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6.0 Assessment of Rainwater Harvesting Systems for New-
Build Domestic Dwellings
6.1 Introduction
This chapter investigates the use of RWH systems installed in new-build
houses. Direct systems were assumed in all instances since these were
recommended by suppliers for domestic situations. Both the water saving
reliability and financial performance results are presented although the focus of
the analysis was primarily on the latter. The purpose of this investigation was to
provide data on the long-term economic viability of new-build domestic RWH
systems at the single building scale, to determine whether they present a
worthwhile financial investment and, if so, under what circumstances.
It was necessary to acknowledge that all not stakeholders will have the same
assessment criteria, especially with regards to the selected discount rate and
discount period. Information presented in chapter four and appendix two
demonstrated that a range of possible values exist dependant on the
stakeholder, and that selection of the most appropriate values will be influenced
by the context of the investigation. Table 6.1 summarises the discount rates and
periods that were considered appropriate for use in domestic simulations and
shows how the different values could be assigned to different stakeholder
groups.
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Table 6.1 Range of discount rates and periods used in the domestic
RWH system simulations
Stakeholder group1 Discount rate Discount period
Homeowner 15% 10Water utility 10% 25Private sector company 5% 5LA / Government 3.5% (declining) 501People or institutions to which the selected discount rates and
periods could be applicable
For each system investigated a total of three harvested water uses were
considered. One of the most common applications for harvested rainwater is
WC flushing and generally this is the most readily accepted (WPCF, 1989;
WROCS, 2000; Hills et al, 2003; Lazarova, 2003). Therefore all simulations
included WC flushing. Vleuten-Balkema (2003) reported that garden irrigation
was viewed as an acceptable application by the majority of people and so this
was included in the simulations with two water uses. Laundry cleaning (washing
machines) was found to be the next highest acceptable use and so this was
included in the simulations that had a total of three non-potable applications.
The water use scenarios considered therefore consisted of WC flushing only,
WC flushing plus garden irrigation, and WC flushing plus garden irrigation plus
washing machine.
According to Fido et al(2005) the average household occupancy in the UK was
2.30 persons in 2005. A decision was taken to model occupancies in the range
of 1-5 people as this was considered to be sufficient to cover a practical range.
For each simulation sixteen tank sizes in the range of 1.2-15.0m3 were
assessed since this was the number of domestic systems for which capital cost
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information was available (see appendix two, table A2.10 for a full list of the
tank sizes investigated). Installation costs for each system were assumed to be
1,000 (see chapter four, section 4.7.3).
All other components and costs, including maintenance activities, were
assumed to be the same for each RWH system. These are summarised below
in tables 6.2 and 6.3. Note that all prices are for the 2007 period.
Table 6.2 Universal component values used in domestic simulations
Component Value(s) CommentsRainfall Daily rainfall data for Emley Moor
weather stationAdapted for UKCIP (2002b)medium-high emissions climatechange scenario
Catchmentsurface
Runoff coefficient: 0.90
Initial losses: 0.25mm
See table 3.2. High value usedbecause initial losses also takeninto accountSee table 3.3 and also Fewkes(1999a)
First flushdevice
No first flush device Use of first flush devices is limitedin the UK
Coarse filter Coarse filter coefficient: 0.90 Commonly applied value. Seetable 3.5
Storage tank Initial degree of filling: 100%
Top-up location: tank
During commissioning and testingthe tank is filled to capacityAssumes direct RWH systemsused, see chapter 2, section 2.4.2
Pump Power rating: 0.8kWPumping capacity: 80 l/min
See table 3.6
UV unit No UV unit Water quality assumed to begood enough for non-potable
domestic uses providing thatcoarse filtration is provided
Continued on next page
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Table 6.2 continued
Component Value(s) CommentsWater demand WC usage: 6/3 litre dual flush, 1
full flush to 2 partial flushes, 4
flushes per person per day Mon-Fri, 6 flushes per person per daySat-Sun
Washing machine usage: 0.2uses per person per day, 50 litresper use (cycle)
Garden irrigation: all gardensassumed to be 60m2 in area.Three irrigation sessions perweek assumed during
spring/summer seasons
See chapter 3, section 3.17.1 andtables 3.11 and 3.12. WC usage
per person per year = 6.7m3
See chapter 3, section 3.17.2 andtables 3.13 and 3.14. WM usageper person per year = 3.7m3
See chapter 3, section 3.17.3.Typical annual garden irrigationrequirement 20m3
Water andseweragecharges
Supply charges: 1.09/m3 for2007-08 period, increasing yearly
Supply standing charges: 25.84for 2007-08 period, increasingyearly
Sewerage charges: 1.17/m3 for2007-08 period, increasing yearly
Sewerage standing charges,used historic mean of 37.54 forall years
Annual increase estimated usingregression analysis of historicYorkshire Water price data, seechapter 4, section 4.7.5 andappendix two
See chapter 4, section 4.7.5 andappendix two
Electricitycharges
Unit charge: 8.7p/kWhr for 2007,increasing yearly
Annual increase estimated usingregression analysis of averagehistoric data, see chapter 4,section 4.7.5 and appendix two
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Table 6.3 Universal maintenance activities and associated costs used
in domestic simulations
Maintenance
Item
Value (inc. VAT) Comments
Scheduledmaintenance
Annual cleaning of roof andgutters recommended butconsidered unlikely thatmost home owners willactually do this, hence nocleaning was assumed
Cleaning of coarse filterassumed carried out bysystem owner at zero cost.
See chapter 4, section 4.7.4 and table4.9
Componentreplacement
Pump: replace every tenyears, 350 + 75installation fee = 425
Storage tank: assumed willremain functional forselected analysis timehorizons
Coarse filter: replace every15 years, 300 + 50installation fee = 350
Electronic controls, replaceevery 15 years, 140 + 50installation fee = 190
Plastic pipes (internal),replace every 35 years, totalcost (parts + labour) = 250
Replace mains top-upsolenoid valve every 7.5years, 60 + 50 installation
fee = 110
Replace mains top-up levelswitch in storage tank every12.5 years, 20 + 50installation fee = 70
For all items in this section: seechapter 4, section 4.7.4 and appendixtwo. Note that complete componentreplacement was assumed, not repair,as cannot be sure repair will bepossible (e.g. specific componentsmay not be manufactured in the future)
The approach taken allowed for the assessment of a number of system
configurations under various conditions. Four discount rates, four discount
periods, three combinations of water uses and five occupancy rates gave a total
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of 240 simulation input conditions. For each simulation condition sixteen tank
sizes were evaluated, meaning that in total 3,840 different scenarios were
assessed.
In all cases the YAS tank operating algorithm was used in preference to the
YBS alternative for modelling hydrological performance (see chapter three).
6.2 Sensitivity analysis of the financial model
The first step was to perform a sensitivity analysis of the financial model in order
to determine the level of variation in predicted RWH system performance to
changes in key hydrological and financial parameters. Sensitivity to changes in
eight parameters was investigated. These were the daily rainfall depth, capital
cost, maintenance costs, mains water supply and sewerage charges, roof area,
discount rate, discount period and the storage operating parameter .
Some parameters were not tested explicitly. These were the initial losses, runoff
coefficient and coarse filter coefficient. This was deemed unnecessary since
sensitivity to changes in rainfall depth was tested and the aforementioned
parameters depend to a large degree on the rainfall depth. Hence the sensitivity
of these were tested by proxy.
The effect of altering the water demand was considered important but this was
not included in the sensitivity analysis. Domestic water demand is a function of
household occupancy rate (Butler, 1991; Butler & Memon, 2006) and the
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implications of altering occupancy rates are considered in more detail later in
section 6.7.
