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Reliability analysis of rainwater tanks in Melbourne using daily water balance model
Resources, Conservation and Recycling 56 (2011) 80–86
Contents lists available at SciVerse ScienceDirect
Resources, Conservation and Recycling journal homepage: www.elsevier.com/locate/resconrec
Reliability analysis of rainwater tanks in Melbourne using daily water balance model Monzur Alam Imteaz a,∗ , Amimul Ahsan b , Jamal Naser a , Ataur Rahman c a
Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, Melbourne, VIC, Australia Department of Civil Engineering, Faculty of Engineering, University Putra Malaysia, Selangor, Malaysia c School of Engineering, University of Western Sydney, NSW, Australia b
a r t i c l e
i n f o
Article history: Received 22 February 2011 Received in revised form 8 September 2011 Accepted 9 September 2011 Keywords: Rainwater tank Daily water balance Climatic conditions Reliability and historical rainfall
a b s t r a c t With the aim of developing a comprehensive decision support tool for the performance analysis and design of rainwater tanks, a simple spreadsheet based daily water balance model was developed using daily rainfall data, contributing roof area, rainfall loss factor, available storage volume, tank overflow and rainwater demand. In order to assess reliability of domestic rainwater tanks in augmenting partial household water demand in Melbourne (Australia) area, the developed water balance model was used for three different climatic conditions (i.e. dry, average, and wet years). Historical daily rainfall data was collected from a rainfall station near Melbourne city central. From historical rainfall data three representative years (driest, average and wettest) were selected for the current analysis. Reliability is defined as percentage of days in a year when rainwater tank was able to supply the intended partial demand for a particular condition. For the three climatic conditions, several reliability charts are presented for domestic rainwater tanks in relations to tank volume, roof area, number of people in a house (i.e. water demand) and percentage of total water demand to be satisfied by harvested rainwater. In brief, for a two-people household scenario, ∼100% reliability can be achieved with a roof size of 150–300 m2 having a tank size of 5000–10,000 L. However, for a four-people household scenario, it is not possible to achieve a 100% reliability, even with a roof size of 300 m2 and a tank size of 10,000 L. © 2011 Elsevier B.V. All rights reserved.
1. Introduction With increasing population and changing climate regime, water supply systems in many cities of the world are under stress. To tackle this problem, water authorities are adopting several measures including demand management and identifying alternative water sources such as stormwater harvesting, greywater and wastewater reuse and desalination. Among all the alternative water sources, stormwater harvesting perhaps has received the most attention. In Australia, government authorities have been promoting stormwater harvesting through campaigns, as well as offering incentives and grants to promote water saving ideas and innovations. Among all the stormwater harvesting options, rainwater tanks have been widely studied. Fewkes (1999) conducted studies on residential rainwater tanks in the United Kingdom, producing a series of dimensionless design curves which allows estimation of the rainwater tank size required to obtain a desired performance measure
∗ Corresponding author. E-mail address: [email protected] (M.A. Imteaz). 0921-3449/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.resconrec.2011.09.008
given the roof area and water demand patterns. Vaes and Berlamont (2001) developed a model to determine the effectiveness of rainwater tanks and stormwater runoff using long term historical rainfall data. Coombes and Kuczera (2003) found that for an individual building with a 150 m2 roof area and 1–5 kL tank in Sydney can yield 10–58% mains water savings (depending on the number of people using the building). According to Coombes and Kuczera (2003), depending on roof area and number of occupants, rainwater tank use can result in mains water annual savings of 18–55 kL for 1 kL sized tanks and 25–144 kL for 10 kL sized tanks. In Sweden, Villarreal and Dixon (2005) investigated water savings potential of stormwater harvesting systems from roof areas. Villarreal and Dixon (2005) discovered that a mains water saving of 30% can be achieved using a 40 m3 sized tank (toilet and washing machine use only). Ghisi et al. (2007, 2009) investigated the water savings potential from rainwater harvesting systems in Brazil (South America) and found that average potential for potable water savings of 12–79% per year for the cities analysed. Coombes (2007) conducted studies on the modelling of the rainwater tanks and the opportunities for effective retention storage using the PURRS (Probabilistic Urban Rainwater and Wastewater Reuse Simulator) water balance model. Following over a decade
M.A. Imteaz et al. / Resources, Conservation and Recycling 56 (2011) 80–86
of research into the quality of rainwater collected from roofs, Coombes (2007) has identified the potential for rainwater to be utilised far more extensively than many government regulators are recommending. Despite positive outcome from many studies, there remains a general community reluctance to adopt stormwater harvesting on a wider scale. Part of the reason for this reluctance can be attributed to lack of information about the effectiveness of a stormwater harvesting system and the optimum storage size required to satisfy the performance requirements under the specific site conditions (Imteaz et al., 2011). A proper in-depth understanding of the effectiveness of any proposed on-site stormwater harvesting system is often lacking. The predicted change in rainfall patterns in Australia as a result of global warming adds further complexity to planning adequate rainwater harvesting schemes. Furthermore, many studies have used