Water losses’ assessment in an urban water network Dídia I. C. Covas, Ana Cláudia Jacob, Helena M. Ramos Civil Engrg. Dept., Instituto Superior Técnico, Technical University of (TULisbon), Av. Rovisco Pais, 1049-001 Lisbon, . E-mail: [email protected], [email protected]

Abstract: This paper presents the assessment of real and apparent losses in a District Metering Area of a Portuguese water utility based on the analysis of collected minimum night flow data and extended period simulations of the system. The DMA covers a 0.7 km2 area, is predominantly domestic consumption, with 6200 inhabitants and a large non-domestic consumer; it is a temporarily DMA, isolated by closing ten boundary valves. It has 9.4 km of pipes with diameter from 50 to 300 mm, 589 service connections and 3400 billed consumers. Flow and pressure data have been collected at the DMA input section, during a leak detection survey carried out during an eight-weak period. A brief description of the leak detection survey is presented. Water losses have been assessed before and after the leakage detection survey by means of a bottom-up approach (a six-step procedure) based on minimum night flow analysis and dynamic hydraulic simulation of the system. Minimum night flow data, between 2:00 and 4:00, were used for estimating real losses. Daily leakage pattern has been estimated by means of hydraulic simulations of the system using EPANET. The analysis has shown that the leak detection survey reduced real losses in 27%, which corresponds to an annual water volume of 130 000 m3 (despite the seasonal demand variation of 22%) and apparent losses and unbilled authorised consumption, even after the survey, still represent 33% of total water volume.

Keywords: Water losses; leakage; network; simulation; minimum night flow.

INTRODUCTION Changing climatic conditions and high temperatures have led to shortages and water restrictions in many countries, simultaneously, with the increase of domestic and industrial demand, in the last twenty years; consequently, leakage reduction and control has become a high priority to water utilities and to the regulators. Every water distribution systems have leaks and ruptures as a result of high operating pressures, inadequate design, construction and operation, life cycle of pipes and infra-structures. Water losses may vary between 10 to 40% of the total water volume distributed, in developed countries, which can be of great economic importance. According to a study performed by 31 water distribution companies in the United Kingdom, almost 50% of water is unmeasured but consumed, 25% measured and consumed, and almost 23% is lost (WRC, 1994). Water losses have several associated costs: the direct costs of water lost, the cost of interrupting the supply and the cost of repairing the system, and the costs to the society associated to the interruption of supply (WRC, 1985; 1994; Lambert et al., 1998; Farley and Trow, 2003; Ferreira et al., 2006). Water input into the system has two main components – authorised consumption and water losses (Alegre et al., 2000). Water losses are the difference between the system input volume and authorised consumption (measured or estimated). Losses have two components (Alegre et al., 2000; Farley and Trow, 2003): real or physical losses that correspond to leaks and ruptures in transmission or distribution mains, storage tanks and service connections until the consumer meter, and apparent losses associated with customer and input metering inaccuracies (errors) and unaccounted for consumption. Real losses include leaks and ruptures. Leakage is water that is lost (undetected) continuously in the system due to the lack of tightness of pipe junctions, valves and other fittings and due to small cracks in pipes, and that is never used by the consumers. Flow rate associated with each leak is usually quite small, therefore leaks are not easily detected. Bursts and ruptures refer to sudden accidental bursts in pipes and fitting. Real losses depend greatly on normal operating pressures, burst frequencies, infra-structure age, construction processes, and rehabilitation strategies. Apparent losses include measurement errors (flow-meters), illegal connections and uncounted for uses (e.g., irrigation, street washing and fire fighting). These can be minimised by using more accurate measurement equipment, installing meters at uncounted for consumption sites (e.g., irrigated green spaces, council consumption) and regularly inspecting the system looking for illegal connections.

Water Practice & Technology Vol 3 No 3 © IWA Publishing 2008 doi: 10.2166/WPT.2008061

This paper presents a methodology to carry out a bottom-up analysis for assessing water losses based on the analysis of minimum night flows as presented in Report F of WRC (1994) and the hydraulic simulation of the system by using EPANET. The proposed methodology is applied to a district metering area (DMA), of Lisbon water distribution system, namely as DMA320, using flow and pressure collected data during a leak detection survey carried during an eight week period. Water losses were assessed before and after the survey and conclusions are drawn concerning the benefit of the leak detection survey.

