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http://dx.doi.org/10.1007/s11269-014-0704-1

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Metadata of the article that will be visualized in OnlineFirst

1 Article Title Water Sav ing and Energy Reduction through Pressure

Management in Urban Water Distribution Networks

2 Article Sub- Title

3 Article Copyright -Year

Springer Science+Business Media Dordrecht 2014(This will be the copyright line in the final PDF)

4 Journal Name Water Resources Management

5

Corresponding

Author

Family Name Chen

6 Particle

7 Given Name Qiuwen

8 Suffix

9 Organization CEER, Nanjing Hydraulic Research Institute

10 Division

11 Address Nanjing 210029, China

12 Organization RCEES, Chinese Academy of Sciences

13 Division

14 Address Beijing 100085, China

15 e-mail qwchen@nhri.cn

16

Author

Family Name Xu

17 Particle

18 Given Name Qiang

19 Suffix

20 Organization RCEES, Chinese Academy of Sciences

21 Division

22 Address Beijing 100085, China

23 e-mail

24

Author

Family Name Ma

25 Particle

26 Given Name Jinfeng

27 Suffix

28 Organization RCEES, Chinese Academy of Sciences

29 Division

30 Address Beijing 100085, China

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31 e-mail

32

Author

Family Name Blanckaert

33 Particle

34 Given Name Koen

35 Suffix

36 Organization RCEES, Chinese Academy of Sciences

37 Division

38 Address Beijing 100085, China

39 Organization Laboratory of Hydraulic Constructions, EPFL

40 Division

41 Address Lausanne 1015, Switzerland

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43

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Family Name Wan

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45 Given Name Zhonghua

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47 Organization Anheng Science and Technology Co. Ltd. ofBeijing

48 Division

49 Address Beijing 100025, China

50 e-mail

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Received 8 July 2013

52 Revised

53 Accepted 28 May 2014

54 Abstract Water shortages and climate change are worldwide issues.Reduction in water leakage in distribution networks as well as theassociated energy saving and environmental impacts have recentlyreceived increased attention by scientists and water industries.Pressure management has been proposed as a cost-effectiveapproach for reduction in water leakage. This study conducted areal-world water pressure regulation experiment to establish thepressure-leakage relationship in a district metering area (DMA) ofthe water distribution network in Beijing, China. Results showedthat flow into the DMA was sensitive to inlet water pressure. A 5.6 mreduction in inlet pressure (from 38.8 m to 33.2 m) led to an 83 %reduction (12.1 l/s) in minimal night flow, which is a good

approximator of leakage. These reductions resulted in 62,633 m3 ofwater saved every year for every km pipe, as well as associated

savings of 1.1  × 106 MJ of energy and 68 t of CO2 equivalentgreenhouse gas emissions. The results of this study providedecision makers with advice for reducing leakage in water

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distribution networks with associated energy and environmentalbenefits.

55 Keywordsseparated by ' - '

Leakage reduction - Pressure management - Water distributionnetwork - Energy saving - Greenhouse gas emission reduction

56 Foot noteinformation

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123

4Water Saving and Energy Reduction through Pressure5Management in Urban Water Distribution Networks

6Qiang Xu & Qiuwen Chen & Jinfeng Ma &

7Koen Blanckaert & Zhonghua Wan

8Received: 8 July 2013 /Accepted: 28 May 20149# Springer Science+Business Media Dordrecht 2014

10

11Abstract Water shortages and climate change are worldwide issues. Reduction in water12leakage in distribution networks as well as the associated energy saving and environmental13impacts have recently received increased attention by scientists and water industries. Pressure14management has been proposed as a cost-effective approach for reduction in water leakage.15This study conducted a real-world water pressure regulation experiment to establish the16pressure-leakage relationship in a district metering area (DMA) of the water distribution17network in Beijing, China. Results showed that flow into the DMA was sensitive to inlet18water pressure. A 5.6 m reduction in inlet pressure (from 38.8 m to 33.2 m) led to an 83 %19reduction (12.1 l/s) in minimal night flow, which is a good approximator of leakage. These20reductions resulted in 62,633 m3 of water saved every year for every km pipe, as well as21associated savings of 1.1×106 MJ of energy and 68 t of CO2 equivalent greenhouse gas22emissions. The results of this study provide decision makers with advice for reducing leakage23in water distribution networks with associated energy and environmental benefits.