mean annual rainfall data or generated rainfall data in modelling rainwater harvesting system. In an area of highly interannual rainfall variability, analysis considering long term mean annual rainfall may not be useful. Jenkins (2007) developed a computer model for the continuous simulations of amount of rainwater stored in the tank, amount of rainwater used, amount overflowed and amount of main water used to top up the tank for household rainwater tanks. The model was used for 12 major cities in Australia using daily rainfall data for the simulations of historical average amounts of the abovementioned variables. Jenkins (2007) concluded that the climate characteristics of the site have a significant influence on the effectiveness of the rainwater tank. The study also showed that the water savings efficiency is a function of the monthly variation in rainfall. Eroksuz and Rahman (2010) investigated the water savings potential of rainwater tanks in multi-storied residential buildings for three cities in eastern Australia. They have concluded that rainwater tank of appropriate size in a multi-storied building can provide significant water savings even in dry years. They have also proposed equations for predicting annual rainwater savings potentials for those cities. Khastagir and Jayasuriya (2010) analysed reliability of rainwater tanks and calculated the reliability using a daily water balance model. They have presented contours of optimum tank sizes for surrounding areas of Melbourne, considering the historical daily rainfall, the demand for rainwater, the roof area for a supply reliability of 90%. All of these analyses were based on historical daily rainfall data, making an average of cumulative historical savings and other variables. Through such analysis of averaged variables/parameters rainwater tank users do not get an actual range of expected outcomes. With the impacts of climate change, such ranges of actual outcomes are expected to be widen further. Furthermore, design charts (contours) presented by Khastagir and Jayasuriya (2010) are based on an expected reliability of 90%. In reality, different user may opt for different reliability. This paper presents development of a daily water balance model for the optimisation of rainwater tank size. The developed model considered daily rainfall, losses due to leakage, spillage and evaporation, roof area, tank volume, rainwater demand, overflow losses and tank top up requirements in case of shortage. Ranges of reliability for a central Melbourne location were presented in relations to tank volume, roof area, total water demand and rainwater demand for three different climatic conditions (driest, average and wettest years).
2. Methodology A spreadsheet based daily water balance model was developed considering daily rainfall, contributing catchment (roof) area, losses due to leakage, spillage and evaporation, storage (tank) volume and water uses. In this model, the prime input value was the daily rain-
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Table 1 Annual rainfall for driest, average and wettest years. Year
Annual rainfall (mm)
Driest (2008) Average (1983) Wettest (1978)
463 654 914
fall amount for three different years (driest, average and wettest years). Historical daily rainfall data was collected from Bureau of Meteorology, Australia for a rainfall station near Melbourne central (Scotch College). The daily runoff volume was calculated from daily rainfall amount by multiplying the rainfall amount with the contributing roof area and deducting the losses. For this study, from the produced runoff, a 10% deduction was applied to account for several losses (leakage, spilling and evaporation). Generated runoff was diverted to the connected available storage tank. Available storage capacity was compared with the accumulated daily runoff. If the accumulated runoff was bigger than available storage volume, excess water (overflow) was deducted from the accumulated runoff. Amount of water use(s) is deducted from the daily accumulated/stored runoff amount, if sufficient amount of water is available in the storage. In a situation, when sufficient amount of water is not available in the storage, model will assume that the remaining water demand is supplied from the town water supply. The model calculates daily stormwater use, daily water storage in the tank, daily overflow and daily town water use. In addition, model calculates accumulated annual rainwater use, accumulated annual overflow and accumulated annual town water use. The overall process can be mathematically described as follows: Cumulative water storage equation, St = Vt + St−1 − D
(1)
St = 0, for St < 0
(2)
St = C, for St > C
(3)
where, St is the cumulative water stored in the rainwater tank (L) after the end of tth day; Vt is the harvested rainwater (L) on the tth day; St−1 is the storage in the tank (L) at the beginning of tth day; D is the daily rainwater demand (L), and C is the capacity of rainwater tank (L). Townwater use equation, TW = D − St , for St < D
(4)
where, TW is the townwater use on tth day (L). Overflow equation, OF = St − C, for St > C
(5)
where, OF is the overflow on tth day (L). Reliability is calculated with the equation, Re =
P × 100 (N − U) × 100 N
(6)
where, Re is the reliability of the tank to be able to supply intended demand (%); U is the number of days in a year the tank was unable to meet the demand, and N is the total number of days in a particular year. 3. Data From the historical (1969–2009) rainfall data, three separate years were selected considering annual total rainfall amount. Selected years and corresponding annual rainfall amounts are shown in Table 1. Developed daily water balance model was simulated with the daily rainfall data for the above-mentioned years for several different tank sizes, roof areas, number of occupants (i.e. total water
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80% Rainwater Demand
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Fig. 1. Reliability curves for a two-people household connected with a roof of 50 m2 .
