UK; Assessment of Rainwater Harvesting Systems for New-Build Domestic Dwellings - Bradford...

8/3/2019 UK; Assessment of Rainwater Harvesting Systems for New-Build Domestic Dwellings - Bradford University

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A Whole Life Costing Approach for Rainwater Harvesting SystemsRichard Roebuck PhD, Bradford University

Rainwater harvesting software from:www.SUDSolutions.com

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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)



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)



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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296

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.


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)



minimum RWH AICs

Capital cost ()


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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



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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299

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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300

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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301

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.

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