Percentage changes to RWH system savings (the difference between mains-
only WLCs and RWH WLCs) were selected as the method for assessing
sensitivity as this was deemed to be the key parameter in assessing the
financial viability of a potential system. Reporting changes in RWH WLCs would
not have been logical since by themselves these results are do not provide
information on RWH system cost effectiveness. They require comparison with
the WLC of the equivalent mains-only system before any significance can be
attached to them.
It could not be assumed that the sensitivity of RWH system savings to changes
in key parameters would be the same for all discount rates and discount
periods. Therefore analyses were conducted for each of the four stakeholder
perspectives shown in table 6.1, with a total of 16 tank sizes assessed in each
case (1.2-15.0m3). In all instances three water uses were assumed: WC
flushing, garden irrigation and washing machine. Changes to parameter values
in the range of 100% were investigated where possible. Exceptions were
changes to the storage operating parameter , which was varied between 0-1 in
0.1 increments, and changes to the discount period which for obvious reasons
could not be reduced by as much as 100%. The savings associated with each
tank size for each of the four stakeholder perspectives are given in appendix
three. These are the base-case results, i.e. the RWH system savings in each
case before any of the selected parameter values were altered, and can be
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used to place the reported percentage changes in RWH system savings into
context.
All the results from the sensitivity analysis investigations are shown graphically
in appendix three. Visual examination of these charts indicated that for each
analysis the results associated with each tank size were, in general, reasonably
closely grouped. This was particularly the case for changes to most of the
parameters in the range of 50% and for the homeowner, water utility and
private sector perspectives.
Table 6.4 shows the average differences between the results for the sixteen
tank sizes. It can be seen that in most cases the average variation within each
stakeholder groupwas no more than a few percentage points. This suggested
that average curves could be used to represent the variations in RWH system
savings and these are shown in figures 6.1-6.8. In each case the average
results from all four stakeholder perspectives were plotted on the same chart to
make direct comparison easier. Note that for the graph titled Average
sensitivity results for change in mains water charges the percentage changes
refer to both the supply and sewerage unit costs of water (/m3) but not the
associated supply and sewerage standing charges. These were not altered.
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Table 6.4 Average difference in sensitivity analysis results between
different tank sizes (constant rand n1)
Key parameters and corresponding average % change in RWH system savings
Stakeholdergroup
Dailyrainfalldepth
Capitalcost
Maint-enance
cost
Mainswater
chargesRoofarea
Discountrate
Discountperiod
value
Homeowner 1.5 1.0 1.4 2.1 1.4 1.1 1.2 0.4Water utility 2.3 2.4 4.2 3.0 2.2 4.0 0.9 0.6
Private sector 1.3 2.0 0.0 2.0 1.3 0.2 1.1 0.3LA/Gov 4.6 6.2 11.3 5.2 4.4 3.9 5.9 1.0
1Where r= discount rate (%) and n= discount period (years)
Figure 6.1 Average sensitivity results for changes in daily rainfall depth
-60%
-50%
-40%
-30%
-20%
-10%
0%
10%
20%
-100% -50% 0% 50% 100%
% change in daily rainfall depth
Average%c
ha
ngeinsavings()
Homeowner
Waterutility
Privatecompany
LA/Gov.
Stakeholder
H
W
P
L
H
W
P
L
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Figure 6.2 Average sensitivity results for changes in capital costs
-150%
-100%
-50%
0%
50%
100%
150%
-100% -50% 0% 50% 100%
% change in capital costs
Average%c
hangeinsavings()
Home
owner
Waterutility
Privatecompany
LA/Gov.
Stakeholder
H
W
P
L
H
W
P
L
Figure 6.3 Average sensitivity results for changes in maintenance costs
-60%
-40%
-20%
0%
20%
40%
60%
-100% -50% 0% 50% 100%
% change in maintenance costs
Average%
changeinsavings()
Homeowner
Waterutility
Privatecompany
LA/Gov.
Stakeholder
H
W
P
LH
W
P
L
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Figure 6.4 Average sensitivity results for change in mains water charges
-60%
-40%
-20%
0%
20%
40%
60%
-100% -50% 0% 50% 100%
% change in mains water charges
A
verage%changeinsavings()
Home
owner
Waterutility
Privatecompany
LA/Gov.
Stakeholder
H
W
P
L
H
W
P
L
Figure 6.5 Average sensitivity results for changes in roof area
-60%
-50%
-40%
-30%
-20%
-10%
0%
10%
20%
-100% -50% 0% 50% 100%
% change in roof area
Average%
changeinsavings()
Homeowner
Waterutility
Privatecompany
LA/Gov.
Stakeholder
H
W
P
L
H
W
P
L
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Figure 6.6 Average sensitivity results for changes in discount rate
-60%
-50%
-40%
-30%
-20%
-10%
0%
10%
20%
-100% -50% 0% 50% 100%
% change in fixed discount rate
A
verage%changeinsavings()
Home
owner
Waterutility
Privatecompany
LA/Gov.
Stakeholder
H
W
P
L
HW
P
L
Figure 6.7 Average sensitivity results for changes in discount period
-8%
-4%
0%
4%
8%
12%
16%
-50% 0% 50% 100%
% change in fixed discount period
Average%
changeinsavings()
Homeowner
Waterutility
Privatecompany
LA/Gov.
Stakeholder
H
W
P
L
H
W
P
L
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Figure 6.8 Average sensitivity results for changes in storage operating
parameter (YAS/YBS algorithm)
0.0%
0.1%
0.2%
0.3%
0.4%
0.5%
0.0 0.2 0.4 0.6 0.8 1.0
value
Avera
ge%c
hangeinsavings()
Homeowner
Waterutility
Privatecompany
LA/Gov.
Stakeholder
H
W
P
L
H
W
P
L = 0, YAS = 1, YBS
Identification of general trends in sensitivity analysis results
Linear relationships were apparent for variations in mains supply and sewerage
changes as well as capital and maintenance costs. For mains supply and
sewerage charges the resulting graph displayed a positive gradient, indicating
that as charges increased the cost effectiveness of the RWH system also
increased, although relatively slowly in most cases. Changes in daily rainfall
depth and roof area produced a non-linear relationship which represented an
exponential decay type relationship (increasing form).
Changes in the discount rate also showed a non-linear exponential decay
pattern for the homeowner, water utility and LA/Government perspectives.
Conversely, for the private sector perspective the relationship was linear and
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with a negative gradient. Results for the discount period gave a less than
straightforward relationship with regards to corresponding changes in system
savings, with various peaks and troughs evident on the graph. These can be
explained by the phasing in and out of additional maintenance requirements as
the analysis time horizon was adjusted.
Concerning changes to the storage operating parameter , which determined
the extent tank that behaviour was represented by the YAS and YBS
algorithms, the shape of the sensitivity analysis results was the same in all
cases. From figure 6.8 it can be seen that there was an exponential decay type
relationship between RWH system savings and the value of , with the rate of
change decreasing as approached 1.
Examination of sensitivity analysis results
Table 6.5 shows the gradients associated with each of the key parameters from
the different stakeholder perspectives, except for which is discussed in the
following subsection. Note that for the non-linear curves these results represent
the average gradients. The steeper the gradient the more sensitive RWH
systems savings were to change in the associated parameter. The maximum
gradients (most sensitive) have been highlighted in red.