demand) and percentage of total water demand to be fulfilled by rainwater tank. A range of tank sizes from 1000 to 10,000 L were considered. In regards to roof sizes, 50–300 m2 were considered. Although typical roof sizes in Melbourne is much bigger than 50 m2 , however this size was considered with the fact that some households will not be able/wish to connect the whole roof to the rainwater tank. Number of people per household considered were 2 and 4, respectively with an average demand of 185 L/person/day. In regards to percent of total water demand to be fulfilled by rainwater tank, 60, 70 and 80% were considered. Several relationship curves are presented to show effects of different parameters on reliability of rainwater tanks under different climatic conditions. 4. Results and analysis Fig. 1 shows the reliability curves under different climatic conditions (driest, average and wettest years) for different tank sizes for a two-people household (i.e. total water demand 370 L/day) connected with a roof size of 50 m2 for two different scenarios; (a) 80% demand to be fulfilled by rainwater and (b) 60% demand to be fulfilled by rainwater. From the figures it is clear that with this relatively small roof size (50 m2 ), maximum reliability of 36 and 22.5% can be achieved for low rainwater demand (60%) and high rainwater demand (80%) respectively. Reliability increases with the tank sizes until a maximum tank size of 3000 L, beyond which reliability cannot be increased with the increase of tank size for this particular condition (roof size of 50 m2 and two-people household). However, with a double water demand (i.e. four-people household and total water demand of 740 L/day) reliability decreases significantly with the same roof size. Fig. 2 shows the reliability curves for four-people household under similar scenario. A maximum reliability of 10 and 6% can be achieved for low rainwater demand (60%) and high rainwater demand (80%) respectively. For a four-people
household scenario, variations of maximum achievable reliability among different climatic conditions are not much (4–10%). However for a two-people household scenario, variations of maximum achievable reliability among different climatic conditions are considerable (13–22.5%). Figs. 3 and 4 show the reliability curves under different climatic conditions (driest, average and wettest years) for different tank sizes for a roof size of 100 m2 for a two-people household and a four-people household respectively. Both the figures presented reliability curves for two different scenarios; (a) 80% demand to be fulfilled by rainwater and (b) 60% demand to be fulfilled by rainwater. From Fig. 3 (two-people household) it is clear that with this a roof size of 100 m2 , maximum reliability of 85 and 62% can be achieved for low rainwater demand (60%) and high rainwater demand (80%) respectively. Reliability increases with the tank sizes until a maximum tank size of 6000–7000 L (depending on climatic conditions), beyond which reliability cannot be increased with the increase of tank size for this particular condition (roof size of 100 m2 and two-people household). However, with a double water demand (i.e. four-people household and total water demand of 740 L/day) reliability decreases significantly with the same roof size. A maximum reliability of 36 and 23% can be achieved for low rainwater demand (60%) and high rainwater demand (80%) respectively. For a four-people household scenario, maximum achievable reliability varies from 8 to 36% among different climatic conditions and rainwater uses. However for a two-people household scenario, maximum achievable reliability widely varies from 28 to 85% among different climatic conditions and rainwater uses. Figs. 5 and 6 show the reliability curves under different climatic conditions for different tank sizes for a roof size of 200 m2 for a two-people household and a four-people household respectively. Both the figures presented reliability curves for two different scenarios; (a) 80% demand to be fulfilled by rainwater and (b)
M.A. Imteaz et al. / Resources, Conservation and Recycling 56 (2011) 80–86
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a
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Fig. 5. Reliability curves for a two-people household connected with a roof of 200 m2 .
Tank Size (L) Fig. 3. Reliability curves for a two-people household connected with a roof of 100 m2 .
a 80% Rainwater Demand
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TankSize (L) Fig. 6. Reliability curves for a four-people household connected with a roof of 200 m2 .
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M.A. Imteaz et al. / Resources, Conservation and Recycling 56 (2011) 80–86
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Fig. 9. Reliability-roof area-tank size relationships for a two-people household (70% rainwater demand).
Fig. 7. Reliability curves for a two-people household connected with a roof of 300 m2 .
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Tank Size (L) Fig. 8. Reliability curves for a four-people household connected with a roof of 300 m2 .
60% demand to be fulfilled by rainwater. From Fig. 5 (two-people household) it is clear that with a roof size of 200 m2 , maximum reliability of 98% can be achieved for both the cases of low rainwater demand (60%) and high rainwater demand (80%). In wettest and average years, reliability increases with the tank sizes until a maximum tank size of 6000–7000 L, however in driest year reliability keep on increasing until a tank size of 10,000 L. However, with a double water demand (i.e. four-people household) reliability decreases significantly with the same roof size. A maximum reliability of 80 and 60% can be achieved for low rainwater demand (60%) and high rainwater demand (80%) respectively. For a fourpeople household scenario, maximum achievable reliability varies from 28 to 80% among different climatic conditions and rainwater uses. However for a two-people household scenario, maximum achievable reliability widely varies from 70 to 98% among different climatic conditions and rainwater uses. In contrast, for smaller roof cases (50 and 100 m2 ), for four-people household scenario, reliability can be increased with the increase in tank size even beyond 10,000 L. Figs. 7 and 8 show the reliability curves under different climatic conditions for different tank sizes for a roof size of 300 m2 for a twopeople household and a four-people household respectively. Both the figures presented reliability curves for two different scenarios; (a) 80% demand to be fulfilled by rainwater and (b) 60% demand to be fulfilled by rainwater. From Fig. 7 (two-people household) it is clear that with a roof size of 300 m2 , maximum reliability of 100% can be achieved for both the cases of low rainwater demand (60%) and high rainwater demand (80%). In driest and average years, reliability increases with the tank sizes until a maximum tank size of 10,000 L or more. However, in wettest year maximum reliability of 100% is achieved even with tank sizes of 4000 and 6000 L for rainwater uses of 60 and 80% respectively. For a 60% expected use of rainwater, 100% reliability can be achieved even in a driest year with a tank size of 10,000 L. However, for a scenario of double water demand (i.e. four-people household) expected reliabilities
M.A. Imteaz et al. / Resources, Conservation and Recycling 56 (2011) 80–86
Reliability (%)
a
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Tank Size (L) Fig. 10. Reliability-roof area-tank size relationships for a four-people household (70% rainwater demand).