24Keywords Leakage reduction . Pressure management .Water distribution network .

25Energy saving . Greenhouse gas emission reduction26

271 Introduction

28Along with rapid socio-economic development and urbanization, water shortages and climate29change are worldwide issues. According to the United Nations, around 1.2 billion people, or

Water Resour ManageDOI 10.1007/s11269-014-0704-1

Q. Xu :Q. Chen : J. Ma : K. BlanckaertRQ2 CEES, Chinese Academy of Sciences, Beijing 100085, China

Q. Chen (*)CEER, Nanjing Hydraulic Research Institute, Nanjing 210029, Chinae-mail: qwchen@nhri.cn

K. BlanckaertLaboratory of Hydraulic Constructions, EPFL, Lausanne 1015, Switzerland

Z. WanAnheng Science and Technology Co. Ltd. of Beijing, Beijing 100025, China

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30almost one-fifth of the world’s population, live in areas of physical water scarcity (available31from: http://www.un.org/waterforlifedecade/scarcity.shtml). At the same time, water use has32been increasing at more than twice the rate of population growth in the last century. By 2025,331.8 billion people will be living in countries or regions with absolute water scarcity, and two-34thirds of the world’s population could be under water stress conditions (WWAP 2006).35Water loss exists, however, in any water distribution system due to structural deterioration36of the pipe network. Each year 35 % of total water supplied is lost from water distribution37networks all over the world (Farley et al. 2008). Water supply is an energy-intensive industry,38which consumes 2–3 % of worldwide energy (James et al. 2002). The energy consumption rate39ranges from 2–42 MJ of energy per cubic meter of water depending on the water source40(Friedrich 2002; Racoviceanu et al. 2007; Lyons et al. 2009; Stokes and Horvath 2009; Mo41et al. 2011). Energy consumption and greenhouse gas emissions are closely related. According42to Stokes and Horvath (2009), 60.7 g of CO2 is emitted for 1 MJ of energy consumed in the43process of producing and distributing imported water. Therefore, water loss not only affects the44revenue of water utility providers, but also wastes a large amount of energy to treat source45water and distribute potable water, and increases the greenhouse gas emissions.46Theoretically, water leakage from the distribution network occurs when the residual47resistance of the pipe can no longer bear the impact of water pressure (Skipworth 2002).48Therefore, approaches for water leakage control can basically be classified into two categories:49improving pipe resistance and reducing water pressure.50The first category focuses on pipes. Breaks are detected and repaired, and deteriorated pipes51are repaired or replaced. Thus, the condition of the distribution network can be improved and52water leakage can be reduced. Researchers have investigated pipe break behavior to optimize53break detection and/or determine the economically optimal time for pipe replacement (Shamir54and Howard 1979; Walski and Pelliccia 1982; Park et al. 2008, 2010; Giustolisi and Berardi552009; Carrión et al. 2010;Q3 Tsitsifli et al. 2011; Xu et al. 2011a, b, 2013; Tabesh and Saber562012; Fontana and Morais 2013). These analyses mostly depended on collected pipe break57data. There are, however, many beaks that cannot be detected with available technologies. Pipe58replacement can further reduce water leakage, but replacement cannot be implemented on a59massive scale due to high costs and long implementation times.60The second category focuses on water pressure management (Araujo et al. 2006; Nazif61et al. 2010). Water leakage is positively related to water pressure, and reduction in water62pressure can be translated into reduction in water leakage. The total leakage in a pipe63distribution network is often estimated according to a pressure-leakage relationship in the64following form (Lambert 2001; Thronton 2003; UKWIR 2003; Thornton and Lambert 2005):