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Table 6.5 Sensitivity analysis results: associated gradients
Stakeholder perspective and corresponding gradients, mParameter Homeowner Water utility Private sector LA/Gov
Rainfall depth 0.06 0.12 0.05 0.28
Capital cost -1.08 -1.07 -1.10 -0.91Maint. costs -0.05 -0.15 0.00 -0.49Mains charges1 0.12 0.22 0.10 0.50
Roof area 0.06 0.11 0.05 0.27Discount rate 0.00 0.02 -0.01 0.28
Discount period -0.02 -0.02 0.01 0.011Mains supply and sewerage unit charges, not standing charges
From figures 6.1-6.8 and table 6.5 it can be seen that the homeowner (r=15%,
n=10 years) and private company (r=5%, n=5 years) perspectives were, with
the exception of the capital costs, the least sensitive to changes. For the
homeowner scenarios, excluding capital costs, the greatest percentage change
in RWH system savings was associated with variations in mains water supply
and sewerage unit charges (i.e. changes in /m3 costs). However, the
associated changes were not particularly large. Even a change in supply and
sewerage unit charges of 100% only resulted in a corresponding change in
RWH system savings of 12.4% (m= -0.124).
The private company results were similar to those of the homeowner. Again,
with the exception of capital costs, the RWH system savings were most
sensitive to changes in mains supply and sewerage charges. Changes tended
to be small, for example a 100% variation in supply/sewerage charges resulted
in a corresponding change in system savings of 10% (m= -0.10).
The water utility scenario (r=10%, n=10 years) proved somewhat more sensitive
than did the homeowner and private company situations. Capital costs aside,
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the greatest sensitivity was associated with changes to mains supply and
sewerage charges. A variation in charges of 100% resulted in a change in
RWH system savings of 21.7% (m= -0.217).
Results for the LA/Government analysis were noticeably different than for the
other three stakeholder scenarios. Savings sensitivity was significantly greater
to changes in the selected parameters than was the case with the homeowner,
water utility and private sector variants. Other than capital costs, the greatest
sensitivity was once again associated with changes in mains supply and
sewerage charges. A variation of 100% resulted in a change in RWH savings
of 50% (m= 0.50). Changes in maintenance costs were also noted to have an
appreciable impact, only marginally less than that of the supply and sewerage
charges (m= -0.490). Gradients for rainfall depth, roof area and discount rates
were 0.28, 0.27 and 0.28 respectively, showing that RWH savings were
moderately sensitive to changes in these parameters.
The propensity towards greater sensitivity displayed by the LA/Government
perspective can be explained by the combination of low discount rate (r=3.5%)
and long discount period (n=50 years). The low discount rate means that costs
incurred in the future have a greater present value than for the other
stakeholder scenarios, and thus a relatively greater contribution to the WLCs.
Making changes to the model that impact on recurring costs (e.g. increasing
maintenance and mains supply/sewerage charges) therefore has a greater
impact on the WLCs, and thus RWH system savings, than for scenarios with
shorter discount periods.
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Sensitivity to changes in capital costs were the most significant. It can be seen
from figure 6.2 that the slope of the graph is negative and approximately equal
to -1. This shows that for these three stakeholder groups the savings were
directly correlated with the capital costs on an almost 1:1 basis. If the capital
costs increase/decrease by a given percentage then there is an almost identical
corresponding decrease/increase in the RWH system savings. The relationship
was also strong for the LA/Government scenarios but the level of correlation
was closer to 0.9, i.e. increasing the capital costs by 100% resulted in a
decrease in systems of about 90%, and visa versa.
It can be concluded that for investigations which consider short to medium
discount periods, the predicted RWH system savings depend overwhelmingly
on the capital costs. For longer discount periods other factors become more
influential, particularly mains supply and sewerage charges as well as
maintenance costs. However, the capital costs still remain an important cost
element in the determination of the relative financial performance of the RWH
system. It is therefore advised that accurate capital cost data be obtained
whenever possible.
Obtaining accurate cost information for component purchase and delivery is
relatively straight forward since any number of suppliers exist that can provide
quotes. Installation expenses, the other aspect of capital costs, are harder to
predict with a high degree of accuracy. A value of 1,000 for each new-build
domestic system was used for the domestic simulations, for the reasons given
in chapter four. It is acknowledged that a more detailed data set would have
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been preferable. This does not exist at the current time due to the limited uptake
of RWH systems in the UK, plus a lack of available data pertaining to most of
the existing systems. If the use of RWH becomes more widespread then it is
anticipated this situation will change and more accurate, site-specific predictions
of installation cost will become possible.
Justification for using the YAS algorithm
With regards to the decision to base the thesis model on the YAS tank
operating algorithm (=0), from a hydrological standpoint this was justified
previously in chapter three. From a financial viewpoint it can be seen from figure
6.8 that, for domestic systems, the choice of either the YAS or YBS algorithm
would have been appropriate. There was little difference in the predicted results
when using either approach. For the averaged results, the percentage
difference in RWH system savings between the YAS and YBS algorithms for
the homeowner, water utility, private sector company and LA/Government
perspectives were 0.1%, 0.2%, 0.1% and 0.4% respectively. These results were
small and essentially inconsequential. Examination of the original data before
averaging occurred showed that the greatest difference occurred in the
LA/Government scenarios. However, even in this instance 14 out of the 16 tank
sizes showed differences of less than 0.5% in RWH savings between the YAS
and YBS algorithms. For the two remaining tanks the differences were 1.3% for
the 1.5m3 tank and 1.7% for the 1.2m3 tank, both of which were still acceptably
small. It was also evident from the original data that for all the stakeholder
scenarios the differences between YAS/YBS algorithms decreased with
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increasing tank size. For capacities greater than or equal to 2.4m3 the variation
in savings was always less than 0.5%
6.3 Hydrological performance results
Figures 6.9, 6.10 and 6.11 show the predicted hydrological results for a range of
occupancies and combinations of water uses. Each simulation was run for 25
years as this was considered long enough to account for inter-year variations in
rainfall patterns. For each occupancy rate the tank sizes required to meet 50%,
90% and 100% of the selected non-potable uses have been marked on the
graphs. Note that the x-axis is logarithmic because large tank sizes were
required to meet 100% of the demand (in some cases very large capacities
were needed). Plotting the data on a linear scale would have resulted in a
significant loss of clarity with respect to the results for the smaller tank sizes.
The legend on the right of the graphs requires an explanation. Each line of text
corresponds to the data series that it is directly next to. The first number before
the brackets is the maximum percentage of demand that could be met for the
selectedwater uses. The figure in the brackets is the maximum percentage of
total household demand that could be met by the RWH system. This was
calculated based on the assumption that the average per capita internal use
was 120 litres/person/day. Note that external water use, when included in the
analysis, was not occupancy dependant. Finally, the text after the brackets
shows how many household occupants there were for each simulation. So for
example in figure 6.9 the entry 100(15)% occ. 5 shows that 100% of WC
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flushing demand could be met and that this represented 15% of the total water
demand for a house with five people.
