no sand or grit was
present on the metal cylinder or rubber O-rings otherwise air and water leakage might
have occurred during the experiment. The initial weight of the dry sample (subtract the
capsule weight) was recorded. Water was carefully metered out to the soil sample
through the base of the soil capsule via a syringe, in such a way as to flush the air out of
the soil voids. Once the sample was completely saturated and water could be observed
brimming at the surface of the soil, the volume of water added was recorded and the lid to
the soil capsule was fixed in place. The weight of the dry sample plus the weight of the
volume of water added (1gmL-1) was recorded and the combined weight of the soil and
capsule was also determined, so that the capsule weight could be subtracted from the
final weight results.
42
Figure 11. Water retention soil capsule, for connection to air pressure supply (U-tube).
Note that “A” is turned upside down to achieve “B” and “C”, thus the wet ceramic disc is
at the base.
The top of the capsule was connected to a U-tube, and exposed to an initial pressure of
4kPa. Pressure was maintained at 4kPa via hourly corrections. Each hour the soil capsule
was disconnected from the pressure apparatus and weighed. Reduction in mass, and thus
loss of water, is recorded for the sample hourly until there is no further reduction, at this
point the pressure is increased to the next increment, 10kPa and 18kPa respectively and
the process is repeated. This data allows a water loss versus pressure curve to be
constructed.
3.9.2 Saturated hydraulic conductivity
The soil hydraulic conductivity was measured by the Constant Head Permeameter
method. The procedure was as follows:
A sample of the oven dried soil from Section 3.6 was placed in the permeameter (Figure
12) and packed to the in-situ bulk density and a height of L = 4cm (Figure 12B). A finely
meshed wire disc was placed over the surface of the soil to prevent soil displacement
43
during the procedure. Water was very slowly added to the permeameter through the base
to expel air from the soil voids (Figure 12A). Once all the air was expelled from the
sample the hose used to input water to the base was placed into the top of the
permeameter and the flow rate was adjusted until the water surface remained steady, at h
= 4cm above the soil surface. Water was allowed to freely drain from the base of the
permeameter. It was necessary to continually adjust the water inflow rate to maintain a
constant 4cm head. Water expelled from the base of the permeameter was collected in a
graduated cylinder, and a stopwatch was used to measure time. In this way, the volume of
water expelled in a 30 second period was determined and used to calculate the saturated
hydraulic conductivity. The hydraulic gradient (φ) necessary for the calculation of Ksat
was determined according to
24
44=
+=
+=
L
Lhφ
where h and L can be seen in Figure 12.
Figure 12. Constant-Head Permeameter.
(17)
44
h (cm) denotes the head of water above the soil; L (cm) denotes the height of the soil
sample. The thickness and flow resistance of the filter paper and wire mesh is assumed
negligible. The permeameter is fixed upright with a clamp during the procedure.
Specific discharge was calculated according to
)/(100
)(min/60min)/30(2
4
302 mcm
hrxsx
Dx
sperExpelledVolume
AreaSurface
Q
πυ ==
where _ is the specific discharge (mhr-1), calculated from the volume of water that has
permeated during at 30s interval and D is the permeameter diameter (cm). From _ and φ
the saturated hydraulic conductivity (mhr-1) can be determined as
φυ
=satK
(18)
(19)
45
4.0 Results
4.1 LAWN IRRIGATION FINDINGS
The pumping times (Table 5) were recorded for irrigation of a near to full sullage tank,
with the exception of the two blockage events where irrigation was not completed.
Pumping times were somewhat influenced by the recency with which the filter had been
cleaned. The frequent need to clean the filter was due largely to the removal of the pre-
pump mesh for filtering hair and lint. Slight build-up on this mesh was causing most of
the greywater inflow to “glide” over the tank inlet pipe and through to the sewer
diversion.
Table 5. Irrigation pumping times. Mean is for the five complete irrigation events, where
blockages did not occur.
Date Pumping Time (min)
20/8/2003 >25 (Filter blockage)
10/9/2003 17.9
17/9/2003 18.8
21/9/2003 18.7
24/9/2003 19.5
28/9/2003 20.6
05/10/2003 >25 (Filter blockage)
Mean pumping time 19.1
46
Table 6. Dripper data, calculated as per Equations 9 & 10, using 325 drippers and an
irrigation volume of 200L. Note that drippers are operating at above the design capacity
of 1.6L/hr. It also should be noted that pumping time may change as the system ages and
as filters clog.
Field Flow Volume per Dripper 0.615L
Dripper Flow Rate 1.93L/hr
Turf roots were found to be well established within the microbially active zone of the soil
after 6 weeks of growth, from installation at the 18/4/2003 to the 4/6/2003. A portion of
the lawn was excavated on the 4/6/2003 and roots were found to be densely packed to a
depth of 0.35m, with some roots to 0.44m (Appendix 13). Soil homogeneity to a depth of
0.64m can be observed in Appendix 14.
4.2 TANK TEST RESULTS
Table 7. Basic measurements for the Tank Test.
Soil bulk density _b (g cm-3) 1.4526
Tank volume (cm-3) 21547.62
Tank soil mass (kg) 31.3
Photographic time-steps from the damp (left) and dry (right) tank test experiments are
provided below (Figures 13-20). There appears to be significant variation between the
two trials, with respect to lateral and vertical dispersion. This variation has a considerable
impact on the wetted area, the area of the lawn that receives water from the irrigation
drippers (Table 8), and thus the localised depth of irrigation at each dripper.
47
Figure 13. Soil tank at time = 0, before irrigation.
Figure 14. Damp Soil. Time = 6.4minutes.
Horizontal dispersion diameter = 10.5cm.
Vertical dispersion length = 12.0cm.
Figure 15. Dry Soil. Time = 6.4minutes.
Horizontal dispersion diameter = 20.9cm.
Vertical dispersion length = 7.5cm.
48
Figure 16. Damp Soil. Time =
12.7minutes. Horizontal dispersion
diameter = 17.0cm. Vertical dispersion
length = 18.5cm.
Figure 17. Dry Soil. Time = 12.7minutes.
Horizontal dispersion diameter = 23.4cm.
Vertical dispersion length = 10.8cm.
Figure 18. Damp Soil. Time =
19.1minutes. Horizontal dispersion
diameter = 19.3cm. Vertical dispersion
length = 27cm.
Figure 19. Dry Soil. Time =
19.1minutes. Horizontal dispersion
diameter = 25.5cm. Vertical dispersion
length = 16.0cm.
49
Figure 20. Dry Soil. Dispersion 8 minutes after cessation of irrigation, or 27.1 minutes
since irrigation commencement. Full tank depth, 27cm.
Table 8. Estimated area of wetting and resultant irrigation based on tank test results.
Dispersion
diameter
(cm)
Wetted
area
(Square m)
Effective irrigation for
wetted area
(mm)
Uniform
wetting
~ 39 5.13
Wet soil 19.3 9.51 21.03
Dry soil 25.5 16.60 12.05
4.3 MOISTURE CONTENT FIELD RESULTS
The preliminary soil moisture tests, for 0-10cm depth, show a considerable lack of
homogeneity in moisture across the lawn (Figures 21 & 22). Error bars are not included
in Figure 22 as only one preliminary north-south transect was done. The strange moisture
readings at the 5m mark on the north-south vertical transect may be due to a rocky patch
of earth. The patch may dry quickly due to its low absorbtivity, thus giving initially low
moisture readings. It may also incur subsurface pooling of moisture after irrigation,
giving an initially high moisture reading after irrigation. Definite increases in soil
moisture after irrigation are shown in all moisture graphs.
50
The soil moisture graph (Figure 23) displays the pre-irrigation soil moisture; the expected
increase in soil moisture after a uniform addition of 5mm water, assuming no infiltrative
loss from the respective soil layers; and the actual observed post-irrigation soil moisture.