L ¼ kP�n ð1Þ

6566where L is the leakage, Pis the average pressure of the network, and k and n are parameters to67be calibrated. The exponent n ranges from 0.5 to 2.5 or even higher depending on the type of68leakage and pipe material (Lambert 2001; Thornton and Lambert 2005). For leaks from joints69and fittings, bigger values of n (>1) are usually obtained. For leaks from holes in pipe, n70usually has smaller values. Regarding to the pipe material, plastic pipes have bigger n values71than metal pipes (Lambert 2001). Obviously, water leakage will be sensitive to water pressure72if n>1.73Pressure management is an effective strategy to reduce water leakage in distribution74networks. Furthermore, it is the only strategy that allows for reductions in residual water75leakage due to undetectable pipe damage. In addition to reducing water leakage from existing76pipe breaks, pressure management also reduces the risk of new breaks and extends pipe

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77lifetime (Farley and Trow 2003; Q4Thornton 2006; =Q5Lambert 2011). Energy consumption and78greenhouse gas emissions can accordingly be reduced.79In some countries, notably the UK and Japan, it has been recognized for over 30 years that80effective pressure management is the key to efficient leakage management (Thronton 2003).81Although more and more countries are realizing the importance of pressure management82(Marunga et al. 2006; Girard and Stewart 2007; Soriano et al. 2012), it is still not applied in83most developing countries for two reasons. The first is the lack of decision support tools that84accurately predict the benefits associated with pressure management and justify the invest-85ment. The second is that water distribution networks are usually not well configured for86effective pressure management (Mutikanga et al. 2013).87This study conducted a large-scale real-world experiment in a sub-network of Beijing’s88water distribution system to investigate the effect of pressure management on water leakage89and gain insight into associated energy and environmental benefits.

902 Material and Methods

912.1 Description of Experimental Pipe Network

92The water pressure regulation experiment was conducted in a district metering area (DMA) of93the water distribution network of Beijing, China. The network has one inlet where the water94pressure is measured and controlled, and where the flow is measured as well. Fig. 1 depicts the95layout of the DMA and Table 1 presents its general features.

")

#I

#I Pressure Monitoring

") Inlet (flow and pressure monitoring)

Pipes

Fig. 1 Layout of experimental District Metering Area (DMA)

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97Water pressure and flow at the inlet were automatically measured and recorded every 15 min.98To ensure that pressure was adequate for reliable water supply, the node (indicated by a99triangle in Fig. 1) with minimal pressure in the DMA was synchronously measured and100recorded. A minimal pressure of 18 m, which was a mandatory rule from the government of101Beijing, was requested at this point in all instances. In fact, considering the users’ satisfactory102and other possible demands for high water pressure, the minimal pressure was finally103maintained at 27 m. The experimental period was from September 1, 2012 to March 10, 2013.104Three strategies of pressure management were investigated and compared. In the first period of10545 days from September 1 to October 15, 2012, the inlet pressure was not manipulated and kept at106its original value of 38.8 m. This value was rather constant during a day. In the second period of10738 days from October 16 to November 22, 2012, the average pressure was reduced by 3.7 m, and108the pressure during peak hours was relatively low. In the third period of 98 days from November10923, 2012 to March 10, 2013, the average pressure was further reduced by 1.9 m. But the pressure110during peak hours was intentionally increased to compensate for the higher energy losses due to111larger water use. Details of the pressure patterns are presented in the results and discussion sections.

1123 Results

113The measured data of the inlet pressure and flow during the three investigated periods are114shown in Fig. 2 and summarized in Table 2. A strong relationship clearly existed between flow

t1:1 Table 1 Basic information on theexperimental District Metering Ar-ea (DMA)

t1:2 Item Value

t1:3 Pipe diameter (mm) 75–300

t1:4 Pipe age (years) About 40

t1:5 Total pipe length (km) 7.2

t1:6 Pipe material Cast iron (97.6 %), Polyethylene (2.4 %)

t1:7 Water user types andquantities

4,427 residential properties, 3 schools, 2hospitals, and 1 police office

2012-9-1 2012-10-1 2012-11-1 2012-12-1 2013-1-1 2013-2-1 2013-3-10

10

20

30

40

pre

ssu

re(m

)

date

0

10

20

30

40

50

60

flow

period 3period 2

flo

w (

l/s)