Figure 6.9 Predicted hydrological performance for WC flushing only1
0
5
10
15
20
25
30
35
0.01 0.10 1.00 10.00
Tank size (m3)
Harveste
dwater(m
3/yr)
Occupancy 5 Occupancy 4 Occupancy 3 Occupancy 2
Occupancy 1 50% demand 90% demand 100% demand
100(15)% occ. 5
100(15)% occ. 4
100(15)% occ. 3
100(15)% occ. 2
100(15)% occ. 1
1For this analysis it was assumed no garden irrigation with mains water occurred. If ithad then the predicted 15% of total household demand met would have been reduced
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Figure 6.10 Predicted hydrological performance for WC flushing and
garden irrigation
0
10
20
30
40
50
60
0.01 0.10 1.00 10.00 100.00 1000.00
Tank size (m3)
Harves
tedwa
ter
(m3/yr)
Occupancy 5 Occupancy 4 Occupancy 3 Occupancy 2
Occupancy 1 50% demand 90% demand 100% demand
100(22)% occ. 5
100(24)% occ. 4
100(27)% occ. 3
100(31)% occ. 2
100(42)% occ. 1
Figure 6.11 Predicted hydrological performance for WC flushing, garden
irrigation and washing machine
0
10
20
30
40
50
60
70
80
0.01 0.10 1.00 10.00 100.00 1000.00
Tank size (m3)
Harves
ted
wa
ter
(m3/yr)
Occupancy 5 Occupancy 4 Occupancy 3 Occupancy 2
Occupancy 1 50% demand 90% demand 100% demand
100(30)% occ. 5
100(31)% occ. 4
100(34)% occ. 3
100(38)% occ. 2
100(48)% occ. 1
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The hydrological results show that for each modelled scenario it was
theoretically possible to meet 100% of the non-potable demand. However, the
graphs demonstrate that in many cases the tank sizes required to achieve this
would need to be unfeasibly large. Increases in tank size initially resulted in the
rapid growth of system efficiency (volumetric reliability) but a point was reached
where further increases in storage capacity resulted in only marginal
improvements in performance. For instance, to meet 50% of WC flushing
demand in a five person household (figure 6.9) a tank size of only 0.26m3 would
be needed. To meet 90% of the demand would require a tank size of 2.15m 3
and to meet 100% of demand would necessitate a 10m3 tank, about 38 times
that required to meet 50%. Similar diminishing returns have been reported by
other researchers, e.g. Appan (1993); Chu et al(1997); Appan (1999); Dixon et
al (1999); Herrmann & Schimda (1999); Coombes & Kuczera (2003b); Liaw &
Tsai (2004); Phillips et al (2004); Villarreal & Dixon (2005) and Ghisi et al
(2007).
The graphs also demonstrate that small tank sizes are sufficient to meet a
reasonable proportion of the demand. For the WC flushing only scenarios, a
tank size of 0.260m3 was able to provide over 50% of the volume required for all
occupancy levels. For the WC flushing and garden irrigation scenarios a tank
size of 0.750m3 supplied at least 50% for all occupancies. For WC flushing,
garden irrigation and washing machine a tank size of 1.0m3 met 50% of the
demand for all occupancies except for five, which needed a capacity of 1.6m3.
Conversely, much larger tank sizes were required to bring the level of demand
met into the 90-100% range. In many cases the capacities required were orders
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of magnitude greater than those required to supply 50%. For meeting 90%, the
WC flushing scenario was the only one which predicted reasonable tank sizes,
requiring up to 2.15m3 for an occupancy of five. For the other water use
scenarios the required capacities were tens or hundreds of cubic metres. Given
that greater tank sizes have, on average, greater capital costs it is questionable
whether attempting to meet most or all of the non-potable demand would be
financially viable in these instances. A more rational approach would be to
utilise lower capacity tanks to provide smaller but still useful volumes of water.
The percentage of totalhousehold demand that could be met ranged between
15% for WC flushing only (which also assumed no garden irrigation with mains
water), 22-42% for WC flushing plus garden irrigation and 30-48% for WC
flushing, garden irrigation and washing machine. The percentage of total
household demand met showed correlation with the occupancy rate, with higher
percentages associated with lower occupancies. The exception was the WC
flushing only scenarios in which 100% of WC demand and 15% of total
household demand was supplied for all occupancies, given large enough tank
sizes.
Previously in chapter two it was stated that for a typical house there is the
potential to replace about 55% of mains supply with harvested rainwater. The
results presented here indicate that this may be true in only a minority of cases,
specifically those with low occupancies and high harvested water uses. In these
situations large tanks would be required in order to supply enough water to
meet >40% of the total demand, potentially increasing the capital costs
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significantly. It will be shown later in this chapter that tank sizes in excess of
about 1.5m3 are the least economic compared to simply relying on mains water.
If the use of tank sizes greater than this was to be avoided, this would then
revise downward the percentage of total household demand that could
realistically be met by harvested water for new-build houses. Under the
modelling assumption employed, it can be seen from figures 6.9-6.11 that:
For WC flushing only: 1.5m3 tank could supply between 85-100% of WC
flushing demand, or 13-15% of total household demand.
For WC flushing and garden irrigation: 1.5m3 tank could supply 58-64%
of non-potable demand, or 13-24% of total household demand.
For WC flushing, garden irrigation and washing machine: 1.5m3 tank
could supply 49-64% of non-potable demand, or 18-28% of total
household demand.
The above indicates that harvesting rainwater will not realistically result in a net
reduction in mains water usage approaching 55% and, in cases where this may
be theoretically possible, the requirement to install realistic (i.e. affordable) tank
sizes would mean that the actual water savings are likely to be significantly
lower.
6.4 Financial performance results
This section reports the main financial results from the 3,840 domestic
simulations and draws a number of conclusions regarding the key factors
influencing system WLCs as well as the most cost effective tank sizes. Figure
6.12 is a composite plot of all the results obtained from the financial modelling
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exercise and shows the general pattern of RWH system WLCs versus mains-
only WLCs.
Figure 6.12 WLC comparison between domestic RWH systems and
equivalent mains-only systems
0
1000
2000
3000
4000
5000
6000
0 2000 4000 6000 8000 10000 12000
RWH WLC ()
Mains-onlyWLC()
WLC RWH = WLC Mains
WLC RWH
WLC Mains
Figures 6.13 and 6.14 show more detailed results for tank sizes 1.2m 3 and
1.5m3. Results for the other fourteen tank sizes that were assessed are given in
appendix three. The format of the graphs requires clarification. On the y-axis the
WLC at NPV of each RWH system and equivalent mains-only system has been
plotted against the simulation number (x-axis). Also on the y-axis is the RWH
system savings at NPV. This is the amount of money that can be expected to
be saved due to the installation of a given rainwater system. The financial
performance of water reuse systems, particular the ability to save money
compared to reliance on mains-only water, has been found to be an important
factor in peoples willingness to adopt such technology (Marks et al, 2002; Hill et
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al, 2003; BMRB, 2006). Therefore the use of RWH system savings as a key
performance indicator is justified in this instance.
The results have been plotted in a hierarchical manner in order to facilitate
comparisons between different scenarios. The top level corresponds to different
combinations of non-potable water uses, where:
Uses = 1 represents WC flushing only.
Uses = 2 represents WC flushing and garden irrigation.
Uses = 3 represents WC flushing, garden irrigation & washing machine.
The next level corresponds to the different discount rates (r) that were utilised,
with each water use category containing results for discount rates of 3.5%, 5%,
10% and 15%. Within each discount rate there are four discount periods (n) of
5, 10, 25 and 50 years. Finally, within each discount period there are five
occupancy rates (occ) of 1-5 inclusive.
A summary of the WLC and savings results for each tank size are given in table
6.6. Examination of figures 6.13 and 6.14, as well as those for the other tank
sizes presented in appendix three, revealed a number of trends with regards to
the WLCs and RWH system savings. Table 6.7 summarises these trends with
respect to variations in water uses, discount rates, discount periods and
occupancy levels. It should be noted that in all cases the WLC of the RWH
system was greater than that of the equivalent mains-only system, hence for all
scenarios the RWH systems resulted in a net financial loss.