A good correlation between the 0-10cm and the 0-45cm moisture data is visible, with the
exception of the 17/09/2003 data point which occurred after a significant dry period. 0-
30cm data shows anomalously high post-irrigation moisture increases relative to the other
depths. 0-10cm and 0-45 cm readings show slightly less than the 5mm increase in soil
moisture expected for uniform wetting across the total turf area.
Top 0-10cm Soil Moisture Content for Horizontal transects
0
5
10
15
20
25
30
0 0.5 1 1.5 2 2.5
Distance, east-west (m)
Mo
istu
re (
mm
)
Before irrig.
After irrig.
Figure 21. West-east horizontal moisture transects for the top 0-10cm. Graph shows
considerable variation.
51
Top 0-10cm Soil Moisture for Vertical Transects
0
5
10
15
20
25
0 2 4 6 8 10 12
Distance, north-south (m)
Mo
istu
re (
mm
)
Beforeirrig.Afterirrig.
Figure 22. North-south vertical moisture transects for the top 0-10cm. There are no error
bars because only one north-south transect was performed.
52
Soil Water Content
0
10
20
30
40
50
60
70
80
7/09
/200
3
8/09
/200
3
9/09
/200
3
10/0
9/20
03
11/0
9/20
03
12/0
9/20
03
13/0
9/20
03
14/0
9/20
03
15/0
9/20
03
16/0
9/20
03
17/0
9/20
03
18/0
9/20
03
19/0
9/20
03
20/0
9/20
03
21/0
9/20
03
22/0
9/20
03
23/0
9/20
03
24/0
9/20
03
25/0
9/20
03
26/0
9/20
03
27/0
9/20
03
28/0
9/20
03
29/0
9/20
03
30/0
9/20
03
Date
Mo
istu
re (
mm
)
Irrigation
Rainfall
10cm
10cm (Expected P.I.)
10cm (Actual P.I.)
30cm
30cm (Expected P.I.)
30cm (Actual P.I.)
45cm
45cm (Expected P.I.)
45cm (Actual P.I.)
Figure 23. Soil water content at 0-10, 0-30 and 0-45cm depths, before and after an
irrigation event. Note the apparent influence of rainfall events. P.I. means Post-Irrigation.
4.4 MATLAB BOX MODEL WATER BALANCE
The cyclic nature of the annual water demand (Figure 24) highlights the Mediterranean
style climate of the study area. Rainfall is in excess of the turf demand from early May to
early September (Figure 25). Rainfall combined with irrigation is in excess from early
March to Early October (Figure 26) indicating a transitional demand for irrigation
between March and May and between September and October.
53
The rainfall curve-fit shows a good approximation (Figure 27). The first 3 and last 3
rainfall data points were each separately curve fitted with 5th order polynomials to
eliminate polynomial wiggle error.
Figure 24. Full year of average climatic data. Note that “prelimwat.bal” is the sum of the
inputs, rain and irrigation, subtract the output, evapotranspiration. Daily evaporation is
Epan, based on monthly average Epan. Note that the ET loss between irrigation is on a 3
daily basis, not daily.
54
Figure 25. Period of rainfall excess, assuming crop coefficient of 0.678 for
evapotranspiration.
55
Figure 26. Period of irrigation excess, for once per 3 day irrigation.
56
Figure 27. Daily rainfall based on monthly average rainfall.
57
Plot of Box-Model Water Balance for Proposed Irrigation Regime
0
1
2
3
4
5
6
7
10/12/2002 29/01/2003 20/03/2003 9/05/2003 28/06/2003 17/08/2003 6/10/2003 25/11/2003 14/01/2004 4/03/2004
Dates (mid. jan.-mid. jan.)
Ap
plic
atio
n (
mm
/day
)
UpperBound
LowerBound
Supply
Figure 28. Mean daily availability of water for turf. Zero irrigation during peak rainfall,
central yellow parabola - 10th of April to the 20th of October. Once per 2 days irrigation
during transitional climate - 20th of February to the 10th of April and 20th of October to
the 10th of December. Once per day irrigation during low rainfall and peak evaporation
period- 10th of December to the 20th of February.
4.5 SWIM MODEL RESULTS
4.5.1 Water retention curve results
Table 9. Water retention apparatus results. Initial water content was 28.8g or 28.8mL.
Pressure kPa 4 10 18 ResidualMass Loss g 17.88 3.44 1.2 6.28
Water Loss mL 17.88 3.44 1.2 6.28
58
As expected for highly permeable sandy soils, considerable drainage occurs for the
sample at low pressure (Table 9). Exponentially decreasing rates of drainage occur at
higher pressures, as remaining water is less abundant and more tightly bound to soil
pores.
4.5.2 Saturated hydraulic conductivity results
Table 10. Constant head permeameter results. Soil saturated hydraulic conductivity for 9
tests on 3 samples.
SampleTrial Thickness of
soilL (cm)
Height ofwaterh (cm)
Hydraulicgradient
_
Flowq
(m/hr)
Ksat
(m/hr)
1 4 4 2 2.222 1.1112 4 4 2 2.000 1.00013 4 4 2 2.079 1.0401 4 4 2 1.784 0.8922 4 4 2 1.750 0.87523 4 4 2 1.760 0.8781 4 4 2 4.330 2.1652 4 4 2 4.448 2.22433 4 4 2 4.420 2.210
Mean 4 4 2 2.755 1.377
Saturated hydraulic conductivity results for the constant head permeameter showed
reasonable consistency. All the values (Table 10) are typical of medium grained sands.
59
4.5.3 Infiltration results
Table 11. SWIM model output for the 18 day period commencing 10/09/03 to 28/09/03
when the moisture versus depth analysis was performed. Model Assumes non-uniform
soil wetting, 21mm effective irrigation to the wetted areas and measured rain-gauge
rainfall.
3-daily irrigation 21mm
Precipitation + rainfall 148mm
ET 79mm
Deep drainage (Beyond 1m) 42mm
Change in soil storage 27mm
Table 12. SWIM model output for the 18 day midsummer period commencing 06/01/03
to 24/01/03 with daily irrigation. Model Assumes uniform soil wetting of 5mm and
1mm/day rainfall.
Daily irrigation 5mm
Precipitation + rainfall 108mm
ET 81mm
Deep drainage (Beyond 1m) 19mm
Change in soil storage 8mm
60
Table 13. SWIM model output for the 18 day midsummer period commencing 06/01/03
to 24/01/03 with daily irrigation. Model Assumes non-uniform soil wetting, 21mm
effective irrigation to the wetted areas and 1mm/day rainfall.
Daily irrigation 21mm
Precipitation + rainfall 396mm
ET 82mm
Deep drainage (Beyond 1m) 265mm
Change in soil storage 49mm
61
Soil Water Content
0
10
20
30
40
50
60
70
80
7/09
/200
3
8/09
/200
3
9/09
/200
3
10/0
9/20
03
11/0
9/20
03
12/0
9/20
03
13/0
9/20
03
14/0
9/20
03
15/0
9/20
03
16/0
9/20
03
17/0
9/20
03
18/0
9/20
03
19/0
9/20
03
20/0
9/20
03
21/0
9/20
03
22/0
9/20
03
23/0
9/20
03
24/0
9/20
03
25/0
9/20
03
26/0
9/20
03
27/0
9/20
03
28/0
9/20
03
29/0
9/20
03
30/0
9/20
03
Date
Mo
istu
re (
mm
)
Irrigation
Rainfall
10cm
10cm pre-irrig (SWIM)
10cm post-irrig (SWIM)
10cm (Actual P.I.)
30cm
30cm (Actual P.I.)
45cm
45cm (Actual P.I.)
Figure 29. Soil moisture data with top 10cm SWIM moisture estimate before and 1 hour
after 21mm irrigation (Blue dotted line).
62
5.0 Discussion
5.1 GENERAL DESIGN
On the whole the tank and irrigation network functioned without significant fault.
However some slight adjustments to the future design will need to be considered.
Successes of the design and necessary adjustments are detailed below.