period 1 pressure

Fig. 2 Inlet pressure and flow during the three investigated periods

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115and pressure. In period 1, the average pressure was 38.8 m and flow was relatively high, with116an average value of 31.2 l/s. The average pressure in period 2 was reduced by 3.7 m, resulting117in a decrease in average flow of 8.1 l/s (or 26 %). The average pressure was further reduced by1181.9 m in period 3, resulting in a further reduction in average flow of 6.2 l/s (or 20 %). It should119be noted that average pressure was restored to the original level of 38.8 m for 8 days from120December 15 to 17 and 20 to 24, 2012, to verify the flow response to changes in inlet pressure.121The data from these days was excluded when calculating pressure and flow statistics. Table 2122lists the statistical characteristics of the three periods. Compared with period 1, the reduction in123the inlet pressure for the considered DMA in periods 2 and 3 allowed yearly savings of12435,476 m3 and 62,633 m3 of water per km pipe, respectively.125Although minimal night flow (MNF) consists of normal night use, e.g. toilet flushing, it is126often adopted as an estimation of leakage in cases where no data on night use is available. In127this research, the night water use was not surveyed, thus MNF was directly adopted as an128estimation of leakage. The average MNF in period 1 was highest (14.5 l/s), and a reduction of1297.3 l/s (or 50 %) and 12.1 l/s (or 83 %) occurred in periods 2 and 3, respectively. The leakage130rate dropped from 46.5 % in period 1 to 31.2 % in period 2, and 14.2 % in period 3.

1314 Discussion

1324.1 Inlet Pressure and Corresponding Flow and Leakage

133The data shown in Fig. 2 reveals that a reduction in pressure led to a considerable reduction in134flow. In the first several days of period 2, the flow remained at a relatively high level compared135to the following days. This was attributed to water uptake by boilers for urban heating, which136started in Beijing around November 1, 2012. The flow subsequently decreased until it reached137a lower and stable level. In period 3, a sharp decrease in flow occurred from February 10 to 17,1382013. This period coincided with the Chinese Spring Festival holiday, when approximately139two thirds of Beijing residents were out of town.140To further investigate the effects of pressure regulation, Fig. 3 shows hourly variations in141pressure and flow during a representative 24-h period for each period. The representative 24-h142period was obtained by averaging the measured pressure and flow at the same hour for seven143consecutive days. Any seven consecutive days consist of five workdays and two weekend144days. Hence, averaging seven consecutive days considers differences in water use between145workdays and weekend days. The seven consecutive days for periods 2 and 3 were November

t2:1 Table 2 Inlet pressure and flow statistics during the three investigated periods

t2:2 Period Period 1 Period 2 Period 3

t2:3 Date 01.09.2012–15.10.2012 16.10.2012–22.11.2012 23.11.2012–10.03.2013

t2:4 Duration (days) 45 38 98

t2:5 Pressure (m), mean±S.D.* 38.8±0.41 35.1±1.75 33.2±1.58

t2:6 Flow (l/s), mean±S.D. 31.2±9.37 23.1±7.97 16.9±8.32

t2:7 MNF* (l/s), mean±S.D. 14.5±1.37 7.2±1.05 2.4±1.67

t2:8 Proportion of MNF to flow (%) 46.5 31.2 14.2

t2:9 Water saved compared to period1 (m3/yr/km)

- 35,476 62,633

*S.D. is Standard Deviation and MNF is Minimal Night Flow

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14615 to 21, 2012, and November 23 to 29, 2012, respectively. December 15 to 17 and 20 to 24,1472012 were used to represent period 1 when the pressure was restored to the original level. This148period was chosen because the pipe conditions could be assumed to be the same during the149period from November 15 to December 24, and also the temperature was similar, which might150influence water consumption. Fig. 3 shows that the flow in period 1 was globally higher than151in the other two periods due to higher pressure. Similarly, the flow in period 2 was globally152higher than that in period 3. Daily averaged flow discharges were 23.6 l/s, 18.6 l/s (21 %153reduction compared to period 1) and 16.4 l/s (31 % reduction compared to period 1) in periods1541, 2, and 3, respectively. Comparison of periods 2 and 3 clearly revealed that higher differences155in pressure resulted in higher differences in flow. Specifically, differences in pressure and flow156were high during the night (0:00 am to 5:00 am), but low during peak hours (8:00 am to15712:00 am and 6:00 pm to 8:00 pm) when the pressure was almost identical. These observations158complied with the hypothesis that differences in flow were mainly incurred by differences in159inlet pressure.160Figure 4 shows measured minimal and average (average from 2:00 am to 5:00 am) night flow161and corresponding inlet pressure during the three periods. The MNF was more stable than the162average night flow, which lends further credit to the hypothesis that MNF is a good estimator of163leakage. Therefore, MNF was used hereafter to establish the pressure-leakage relationship.