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Figure 6.13 WLC results for domestic 1.2m3 tank
-6,000
-4,000
-2,000
0
2,000
4,000
6,000
8,000
10,000
0 20 40 60 80 100 120 140 160 180 200 220 240
Simulation number
Va
luea
tNPV()
RWH WLC Mains WLC RWH savings CapCost
r = 3.5% r = 5% r = 10% r = 15% r = 3.5% r = 5% r = 10% r = 15% r = 3.5% r = 5% r = 10% r = 15%
Uses = 1 Uses = 2 Uses = 3n=5,10,25,50
occ=1,2,3,4,5
Capital cost = 2,660
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Figure 6.14 WLC results for domestic 1.5m3 tank
-6,000
-4,000
-2,000
0
2,000
4,000
6,000
8,000
10,000
0 20 40 60 80 100 120 140 160 180 200 220 240
Simulation number
Va
luea
tNPV()
RWH WLC Mains WLC RWH savings CapCost
r = 3.5% r = 5% r = 10% r = 15% r = 3.5% r = 5% r = 10% r = 15% r = 3.5% r = 5% r = 10% r = 15%
Uses = 1 Uses = 2 Uses = 3n=5,10,25,50
occ=1,2,3,4,5
Best savings performance from all
3,840 simulations, savings = -2,256
Capital cost = 2,667
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Table 6.6 Summary of WLC and savings results for domestic RWH system simulations
RWH WLC summary Mains-only WLC summary RWH system savings summary
Tanksize(m3)
AverageWLC()
Max.WLC()
Min.WLC()
Standarddeviation
()
AverageWLC()
Max.WLC()
Min.WLC()
Standarddeviation
()
Averagesavings
()
Max.savings
()
Min.savings
()
Standarddeviation
()
1.2 3,743 8,207 2,698 1,076 1,089 5,463 96 921 -2,654 -2,271 -4,493 3411.5 3,727 8,107 2,705 1,060 1,089 5,463 96 921 -2,638 -2,256 -4,511 3422.4 4,550 8,797 3,454 1,036 1,089 5,463 96 921 -3,461 -2,932 -5,406 3473.0 4,609 8,811 3,640 1,026 1,089 5,463 96 921 -3,520 -3,059 -5,501 351
3.5 4,814 8,998 3,697 1,022 1,089 5,463 96 921 -3,725 -3,176 -5,735 3534.0 4,707 8,877 3,756 1,017 1,089 5,463 96 921 -3,618 -3,120 -5,653 3554.7 5,089 9,256 3,865 1,013 1,089 5,463 96 921 -4,000 -3,344 -6,072 3595.0 4,298 8,460 3,355 1,010 1,089 5,463 96 921 -3,209 -2,686 -5,288 3646.0 4,922 9,103 3,990 1,006 1,089 5,463 96 921 -3,833 -3,304 -5,965 3646.5 5,363 9,558 4,083 1,007 1,089 5,463 96 921 -4,274 -3,562 -6,432 3677.0 4,515 8,715 3,592 1,003 1,089 5,463 96 921 -3,425 -2,887 -5,598 3749.0 4,836 9,100 3,931 1,000 1,089 5,463 96 921 -3,747 -3,181 -6,010 3799.4 5,752 10,034 4,527 1,002 1,089 5,463 96 921 -4,663 -4,006 -6,948 38011.0 5,062 9,388 4,164 1,002 1,089 5,463 96 921 -3,973 -3,376 -6,316 39513.0 5,816 10,220 4,929 1,007 1,089 5,463 96 921 -4,727 -4,111 -7,154 39815.0 6,580 11,054 5,695 1,014 1,089 5,463 96 921 -5,490 -4,857 -7,992 410
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Table 6.7 Summary of trends in WLCs and RWH system savings
For a given RWH system, effect ofincreasingparameter value on:
ParameterRWHWLC
MainsWLC
RWHsavings
Water uses Increase Increase IncreaseDiscount rate Decrease Decrease Varies
Discount period Increase Increase DecreaseOccupancy Varies Increase Increase
Increasing water uses: comments
Greater water use led to higher WLCs for both RWH and mains systems which
can be explained by the need for more mains top-up and increased pump
usage in the latter case, and a greater demand for mains water in the former.
RWH system savings increased with higher water usage but in general any
improvement was marginal, although it was more pronounced with low discount
rates and long discount periods.
Increasing discount rate: comments
Higher discount rates reduced the present value of future expenditures which
explains why the WLCs of both the RWH and mains-only systems decreased as
the discount rate increased. The effect on RWH system savings varied. At lower
discount periods (principally 5 years) increasing the discount rate led to a
marginal reduction in the RWH system savings. However at higher discount
periods (principally 25 and 50 years) increasing the discount rate led to
improved RWH system savings performance. This was due to the cost of
maintenance becoming a larger factor for systems in operation for about ten
years or longer. Increasing the discount rate for these systems reduced the
present value of maintenance, thus reducing RWH WLC and improving RWH
system savings. This is an interesting result because the use of lower discount
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rates is often advocated where consideration of wider social and sustainability
issues are required, e.g. see Larkin et al(2000) for a more detailed discussion.
However, in this case the use of lower discount rates can, for a scenario using
long discount periods, result in lower RWH system savings. As a result the
installation of a RWH system may appear less financially attractive than if
higher discount rates had been used.
Increasing discount period: comments
Longer discount periods led to an increase in the WLC of both the RWH
systems and equivalent mains-only systems. This was to be expected since
longer periods resulted in a requirement for increased maintenance and mains
top-up for the RWH systems, and increased mains water usage for the mains-
only systems. Longer discount periods were found to result in decreased RWH
system savings. This was likely due to maintenance requirements which
become more onerous the longer a system is operated, particularly with regards
to component replacement which begins to become increasingly necessary
after about ten years. Some authors have called for the use of long discount
periods on the grounds of intergenerational equity, principally with regards to
environmental sustainability (e.g. see Larkin et al, 2000). However, in this
instance the use of longer discount periods would result in greater financial
losses from the RWH system, making them less attractive as a sustainable
technology.
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Increasing occupancy: comments
With regards to the RWH systems, increasing the occupancy rate either had no
effect on the WLC or caused it to increase. The instances of zero increase can
be explained by reference to the percentage of water demand that was met. For
tank sizes that had the same water uses, discount rate and discount period but
varying occupancy rates, those that had the same WLCs were also those that
met 100% of the non-potable demand. The costs were the same because each
of these systems required no mains top up, pumped the same volume of water
and was subject to the same level of maintenance. For those tank sizes that
exhibited increasing WLCs with increasing occupancy, the percentage of
demand met was less than 100%, requiring mains top-up which incurred some
additional cost. For the mains-only system, increased occupancy resulted in
increased WLCs. This was to be expected since more people use collectively
greater volumes of water, resulting in higher bills.
With regards to RWH system savings, increasing occupancy resulted in
improved RWH system savings in all cases. The rate of improvement was more
pronounced over longer discount periods and lower discount rates.
Most cost-effective domestic RWH system
Figure 6.15 shows a composite plot of the RWH system savings results for all of
the simulations that were run. Graphs showing the results sorted according to
the selected water uses are given in appendix three. The performance of any
individual tank is easier to determine from these graphs.
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Figure 6.15 Predicted savings at NPV () for simulated domestic RWH systems
-8,000
-7,000
-6,000
-5,000
-4,000
-3,000
-2,000
-1,000
0 20 40 60 80 100 120 140 160 180 200 220 240
Simulation number
Sav
ings
@N
PV()
1.2cu.m
1.5cu.m
2.4cu.m
3.0cu.m
3.5cu.m4.0cu.m
4.7cu.m
5.0cu.m
6.0cu.m
6.5cu.m
7.0cu.m
9.0cu.m
9.4cu.m
11.0cu.m
13.0cu.m
15.0cu.m
Uses = 1r = 3.5% r = 5% r = 10% r = 15%
Uses = 2r = 3.5% r = 5% r = 10% r = 15%
Uses = 3r = 3.5% r = 5% r = 10% r = 15%
Tank Sizesn=5,10,25,50
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It can be seen from figure 6.15 and those in appendix three that tank size is
broadly correlated with system savings, with larger tank sizes showing reduced
savings (technically, greater losses). More precisely, RWH system savings are
correlated with capital costs. This is shown graphically in figures 6.16 and 6.17.