CASE STUDY The water distribution system of Lisbon belongs to the water utility EPAL, S.A. (Empresa Portuguesa das Águas Livres, S.A.); the system has 1400 km of pipes, supplying directly a population of 700 000 inhabitants and conveying water to boundary Lisbon boroughs. DMA320 is one of the 128 district metering areas of Lisbon water distribution system, located in the high zone of the network (with elevations between 60-90 m). DMA320 covers a 0.7 km2 area in the council of S. Domingos de (Figure 1a), predominantly residential (mainly, domestic consumption), with approximately 6200 inhabitants and a large non-domestic consumer - the – that represents one- third of total billed consumption. DMA320 has been temporarily isolated by closing ten boundary valves. It has 9.4 km of pipes made of asbestos cement, cast and ductile iron and polyethylene, diameters from 50 to 300 mm, 589 service connections and 3400 consumers. The train line divides the council (and DMA320) in two main areas with urban characteristics completely different: the north zone (above the train line) and the south zone (below the train line). North zone covers 65% of the area, being 33% of the area occupied by the Lisbon Zoo; however, this zone is the most populated with 94% of the resident population, being, thus, a highly occupied urban area (Figure 1b). South Zone has buildings from the XX century, mainly non-residential, a College, a Church, a Palace and a large green area (Monsanto Park); there are no commercial areas in the zone (Figure 1c). (a) Campo Grande

North Zone N. S. de Fátima South Zone

Benfica

Boundaries of S. Domingos de Benfica Limit of DMA 320 Train line (b) (c)

Figure 1. (a) Map of S. Domingos de Benfica DMA320. Photos of (b) North Zone and (c) South Zone

2 LEAK DETECTION SURVEY Most DMAs in Lisbon water distribution system are temporary, created by the closure of valves during the period of the survey. Typically, a leak detection survey has duration of three weeks and overlaps in the first and in the last week with two other surveys; thus, there are approximately 50 surveys per year and each DMA is checked every three years. The first week is used for the preliminary works: closure of valves, installation of measurement equipment and installation of leak noise detectors. A digital flow meter and pressure transducer are installed at the input section of the DMA, and connected to a data logger (Figure 2a). The two following weeks are used for the leak detection and location. Maximum night pressures and minimum flows are monitored to continuously assess the progress of the survey and estimate leakage reduction. Leak pre-location is done by using an acoustic leak detection system, composed of a number of acoustic noise loggers and a leak seeker (Figure 3). Acoustic noise loggers are installed at available pipe- fittings (fire hydrants, valves and scours), spread all over the DMA. Every day, the survey team drives along all installed loggers with a leak seeker that reads minimum noise registered during the last 24 h in each installed logger. The seeker provides on-site information of the leakage situation (leak or no-leak) in each logger. Comparison of recorded noise levels between loggers provides information about which loggers are located closest to the leaks. Once identified the area of the DMA with a leak, other leak locations techniques are necessary to pinpoint the accurate position of the leak. Usually leaks are located in valves or fire hydrants. Examples of two equipments used are the leak noise correlator, the acoustic stethoscope, the listening stick and the ground microphone (Figure 3).

Figure 2. (a) Pressure and flow meters installed and datalogger. (b) Acoustic leak detection system

Figure 3. Leak listening system: acoustic correlator, stethoscope, listening stick and ground microphone DATA COLLECTION Flow and pressure data have been collected in the DMA320 input section, during an atypical survey eight- week measurement survey carried out during from 13th October to 13th December 2004; this was because the DMA was known to have a high volume of non-revenue water as high as billed consumption. Data were collected every 2 minutes (i.e., with a frequency of 30 measurements per hour) – see data collected in the first week in Figure 4a. A flow meter was installed at the inlet of the largest consumer of the DMA (the Lisbon Zoo) during the fifth week. This consumer showed a high variation of daily consumption with two peak flows at 9:30 a.m. and 3:30 p.m., and other random extremely high peak flows, and a constant night consumption.