1644.2 Pressure-Leakage Relationship

165To quantify the relationship between inlet pressure and leakage, the following equation, similar166to Eq. 1, was fitted to the measured data:

L ¼ekPne ð2Þ

167168whereP is the inlet pressure (m), L is the leakage (l/s),ek anden are the parameters to be calibrated.

169In this study, ek and en were calibrated using the MNF and the corresponding inlet pressure.

00:00 06:00 12:00 18:00 24:000

10

20

30

40

pre

ssu

re (

m)

time

P1

P2

P3

0

10

20

30

40

50

60

F1 L1

F2 L2

F3 L3

flo

w &

lea

kag

e (l

/s)

Fig. 3 Hourly inlet pressure (P1, P2 and P3), flow (F1, F2 and F3) and leakage estimated according to calibratedequation (5) (L1, L2 and L3) during a representative 24-h period for each period

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170A relatively short period of data (November 1, 2012 to January 31, 2013) was used for the171calibration instead of the whole series because it can be assumed that the pipe conditions, e.g.172amount of breaks, did not change over a short period. In the dataset, the pressure and flow173characteristics of all three periods were included. Data from December 15 to 17 and from 20 to17424 represented period 1, data from November 1 to 22, 2012 represented period 2, and the175remaining data represented period 3. The calibration was based on the measured MNF and176corresponding inlet pressure, as shown in Fig. 4. This calibration resulted in parameter values

177of ek = 1.51×10−12 and en = 8.02 (Eq. 2). Fig. 5 illustrates the pressure-leakage curve.178The calibrated leakage relationship, Eq. 2, estimated leakage for every inlet pressure. The179estimated leakage for a representative 24-h period in all three periods is included in Fig. 3.180Daily averaged leakages were 8.5 l/s, 4.0 l/s (53 % reduction compared to period 1) and 2.2 l/s181(74 % reduction compared to period 1) in periods 1, 2, and 3, respectively.182In the absence of experimental data, Farley and Trow (2003) proposed adopting an183exponent n = 1 in Eq. 1, meaning that a 10% reduction in the average pressure of the network184will lead to a 10% reduction in leakage. The exponent en = 8.02 in the pressure-leakage185equation (Eq. 2) was much larger than the value of n=1 and also much larger that the186exponents n=0.5 to 2.5 reported for Eq. 1 (Lambert 2001; Thornton and Lambert 2005),

2012-9-1 2012-11-1 2013-1-1 2013-3-10

10

20

30

40period 3period 2

pre

ssure

and f

low

date

pressure when minimal flow happens (m)

minimal night flow (l/s)

average night pressure (m)

average night flow (l/s)

period 1

Fig. 4 Average (from 2:00 am to 5:00 am) and minimal night flow and corresponding inlet pressure during thethree investigated periods

30 32 34 36 38 400

2

4

6

8

10

12

observed data

fitted curve

R2=0.92

leak

age

(l/s

)

pressure (m)

Fig. 5 Calibrated pressure-leakage equation (2)