Figure 6.16 Relationship between tank size and capital cost
y = 163.76x + 2874.2
R2 = 0.7491
0
1,000
2,000
3,000
4,000
5,000
6,000
0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0
Tank size (m
3
)
Capitalcost()
Tank size (cu.m) Linear (Tank size (cu.m)) Tank Size (cu.m)
Figure 6.17 Relationship between capital cost and average, maximum
and minimum RWH system savings
y = -0.9485x - 91.367
R2
= 0.9989
-8,000
-7,000
-6,000
-5,000
-4,000
-3,000
-2,000
2,500 3,000 3,500 4,000 4,500 5,000 5,500 6,000
Capital cost ()
AverageRWHsavings(
)
Tanks assessed Linear (Tanks assessed)
Error bars show maximum and
minimum RWH system savings
Capital cost ()
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Figure 6.16 shows a reasonable correlation between tank size and capital cost.
This is not linear because different suppliers charge different amounts and in
some cases larger tanks were available at less cost, in terms of purchase and
delivery, than some smaller tanks. Figure 6.17 shows that capital costs are
strongly correlated to the average, maximum and minimum RWH system
savings and explains why, in figure 6.15, smaller tanks in general show better
financial performance than larger tanks. Analysis of the level of capital cost
recovery revealed that the average value was in the range of only 0.2-3.8% for
the sixteen tank sizes assessed, i.e. the ultimate financial losses were
approximately equal to the capital cost expenditure.
From figure 6.15 it can be seen that a tank size of 1.5m3 offered the best
financial performance in the majority of cases (in that it showed the smallest
financial loss). Out of 240 simulations it was ranked first a total of 193 times and
was placed second for the remaining simulation runs. A tank size of 1.2m3
proved to be the next best choice and this was ranked first a total of 47 times
and second on all other occasions. (Note that on the graph the data points for
the 1.2m3 tank are somewhat obscured by those of the 1.5m3 tank because the
results were generally very similar). No other tank sizes ranked in the top two
positions. The similar financial performances of the 1.5m3 and 1.2m3 tanks was
not especially surprising given that the capital costs were almost the same
(2,667 and 2,660 respectively). The larger capacity of the 1.5m3 tank explains
why it outranked the smaller one in most cases as it was able to meet a greater
portion of the demand on more occasions. Further information on the
performance of these two tanks is given in tables 6.8 and 6.9.
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Table 6.8 Summary of results for 1.2m3 tank
Parameter and associated values
ValuesRWH system
WLC ()RWH systemsavings ()
% demandmet
Harvestedwater (m3/yr)*
Maximum 8,207 -2,271 100% 37Average 3,743 -2,654 70% 23
Minimum 2,698 -4,493 45% 7
Standard dev. 1,076 341 18% 8*Harvested water supplied per year, averaged over analysis time period
Table 6.9 Summary of results for 1.5m3 tank
Parameter and associated values
ValuesRWH system
WLC ()RWH systemsavings ()
% demandmet
Harvestedwater (m3/yr)*
Maximum 8,107 -2,256 100% 39
Average 3,727 -2,638 73% 24
Minimum 2,705 -4,511 47% 7Standard dev. 1,060 342 18% 8
* Harvested water supplied per year, averaged over analysis time period
6.4.1 Importance of maintenance costs in determining the direction of
RWH system savings
All of the simulated RWH systems led to a financial loss compared to the
equivalent mains-only systems once all major costs were taken into account.
However, it is not yet clear whether the rainwater systems lost or gained money
once installation had occurred, i.e. did they begin to payback the initial capital
cost investment or did they continue to lose money during the operational
phase? Analysis of the results showed that out of 3,840 simulated systems,
2,933 (76%) recouped at least some of the initial capital investment. The
remaining 907 systems (24%) continued to lose money during the operation
phase. Of those that did recoup some of the capital investment the average
reduction was 268 (standard deviation of 142). This was not especially large
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considering that the lowest capital cost, associated with the 1.2m3 tank, was
2,660.
A number of trends were evident amongst the systems that did not recover any
of the capital expenditure. These tended to have lower occupancy rates, water
uses and discount rates but higher discount periods. Figure 6.18 shows the
various values of these parameters and the associated percentage of systems
that continued to accrue losses (note that the parameter categories are
independent and indicate general trends only).
Figure 6.18 Key characteristics of systems which exhibited accruing
financial losses
0%
25%
50%
75%
100%
1 2 3 4
%o
fto
talnum
bero
fRWHsys
tems
with
accru
ing
losses
Occ. Uses r (%) n (yrs)
1
2
3
45
1
2
3
3.5
5
10
15
50
2510
5
Parameter
Closer examination of the model results showed that for most simulation years
all of the modelled RWH systems, even those that ultimately lost in excess of
the capital costs, did manage to repay some of the initial expenditure. This
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included the cost of covering intra-yearly expenditures such as mains top-up,
supply/sewerage standing charges and pump operating expenses. However, it
was apparent that some recurring inter-yearly cost was diminishing the
magnitude of the savings. This was due to the maintenance costs, which in
these instances (accruing losses) proved to be ultimately of greater magnitude
than the reductions in water bills. This is shown graphically in figures 6.19 and
6.20 for a tank size of 1.5m3 (capital cost = 2,667), household occupancy of
two and three water uses (WC flushing, garden irrigation and washing
machine). This particular RWH system was selected because the results
straddled the border between some improvement in savings and further losses,
depending on the discount rate. Hence this particularly example was useful for
investigating the factors which could drive a system in either direction.
Figure 6.19 Increasing/decreasing system savings over 25 years owing to
maintenance requirements
-3,000
-2,900
-2,800
-2,700
-2,600
-2,500
-2,400
-2,300
-2,200
-2,100
-2,000
1 6 11 16 21
Year
RWHsys
temsav
ings
()
r = 15%
r = 10%
r = 5%
r = 3.5%
CapCost
15%
10%
5%
3.5%
Solenoid valve
Pump
Level switch
Solenoid valve, control
unit, coarse filter Pump
Capital
expenditure
= 2,667
25
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Figure 6.20 Increasing/decreasing system savings over 100 years owing
to maintenance requirements
-3,200
-3,000
-2,800
-2,600
-2,400
-2,200
-2,000
0 20 40 60 80 100
Year
RW
Hsys
temsav
ings
()
r = 15%
r = 10%
r = 5%
r = 3.5%
CapCost
15%10%
5%
3.5%
Capital
expenditure
= 2,667
Figure 6.19 shows that repayment of the capital costs began to occur once the
RWH system became operational. Within the first ten years cumulative returns
of between 300-400 were evident, depending on the discount rate. However,
beyond this point maintenance became increasingly necessary and this began
to erode the value of any savings that had accumulated. A cycle of
increasing/decreasing returns became evident, the amplitude of which
attenuated over time to a degree dependant on the selected discount rate. For
higher rates (10% and 15%) a constant savings value was reached (gradient
tended towards zero) and this could be considered the ultimate level of financial
loss/gain. The same tendency towards a zero gradient was observed for the
lower discount rates (3.5% and 5% in figure 6.20).
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For the lower rates the erosive power of maintenance costs caused the savings
to dip below the original capital cost expenditure (-2,667 on the graph) after 15
years. They then briefly spiked above this level on two occasions before
permanently dropping below it after about 30 years. Final system savings were
in the region of -2,997 and -2,822 for discount rates of 3.5% and 5%
respectively. For the higher discount rates, the stronger attenuating effects
meant that the present value of future maintenance costs were never high
enough to totally diminish the savings that had accrued in the first decade of
operation. However, this also meant that any future savings were also strongly
attenuated and so the present value of future savings quickly reached a
relatively constant level after about 30 years. Although some savings had
accrued during the operational phase, these were only a small fraction of the
capital cost. For discount rates of 10% and 15% only 337 and 330 of the
initial 2,667 investment was repaid after 100 years.