3

Flow (l/s) Pressure Flow (l/s) Pressure 360 41 360 42 330 330 39 40 300 300 270 37 270 38 240 35 240 36 210 210 33 34 180 180 150 31 150 32

120 29 120 30 90 90 27 28 60 60 18/09/04 19/09/04 20/09/04 21/09/04 22/09/04 23/09/04 24/09/04 25/09/04 23/10/04 24/10/04 25/10/04 26/10/04 27/10/04 28/10/04 29/10/04 30/10/04

Figure 4. Data collected during the first and sixth week of the survey (“blue-line”–flow; “red-line”–pressure)

Statistical tests have been carried out for organizing flow measurements in classes. These were divided in three groups according to the pattern of flow profile: “working days”, “Saturdays” and “Sundays and holidays”. These groups are important for carrying out hydraulic simulations. Data from the first and eighth week of the survey were used for water losses assessment. Collected data have shown two night flow unbilled uses. The first is the use of fire hydrants to fill water tank trucks for street washing. This is typified by local flow peaks occurring at 0:45 am, 2:25 am and 4:45 am (Figure 5a), being the two hours interval between these peaks the time taken to empty the tank and to fill it again. The second is the use of fire hydrants to continuously wash the streets and irrigate green spaces (connecting directly hosepipes to the hydrants). This is characterised by constants flows with local flow drops associated to the time to close that hydrant to connect to another one (Figure 5b). (a) 360 Detail (a) 340 EFilnchliminegn wtoa dtee r 320 tatnaknq trueuscks 300 280 260 240 220 200 180 160 140 120 Public holiday 100 80 60 40 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 st nd rd th Time (h) th th th th 1 week 2 week 3 week 4 week 5 week 6 week 7 week 8 week

360 (b) 340 320 CUosnto icnouontínuous 300 usdee hi odf rfairnete s 280 hydrants 260 240 220 200 180 160 140 120 100 80 60 40 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Time (h) Saturday Sunday Monday Tuesday Wednesday Thursday Friday

Figure 5. (a) Average flow data every 10 minutes (m3/h) on Mondays during the eight-week survey: typical night filling water tanks. (b) Average flow data every 10 minutes (m3/h) in the fifth week: (a) continuous use of fire hydrants.

THE BOTTOM-UP APPROACH Water losses have been assessed before and after the leakage detection survey by two different approaches. The first was the top-down annual water balance as presented by IWA (Alegre et al., 2000; Farley and Trow, 2003), and the second was the bottom-up approach based on minimum night flow analysis and the extended-period simulation of the system; however, only the latter is presented herein. Minimum night flow data were used for estimating real water losses (leakage) based on several assumptions (WRC, 1994);

4 although WRC (1994) publication has 15 years there is no other published work based on experimental data (ideally with Portuguese data), that the current work could use for minimum night flow analysis. Leakage and apparent losses during the day have been estimated by means of hydraulic simulations of the system using collected flow and pressure data. EPANET was used to carry out the extended period simulations. The bottom-up approach followed can be summarised in a six-step procedure, as presented in Figure 6. Input data Output results Step I Components of MNF Components of average MNF

(pç) (antes das reparaõçes) Estimation of real losses, apparent 180 180 160 160 Caudal Mínimo Nocturno 140 140 Médio - CMNM (107 m³/h)

losses, authorised unbilled 120 Caudal Mínimo Nocturno 120

) Absoluto - CMNA (83.2 m³/h) ) /h 3 100 /h 3 m 100 Consumo Autorizado m ( l

( não Facturado (23.9 m³/h) 80 l Caudal Mínimo Nocturno uda Uso excepcional (16.7 m³/h) Caudal Base Nocturno 80 uda Absoluto - CMNA (83.2 m³/h) consumption and billed consumption Ca (25.5 m³/h) a