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187which suggests that leakage was sensitive to pressure management. Direct comparison of en188and n was, however, not meaningful, because fundamentally different pressure variables were189used in Eqs.1 and 2: the network’s average pressure was used in the former and the inlet190pressure in the latter.191In practical applications, water utilities directly regulate inlet pressure to a DMA. Therefore192it is important to determine the relationship between inlet pressure and leakage according to193Eq. 2. This relationship is, however, case dependent and needs to be calibrated for each DMA.194In fact the pressure at the leakage location should be used to calibrate the leakage-pressure195relationship function. The pressure inside the water mains at the leakage location varies196between a maximal value given by inlet pressure P, and a minimal Pmin, which was measured197in the present real-world application (Fig. 1). Fig. 6 shows estimates of n according to Eq. 1 for198values of P= (1-a) P+aPmin where 0≤a ≤1, which corresponds to P in the range between the199inlet pressure and minimal pressure . From Fig. 6, a range between 7.41 and 8.02 was obtained200for n, which decreased linearly as a increased. A reasonable estimation of n was obtained by201adopting the average value 0.5 (P+Pmin) in Eq. 1, which yielded k=5.91 × 10−12 and n=7.73.202It was concluded that leakage was sensitive to pressure management, and that pressure203reduction provided an efficient method to reduce leakage.204For a pipe network with multiple leakage points, the following equation could be used.

L ¼Xi

kiPnii ð3Þ

205206where L is the leakage (l/s), Pi is the pressure at the leakage location i (m), and ki and ni are the207parameters associated with leakage location i. Pi could be much smaller than the inlet pressure208of the pipe network if the leakage occurs in service pipes with high level. Therefore, if a209pressure reduction is implemented at the inlet, the change rate of Pi can be much larger than210that of the inlet pressure P. To a given change rate of leakage, a more sensitive leakage-211pressure relationship will be obtained when using the inlet pressure. In this study, Eq. 2 was212used to approximate Eq. 3, which explained why a big value of parameter n was obtained.213Other possible reasons included the type of leakage and pipe material, as introduced in the214introduction section. However, it is hard to determine the exact reasons because these leaks are215usually undetectable.

0.0 0.2 0.4 0.6 0.8 1.07.2

7.4

7.6

7.8

8.0

8.2

n

a

Fig. 6 Estimates of n depending on adopted average pressure P = (1-a) P+aPmin (P=inlet pressure, Pmin=minimal pressure, 0≤a ≤1) according to equation (4)

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2164.3 Associated Benefits from Pressure Management

217According to Table 2, total flow reduction by decreasing pressure from period 1 to period 3 was21814.3 l/s, of which leakage reduction (indicated by MNF) was 12.1 l/s. The reduction in leakage219accounted for 85%, while the reduction in water use by residents accounted for only 15%, which220was comparatively negligible. It also indicated that pressure management would not significantly221affect normal water use of the residents. The 2.2 l/s water use reduction was not included in the222further analyses, thus the estimations of energy saving hereafter were in fact conservative.223The reduction in leakage and water use was accompanied by savings in energy consump-224tion and greenhouse gas emissions. Stokes and Horvath (2009) reported that 18 MJ of energy225was needed to treat and distribute 1 m3 of imported water, and associated CO2 emissions were2261.093 kg. Because Beijing will use imported water as a source of drinking water from 2014,227the two above figures were adopted in the present study for estimating energy savings and CO2

228equivalent greenhouse gas emission reduction associated with the proposed pressure manage-229ment. In this study, 62,633 m3 of water was saved every year for every km pipe by adopting230the pressure reduction of period 3, which corresponded to 1.1×106 MJ of energy and 68 t of231CO2 equivalent greenhouse gas emission.