These observations led to the conclusion that even systems which perform well
financially during the operational phase may not ultimately result in an NPV
greater than zero due to the profit eroding effects of discounting. Some authors
have calculated long payback periods. For example Brewer et al(2001) discuss
two RWH systems with estimated payback times of 55 and 267 years. Given
the attenuating effect of discounting future cash flows even these extended
timeframes seem unrealistic, especially when using higher discount rates.
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In the literature review, particularly chapter four, it was shown that existing
research to date has not included the full range of maintenance requirements
with regards to major component replacement, and in some instances no
maintenance was assumed to occur at all. In general only pump replacement
was explicitly considered. Given the noted importance of maintenance costs in
determining whether a system pays back some of the capital expenditure or
continues to lose money, a decision was taken to conduct an investigation into
the implications of assuming that pump replacement was the only maintenance
activity required throughout the operational life of the system.
Figure 6.21 shows the results of simulating the same system described
previously (1.5m3 tank, occupancy of two and three water uses) but with a
maintenance schedule consisting solely of pump replacement every 10 years.
The assumed cost was 350, not 425 since other researchers have tended to
ignore the installation cost, previously assumed here to be 75.
For higher discount rates the repayment of capital costs occurred at a relatively
rapid decreasing rate. After approximately 40 years the RWH system savings
had reached an essentially constant value of -1,961 and -2,141 at discount
rates of 10% and 15% respectively. For rates of 3.5% and 5% savings
continued to accrue beyond 100 years which was the maximum length of time
that the thesis model was capable of simulating. Therefore, logarithmic trend
lines were fitted to the data series (r2 > 0.93 in both instances) and extrapolated
forward.
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Figure 6.21 Savings for RWH system with limited maintenance
requirements (pump replacement only)
-2,700
-2,200
-1,700
-1,200
-700
-200
300
800
1,300
1,800
0 1000 2000 3000 4000
Year
RW
Hsys
temsav
ings
()
r = 15%
r = 10%
r = 5%
r = 3.5%
CapCost
Log. (r = 3.5%)
Log. (r = 5%)
Capital
expenditure
= 2,667
15%10%
5%
3.5%Payback = 302 years
Payback = 3,027years
Payback not possible
Payback of the initial investment was found to be theoretically possible but
required very long time periods to achieve. For a discount rate of 3.5% the
predicted payback period was 302 years. This was well beyond the predicted
useful life for rainwater storage tanks, which has been estimated at up to 65
years for the underground GRP varieties (see appendix two). Realistically
speaking timeframes of this magnitude are probably beyond the life of most
modern buildings and so are essentially meaningless as guides to payback
periods for RWH systems. The results for the 5% discount were even less
plausible, with an estimated payback period of over 3,000 years. Again,
timeframes on this scale are meaningless in real terms within the context of this
investigation.
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Although the above payback periods were improbably long, the analysis was
revealing in that any payback was predicted at all. This was in stark contrast to
the thesis model which, analysing the same RWH system using the same range
of discount rates and periods, predicted that payback could not be achieved in
any timeframe. This highlights the importance of the approach taken in the
thesis of including a more realistic range of maintenance requirements. This can
make the difference between predicting on-going savings and recouping at least
some of the initial capital cost, and predicting an on-going loss which ultimately
leads to losses greater than the initial capital cost. It can also mean the
difference between predicting no payback achievable in any timeframe, and
predicting payback but over a long time period.
These findings may have implications regarding the provision of capital cost
subsidies/grants for RWH systems. Although these have not to date been
widely implemented in the UK this may change in the future. For example,
domestic RWH may become more common due to the implementation of the
Code for Sustainable Homes (DCLG, 2006c). The results presented here
indicate that there may be some circumstances where, even if a homeowner
was able to offset 100% of the capital costs, they may still ultimately be worse
off financially due to the maintenance requirements (assuming that they were
responsible for paying these).
Referring back to figure 6.18 it can be seen that the systems that lost money
during the operational phase were generally associated with low occupancy
rates, water uses and discount rates, and long discount periods. Conversely,
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systems that recouped at least some of the capital expenditure were associated
with higher occupancy rates, water uses and discount rates, and shorter
discount periods. These latter two criteria may not be an issue for most
homeowners. Voinov & Farley (2006) state that individuals tend to use high
discount rates and short discount periods, even if only subconsciously.
However, occupancy rates and water uses are physical quantities that are likely
to vary from building to building. Therefore, if the installation of domestic RWH
systems were to become more widespread in new-build developments, or
capital cost subsidies/grants were to become available, it is recommended that
preference be given to those buildings that have high occupancy rates and that
use harvested water for the widest range of applications. If installed in low
occupancy, low water use buildings even a free rainwater system could
ultimately cost the homeowner money. This may prompt them to discontinue
use of the system and would be unlikely to imp rove the publics perception of
such technology.
6.5 Financial results presented as average incremental costs (AICs)
Presenting results as WLCs can make it difficult to compare costs and benefits
between RWH systems that have dissimilar characteristics, such as different
water uses or occupancy rates. An alternative way to present the financial
results is as average incremental costs (AICs). This method allows the cost per
unit of benefit derived to be calculated, which in this case would be the cost per
cubic metre of water supplied from a RWH system compared to that supplied
from the equivalent mains-only system. This normalises the results and data
from different systems with different characteristics can be directly compared.
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This approach has been used by a number of other researchers in the field, e.g.
Brewer et al, 2001; Coombes et al, 2003b; Shaaban & Appan, 2005; MJA,
2007.
Using the same assessment criteria as for the WLC analysis, a further 3,840
simulations were run and the AICs from each recorded. Figure 6.22 shows a
plot of the results. Details of any specific system are not discernible from this
graph. However, it does demonstrate that the unit cost of water supplied by the
RWH systems was in all instances greater than that from the mains-only
systems, in some cases by an order of magnitude. Figure 6.23 shows a close
up of the origin, with the line of equivalence marked on the graph (that is, the
line that a data point would lie on if the RWH AIC was equal to the equivalent
mains-only AIC). This scale demonstrates the best results in terms of how close
the RWH AICs were to matching those of the mains-only system. However, in
each case it can be seen that water supplied from the RWH systems was more
expensive on a per unit basis than that supplied from the mains. The best single
result and corresponding simulation conditions is marked on the graph. Even in
this instance the AIC ratio (RWH AIC divided by mains-only AIC) was 1.48. For
a RWH system to be cost effective on a per-unit basis the AIC ratio would have
to be less than 1.
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Figure 6.22 AIC comparison between domestic RWH systems and
equivalent mains-only systems
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
0.00 20.00 40.00 60.00 80.00 100.00 120.00 140.00 160.00 180.00
AIC (/m3) water supplied by RWH system
AIC(/m
3)mains-onlywater
Figure 6.23 Close-up of figure 6.22 showing line of equivalence for low
AICs
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00
AIC (/m3) water supplied by RWH system
AIC(/m
3)ma
ins-on
lywa
ter
1.2cu.m
1.5cu.m
2.4cu.m
3.0cu.m
3.5cu.m
4.0cu.m
4.7cu.m
5.0cu.m
6.0cu.m
6.5cu.m
7.0cu.m9.0cu.m
9.4cu.m
11.0cu.m
13.0cu.m
15.0cu.m
Tank Sizes
AIC RWH = WLC AICAIC RWH
WLC AICLowest AIC ratio = 1.48
1.5m tank, occ = 5, water
uses = 3, r = 3.5%, n = 50yrs
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The correlation between capital costs and RWH system AICs as well as AIC
ratios was investigated. From figures 6.24 and 6.25 it can be seen that both the
RWH system AICs and AIC ratios were strongly correlated with capital costs,
with lower costs resulting in correspondingly lower AICs. It was shown
previously that capital costs are broadly correlated with tank size, thus smaller
tank sizes have generally lower AICs and AIC ratios than do the larger variants.