Surface pooling of greywater was not observed to occur at any time during the trial of the
greywater system, however some surface dampness was observed at the southern end of
the lawn after irrigation. Drippers were close to the surface in this area as a result of
compaction and wear from building and excavation that was occurring independently of
the study. Gradually top dressing the soil with a soil conditioner mix, containing 5-10%
clay, until drippers are at 5cm depth will increase soil water retention and reduce deep
infiltration and health risks associated with surface dampening. Results from the tank test
show that lateral dispersion is small and highly localised to the dripper outlets, and that
only vertical transport through the soil was significant. This is supported by the SWIM
estimation of infiltration and the water supply excess of the box model discussed in the
proceeding section.
The filter mesh overlying the tank inlet rapidly accumulated a film of hair and lint
allowing flow from the greywater intake pipe to “glide” over this viscous layer directly to
the sewer bypass. Removal of the filter mesh overlying the tank inlet led to total reliance
on the fine screen post-pump filter cartridge for removal of solids that could pose a
blockage risk in the irrigation network. Increased loading to the filter cartridge resulted in
rapid filter build-up and increased flow resistance and irrigation pumping time. The need
to clean the filter cartridge once every 3-4 weeks is undesirable as it can tend to become a
neglected chore (CDWR 1995). Re-installation of a coarse screening mesh or filter is
necessary to reduce maintenance frequency.
63
The design dripper spacing of 30cm (east-west) and 40cm (north-south) slightly exceeded
the maximum spacing recommended by Jeppesen (1996) of 35cm in any direction, but
resided within the AS/NZS (2000) guideline of 60cm. Due to the lack of uniformity in
soil wetting it is likely that both the design and recommended spacings are much too
large for sandy soils. The tank test results show that the shape and uniformity of wetting
within the soil may not be constant for each irrigation event. Periods of soil drying, such
as the moderately dry period for the five days preceding the 17/09/2003 (Figure 23),
result in reduced soil hydraulic conductivity and increased lateral dispersion (Figures 13-
20). This increase in lateral dispersion is likely to be responsible for the anomalous peak
in post-irrigation soil moisture on the 17/09/2003 for the 0-10cm electrodes. The top
10cm of soil is exposed to a comparatively large amount of ET and heating, relative to
the other depths, resulting in more rapid moisture loss. Irrigation, as a result of the
dripper network, is quite patchy and moisture loading is highly dependent on proximity to
a dripper outlet. This can be observed in Figures 10 & 21 where relatively large mean
post irrigation increases (5-8mm) in the top 10cm of soil can be seen to correlate to
sample points that are close to the known dripper outlets towards the western edge of the
lawn. Thus soil wetting close to that of homogeneity is not achieved with the current
dripper spacings. The following section (Section 5.2) discusses the consequences of the
40cm x 30cm dripper spacing with respect to infiltration risk. Based on the wet soil
dispersion diameter (Table 8), optimal spacing for drippers is between 15 and 20cm in all
directions. This spacing allows some overlap of the wetting fronts.
5.2 WATER BALANCE
Three methods for determining a water balance for the turf at 72 Keightly Road Shenton
Park are presented here for discussion. An analytical approach, a numerical box model
approach and a 1-dimensional computational approach using the Soil Water Infiltration
and Movement model (SWIM), are employed for comparison purposes. Each mode of
analysis displayed certain strengths and weaknesses, giving a broader picture of the
64
hydraulic processes at the study site than would have been obtained from the use of one
method alone.
The soil moisture, with respect to depth, measurements were inconclusive on the
occurrence of infiltration beyond 45cm depth. This is due largely to the non-uniformity of
soil wetting and the location of the moisture electrodes. In the event of uniform 5mm soil
wetting and neglecting the 0-30cm moisture results, Figure 23 would seem to imply that
3-5mm (the distance between the dotted and dashed lines) of moisture could not be
accounted for and must have infiltrated beyond 45cm. This infiltration is very unlikely
however as the moisture increase in the top 10cm is almost identical to the moisture
increase measured over the top 45cm for most of the sample days. This implies that the
moisture added to the top 10cm, at the location of the 10cm and 45cm electrodes, has
remained within the top 10cm. Moisture infiltrating from the top 10cm would have
resulted in a greater increase in moisture for the 45cm electrodes than the 10cm
electrodes, as the soil is not saturated and some of the moisture would have been
absorbed by soil pores as it infiltrated downwards. However, this doesn’t mean that
infiltration is not occurring closer to the dripper outlet. Figure 23 indicates that the
electrodes furthest from the dripper outlets, the 0-10 and 0-45cm electrodes, increase by
significantly less (dotted lines) than the 5mm we would expect in the event of uniform
wetting (dashed lines). The 0-30cm electrodes, although they exhibit significant variation,
show much greater than 5mm moisture loading. These electrodes were on average 2.5cm
closer to the dripper outlets. Thus the degree of soil wetting is heavily affected by radial
distance from the nearest dripper. The high moisture reading for the 0-10cm electrode on
the 17/09/2003 is not mirrored in the 0-45cm moisture reading. It is possible that
moisture dispersion to the 45cm electrode was inhibited somewhat by the slight land
surface gradient, as the 45cm electrodes were slightly uphill relative to the other
electrodes. The increase in soil moisture storage from the two storm events, centred on
the 10/09/2003 and 23/09/2003, is responsible for the background “curviness” of Figure
23 on a daily-weekly timescale. Note that increases in soil moisture between pre-
irrigation measurements can be observed uniformly at all depths; the distance between
the pre-irrigation lines for the 0-10cm, 0-30cm and 0-45cm depths remains roughly the
65
same despite the overall curvature on a daily to weekly timescale. Thus the homogeneous
wetting effect of rainfall, which is not affected by radial distance from drippers, can be
observed. This supports that the patterns shown in the results, due to irrigation, are a
result of non-uniform wetting rather than equipment failure. As is implied by the 0-30cm
moisture results, when the 200L of irrigation is applied to a corrected wetting area based
on the wetting diameter of the damp soil tank test, the effective irrigation is much higher
than 5mm. With a damp tank test wetting diameter of 19.3cm, the area over which the
irrigation is dispersed, the wetted area, is reduced from 39 square metres to 9.51 square
metres with an effective irrigation of 21.03mm. This is a very heavy irrigation for such
sandy soil and poses a high risk of infiltration.
Plots of water supply and demand (Figures 24, 25 & 26), based on 3-daily irrigation of
200L to a turf area of 39 square metres, show that maximum demand is equal to or above
the supply from the 10th of October to the 10th of March if infiltration is negligible. Figure
25 shows that rainfall alone is insufficient to support Buffalo turf transpiring at its
maximum rate from early May to the 10th of September. This means irrigation is required
during this period. However, Short & Colmer (2001) state that warm season turf grasses,
such as Buffalo, can be sustained for up to 10 weeks at an irrigation rate of only 33% of
the daily Epan and display rapid recovery on resumption of full irrigation. Thus warm
season turf has the capacity to adjust to periods of water shortage. Thus turf irrigation
rates do not need to be altered weekly or monthly to account for seasonal climatic
changes. However, summer Epan is 7mm-8.5mm per day which represents a minimum
33% Epan turf irrigation demand of 2.31mm-2.80mm per day. This is much more than the
5mm per 3 days represented in the box model. Using the maximum irrigation
consumption of 67.8 % of the daily Epan presented by Short (2002), for turf grown at the
nearby Shenton Park UWA Turf Research Centre in summer, as an upper boundary
requirement irrigation should be conducted on a daily basis during summer. Irrigation
once every 2 days may be tentatively sustainable, however this represents 2.5mm per day
which is less than the 2.80mm per day minimum requirement during peak 8mm summer
Epan. Short & Colmer (2001) recommend a minimum irrigation of 50% Epan and report
some degree of turf degeneration at irrigation rates of 33% Epan, with a 40.3% loss of
66
colour over 10 weeks, thus making sustained low irrigation undesirable. Based on the
climatic box model presented in Figures 24-26 and the considerable buffer to irrigation
requirement (33%-67.8% Epan) an irrigation regime can be devised and maintained within
the upper and lower boundary requirements (Figure 28). The ideal irrigation regime
consists of irrigating daily from the 10th of December to the 20th of February, once every
2 days from the 20th of February to the 10th of April, no irrigation from the 10th of April
to the 20th of October, and once every 2 days from the 20th of October to the 10th of
December. The once per 3 day irrigation used in the preliminary analysis was omitted
from the final irrigation regime, as it was only found to be suitable for a small part of the
year. A short once per 3 day irrigation period before winter results in overly regular
changes to irrigation frequency and might become confusing to system owners who do
not automate their irrigation schedule. The emphasis is on keeping supply slightly in
excess during the transition from one regime to another to help protect the turf against
seasonal climatic variation and thus water deficiency. The large excess of water supply
due to rainfall alone in winter is several times the maximum ET capacity of Buffalo
grass, indicating that regardless of the infiltration rate there will be an increase in soil
moisture storage and groundwater recharge during the period.