2324.4 Potential of Further Reductions in Leakage, Energy Consumption and Greenhouse gas233Emissions

234As introduced in section 2.2, a minimal pressure of 18 m has to be guaranteed at all instances.235According to pressure monitoring, however, the actual average pressure at the minimal236pressure point (triangle in Fig. 1) was 35.2 m, 31.2 m, and 29.5 m in the three periods237respectively. This implied there was still large potential to further reduce the inlet pressure.238Supposing pressure was reduced by another 10 m, according to Eq. 2 the minimal night flow239would have dropped to 0.1 l/s and approximately 9,900 m3 of water per year per km pipe240would have been saved, corresponding to 1.8×105 MJ of energy and 10.8 t of CO2 equivalent241greenhouse gas emissions. Unfortunately, the water supply company declined to further reduce242the pressure after considering the customer satisfactory and firefighting requirement.243In many cases, water pressure is regulated by pressure reduction valves (PRVs). The system244pressure and consequently leakage can be well controlled through this method. However, the245mechanism of this method is that local energy loss is provoked at the PRV, implying that246energy for pumping water is not really saved. Therefore, there is a potential to reduce energy247used in water distribution networks by lowering redundant water pressure at the pumping248station. By combining PRVs and pumping regulation, a two-level water pressure management249scheme can be outlined, especially for large water distribution network with multiple water250plants. The first level is large-zone pressure management by regulating the pumps, and the251second level is pressure reduction at the inlet of DMAs using PRVs. Figure 7 illustrates this252two-level pressure management strategy. If the water pressure of the whole pipe network is too253high, the pressure should be first reduced at the pumping station. Then if there are still some254areas having high water pressure because of other reasons, e.g. low ground elevation, further255pressure reduction at DMA level should be considered. It must be realized that water pressure256management for water distribution pipe network is very complex, thus the present sptio-257temporal distribution of water pressure, which is influenced by water plants locations, urban258topography, characteristics of water use and etc., should firstly be investigated. Based on the259results, careful calculations should be made to compare different scenarios so as to obtain an260optimized cost-effective management. The optimized pressure management strategy is case261dependent, and there does not exist a strategy that suits for all pipe networks.

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262Although the results obtained for this DMA cannot be directly extrapolated to the entire city263of Beijing, the benefits of the pressure management would likely be large if the proposed264strategy was implemented. For a city like Beijing, whose total water supply is about 2.5265million m3 per day, even a 1 % reduction in leakage would result in 9.1 million m3 of water266saving per year and 1.6×108 MJ of energy and 9.9×103 t of CO2 equivalent greenhouse gas267emission. These values would make a relevant global contribution to the sustainable manage-268ment of water resources.

2695 Conclusions

270This study investigated the possibility and efficiency of regulating water pressure in a water271distribution network in order to reduce leakage, as well as associated energy consumption and272greenhouse gas emissions. A large-scale real-world experiment was conducted in a DMA of a273water distribution network of Beijing, China. We found that flow was considerably more274sensitive to pressure than expected. By analyzing minimal night flow, a pressure-leakage275relationship was established, which improved knowledge on water leakage behavior. In the276experimental DMA, average flow decreased from 31.2 l/s to 16.9 l/s (or 46 %) after pressure277management. Reduction in leakage and water use contributed 12.1 l/s and 2.2 l/s, respectively,278to this total flow reduction of 14.3 l/s. The corresponding savings per year and per km pipe279were 62,633 m3 of water, and 1.1×106 MJ of energy and 68 t of CO2 equivalent greenhouse280gas emissions. These numbers could be even larger if a more complicated pressure manage-281ment method, e.g. combining pump regulation and PRV control, was applied. These results282should be persuasive for decision makers to recognize the importance and benefits of283managing water pressure in water pipe networks.284The paper investigated the response of water leakage as well the associated energy285consumption and greenhouse gas emissions to the water pressure reduction of distribution286system. However, more studies are requested when optimize the water pressure management287for practical implementation. First, the energy consumption and greenhouse gas emissions288should be estimated for the pilot pipe network based on the lifetime cycle analysis of the water289supplied. Second, other factors should be explicitly considered in the formulation of a water290pressure reduction scheme, such as the potential of water discoloration and increased mineral291build-up in pipelines due to the reduced water velocity, the possibility of failures of the city’s

pump station

PRV

pipe

DMA boundary

1st level:

pump regulation

2nd level:

PRVs control

ENERGY SAVING

Fig. 7 Two-level pressure management strategy

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292heating system due to reduced water pressure, etc. All these aspects have not yet included in293the current work, and will be the focus of our future studies.

294Acknowledgments The authors are grateful for funding from the Ministry of Sciences and Technology of the295People’s Republic of China (No. 2012ZX07408-002) and National Natural Science Foundation of China296(No.51309216). Blanckaert was partially funded by the Chinese Academy of Sciences Visiting Professorship297for Senior International Scientists (No. 2011T2Z24). Appreciations are extended to the anonymous reviewers298whose comments are of great value to improve the quality of this manuscript.299

300

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