Figure 6.24 Relationship between capital cost and average, maximum
and minimum RWH system AICs
y = 0.0035x + 1.7323
R2
= 0.9998
0.00
30.00
60.00
90.00
120.00
150.00
180.00
2,500 3,000 3,500 4,000 4,500 5,000 5,500 6,000
Capital cost ()
AverageRWHAICs(/m3)
Tanks assessed Linear (Tanks assessed)
Error bars show maximum and
minimum RWH AICs
Capital cost ()
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Figure 6.25 Relationship between capital cost and average, maximum
and minimum AIC ratios
y = 0.0017x + 1.0089
R2 = 0.9998
0.00
10.00
20.00
30.00
40.00
50.00
60.00
2,500 3,000 3,500 4,000 4,500 5,000 5,500 6,000
Capital cost ()
AverageAICratios
Tanks assessed Linear (Tanks assessed)
Error bars show maximum and
minimum AIC ratios
Capital cost ()
Figures 6.26 and 6.27 show detailed results for tank sizes 1.2m3 and 1.5m3.
Results for the other fourteen tank sizes that were assessed are given in
appendix three. With regards to the graphs, the notation located at the top is the
same as for the WLC graphs shown previously. On the left-hand (logarithmic) y-
axis is the AICs of the RWH and equivalent mains-only systems which have
been plotted against the simulation number (x-axis). On the right-hand (linear)
y-axis has been plotted the AIC ratio. A summary of the main AIC results for
each tank size are given in table 6.10.
A number of trends were apparent in the results. These are summarised in table
6.11 with respect to variations in water uses, discount rates, discount periods
and occupancy levels. It should be noted that in all cases the AIC of the RWH
systems was greater than that of the equivalent mains-only systems. Therefore,
in all the scenarios assessed the cost of water on a per unit basis was more
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expensive when supplied from the RWH systems than it was from relying solely
on mains water. AIC ratios ranged from between 1.48 (1.5m3 tank, occ=5, water
uses=3, r=3.5%, n=50yrs) to 59.04 (15.0m3 tank, occ=1, water uses=1, r=15%,
n=5yrs). On average the unit cost of harvested water was 7.58 times greater
than that supplied from the mains.
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Figure 6.26 AIC results for domestic 1.2m3 tank
0.10
1.00
10.00
100.00
0 20 40 60 80 100 120 140 160 180 200 220 240
Simulation number
AICs
(/m
3)
0
5
10
15
20
25
30
RWH AIC Mains AIC AIC Ratio (RWH/mains)
r = 3.5% r = 10% r = 15%n=5,10,25,50
Uses = 1
r = 5%
Uses = 2
occ=1
Uses = 3
AICra
tio
(RWH/ma
ins
r = 3.5% r = 10% r = 15%r = 5% r = 3.5% r = 10% r = 15%r = 5%
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Figure 6.27 Primary AIC results for domestic 1.5m3 tank
0.10
1.00
10.00
100.00
0 20 40 60 80 100 120 140 160 180 200 220 240Simulation number
AICs
(/m
3)
0
5
10
15
20
25
30
RWH AIC Mains AIC AIC Ratio (RWH/mains)
r = 3.5% r = 10% r = 15%n=5,10,25,50
Uses = 1
r = 5%
Uses = 2
occ=1
Uses = 3
AICra
tio
(RWH/ma
ins
)
r = 3.5% r = 10% r = 15%r = 5% r = 3.5% r = 10% r = 15%r = 5%
Lowest AIC ratio = 1.48
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Table 6.10 Summary of AIC results for domestic RWH systems
RWH AIC summary Mains-only AIC summary AIC ratio (RWH/mains) summary
Tanksize(m3)
AverageAIC()
Max.AIC()
Min.AIC()
Standarddeviation
()
AverageAIC()
Max.AIC()
Min.AIC()
Standarddeviation
()
AverageAICratio
Max.AICratio
Min.AICratio
Standarddeviation
1.2 11.07 81.12 1.05 12.69 1.79 3.51 0.40 0.73 5.50 27.97 1.50 4.141.5 11.06 81.33 1.04 12.73 1.79 3.51 0.40 0.73 5.49 28.04 1.48 4.152.4 14.08 107.17 1.26 16.77 1.79 3.51 0.40 0.73 6.94 36.98 1.61 5.513.0 14.32 109.36 1.27 17.11 1.79 3.51 0.40 0.73 7.05 37.74 1.61 5.63
3.5 15.08 115.83 1.33 18.13 1.79 3.51 0.40 0.73 7.41 39.98 1.65 5.974.0 14.71 112.83 1.30 17.66 1.79 3.51 0.40 0.73 7.24 38.94 1.62 5.824.7 16.10 124.65 1.40 19.51 1.79 3.51 0.40 0.73 7.90 43.03 1.69 6.445.0 13.28 100.81 1.18 15.79 1.79 3.51 0.40 0.73 6.54 34.78 1.55 5.196.0 15.53 120.00 1.36 18.78 1.79 3.51 0.40 0.73 7.63 41.42 1.67 6.206.5 17.11 133.46 1.48 20.89 1.79 3.51 0.40 0.73 8.39 46.07 1.75 6.917.0 14.09 107.92 1.24 16.90 1.79 3.51 0.40 0.73 6.93 37.24 1.60 5.579.0 15.26 118.08 1.33 18.49 1.79 3.51 0.40 0.73 7.50 40.75 1.67 6.119.4 18.54 145.78 1.59 22.82 1.79 3.51 0.40 0.73 9.08 50.33 1.84 7.5611.0 16.09 125.06 1.40 19.58 1.79 3.51 0.40 0.73 7.90 43.17 1.72 6.4813.0 18.80 148.00 1.60 23.17 1.79 3.51 0.40 0.73 9.20 51.10 1.87 7.6815.0 21.53 170.96 1.81 26.77 1.79 3.51 0.40 0.73 10.51 59.04 2.02 8.89
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Table 6.11 Summary of trends in AICs and AIC ratios
For a given RWH system, effect ofincreasingparameter value on:
ParameterRWHAIC
MainsAIC
AICratio
Water uses Decrease Decrease DecreaseDiscount rate Decrease Decrease Increase
Discount period Decrease Decrease DecreaseOccupancy Decrease Decrease Decrease
Increasing water uses: comments
For low water uses (WC only) RWH AICs were significantly higher than for the
other water use scenarios. Moving from uses = 1 to uses = 2 resulted in a
significant drop in all associated RWH AICs. Moving from uses = 2 to uses =
3 also resulted in a reduction but this was much less pronounced than in the
former case. Higher RWH AICs were associated with lower water uses primarily
because the costs of the system were divided between lower volumes of water.
Mains-only AICs showed much less variation between water use scenarios
although there was still a trend of decreasing AICs with increasing usage. This
occurred because as water demand increased the fraction of supply and
sewerage standing charges assigned each unit of water was reduced.
The AIC ratio (RWH/mains) decreased as water use increased, primarily driven
by a reduction in RWH AICs. Again reductions were more significant when
moving from uses = 1 to uses =2 than they were between uses = 2 and
uses = 3.