Uso normal (6.7 m³/h) C Consumo Facturado (21 m³/h) 60 Perdas não detectáveis (2.1 m³/h) 60 40 Perdas Aparentes (4 m³/h) during the minimum night flow Roturas e outras perdas não estimadas (57.7 m³/h) 40 20 Perdas Reais (58.1 m³/h) 20 0 01234567 0 period. Tempo (h) 01234567 Tempo (h)

81 80 Nod22 al demands 79 82 78 77 23 17 89 83 155 16 15 24 88 76 75 84 14 156 74 90 13 12 93 71 19 86 85 94 20 151 73 87 91 95 72 70 11 21 69 10 144 152 Step II 157 154 9 158 160 68 8 7 145 92 153 161 96 159 6 18 142 143 97 100 25 5 4 28 3 27 26 63 64 146 1 (RNF) 29 67 62 98 99 30 66 138 33 59 147 60 65 140 136 101 31 58 137 103 34 148 141 132 37 57 Simulation the hydraulic behaviour of 139 135 102 56 131 32 61 134 50 51 130 36 35 149 133 38 49 104 39 48 129 40 105 150 123 119 46 52 55 300 122 47 54 121 120 44 106 53 Flow pattern 280 41 45 43 the system based on flow 42 260 108 107 EPANET 125 C1 118 240 127 124 109 126 110 220 200 128 117 1.8

111 ) 116 180 /h

112 3

113 48 ) 1 114 m 8

- 160 1. 4 ( ( 3 115 1.5 l 1. measurements at the input section of 1. 140 o 26 25 uda 22 1. a 19 1. m 16 120 0 1. C 1. u 1 10 1.2 1. s 1. 9 03 1. 100 00 n 9 4 3 1. 95 94 9 o 1. 0. 9 0.

0. 80 0. 87 0. 85 C 0.

0.9 0. e 60 68 62 0. e d 6 40 t 5

the DMA (C1), spatial distribution of 56 0. 55 n 0. 0. 0.6 0. 20 e i

c 0 K = 0 i 0123456789101112131415161718192021222324 fi ef 0.3 o Tempo (h) C 0.0 1 2 3 4 5 6 7 8 9 0 1 2 3 4

consumers and without leakage. 1 2 3 4 5 6 7 8 9 10 1 1 1 1 1 1 1 1 1 2 2 2 2 2 0 - 1 - 2 - 3 - 4 - 5 - 6 - 7 - 8 ------9 - 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Intervalo de Tempo (h)

Step III Calculation by: Q RL ( Step _ I ) Calculation of leak coefficient “c” c = ⎛ M i ⎞ ⎜ p 1 .18 0 .5 ⋅ L ⎟ ∑∑⎜ i ji ⎟ i ⎝ j =1 ⎠

81 80 81 80 22 Effective nodal Nodal demands 79 22 82 78 77 23 7978 17 82 77 23 89 17 83 155 16 15 24 88 7675 83 89 24 14 demands not 155 16 including leakage 84 Step IV 15 88 76 75 156 74 14 90 13 12 84 93 71 19 156 74 13 86 90 93 71 12 85 94 20 19 95 151 73 11 21 86 87 91 72 70 85 94 20 10 151 73 incl69 uding leakage 95 70 11 21 144 152 87 91 72 157 154 9 69 10 158 144 157 152 9 EPANET 160 68 8 7 154 145 158 68 160 8 7 92 153 145 161 96 159 18 92 153 6 Calibration of flow pattern and nodal 161 96 159 18 142 143 97 100 25 5 4 6 28 3 100 25 4 + 27 26 63 146 1 (RNF) 142 143 97 5 64 28 29 67 62 3 98 99 30 66 27 26 63 64 146 1 (RNF) 138 59 147 60 65 67 62 140 136 33 98 99 30 29 101 31 58 59 60 65 66 137 103 34 148 138 136 33 147 141 132 37 57 140 101 31 58 139 135 102 56 137 103 34 148 Iterations 131 32 61 134 51 141 139 132 102 37 57 56 50 135 131 130 36 35 149 134 32 51 61 38 demands associated with authorised 50 133 39 49 130 36 35 104 48 149 40 133 38 49 129 150 104 39 48 105 40 123 119 52 129 150 122 46 55 105 47 54 123 119 121 120 44 46 52 55 106 53 122 47 54 41 43 121 120 44 45 106 41 53 42 45 43 108 Flow Pattern 125 107 42 118 108 127 124 109 billed consumption by an iterative 125 107 118 126 110 127 124 109 126 110 128 117 Flow pattern 111 117 (initial) 116 128 112 111 113 116 1.8 114 113 112 115 114

115 48 1 300 8 1.