The SWIM model was run for three different 18 day scenarios. The first scenario
involved once per 3 day irrigation of 21mm (Table 11) during the climatic transitional
period 10/09-28/09 where rainfall ceases to be in excess of turf maximum demand. This
gives an indication of the maximum amount of infiltration during the period of soil
moisture analysis (10/09-28/09). In the case of non-uniform soil wetting, maximum
infiltration will occur at the drippers within the maximum lateral dispersion diameter.
This diameter is assumed to be equivalent to that of the damp soil tank test. 42mm of
deep drainage is predicted by the model for the period. However, the increase in soil
storage represents an unsustainable sink. Once soil storage can not support additional
moisture, the remainder will become deep infiltration, thus the maximum expected
equilibrium rate of infiltration over the 18 day period would be 27mm + 42mm or
approximately 656L for the wetted area. This infiltration is unnecessary for the support of
67
the turf, as rainfall alone is sufficient during the period; according to the devised
irrigation regime. The SWIM predicted infiltration cannot be validated by the
inconclusive results of the soil moisture analysis.
The SWIM model was run for the 18 day summer period commencing 06/01 to the 24/01
at a daily irrigation frequency for the second two trials. Uniform soil wetting of 5mm was
assumed across the turf area for the first summer trial (Table 12) and compared to the
second summer trial assuming non-uniform wetting of 21mm surrounding each dripper
(Table 13). Once again, this 21mm was based on the lateral dispersion, or soil wetting
diameter, of the damp soil tank test. The uniform wetting scenario resulted in an
infiltration of 19mm + 8mm, which amounts to approximately 1050L across the total turf
area for the 18 day period. The non-uniform wetting scenario resulted in a maximum
expected infiltration of 265mm + 49mm or 2985L over the wetted area for the 18 day
period. These results imply that infiltration can be reduced approximately three-fold by
improving the uniformity of the greywater application. However, due to the high
permeability of the soil, the model predicts that infiltration can not be eliminated. Even a
small application of 5mm, whether due to irrigation or rainfall, results in some loss below
1m depth. This largely discounts the risk of sodium and salt accumulation within the soil
but presents the risk of nutrient leaching.
The SWIM model was not run for the once per 2 day irrigation transition period, as
infiltration is expected to be of similar magnitude to summer results due to the
approximate balancing of reduced ET demand and reduced rainfall + irrigation supply for
the period. It is worth noting the SWIM predictions of infiltration may be slight over
estimates due to the disruption of in-situ soil properties, such as subtle layering, when
samples were removed for water retention analysis.
All three modes of analysis highlight that, in the event that soil biological decomposition
is insufficient, fertilizers applied to lawns on sandy soils with or without greywater
systems are likely to leach into the groundwater. As mean daily rainfall is used, heavy
soil flushing due to storm events is not considered. Heavy periods of rainfall may result
68
in greater deep infiltration than a temporally even distribution of rainfall in sandy soil.
This is because short heavy falls of rain will be in excess and infiltrate before plants can
transpire a significant proportion. Light regular rain will result in a greater proportional
ET loss before deep infiltration can occur.
For environmental reasons it is desirable to allow the leaching of highly soluble and
conservative chemicals such as sodium and chloride, but undesirable to allow the
leaching of coliforms, phosphates or nitrates. To achieve this balance would depend on
rates of nutrient uptake and pathogen degradation within the soil rather than the blanket
prevention of deep infiltration. However, these processes may be aided by a reduction in
infiltration rate and thus an increase in water soil residence time within the biologically
active zone. Some soil leaching is required to prevent the accumulation of salts, such as
sodium chloride, that are not readily taken up by plants or removed by other means.
In the event of insufficient nutrient degradation within the soil the infiltration
implications for the box model and the SWIM model are that all household lawns,
whether fertilized or greywater irrigated, pose a potential for nutrient leaching to the
groundwater. Thus the issue for consideration may be the relative annual nutrient
loadings of greywater irrigation, based on the proposed irrigation regime, compared to
standard fertilization. The rapidity of pathogen decay within the soil is the other major
consideration for risk assessment.
69
6.0 Conclusions
Infiltration of rainfall and irrigation to the groundwater cannot be prevented for the sandy
soil at 72 Keightly Road Shenton Park. There is an excess of water in winter, due to
rainfall alone, which will result in groundwater recharge. Irrigation is required daily from
the 10th of December to the 20th of February, once every 2 days from the 20th of February
to the 10th of April, no irrigation from the 10th of April to the 20th of October, and once
every 2 days from the 20th of October to the 10th of December. This is the minimum
irrigation requirement to sustain warm season turf grass. The irrigation regime presented
will also result in deep infiltration. The lack of uniformity of soil wetting, as a result of
large spacings between drippers, contributes to the degree of deep infiltration. Optimal
dripper spacings for the sandy Keightly Road soil are 15-20cm in both lateral directions.
This is a much higher density than the recommended maximum spacing of 35-60cm for
sandy soils. Pathogens, phosphorus, nitrogen, boron and high TDS are contaminants of
concern for irrigation reuse. The degradation rates and risk these contaminants pose needs
to be evaluated, as the infiltration results show that the vertical transport of conservative
contaminants, such as sodium, is inevitable.
Infiltrative flushing and low clay levels dictates that Salinisation and reduced soil
permeability are highly unlikely. Increasing the clay content of the soil will help increase
the nutrient residence time within the active root zone and the microbially active zone of
the soil. The effect of adding a clay top-dress to the soil, to deepen overly shallow drip-
lines and to increase water retention, should be noted. If necessary gypsum may need to
be added to increase soil permeability in the event that clay addition is excessive.
Coarse post-tank hair and lint screening needs to be re-designed and implemented. Two
proposed solutions to the design are to increase the filter mesh surface area by bending
undulations (Appendix 16), or the addition of a smaller tank that allows a head of
pressure to build up over the mesh.
70
7.0 Recommendations
Digging 5cm furrows between and parallel to the north-south columns of drippers, and
adding 9 new dripper columns will help to increase the wetting efficiency. This would
allow horizontal wetting diameters to overlap (in the east-west direction), according to
the findings of the damp tank test experiment, and increase the uniformity of soil wetting.
However, for future installations in sandy soil, dripper spacings on the columns between
15 and 20cm would be ideal.
Deepening the drippers on the southern section of the lawn, that have become shallow as
a result of soil compaction and wear from building and construction, would reduce the
risk of pathogen exposure. Some soil top dressing is required to eliminate the surface
dampening and to deepen drippers at southern end of the lawn. Occasional topdressing of
the entire lawn may be required to maintain dripper depth. Top dressing with a clay soil
mix will help prevent surface dampening and will increase lateral dispersion of irrigation.
However, only one clay dressing should be applied due to the adverse effects of
greywater on clay permeability. In the event of problematic permeability loss from over
addition of clay, gypsum may be added as a top dress to reduce the SAR and improve
permeability. Research into an appropriate long term soil clay balance for greywater
irrigation may be of future benefit.