are quite different. Even in wettest year, a 100% reliability is not possible to achieve even with a tank size of 10,000 L and reliability keep on increases with the increase of tank size, even beyond a tank size of 10,000 L. A maximum reliability of 98 and 82% can be achieved for low rainwater demand (60%) and high rainwater demand (80%) respectively. For a four-people household scenario, reliability can vary from 45 to 98% among different climatic conditions and rainwater uses. However for a two-people household scenario, reliabilities do not vary widely, as in such cases with the aid of bigger roof size and lower water demand, reliability quickly approaches to 100% with the increase of rainwater tank size. To know the influence of roof size on reliability under different tank sizes, reliability curves of different roof sizes are presented in a single plot. Figs. 9 and 10 show the relationships of reliability, roof area and tank volume for a two-people household and four-people household scenario respectively. Both the figures were produced for a rainwater demand of 70%. From Fig. 9 (two-people household) it is clear that in a wet year, effect of roof area is very significant upto an area of 150 m2 , beyond which the effect become insignificant as a reliability of about 100% can be achieved even with a roof size of 150 m2 . However, the scenario is different in a dry year. The effect of roof size on the reliability is significant and the reliability keeps on increasing with the increase of roof size. Fig. 10 shows the similar plots for a four-people household scenario. It is clear from the figure that for a higher water uses (i.e. four-people household), the reliability is significantly dependent on roof size and keeps on increasing with the increase of roof size for a widely varied roof sizes. 5. Conclusions This paper investigated reliability of rainwater tanks under different scenarios i.e. climatic conditions, roof areas, tank volumes, household water demands and portion of total demand to be ful-
85
filled by rainwater. The study considered recorded daily rainfall data instead of annual average rainfall data. Analysis using recorded rainfall data reveals more realistic scenarios instead of a hypothetical average scenario. Analysis was performed for three different climatic conditions (driest, average and wettest years) having significant differences in rainfall amounts. In regards to tank sizes, a wide range of sizes (1000–10,000 L) were investigated. Typical roof (connected to the tank) sizes from 50 to 300 m2 were considered in the analysis. In regards to total water demand, two scenarios i.e. two people household and four-people household with a typical average water demand (for Melbourne) of 185 L/person/day was considered. Portions of total water demand to be fulfilled by rainwater considered were 60%, 70% and 80%. The reliability was defined as the percentage of the total days in a year, when the rainwater tank was able to fulfil the intended demand. Several reliability charts are presented and discussed under different input conditions. In reality numerous different reliability can be achieved for different combinations of several input variables (roof size, tank volume, climate condition, number of people in the house and percentage of rainwater demand). However, for some variables there are threshold values, beyond which reliability does not change. In general, for two-people household scenario, with the amount of rainfall for the investigation area (Melbourne), it is found that for a roof size of upto 150 m2 , it is almost impossible to achieve a 100% reliability even in wettest year. Also, effect of tank size on reliability becomes insignificant for tank sizes approximately beyond 5000 L. However, with a bigger roof size (>150 m2 ), it is possible to achieve 100% reliability, even with a tank size of 5000–6000 L. For a lower percentage of rainwater demand, it is even easier to achieve 100% reliability. Even in a driest year it is possible to achieve 100% reliability with a suitable tank size and bigger roof area (300 m2 ). However, for a four-people household scenario, with the tank sizes investigated (maximum 10,000 L) the outcomes are quiet different. For a roof size of 50 m2 , a maximum reliability of only 10% can be achieved even in a wettest year and effect of tank sizes becomes insignificant for a tank sizes approximately beyond 3000 L. This is because a higher demand of rainwater, compared to a lower runoff/inflow from smaller roof. Even with a roof size of 300 m2 , a 100% reliability is not possible to achieve for tank sizes upto 10,000 L. However, as reliability keeps on increasing with the increase of tank sizes (even beyond 10,000 L), a bigger tank size (>10,000 L) will be able to achieve 100% reliability, specially in wet years. This study was based on a particular geographical area near central Melbourne. The results would vary with geographical locations i.e. with different climatic conditions or in general with different rainfall intensities and pattern. In reality, there will be numerous optimal solutions with different combinations of storage volumes, roof sizes, rainwater demand and number of people in the household. A comprehensive decision support tool would be able to produce reliability, cumulative water savings, cumulative overflow losses and cumulative townwater supply used for any geographical location with any value of above-mentioned variables.
References Coombes P. Rainwater Research 2007. www.rainwaterharvesting.com.au (Viewed 13 March, 2010). Coombes P, Kuczera G. Analysis of the performance of rainwater tanks in Australian capital cities. In: 28th International Hydrology and Water Resources Symposium; 2003. Eroksuz E, Rahman A. Rainwater tanks in multi-unit buildings: a case study for three Australian cities. Resources, Conservation and Recycling 2010;54:1449–52. Fewkes A. The use of rainwater for WC flushing: the field testing of a collection system. Building and Environment 1999;34(6):765–72. Ghisi E, Bressan DL, Martini M. Rainwater tank capacity and potential for potable water savings by using rainwater in the residential sector of southeastern Brazil. Building and Environment 2007;42:1654–66.
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Ghisi E, Tavares DF, Rocha VL. Rainwater harvesting in petrol stations in Brasilia: potential for potable water savings and investment feasibility analysis. Resources, Conservation and Recycling 2009;54:79–85. Imteaz MA, Shanableh A, Rahman A, Ahsan A. Optimisation of rainwater tank design from large roofs: a case study in Melbourne, Australia. Resources Conservation and Recycling 2011;55:1022–9. Jenkins G. Use of continuous simulation for the selection of an appropriate urban rainwater tank. Australian Journal of Water Resources 2007;11(2):231–46.