4 (calibrated) (-) 3 1.5

1. 2.1

procedure 1. 280 o 26 25 22 1. 19 1.

16 260 1. 0 ) 1. 70 um 10 1 1.

1.2 - 1.8 s 1. ( 9 1. 5 03 60 1. C1 240 00 5 9 4 3 1. 1. 95 94 o 9 1. 0. 9 1. 9 0.

0. 220 87 0. 0. 3 85 37

M Con 1.5 0. 32 1. 0.

0.9 um i 1.

200 27 s 23 1. 1. 68 de ) n 1. 15 14 62 0. e 6 180 5 /h o 1. 1. 3 5

56 0 55 0. 1.2 nt 00 99 m 0. 0. 0. 0.6 1.

160 C e 93 ( 1. 91 91 0. 89 l i e 0. 0. 0. c 6 0. 140 81 K = c ⋅ 0.5 ⋅ L i d 0.9 7 f fi ji 0. e

∑ 0. e 120 0.3 Cauda nt e 52

Co 100 i 45

0.6 0.

j=1 c i 0. 36 35 80 34 f 0. 0.

0.0 0. e 1 2 3 4 5 6 7 8 9 0 1 2 3 4

60 o 1 2 3 4 5 6 7 8 9 0.3 1 1 1 1 1 1 1 1 1 2 2 2 2 2 10 C 0 - 1 - 2 - 3 - 4 - 5 - 6 - 7 - 8 ------40 9 - 10 11 12 13 14 15 16 17 18 19 20 21 22 23 20 0.0 0

Intervalo de Tempo (h) 1 2 3 4 5 6 7 8 9

0 1 11 12 13 14 15 16 17 18 19 20 21 22 23 24

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 0 - 1 - 2 - 3 - 4 - 5 - 6 - 7 - 8 ------9 - Tempo (h) 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Intervalo de Tempo (h)

81 80 Effective nodal 22 79 82 78 77 23 17 89 83 155 16 15 24 demands 88 76 75 84 14 156 74 90 13 12 93 71 19 86 20 Step V 85 94 73 151 87 91 95 72 70 11 21 69 10 144 157 152 9 158 154 160 68 8 7 145 92 153 161 96 159 6 18 142 143 97 100 25 5 4 28 3 27 26 63 146 1 (RNF) 67 62 64 98 99 30 29 Calculation of daily water 59 60 65 66 138 33 147 140 136 101 31 58 137 103 34 148 141 132 37 57 139 135 102 56 131 32 61 134 50 51 130 36 35 149 133 38 49 104 39 48 129 40 105 150 300 123 119 52 consumption without leakage 122 46 55 47 Flow pattern 280 54 121 120 44 106 41 53 45 43 260 42 108 240 C1 125 107 118 220 127 124 109 (calibrated) EPANET 126 110 2.1 200

128 117 ) 180 /h (authorised consumption + apparent 111 3 ) 116 70 m

112 - 1.8 160 1. 113 ( ( 5 60 l

114 5 C2 1.

115 o 140 1. 9 uda a 3 1.5 37 120 C 32 1. um 1. 27 s 23 1.

1. 100 n 1. 15 14 5 o 1. 1. 1.2 0 80

00 99 1. C 93 1. 91 91 0. 89 e 60 0. 0. 0. 6 losses) and daily leakage flows 0. 81 d 0.9 7 0. 40 e 0.

nt 20 e 52

i C3 45

0.6 0.

c 0 i 0. 36 35 34

f 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 0. 0. 0. e

K 0 o = Tempo (h) 0.3

fi C

0.0 0 1 2 3 4 5 6 7 8 9 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1

0 - 1 - 2 - 3 - 4 - 5 - 6 - 7 - 8 ------9 - 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Intervalo de Tempo (h)

Flow pattern Billed consumption Billed flow pattern (calibrated) (calibrated) during MNF 2.1

2.1 (antes das reparaõçes) 8 180 7 ) 1. 66

- 1.8 61 ( 1. ) 70 1.