Reintroduction of primary hair and lint screening is necessary for extending the lifespan
of the design and reducing maintenance. Increasing the surface area of the mesh screen
by bending undulations, perpendicular to the pipe wall, may be a simple solution
(Appendix 16). The screen can easily be inserted and removed for cleaning by means of
opening the access cap. Alternatively a small catchment tank or pipe may be inserted to
allow the buildup of some hydrostatic pressure above the mesh. This tank would
overflow to the sewer when full. A design such as this could be improved with the aid of
electronics, allowing a short period of backwashing or reverse flow through the filter
mesh at the start of each pumping, so that filter cleaning is seldom, or never, required.
71
A new tank test could be run to examine the effects of laundry surfactants on soil
hydrological properties, particularly rates of lateral and vertical dispersion.
Computer analysis could be performed using more complex 2-D packages such as
HYDRUS 2-D and extrapolating results to a third spatial dimension. This would give
improved consideration to non-uniform wetting and thus a more accurate volumetric
infiltration estimate. A comparison of the SWIM model performance to other models
such as the Multiple Gravity-front Model may also be of interest.
72
8.0 References
Atkins, P. W. 1996, The Elements of Physical Chemistry, Oxford University Press,
Oxford, England.
Augustin, B. J. 1983, Water requirements of Florida Turfgrasses, University of Florida,
Cooperative Extension Service. Bul200.
Australian Bureau of Statistics. 1998, Environmental Issues – Peoples Views and
Practices. March 1998, Cat. No 4602.0, ABS, Canberra.
Australian Capital Territory Government. July 1999, Environment Protection Policy:
Wastewater Reuse for Irrigation. Environment ACT. BDM 99/0415, Canberra.
Australian/New Zealand Standards™. 2000, On-site domestic wastewater management,
ISBN 0 7337 3439 1, jointly published by Standards Australia International Ltd and
Standards New Zealand.
Australian Water Association. 2003. On-site Systems 1, article 27 of the ‘We all use water
flyer Series: A users guide to water and wastewater management’ [online]. Australian
Water Association, Sunshine Coast Environment Council, and The Natural Heritage
Trust initiative Available from <http://www.awa.asn.au/education/27_Onsite2.pdf>
[20th of August 2003].
Barton, L. & Colmer, T. 2001. ‘ Maximising turf quality, minimizing nutrient leaching’,
Research Rap, Australian Turfgrass Management, vol. 3.4.
Bevan, K. J. 2001, Rainfall-Runoff Modelling: The Primer, John Wiley & Sons Limited,
West Sussex, England.
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Biran, I., Bravdo, B., Bushkin-Harav, I. & Rawitz, E. 1981, ‘Water consumption and
growth rate of 11 turfgrasses as affected by mowing height, irrigation frequency, and soil
moisture’. Agronomy Journal 73(1): 85-90.
Brooks, R. H. & Corey, A. T. 1966. ‘Properties of porous media affecting fluid flow’, J.
Irrig. Drainage Div., A.S.C.E. Proc., vol. 72 (IR2), pp. 61-68.
California Department of Water Resources. January 1995, Graywater Guide: Using
Graywater in Your Home or Landscape. California Department of Water Resources,
Water Conservation Office, P.O. Box 942836, Sacramento, CA 94236-0001. (916) 643-
1097.
Campbell, G. S. 1974. ‘A simple method for determining saturated conductivity from
moisture retention data’, Soil Sci., vol. 117, pp. 311-314.
Department of Environment and Heritage. 2001, Water Conservation Partnerships
Project – Review of Urban Domestic and Local Council Water Conservation, Roof
Runoff, ASR and Wastewater Reuse Opportunities, ISBN 0 759 010 250, DEH, Adelaide.
Department of Health, Water Corporation & Department of Environment, Water and
Catchment Protection. July 2002, Draft Guidelines for the Reuse of Greywater in Western
Australia. Western Australia.
Electrical Power Research Institute. 2001, Final Report for the National Research Needs
Conference Proceedings: Risk-Based Decision Making for Onsite Wastewater Treatment,
EPRI, Palo Alto, CA, U.S. Environmental Protection Agency, and National Decentralized
Water Resources Capacity Development Project: 2001. 1001446.
Emmerson, G. 1998, Every Drop is Precious: Greywater as an Alternative Water Source,
ISSN 1325-1341, ISBN 0 7242 7838 9, Queensland Parliamentary Library - Publication
and Resources section, Queensland, Australia.
74
Environment ACT. (13 August 2003), Greywater Use Around the Home, [online], ACT
Government and dept. of Urban Services, available from:
<http://www.environment.act.gov.au/files/greywater.pdf>
[15 August 2003].
Fetter, C. W. 2001, Applied Hydrogeology, 4th edn., Prentice-Hall, New Jersey.
Frank, K. W., Leach, B. E., Crum, J. R., Rieke, P. E., Leinauer, B. R., Nikolai, T. A. &
Calhoun, R. N. 2001. ‘The Effects of a Variable Depth Root-zone on Moisture Retention
in a Sloped USGA Putting Green’, Australian Turfgrass Management, vol. 3.3.
Frankenberger, W. T. 1992, ‘Gray = Green2, A Gray Water Seminar’, in Fate of
Wastewater Constituents in Soil and Groundwater: Pathogens Conference, November 18
and 19, The Water Re-use Association of California, pp 14.1-14.19.
Haque, A. 2002, ‘Estimating Actual Areal Evapotranspiration from Potential
Evapotranspiration using Physical Models Based on Complementary Relationships and
Meteorological Data’, Bulletin of Engineering Geology and the Environment, vol. 62, no.
1.
Hemond, H. F. & Fechner-Levy, E. J. 2000, Chemical Fate and Transport in the
Environment, 2nd edn, Academic Press, California, U.S.
Jeppesen, B. & Solley, D. 1994, Domestic Greywater Reuse: Overseas Practice and its
Applicability to Australia, Urban Water Research Association of Australia. Research
Report No 73, March 1994.
Jeppesen, B. 1996, Model Guidelines for Domestic Greywater Re-use in Australia, Urban
Water Research Association of Australia. Research Report No. 107, March 1996.
75
Kowald, B. 2003, Bureau of Meteorology, email, 16th October.
Marshall, G. 1996, ‘Greywater Re-Use: Hardware, Health, Environment And The Law’
in Designing for a sustainable future: Proceedings of the Sixth International
Permaculture Conference and Convergence.
NSW Department of Health. April 2000, Greywater Reuse in Single Domestic Premises.
Parish, J. 1987, Turf News, no.7. Perth Western Australian Department of Agriculture:1-
4.
Passmore, N. 1999, ‘Turf Trials’, Gardening Australia Factsheet, 2nd of August.
Patterson, R. A. 1996, ‘Demonstration of the effects of sodicity on soil hydraulic
conductivity’ in proceedings of conference on Innovative Approaches to the On-site
Management of Waste and Water, Southern Cross University, Lismore, November 26th.
Penman, H. L.1948, ‘Natural evaporation from open water, bare soil and grass’,
Proceedings of the Royal Society, A193, pp. 120-145.
Prescott, L. M., Harley, J. P. & Klein, D. A. 1999, Microbiology, 4th edn., McGraw-Hill.
Richards, L. A. 1931. ‘Capillary conduction of liquids through porous mediums’,
Physics, vol.1, pp. 318-333.
Rosenberg, N.J. 1974, Micro-climate: The Biological Environment. John Wiley & Sons,
New York.
Ross, P. J. 1990, ‘SWIM – a simulation model for Soil Water Infiltration and Movement’,
reference manual, CSIRO Division of Soils, Davies Laboratory, Townsville, Queensland,
Australia.
76
Short, D. C. & Colmer, T.D. 2001, Reducing water use by turf grasses in aMediterranean environment: evaluation of diverse species, Australian TurfgrassManagement, 3.4:August-September 2001.
Short, D. C. 2002, Irrigation Requirements and Water-Use of Turf Grasses in a
Mediterranean-Type Environment, PhD thesis, University of Western Australia.