Khastagir A, Jayasuriya N. Optimal sizing of rain water tanks for domestic water conservation. Journal of Hydrology 2010;381:181–8. Vaes G, Berlamont J. The effect of rainwater storage tank on design storms. Urban Water 2001;3:303–7. Villarreal EL, Dixon A. Analysis of a rainwater collection system for domestic water supply in Ringdansen, Norrkoping, Sweden. Building and Environment 2005;40:1174–84.
Contents lists available at SciVerse ScienceDirect
Resources, Conservation and Recycling journal homepage: www.elsevier.com/locate/resconrec
Reliability analysis of rainwater tanks in Melbourne using daily water balance model Monzur Alam Imteaz a,∗ , Amimul Ahsan b , Jamal Naser a , Ataur Rahman c a
Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, Melbourne, VIC, Australia Department of Civil Engineering, Faculty of Engineering, University Putra Malaysia, Selangor, Malaysia c School of Engineering, University of Western Sydney, NSW, Australia b
a r t i c l e
i n f o
Article history: Received 22 February 2011 Received in revised form 8 September 2011 Accepted 9 September 2011 Keywords: Rainwater tank Daily water balance Climatic conditions Reliability and historical rainfall
a b s t r a c t With the aim of developing a comprehensive decision support tool for the performance analysis and design of rainwater tanks, a simple spreadsheet based daily water balance model was developed using daily rainfall data, contributing roof area, rainfall loss factor, available storage volume, tank overflow and rainwater demand. In order to assess reliability of domestic rainwater tanks in augmenting partial household water demand in Melbourne (Australia) area, the developed water balance model was used for three different climatic conditions (i.e. dry, average, and wet years). Historical daily rainfall data was collected from a rainfall station near Melbourne city central. From historical rainfall data three representative years (driest, average and wettest) were selected for the current analysis. Reliability is defined as percentage of days in a year when rainwater tank was able to supply the intended partial demand for a particular condition. For the three climatic conditions, several reliability charts are presented for domestic rainwater tanks in relations to tank volume, roof area, number of people in a house (i.e. water demand) and percentage of total water demand to be satisfied by harvested rainwater. In brief, for a two-people household scenario, ∼100% reliability can be achieved with a roof size of 150–300 m2 having a tank size of 5000–10,000 L. However, for a four-people household scenario, it is not possible to achieve a 100% reliability, even with a roof size of 300 m2 and a tank size of 10,000 L. © 2011 Elsevier B.V. All rights reserved.
1. Introduction With increasing population and changing climate regime, water supply systems in many cities of the world are under stress. To tackle this problem, water authorities are adopting several measures including demand management and identifying alternative water sources such as stormwater harvesting, greywater and wastewater reuse and desalination. Among all the alternative water sources, stormwater harvesting perhaps has received the most attention. In Australia, government authorities have been promoting stormwater harvesting through campaigns, as well as offering incentives and grants to promote water saving ideas and innovations. Among all the stormwater harvesting options, rainwater tanks have been widely studied. Fewkes (1999) conducted studies on residential rainwater tanks in the United Kingdom, producing a series of dimensionless design curves which allows estimation of the rainwater tank size required to obtain a desired performance measure
∗ Corresponding author. E-mail address: [email protected] (M.A. Imteaz). 0921-3449/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.resconrec.2011.09.008
given the roof area and water demand patterns. Vaes and Berlamont (2001) developed a model to determine the effectiveness of rainwater tanks and stormwater runoff using long term historical rainfall data. Coombes and Kuczera (2003) found that for an individual building with a 150 m2 roof area and 1–5 kL tank in Sydney can yield 10–58% mains water savings (depending on the number of people using the building). According to Coombes and Kuczera (2003), depending on roof area and number of occupants, rainwater tank use can result in mains water annual savings of 18–55 kL for 1 kL sized tanks and 25–144 kL for 10 kL sized tanks. In Sweden, Villarreal and Dixon (2005) investigated water savings potential of stormwater harvesting systems from roof areas. Villarreal and Dixon (2005) discovered that a mains water saving of 30% can be achieved using a 40 m3 sized tank (toilet and washing machine use only). Ghisi et al. (2007, 2009) investigated the water savings potential from rainwater harvesting systems in Brazil (South America) and found that average potential for potable water savings of 12–79% per year for the cities analysed. Coombes (2007) conducted studies on the modelling of the rainwater tanks and the opportunities for effective retention storage using the PURRS (Probabilistic Urban Rainwater and Wastewater Reuse Simulator) water balance model. Following over a decade