- 1.8 o 1. ( 60 5 160 43 41 5 1.

0 o 1. 1.5 35 1. 1. 3 9 um

Caudal Mínimo Nocturno 1. 26 3 s 37 1. 1.5 140 6 1. 32 1. 16 n um Médio - CMNM (107 m³/h) 1 1. 27 s 1. 23 o 1. 1. 1.

05 1.2 n Step VI 1. 15 14 00 99 2 1. 5 0 0 o C

1. 120 1. 9 1. 0 9 9 1.2 0. e 88 00 99 0. ) 1. 0. 0. C 0. 93 79 1. 0. 91 91 d /h 89

e 0.9 74 3 0. Consumo Autorizado 0. e 0. 0. 0. 6

81 100 0. m d 0.9 7 0. ( não Facturado (23.9 m³/h) nt e l 0.

Caudal Mínimo Nocturno e i 47

nt 0.6 9

80 c uda Absoluto - CMNA (83.2 m³/h) 0. 3 e 52 i a i f 45 0. 0.6 0.

C Consumo Facturado (21 m³/h) 29 28 c 27 e i 0. 36 35 34 0. 0. 0. f 60 o

0. 0.3 0. 0. e

Perdas Aparentes (4 m³/h) C o 0.3

Calculation of daily billed C 40 0.0 Perdas Reais (58.1 m³/h) 0 1 2 3 4 5 6 7 8 9 1 0.0 11 12 13 14 15 16 17 18 19 20 21 22 23 24

20 ------0 - 1 - 2 - 3 - 4 - 5 - 6 - 7 - 8 - 0 1 2 3 4 5 6 7 8 9 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 9 -

10 11 12 13 14 15 16 17 18 19 20 21 22 23 ------0 - 1 - 2 - 3 - 4 - 5 - 6 - 7 - 8 - 9 -

10 11 12 13 14 15 16 17 18 19 20 21 22 23 0 01234567 Intervalo de Tempo (h) Intervalo de Tempo (h) (pç) consumption and of daily apparent Tempo (h) 300 280 260 240 C1 220 losses plus authorised unbilled 200 ) 180 /h 3

m 160 ( l

a C2 140 d u 120 X − X = A ⋅ X − X Ca C4 i( corrigido ) i ( i ) 100 consumption. 80 60 C5 40 20 C3 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Tempo (h)

Figure 6. Bottom-up approach for assessing daily water losses

ASSESSMENT OF WATER LOSSES: FIRST WEEK OF THE LEAK SURVEY The application of the bottom-up approach to DMA 320 during the first week of leak detection survey (from 20th to 24th of September 2004), before repairs, will be presented herein.

Analysis of minimum night flow data (Step I) Minimum night flow data was analysed based on a methodology presented in Report F – Using Night Flow Data (WRC, 1994). This report is the result of practical experience of a group of water utilities in the United Kingdom. Demand components and reference values presented may not be the most appropriate to the Portuguese case study. The methodology consists of the detailed analysis of background minimum night

5 flow, that includes all demands except detectable leaks and ruptures and can be divided in the diferent components. DMA320 infrastructure is rather old (40-50 years), being the corresponding background losses 60 l/km/hr in distribution mains and 4 l/property/hr in services. Average night zone pressure is 29 m. Based on reference values proposed in WRC (1994) and DMA local characteristics (e.g., number of households, length of mains and services), components of background minimum night flow were estimated (Table 1). Table 1. Estimation of background minimum night flows in DMA 320 (first week of leak detection survey)