Smettem K. R. J., Ross P.J. 1992. ‘Measurement and prediction of water movement in a
field soil: The matrix-macropore dichotomy’ Hydrol. Proc., vol.6, pp. 1-10.
Smettem K. R. J. 2003, Centre for Water Research, University of Western Australia,
email, 28th October, <[email protected]>.
Stone, R. 1996, ‘Water efficiency program for Perth’, Desalination, Vol. 106, p377-390.
Water Authority of Western Australia. 1995, The Flow, August, No 8, Wastewater 2040,
Leederville, Western Australia.
Water Authority of Western Australia. 1993, What is wastewater?, Wastewater 2040,
Leederville, Western Australia.
Water corporation of Western Australia. Greywater, [online], available from:
<http://www.watercorporation.com.au/residential/owf_options_greywater.cfm>
[05 August 2003].
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England.
77
9.0 Appendices
Appendix 1. Suitable/un-suitable vegetation.
Un-suitable vegetationazaleas camellias gardenias begonias fernsProteaceae Family
Suitable vegetationTrees Shrubs Climbers Perennials GrassesNyssa Sylvatica Nerium oleander Bougainville
aAgapanthus preaecos Kikuyu
Casuarina glauca-“Swamp oak”
Abelia x grandiflora Hibbertiascandens
Aster novi-belgii Buffalo
Protinea x fraseri-“Robusta”
Cassia bicarpsularis Kennedia Canna x generalis (Most grassessuitable)
Callistemon viminalis Hebe speciosa Lonicerajaponica
Chrysanthemummaximus
Angophora costa Lantana montevidensis Panoreajasminoides
Salvia x superbra
Melaleuca armillaris-“Bracelet honeymyrtle”
Pyrachantha fortuneana Hardenbergia
Stokesia laevis
Melaleucaquinquenervia-“Broad leavedpaperbark”
Jasminium officinale-“Grandiflorum”
Viola hederacea
Leptospermumlaevigatum
Jasminium polyanthum Gazania x hybrida
Leptospermumpetersonii
Callistermon citrinus-“Lemon scentedbottlebrush”
Tristaniopsis laurina Thunbergia alataChaenomeles laegenariaEuonymum mesnyiAcacia longifolia-Sydney wattle”Salvia ulignosia- “Bogsage”RosemaryCanna lilyCeratostigma
78
Appendix 2. Bore Drilling Logs Near Study Site.
WIN SiteId
Site Type Feature Type AQWABase Reference
20029855 Ground Borehole or Well 2034-2-SW-0949 50
20030034 Ground Borehole or Well 2034-2-SW-1128 50
WIN SiteId
Easting Northing Latitude
20029855 388399.00 6463676.00 -31.957412510 115
20030034 388465.00 6463321.00 -31.960621099 115
WIN SiteId
Geographic Datum Geographic Precision (+/- x metres) Geographic Assessment Method
20029855 Geodetic Datum of Australia1994
100 GDA94 Conversion (Accuracy of 0.05 -0.9m)
15/0
20030034 Geodetic Datum of Australia1994
100 GDA94 Conversion (Accuracy of 0.05 -0.9m)
WIN SiteId
Location Map Code 1:250,000 Map Code Sketch Indicator
20029855 BG34/3.5 SH50-14 N ()
20030034 BG34/3.5 SH50-14 N ()
WIN SiteId
River Basin Owning AuthorityComments
20029855 616 - Swan Coastal
20030034 616 - Swan Coastal Rosalie Court DEPTH ORIGINALLY: 26M/24M.
WIN SiteId
Numbering System End Date Cons. Organisation
20029855 AQWAB 15/09/1978
20030034 AQWAB 13/10/1978 Hugall & Hoile
20030034 AQWAB 13/10/1978 Hugall & Hoile
79
.
WIN SiteId
Depth Reference Point Drilled Depth Drill Method Co
20029855 Ground level 19.200 Percussion Lini
20030034 Ground level 26.000 (none) Inle
20030034 Ground level 26.000 (none) Unk
WIN SiteId
Construction Element Construction Material Distance To Top(m)
D
20029855 Line unknown Unknown
20030034 Screen Unknown 22.000 24.0
20030034 Unknown Unknown 24.000 26.0
WIN SiteId
Screen Aperture (mm) Element Comment
20029855 PVC 100MM; SLOTTED: 1.5M PVC S/S COVERED
20030034 0.000
20030034 Element added to align distance to bottom for last element withtotal drilled depth.
WIN SiteId
Numbering System Reference Log Date L
20029855 AQWAB 2034-2-SW-0949 15/09/1978 Kno
20030034 AQWAB 2034-2-SW-1128 13/10/1978 Kno
WIN SiteId
Depth ToStratigraphy
Lithology
20029855 19.200 SAND ALL THE WAY; YELLOW TO WATER THENBECOMING PALER TILL AT 3M BELOW WATER SAND WASWHITE AND REMAINED SO TO TD. SAND VARIED FROMFINE TO COARSE GRAINS.
sand
20030034 26.000 Quaternary sand
80
Appendix 3. Water and Rivers Commission – Groundwater Atlas.
The above figures were calculated from the following values which were extracted from the three surfaces at location388339 East, 6463407 North**
Natural Surface Level: 20.2 metres
Watertable Level: 6.3 metres
Base of Aquifer Level: -30. metres
All levels are relative to AHD (Australian Height Datum)
* Estimates may fluctuate between 0.5 and 3m due to seasonal variation. Under normal circumstances, a garden bore willbe drilled to a depth 10 metres below the watertable. Add 10 m to the depth-to-groundwater to estimate the drilling depth.
Groundwater contours are estimated maxima based on recorded water levels. Because of changes in groundwater andnatural surface levels that can occur overtime it should be clearly understood that the Water and Rivers Commission is notin a position to guarantee the accuracy of the data. Further, the location of possible sources of contamination to thegroundwater supply, while believed to be accurate, is not guaranteed, nor is it guaranteed that all such sources have beenidentified.
The Perth Groundwater Atlas is not suitable for calculating the depth of water bodies such as rivers or lakes.
** The map data currently displayed by the Groundwater Atlas is in AMG Zone 50 co-ordinates, using the AGD84 datum.
81
Appendix 4. Chem. Centre Soil Log.
82
Appendix 5. Site Location.
83
Appendix 6. Household Layout.
84
Appendix 7. Split Plumbing Cartoon Schematic.
85
Appendix 8. Greywater Irrigation Volumes.
DateMeterreading(after)
Volume(L)
9/07/2003 1415.812/07/2003 1509.4 93.617/07/2003 1568.4 5920/07/2003 1769.6 201.224/07/2003 1891 121.427/07/2003 1921.6 30.630/07/2003 1937.3 15.7
3/08/2003 1971 33.76/08/2003 2172.7 201.7 Coarse screen removed 4/08/2003
10/08/2003 2361.6 188.913/08/2003 2563.7 202.117/08/2003 2767.1 203.420/08/2003 2875 107.924/08/2003 3094.6 219.6 Filter cleaned. Greywater inflow during pumping27/08/2003 3295 200.431/08/2003 3596.3 301.3
5/09/2003 3798.2 201.97/09/2003 3947 148.8
10/09/2003 4142.1 195.114/09/2003 4241.4 99.317/09/2003 4443.3 201.9 21/09/2003 4647.7 204.424/09/2003 4848.5 200.8 28/09/2003 5049.7 201.2
2/10/2003 5251 201.3 5/10/2003 5372.1 121.1 Filter blockage 8/10/2003 5572.2 200.1
TOTAL 4156.4
86
Appendix 9. On-Site Rain Gauge Data.