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of research into the quality of rainwater collected from roofs, Coombes (2007) has identified the potential for rainwater to be utilised far more extensively than many government regulators are recommending. Despite positive outcome from many studies, there remains a general community reluctance to adopt stormwater harvesting on a wider scale. Part of the reason for this reluctance can be attributed to lack of information about the effectiveness of a stormwater harvesting system and the optimum storage size required to satisfy the performance requirements under the specific site conditions (Imteaz et al., 2011). A proper in-depth understanding of the effectiveness of any proposed on-site stormwater harvesting system is often lacking. The predicted change in rainfall patterns in Australia as a result of global warming adds further complexity to planning adequate rainwater harvesting schemes. Furthermore, many studies have used mean annual rainfall data or generated rainfall data in modelling rainwater harvesting system. In an area of highly interannual rainfall variability, analysis considering long term mean annual rainfall may not be useful. Jenkins (2007) developed a computer model for the continuous simulations of amount of rainwater stored in the tank, amount of rainwater used, amount overflowed and amount of main water used to top up the tank for household rainwater tanks. The model was used for 12 major cities in Australia using daily rainfall data for the simulations of historical average amounts of the abovementioned variables. Jenkins (2007) concluded that the climate characteristics of the site have a significant influence on the effectiveness of the rainwater tank. The study also showed that the water savings efficiency is a function of the monthly variation in rainfall. Eroksuz and Rahman (2010) investigated the water savings potential of rainwater tanks in multi-storied residential buildings for three cities in eastern Australia. They have concluded that rainwater tank of appropriate size in a multi-storied building can provide significant water savings even in dry years. They have also proposed equations for predicting annual rainwater savings potentials for those cities. Khastagir and Jayasuriya (2010) analysed reliability of rainwater tanks and calculated the reliability using a daily water balance model. They have presented contours of optimum tank sizes for surrounding areas of Melbourne, considering the historical daily rainfall, the demand for rainwater, the roof area for a supply reliability of 90%. All of these analyses were based on historical daily rainfall data, making an average of cumulative historical savings and other variables. Through such analysis of averaged variables/parameters rainwater tank users do not get an actual range of expected outcomes. With the impacts of climate change, such ranges of actual outcomes are expected to be widen further. Furthermore, design charts (contours) presented by Khastagir and Jayasuriya (2010) are based on an expected reliability of 90%. In reality, different user may opt for different reliability. This paper presents development of a daily water balance model for the optimisation of rainwater tank size. The developed model considered daily rainfall, losses due to leakage, spillage and evaporation, roof area, tank volume, rainwater demand, overflow losses and tank top up requirements in case of shortage. Ranges of reliability for a central Melbourne location were presented in relations to tank volume, roof area, total water demand and rainwater demand for three different climatic conditions (driest, average and wettest years).
2. Methodology A spreadsheet based daily water balance model was developed considering daily rainfall, contributing catchment (roof) area, losses due to leakage, spillage and evaporation, storage (tank) volume and water uses. In this model, the prime input value was the daily rain-
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Table 1 Annual rainfall for driest, average and wettest years. Year
Annual rainfall (mm)
Driest (2008) Average (1983) Wettest (1978)
463 654 914
fall amount for three different years (driest, average and wettest years). Historical daily rainfall data was collected from Bureau of Meteorology, Australia for a rainfall station near Melbourne central (Scotch College). The daily runoff volume was calculated from daily rainfall amount by multiplying the rainfall amount with the contributing roof area and deducting the losses. For this study, from the produced runoff, a 10% deduction was applied to account for several losses (leakage, spilling and evaporation). Generated runoff was diverted to the connected available storage tank. Available storage capacity was compared with the accumulated daily runoff. If the accumulated runoff was bigger than available storage volume, excess water (overflow) was deducted from the accumulated runoff. Amount of water use(s) is deducted from the daily accumulated/stored runoff amount, if sufficient amount of water is available in the storage. In a situation, when sufficient amount of water is not available in the storage, model will assume that the remaining water demand is supplied from the town water supply. The model calculates daily stormwater use, daily water storage in the tank, daily overflow and daily town water use. In addition, model calculates accumulated annual rainwater use, accumulated annual overflow and accumulated annual town water use. The overall process can be mathematically described as follows: Cumulative water storage equation, St = Vt + St−1 − D
(1)
St = 0, for St < 0
(2)
St = C, for St > C
(3)
where, St is the cumulative water stored in the rainwater tank (L) after the end of tth day; Vt is the harvested rainwater (L) on the tth day; St−1 is the storage in the tank (L) at the beginning of tth day; D is the daily rainwater demand (L), and C is the capacity of rainwater tank (L). Townwater use equation, TW = D − St , for St < D
(4)
where, TW is the townwater use on tth day (L). Overflow equation, OF = St − C, for St > C
(5)
where, OF is the overflow on tth day (L). Reliability is calculated with the equation, Re =
P × 100 (N − U) × 100 N
(6)
where, Re is the reliability of the tank to be able to supply intended demand (%); U is the number of days in a year the tank was unable to meet the demand, and N is the total number of days in a particular year. 3. Data From the historical (1969–2009) rainfall data, three separate years were selected considering annual total rainfall amount. Selected years and corresponding annual rainfall amounts are shown in Table 1. Developed daily water balance model was simulated with the daily rainfall data for the above-mentioned years for several different tank sizes, roof areas, number of occupants (i.e. total water
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80% Rainwater Demand
80% Rainwater Demand
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Fig. 1. Reliability curves for a two-people household connected with a roof of 50 m2 .