Reference values DMA320 Components DMA320 flow rates (WRC, 1994) characteristics Exceptional customer night use - 15 000 l/h 16.7 m³/h 23.4 Household 1.7 l/ household /h 3071 households Normal night use 6.7 m³/h m³/h Non-household 8 l/non- household /h 95 non-household Background losses (pressure Mains 60 l/km/h 9.33 km 2.1 2.1 m³/h correction factor = 0.51) Services 6 l/services/h 589 services m³/h Background minimum night flow 25.5 m³/h There are two different minimum night flows: (i) average minimum night flow obtained based on average flow pattern defined every 10 min for the first week (107.0 m³/h) and (ii) absolute minimum night flow which is the lowest value verified during the same period (83.2 m³/h) – see Figure 7a. Flow rate associated with ruptures and detectable leaks are obtained by the difference between the referred two minimum night flows (57.7 m3/s). Components of average minimum night flow have to be rearranged in order to calculate different components of average minimum night flow (water balance) (Figure 7b). (a) 180

160

140 Absolute minimum night

) 120 flow (83.2 m³/h) h / 100 te (m3 a

r 80

w Exceptional customer night usel (16.7 m³/h) Background minimum o Normal night use (6.7 m³/h) Fl 60 night flow (25.5 m³/h) Undetectable leaks (2.1 m³/h) 40 Ruptures and detectable leaks (57.7 m³/h) 20

0 01234567 Time (h)

(b) 180

160

140 Average minimum night flow (107 m³/h)

) 120 3/h

m 100 Authorised unbilled consumption al ( 80 Absolute minimum night

ud flow (83.2 m³/h) a Billed consumption (21 m³/h) C 60 Apparent losses (4 m³/h) 40

20 Real losses (58.1 m³/h)

0 0123Tempo (h) 4567 Figure 7. (a) Components of absolute minimum night flow in DMA 320. (b) Components of average minimum night flow in DMA 320 (first week of leak detection survey)

6 Extended period simulations of the system (Steps II-VI) DMA320 was modelled by means of the hydraulic simulator EPANET. The topology of the system system is composed of 161 nodes connected by 183 pipes (Figure 8a). There is a storage tank at the upstream with an average water level and a level pattern according to pressure data. Billed authorised consumption has been organised based on a customer database with monthly metered or estimated consumptions. The overlap of this data base with the DMA location allowed the spatial distribution of demands through the nodes as a percentage of total demand. After the analysis of minimum night flows, Steps II to VI of the bottom-up approach were carried out. In Step II, average input volume was 195.2 m³/h. In Step III, leak coefficient was estimated in c=3.2E-5 l/s/m/m1,18, considering real losses during the minimum night flow estimated in Step I (58.1 m³/h). Obtained results are presented in Figure 8b.

81 80 22 7978 (a) 82 77 23 17 83 89 155 16 15 24 88 7675 84 14 156 74 90 13 12 93 71 19 86 85 94 20 151 73 87 91 95 72 70 11 21 69 10 144 152 157 154 9 158 160 68 8 7 145 92 153 96 161 18 159 6 142 143 97 100 25 5 4 28 3 27 26 63 146 1 (RNF) 67 62 64 99 29 98 30 59 66 138 33 147 60 65 140 136 101 31 58 137 103 34 148 141 132 37 57 139 135 102 56 131 32 61 134 50 51 130 36 35 149 133 38 49 104 39 48 129 40 105 150 123 119 46 52 55 122 47 54 121 120 44 106 41 53 45 43 42 108 107 125 118 127 124 109 126 110 117 128 111 116 113 112 114 115 (b) 300 Input volume 250 Apparent losses + authorised

) h / 200 unbilled consumption + billed 3 consumption

(m Real losses

te 150 a

r w o

l 100 Billed consumption F

50 Apparent losses + Authorised unbilled consumption 0 0 2 4 6 8 1012141618202224 Figure 8. (a) Topology of DMA320 as used in EPANET. (b) Daily water balance components (first week).