DateRainfall in24hours to
7.30am (mm)Comments
4/09/2003 05/09/2003 06/09/2003 07/09/2003 0.58/09/2003 39/09/2003 7.510/09/2003 511/09/2003 512/09/2003 0.513/09/2003 3.514/09/2003 015/09/2003 016/09/2003 017/09/2003 018/09/2003 019/09/2003 020/09/2003 821/09/2003 122/09/2003 623/09/2003 824/09/2003 125/09/2003 626/09/2003 027/09/2003 0
28/09/2003 0(girls playing with hose - perhaps 0.5mm)
29/09/2003 2130/09/2003 6total 82
87
Appendix 10. MATLAB Evapotranspiration, Rainfall and Irrigation Script
clear allclose all
%Still need to add irrigation quantites
load evapdat.datload nedlandsrain.daty = evapdat(:,2);x = evapdat(:,1);%Have assumed all given data means occur at the middle of each monthjuliandays = 16:381;
%our irrigation regime started 21/06/03 = julian day 172%julian day = 185 as at 04/07/03n = 5;coeff = polyfit(x./100,y,n); %had to divide by 100 to reduce rounding errorEraw = polyval(coeff,juliandays./100);upscale = 1.07; %Scale Epan up due to bird guard.E = Eraw.*upscale;Kcrop = 0.678;
K = Kcrop; %crop coefficient from lit review... non moisture limited.
irrigationday = (172:3:381)'; %1 irigation per 3 days
ETloss = K.*E;
for i = 3:366;A = sum(ETloss(i-2:i));Lossbetweenirrig(i-2) = A;i = i+3;end
lawnarea = 13*3; %m^2irrigoutput = 205/1000; %L->m^3irrigation = 1000*irrigoutput/lawnarea; %(mm) Assuming uniform dispersal (not entirely true)Cound decrease area according to tank test
%Irrigation starting from julian day 172 onwardsirrigmatrix = zeros(366, 1);for i = 172-16:3:366;irrigmatrix(i) = irrigmatrix(i) + irrigation;endirrigmatrix = irrigmatrix';%This can be used later to represent stepwise irrigationdailyirrig = zeros(366,1);
88
%dailyirrig(156:366,1) = (irrigation/3);%entry 156 is julian day 172 in Matrix (-16)dailyirrig = (irrigation/3);dailyirrig = dailyirrig';
yrain = nedlandsrain(:,2);xrain = nedlandsrain(:,1);daysinmonth = [31;28;31;30;31;30;31;31;30;31;30;31;31]; %jan 2003:2004dailyrain = yrain./daysinmonth;coeffrain = polyfit(xrain./100,dailyrain,11); %had to divide by 100 to reduce errorRain = polyval(coeffrain,juliandays./100);Fitcorrection1 = polyfit(xrain(1:3)./100,dailyrain(1:3),5);Fitcorrection2 = polyfit(xrain(11:13)./100,dailyrain(11:13),5);Rain(1:60) = polyval(Fitcorrection1,juliandays(16:75)./100);Rain(303:366) = polyval(Fitcorrection2,juliandays(303:366)./100);
watbal = Rain + dailyirrig - ETloss;
%plot(xrain,dailyrain,'r+',juliandays,Rain,'m--')%Note 364 because of julian days. Data starts at day 16 and ends 15th jan next year.B = Lossbetweenirrig(1:3:364)';%ET losses between irrigation trialsplot(juliandays,-E,'b--',juliandays,-ETloss,'g--',16:3:381,-B,'rx:',juliandays,Rain,'m--',juliandays,Rain-ETloss,'r-',juliandays,watbal, 'k-.')xlabel('Julian days commencing 16/01/03 and ending 16/01/04')ylabel('mm/day water')legend('Evaporation curve fit','ET curve','ET loss between irrig (per 3 days)','Daily rainfall','Rain-ET','prelimwat.bal.');title('Plot of Evap ET and Average Rainfall')%is ET (K*evap) in addition to evap... ie is total loss is ET+Evap)%Will assume ET is K*E... therefore grass reduces evap by 0.85figurefigureplot(xrain,dailyrain,'rx',juliandays,Rain,'m--')xlabel('Julian days commencing 16/01/03 and ending 16/01/04');ylabel('rainfall (mm)');legend('Average daily rainfall (per month)','Daily rainfall curve-fit');title('Average daily rainfall curve');
figureplot(juliandays,-E,'b--',juliandays,-ETloss,'g--',16:3:381,-B,'rx:',juliandays,Rain,'m--',juliandays,Rain-ETloss,'r-',juliandays,watbal, 'k-.')xlabel('Julian days commencing 21/06/03 and ending 31/08/03')ylabel('mm/day water')legend('Evaporation curve','ET curve','ET loss between irrig (3 daily)','Daily rainfall','Rain-ET','prelimwat.bal.');title('Plot of Evap ET and Average Rainfall 21/06/03-31/08/03')AXIS([172 243 -10 10])
89
%This plot focusses on the likely period of study
figureplot(juliandays,-E,'b--',juliandays,-ETloss,'g--',16:3:381,-B,'r+:',juliandays,Rain,'m--',juliandays,Rain-ETloss,'r-',juliandays,watbal, 'k-.')xlabel('Julian days commencing 1/05/03 - 10/09/03')ylabel('mm/day water')legend('Evaporation curve','ET curve','ET loss between irrig (3 daily)','Daily rainfall','Rain-ET','prelimwat.bal.');title('Plot of Evap ET and Average Rainfall during rainfall surplus period 1/05/03 - 10/09/03')AXIS([121 253 -10 10])%Average daily rainfall >average daily ET%This plot shows period where water input exceeds ET.
%AXIS([100 283 -10 10]) = watbal excess = 10/3/03 - 10/10/03%AXIS([121 253 -10 10]) = rainfall - ET excess = 1/05/03 - 10/09/03%247
figureplot(juliandays,-E,'b--',juliandays,-ETloss,'g--',16:3:381,-B,'r+:',juliandays,Rain,'m--',juliandays,Rain-ETloss,'r-',juliandays,watbal, 'k-.')xlabel('Julian days commencing 10/3/03 - 10/10/03')ylabel('mm/day water')legend('Evaporation curve','ET curve','ET loss between irrig (3 daily)','Daily rainfall','Rain-ET','prelimwat.bal.');title('Plot of Evap ET and Average Rainfall during water balance surplus period 10/3/03 -10/10/03')AXIS([100 283 -10 10])%Average daily rainfall >average daily ET
%Note: evapdat.dat and nedlandsrain.dat are data files containing the month in the first column,from January to January and the mean monthly evaporation or rainfall in the second column.
90
App
endi
x 11
. Ned
land
s C
limat
e D
ata.
Clim
ate
aver
ages
for
Sta
tion
- w
eath
er d
ata
0090
35 N
ED
LAN
DS
UW
A C
omm
ence
d: 1
940;
Las
t rec
ord:
197
4; L
atitu
de (
deg
S):
-31
.986
1; L
ongi
tude
(de
g E
): 1
15.8
192;
Sta
te: W
A
Ele
men
tJa
nF
ebM
arA
prM
ayJu
nJu
lA
ugS
epO
ctN
ovD
ecM
ean
mon
thly
rai
nfal
l - m
m7.
812
.117
.450
.311
118
717
011
470
.349
.219
.412
.6M
edia
n (5
th d
ecile
) m
onth
ly r
ainf
all -
mm
3.6
2.7
10.2
42.4
116
188
162
108
67.1
45.8
14.6
7.1
9th
deci
le o
f mon
thly
rai
nfal
l - m
m22
3460
.399
.519
429
925
218
212
410
148
321s
t dec
ile o
f mon
thly
rai
nfal
l - m
m0
00
6.9
3296
.987
.959
.528
.812
.83
0M
ean
no. o
f rai
nday
s2.
22
3.4
7.5
12.1
17.3
17.4
15.1
12.3
9.1
4.8
2.8
Hig
hest
mon
thly
rai
nfal
l - m
m74
160
67.8
151
257
341
419
251
138
140
72.9
74.7
Low
est m
onth
ly r
ainf
all -
mm
00
00.