demand) and percentage of total water demand to be fulfilled by rainwater tank. A range of tank sizes from 1000 to 10,000 L were considered. In regards to roof sizes, 50–300 m2 were considered. Although typical roof sizes in Melbourne is much bigger than 50 m2 , however this size was considered with the fact that some households will not be able/wish to connect the whole roof to the rainwater tank. Number of people per household considered were 2 and 4, respectively with an average demand of 185 L/person/day. In regards to percent of total water demand to be fulfilled by rainwater tank, 60, 70 and 80% were considered. Several relationship curves are presented to show effects of different parameters on reliability of rainwater tanks under different climatic conditions. 4. Results and analysis Fig. 1 shows the reliability curves under different climatic conditions (driest, average and wettest years) for different tank sizes for a two-people household (i.e. total water demand 370 L/day) connected with a roof size of 50 m2 for two different scenarios; (a) 80% demand to be fulfilled by rainwater and (b) 60% demand to be fulfilled by rainwater. From the figures it is clear that with this relatively small roof size (50 m2 ), maximum reliability of 36 and 22.5% can be achieved for low rainwater demand (60%) and high rainwater demand (80%) respectively. Reliability increases with the tank sizes until a maximum tank size of 3000 L, beyond which reliability cannot be increased with the increase of tank size for this particular condition (roof size of 50 m2 and two-people household). However, with a double water demand (i.e. four-people household and total water demand of 740 L/day) reliability decreases significantly with the same roof size. Fig. 2 shows the reliability curves for four-people household under similar scenario. A maximum reliability of 10 and 6% can be achieved for low rainwater demand (60%) and high rainwater demand (80%) respectively. For a four-people
household scenario, variations of maximum achievable reliability among different climatic conditions are not much (4–10%). However for a two-people household scenario, variations of maximum achievable reliability among different climatic conditions are considerable (13–22.5%). Figs. 3 and 4 show the reliability curves under different climatic conditions (driest, average and wettest years) for different tank sizes for a roof size of 100 m2 for a two-people household and a four-people household respectively. Both the figures presented reliability curves for two different scenarios; (a) 80% demand to be fulfilled by rainwater and (b) 60% demand to be fulfilled by rainwater. From Fig. 3 (two-people household) it is clear that with this a roof size of 100 m2 , maximum reliability of 85 and 62% can be achieved for low rainwater demand (60%) and high rainwater demand (80%) respectively. Reliability increases with the tank sizes until a maximum tank size of 6000–7000 L (depending on climatic conditions), beyond which reliability cannot be increased with the increase of tank size for this particular condition (roof size of 100 m2 and two-people household). However, with a double water demand (i.e. four-people household and total water demand of 740 L/day) reliability decreases significantly with the same roof size. A maximum reliability of 36 and 23% can be achieved for low rainwater demand (60%) and high rainwater demand (80%) respectively. For a four-people household scenario, maximum achievable reliability varies from 8 to 36% among different climatic conditions and rainwater uses. However for a two-people household scenario, maximum achievable reliability widely varies from 28 to 85% among different climatic conditions and rainwater uses. Figs. 5 and 6 show the reliability curves under different climatic conditions for different tank sizes for a roof size of 200 m2 for a two-people household and a four-people household respectively. Both the figures presented reliability curves for two different scenarios; (a) 80% demand to be fulfilled by rainwater and (b)
M.A. Imteaz et al. / Resources, Conservation and Recycling 56 (2011) 80–86
80% Rainwater Demand
a
a
70
50
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Reliability %
Reliability %
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Fig. 5. Reliability curves for a two-people household connected with a roof of 200 m2 .
Tank Size (L) Fig. 3. Reliability curves for a two-people household connected with a roof of 100 m2 .
a 80% Rainwater Demand
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Reliability %
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30 20 10
0 1000
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Tank Size (L) Fig. 4. Reliability curves for a four-people household connected with a roof of 100 m2 .
0 1000
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TankSize (L) Fig. 6. Reliability curves for a four-people household connected with a roof of 200 m2 .
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M.A. Imteaz et al. / Resources, Conservation and Recycling 56 (2011) 80–86
0
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Roof = 50 sqm
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Roof = 150 sqm Roof = 200 sqm
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20 2000
4000
6000
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10000
Fig. 9. Reliability-roof area-tank size relationships for a two-people household (70% rainwater demand).
Fig. 7. Reliability curves for a two-people household connected with a roof of 300 m2 .
90
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Tank Size (L)
TankSize (L)
a
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Dry Year
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0 0
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Reliability (%)
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Tank Size (L) Fig. 8. Reliability curves for a four-people household connected with a roof of 300 m2 .
60% demand to be fulfilled by rainwater. From Fig. 5 (two-people household) it is clear that with a roof size of 200 m2 , maximum reliability of 98% can be achieved for both the cases of low rainwater demand (60%) and high rainwater demand (80%). In wettest and average years, reliability increases with the tank sizes until a maximum tank size of 6000–7000 L, however in driest year reliability keep on increasing until a tank size of 10,000 L. However, with a double water demand (i.e. four-people household) reliability decreases significantly with the same roof size. A maximum reliability of 80 and 60% can be achieved for low rainwater demand (60%) and high rainwater demand (80%) respectively. For a fourpeople household scenario, maximum achievable reliability varies from 28 to 80% among different climatic conditions and rainwater uses. However for a two-people household scenario, maximum achievable reliability widely varies from 70 to 98% among different climatic conditions and rainwater uses. In contrast, for smaller roof cases (50 and 100 m2 ), for four-people household scenario, reliability can be increased with the increase in tank size even beyond 10,000 L. Figs. 7 and 8 show the reliability curves under different climatic conditions for different tank sizes for a roof size of 300 m2 for a twopeople household and a four-people household respectively. Both the figures presented reliability curves for two different scenarios; (a) 80% demand to be fulfilled by rainwater and (b) 60% demand to be fulfilled by rainwater. From Fig. 7 (two-people household) it is clear that with a roof size of 300 m2 , maximum reliability of 100% can be achieved for both the cases of low rainwater demand (60%) and high rainwater demand (80%). In driest and average years, reliability increases with the tank sizes until a maximum tank size of 10,000 L or more. However, in wettest year maximum reliability of 100% is achieved even with tank sizes of 4000 and 6000 L for rainwater uses of 60 and 80% respectively. For a 60% expected use of rainwater, 100% reliability can be achieved even in a driest year with a tank size of 10,000 L. However, for a scenario of double water demand (i.e. four-people household) expected reliabilities
M.A. Imteaz et al. / Resources, Conservation and Recycling 56 (2011) 80–86
Reliability (%)
a
Wet Year
100 80
Roof = 50 sqm
60
Roof = 100 sqm Roof = 150 sqm
40
Roof = 200 sqm Roof = 300 sqm
20 0
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Reliability (%)
b
60
Roof = 50 sqm
40
Roof = 100 sqm Roof = 150 sqm Roof = 200 sqm
20
0
Roof = 300 sqm
0
2000
4000
6000
8000
10000
Tank Size (L) Fig. 10. Reliability-roof area-tank size relationships for a four-people household (70% rainwater demand).