ASSESSMENT OF WATER LOSSES: EIGHTH WEEK OF THE LEAK SURVEY Night flow data in the last week were analysed. Average night pressure was 35 m and the respective correction factor was 0,64. Table 2 and Figure 9 depict the results of background minimum night flows, where as Table 3 presents the components of average night flow Table 2. Estimation of background minimum night flows in DMA 320 (8th week of leak detection survey)

Reference values Components DMA320 characteristics DMA320 flow rates (WRC, 1994) Exceptional customer night use - 15 000 l/h 13.1 m³/h 18.3 Household 1.7 l/ household /h 3071 households Normal night use 5.2 m³/h m³/h Non-household 8 l/non- household /h 95 non-household Background losses 9.33 km Mains 60 l/km/h 2.6 (pressure correction factor 2.6 m³/h 589 services m³/h = 0.64) Services 6 l/services/h Background minimum night flow 21.0 m³/h

7 After the analysis of minimum night flows, Steps II to VI of the bottom-up approach were carried out. Leak coefficient was c=1.8E-5 l/s/m/m1,18.

(a) (b) 120 250 Input volume 100 Average minimum night 200 flow (72.6 m³/h) Apparent losses + authorised 80 unbilled consumption + billed Flow 150 consumption () Real losses 60 rate Absolute minimum night 3 flow (60.6 m³/h) Billed consumption (16.5 m³/h) 100 (m /h) Authorised unbilled 40 Apparent losses (3.1 m³/h) consumption (12.1 m³/h) Billed consumption Real losses (40.9 m³/h) 50 20 Apparent losses + Authorised unbilled consumption 0 0 012345670 2 4 6 8 1012141618202224 TTemimep o( (h)h) Figure 9. (a) Components of average minimum night flow in DMA 320 (8th week of leak detection survey). (b) Daily water balance components (8th week).

Table 3 presents the comparison of different water balance components obtained by bottom- up analysis before and after the leak detection survey. The analysis of these figures shows that: (i) The decrease of billed consumption in 22% is caused by the seasonal variation of demand from September to November: monthly load factor decreased from 1.114 to 0.874 (i.e., 22%) according to billed consumption. (ii) The reduction of real losses in 27% is essentially due to the leak repairs carried out in pipe-fittings and valves during the eight-week survey. Considering that real losses vary linearly with pressure (Eq. 2) and pressure increased 15% from the 1st to the 8th week, the effective reduction of real losses was even higher (42%). (iii) The decrease of apparent losses plus authorised unbilled consumption is due to two reasons: the reduction of authorised unbilled consumption in the last week due to the inspection of all service connections during the survey (which could be seen in minimum night flow data), and the decrease of apparent losses due to the seasonal variation of demand (as these losses are directly related with water uses. Table 3. Average water balance components in the first and last week of the leak detection survey

1st week 8th week Variation from Average flow rates Input th Flow Input volume Flow 1st to 8 week volume Input volume 195,2 m³/h 100 % 151,3 m³/h 100 % - 23% Billed consumption 77,7 m³/h 40 % 60,9 m³/h 40 % - 22% Real losses 53,0 m³/h 27 % 38,5 m³/h 26 % - 27% Apparent losses + Authorised 64,6 m³/h 33 % 51,8 m³/h 34 % - 20% unbilled cons.

SUMMARY AND CONCLUSIONS Water losses have been assessed in a DMA of Lisbon water distribution system by bottom-up calculations based on the analysis of minimum night flow data and the extended period simulation of the system. The DMA was temporarily isolated by closing ten boundary valves; the network sector has 9.4 km of pipes made of different materials, aging more than 50 years, with diameters from 50 to 300 mm, 589 service connections and 3400 billed consumers. Pressure and flow data have been collected during a eight-week leak detection survey with an acquisition frequency of 30 measurements per hour. A brief description of the leak detection survey was presented. The bottom- up approach is described in detail and applied to the first and last week of leak detection survey, that is before and after repair works have been carried out in the system and illegal service connected have been inspected. The balance of the survey was very positive as it reduced real losses in approximately 40% which represents a pay-back of 63 500 €/year.

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ACKNOWLEDGMENTS The authors wish to acknowledge the financial support of this research work to the Portuguese foundation for science and technology (FCT) for grants reference PTDC/ECM/65731/2006 and PTDC/ECM/64821/2006.

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