811
.686
.271
.936
.824
.11
00
Hig
hest
rec
orde
d da
ily r
ainf
all -
mm
38.1
83.3
40.6
38.1
81.3
74.9
56.9
4741
.167
.339
.161
Mea
n no
. of c
lear
day
s1.
54
7.5
93
3.3
32
4.7
7.5
0M
ean
no. o
f clo
udy
days
12
32
3.5
36.
52.
54
53
Hig
hest
rec
orde
d w
ind
gust
- k
m/h
66.6
61.2
72.4
83.5
87.1
85.3
83.5
85.3
90.7
92.5
94.7
66.6
91
App
endi
x 12
. Per
th R
egio
nal O
ffic
e C
limat
e D
ata.
CLI
MA
TE
AV
ER
AG
ES
- lo
ng te
rm m
ean
valu
es o
f wea
ther
dat
a 18
76 to
199
2
PE
RT
H R
EG
ION
AL
OF
FIC
ELa
titud
e:31
.95
SLo
ngitu
de: 1
15.8
7 E
Ele
vatio
n:19
.0 m
Com
men
ced:
187
6La
st r
ecor
d: 1
992
Sta
te:
WA
JAN
FE
BM
AR
AP
RM
AY
JUN
JUL
AU
GS
EP
OC
TN
OV
DE
CM
ean
Dai
ly M
ax T
emp
(deg
C)
3030
2824
.620
.918
.317
.418
19.5
21.4
24.6
27.4
Mea
n no
. Day
s, M
ax >
= 4
0.0
deg
C1.
10.
60.
20
00
00
00
00.
3M
ean
no. D
ays,
Max
>=
35.
0 de
g C
6.3
5.5
2.7
0.3
00
00
00.
21
3.2
Mea
n no
. Day
s, M
ax >
= 3
0.0
deg
C15
14.6
10.9
30.
20
00
0.2
1.5
4.6
8.7
Hig
hest
Max
Tem
p (d
eg C
)46
46.2
42.3
37.1
31.8
28.1
26.3
27.2
32.3
37.3
40.1
42.3
Low
est M
in T
emp
(deg
C)
9.7
10.6
7.8
4.6
31.
62
2.3
2.6
4.2
6.2
8.6
Mea
n 9a
m A
ir T
emp
(deg
C)
2423
.321
.518
.615
.213
.112
.113
1517
.220
.122
.4M
ean
9am
Rel
ativ
e H
umid
ity (
%)
5052
5664
7278
7874
6860
5451
Mea
n 3p
m R
elat
ive
Hum
idity
(%
)41
4042
4853
6059
5653
5046
44M
ean
Rai
nfal
l (m
m)
8.6
13.3
19.3
45.5
123
182
173
135
79.9
54.5
21.7
13.9
Mea
n no
. of R
aind
ays
2.9
2.7
4.3
7.6
13.8
17.2
18.2
17.2
1411
.16.
54.
2H
ighe
st M
onth
ly R
ainf
all (
mm
)11
516
614
514
930
847
642
531
819
920
073
.280
.7Lo
wes
t Mon
thly
Rai
nfal
l (m
m)
00
00
14.1
54.9
61.5
11.8
8.7
10
0H
ighe
st R
ecor
ded
Dai
ly R
ain
(mm
)55
121
7766
.576
.299
.195
73.9
51.8
55.4
39.1
46.7
Mea
n no
. of C
lear
Day
s16
14.1
13.5
8.5
6.4
4.9
4.9
6.7
7.5
8.7
9.7
13.3
Mea
n no
. of C
loud
y D
ays
2.7
2.8
3.5
5.9
6.6
8.4
75.
55
4.2
3.6
2.7
Mea
n D
aily
Sun
shin
e (h
rs)
1110
.29
7.3
65
5.4
6.4
7.4
8.8
9.9
10.7
Max
imum
Win
d G
ust (
km/h
r)89
113
113
130
118
128
137
156
113
117
102
102
Mea
n D
aily
Eva
pora
tion
(mm
)8.
17.
76.
24
2.7
22
2.5
3.5
56.
37.
5
92
Appendix 13. Photo of turf roots after x weeks of growth. Root depth = 0.32-0.44m.
93
Appendix 14. Soil profile, showing relative homogeneity with some builder’s sand at thesurface. Depth of profile is 0.64m at max.
94
App
endi
x 15
. TD
R s
oil m
oist
ure
data
.
Moi
stur
e D
ata
%Q
uant
itym
m10
/09/
2003
vol =
195
.1L
Bef
ore
irrig
Site
1S
ite 2
Site
3S
ite 1
Site
2S
ite 3
Mea
nst
d de
v10
cm21
.119
.321
.321
.119
.321
.320
.566
671.
1015
1430
cm14
.510
.743
.532
.137
.88.
0610
1745
cm13
.313
.610
.759
.85
61.2
48.1
556
.47.
1765
24A
fer
irrig
10cm
26.4
21.5
24.5
26.4
21.5
24.5
24.1
3333
2.47
0493
30cm
19.1
1257
.336
46.6
515
.061
3745
cm13
.314
12.5
59.8
563
56.2
559
.73.
3774
9917
/09/
2003
vol =
201
.9L
Bef
ore
irrig
Site
1S
ite 2
Site
310
cm14
.67.
17.
914
.67.
17.
99.
8666
674.
1186
5730
cm10
.29.
930
.629
.730
.15
0.63
6396
45cm
10.7
12.1
11.4
48.1
554
.45
51.3
51.3
3.15
Afe
r irr
ig10
cm19
.818
.124
19.8
18.1
2420
.633
333.
0369
9430
cm15
.611
.846
.835
.441
.18.
0610
1745
cm11
.212
.510
.850
.456
.25
48.6
51.7
53.
9996
8721
/09/
2003
vol =
204
.4L
Bef
ore
irrig
Site
1S
ite 2
Site
310
cm18
.821
.721
.118
.819
.719
.119
.20.
4582
5830
cm12
.213
36.6
3937
.81.
6970
5645
cm12
.612
.911
.756
.758
.05
52.6
555
.82.
8102
49A
fer
irrig
10cm
20.9
21.3
20.6
20.9
21.3
20.6
20.9
3333
0.35
1188
30cm
17.4
13.8
52.2
41.4
46.8
7.63
6753
45cm
12.5
13.5
12.6
56.2
560
.75
56.7
57.9
2.47
8407
24/0
9/20
03vo
l = 2
00.8
Lsu
nny/
war
mB
efor
e irr
igS
ite 1
Site
2S
ite 3
10cm
2829
.627
.128
26.9
27.1
27.3
3333
0.58
5947
30cm
17.2
15.2
51.6
45.6
48.6
4.24
2641
95
45cm
15.4
14.9
14.5
69.3
67.0
565
.25
67.2
2.02
9162
Afe
r irr
ig10
cm26
.429
.426
.930
.429
.429
.829
.866
670.
5033
2230
cm25
.517
.276
.551
.664
.05
17.6
0696
45cm
16.1
15.9
14.4
72.4
571
.55
64.8
69.6
4.18
1208
28/0
9/20
03vo
l = 2
01.2
LB
efor
e irr
igS
ite 1
Site
2S
ite 3
sunn
y/ho
t10
cm18
20.2
2318
20.2
2320
.42.
5059
9330
cm10
.810
.732
.432
.132
.25
0.21
2132
45cm
12.8
12.6
11.5
57.6
56.7
51.7
555
.35
3.15
Afe
r irr
ig10
cm23
.725
.726
.423
.725
.726
.425
.266
671.
4011
930
cm15
.312
.745
.938
.142
5.51
5433
45cm
13.1
1311
.858
.95
58.5
53.1
56.8
53.
2553
8
96
Appendix 16. Preliminary filter modification. Consists of smaller diameter PVC pipe fitted
inside inflow pipe and an undulating mesh screen supported by plastic cylinders glued to the
small pipe wall. A large hole is made in the small pipe over the tank intake. Undulations should
be only half the pipe diameter high otherwise blockages may occur, preventing tank inflow and
sewer diversion.