are quite different. Even in wettest year, a 100% reliability is not possible to achieve even with a tank size of 10,000 L and reliability keep on increases with the increase of tank size, even beyond a tank size of 10,000 L. A maximum reliability of 98 and 82% can be achieved for low rainwater demand (60%) and high rainwater demand (80%) respectively. For a four-people household scenario, reliability can vary from 45 to 98% among different climatic conditions and rainwater uses. However for a two-people household scenario, reliabilities do not vary widely, as in such cases with the aid of bigger roof size and lower water demand, reliability quickly approaches to 100% with the increase of rainwater tank size. To know the influence of roof size on reliability under different tank sizes, reliability curves of different roof sizes are presented in a single plot. Figs. 9 and 10 show the relationships of reliability, roof area and tank volume for a two-people household and four-people household scenario respectively. Both the figures were produced for a rainwater demand of 70%. From Fig. 9 (two-people household) it is clear that in a wet year, effect of roof area is very significant upto an area of 150 m2 , beyond which the effect become insignificant as a reliability of about 100% can be achieved even with a roof size of 150 m2 . However, the scenario is different in a dry year. The effect of roof size on the reliability is significant and the reliability keeps on increasing with the increase of roof size. Fig. 10 shows the similar plots for a four-people household scenario. It is clear from the figure that for a higher water uses (i.e. four-people household), the reliability is significantly dependent on roof size and keeps on increasing with the increase of roof size for a widely varied roof sizes. 5. Conclusions This paper investigated reliability of rainwater tanks under different scenarios i.e. climatic conditions, roof areas, tank volumes, household water demands and portion of total demand to be ful-
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filled by rainwater. The study considered recorded daily rainfall data instead of annual average rainfall data. Analysis using recorded rainfall data reveals more realistic scenarios instead of a hypothetical average scenario. Analysis was performed for three different climatic conditions (driest, average and wettest years) having significant differences in rainfall amounts. In regards to tank sizes, a wide range of sizes (1000–10,000 L) were investigated. Typical roof (connected to the tank) sizes from 50 to 300 m2 were considered in the analysis. In regards to total water demand, two scenarios i.e. two people household and four-people household with a typical average water demand (for Melbourne) of 185 L/person/day was considered. Portions of total water demand to be fulfilled by rainwater considered were 60%, 70% and 80%. The reliability was defined as the percentage of the total days in a year, when the rainwater tank was able to fulfil the intended demand. Several reliability charts are presented and discussed under different input conditions. In reality numerous different reliability can be achieved for different combinations of several input variables (roof size, tank volume, climate condition, number of people in the house and percentage of rainwater demand). However, for some variables there are threshold values, beyond which reliability does not change. In general, for two-people household scenario, with the amount of rainfall for the investigation area (Melbourne), it is found that for a roof size of upto 150 m2 , it is almost impossible to achieve a 100% reliability even in wettest year. Also, effect of tank size on reliability becomes insignificant for tank sizes approximately beyond 5000 L. However, with a bigger roof size (>150 m2 ), it is possible to achieve 100% reliability, even with a tank size of 5000–6000 L. For a lower percentage of rainwater demand, it is even easier to achieve 100% reliability. Even in a driest year it is possible to achieve 100% reliability with a suitable tank size and bigger roof area (300 m2 ). However, for a four-people household scenario, with the tank sizes investigated (maximum 10,000 L) the outcomes are quiet different. For a roof size of 50 m2 , a maximum reliability of only 10% can be achieved even in a wettest year and effect of tank sizes becomes insignificant for a tank sizes approximately beyond 3000 L. This is because a higher demand of rainwater, compared to a lower runoff/inflow from smaller roof. Even with a roof size of 300 m2 , a 100% reliability is not possible to achieve for tank sizes upto 10,000 L. However, as reliability keeps on increasing with the increase of tank sizes (even beyond 10,000 L), a bigger tank size (>10,000 L) will be able to achieve 100% reliability, specially in wet years. This study was based on a particular geographical area near central Melbourne. The results would vary with geographical locations i.e. with different climatic conditions or in general with different rainfall intensities and pattern. In reality, there will be numerous optimal solutions with different combinations of storage volumes, roof sizes, rainwater demand and number of people in the household. A comprehensive decision support tool would be able to produce reliability, cumulative water savings, cumulative overflow losses and cumulative townwater supply used for any geographical location with any value of above-mentioned variables.
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