- Email: [email protected]
Ranking pipes in water supply systems based on potential to cause discolored water complaints
Accepted Manuscript Title: Ranking Pipes in Water Supply Systems Based on Potential to Cause Discoloured Water Complaints Author: Najah Kadhim Al-Bedyry Arumugam Sathasivan Afrah Jaber Al-Ithari PII: DOI: Reference:
S0957-5820(16)30155-0 http://dx.doi.org/doi:10.1016/j.psep.2016.08.002 PSEP 843
To appear in:
Process Safety and Environment Protection
Received date: Revised date: Accepted date:
7-12-2015 1-8-2016 2-8-2016
Please cite this article as: Al-Bedyry, Najah Kadhim, Sathasivan, Arumugam, AlIthari, Afrah Jaber, Ranking Pipes in Water Supply Systems Based on Potential to Cause Discoloured Water Complaints.Process Safety and Environment Protection http://dx.doi.org/10.1016/j.psep.2016.08.002 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1
Highlights
2
Conditioning velocity is the historical daily maximum velocity in a pipe.
3
Affected pipe experienced a higher velocity than the conditioning velocity.
4
The total affected length (TAL) of pipes for each broken pipe was used to rank.
5
Smaller the diameter of the broken pipe, more the TAL.
6
The method can guide the utilities when prioritising the pipe to replace/repair.
7 8 9 10 11
12
Graphical abstract
13 3
14
5
4 4
15 2
16 1
Water tank A
17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38
Study area with hypothetical burst pipes showing
Reservoir A
39
Ranking Pipes in Water Supply Systems Based on Potential to Cause
40
Discoloured Water Complaints
41 42 43 44
Najah Kadhim Al-Bedyry, Department of Civil Engineering, College of Engineering,
45
Babylon University,
46
Babylon, Iraq, [email protected]
47
Arumugam Sathasivan, School of Computing, Engineering and Mathematics,
48
University of Western Sydney, Locked Bag 1797, Penrith NSW 2751, Australia
49
Corresponding author: [email protected]
50
(Phone: 61-02-4736-0941, Fax: 61-02-47360833)
51
Afrah Jaber Al-Ithari, Caledonian College of Engineering, Al Hail South, Sultanate of
52
Oman, [email protected]
53 54 55 56 57 58 59 60 61 62 63 64 65 66
67
ABSTRACT
68 69
A novel concept to rank pipes based on the potential (risk) to cause discoloured water
70
complaints when broken is presented. A fixed re-suspension velocity for all sediments
71
was used previously to model sediment transport. However, there is always a risk of
72
sediment re-suspension and discoloration, if the velocity caused by hydraulic
73
disturbance is greater than the conditioning velocity- the maximum daily velocity
74
historically experienced in a pipe before the disturbance. In a full scale system, five
75
pipes of different diameters (99 - 222 mm) and locations (loop or open) were
76
simulated to break (break main flow at 10L/s) and the hydraulic response was
77
analysed using hydraulic software. The total affected length of the pipes where
78
velocity was more than the conditioning velocity was used for ranking. In general,
79
breakage of a smaller diameter pipe (100 mm diameter) caused more widespread
80
disturbance. If proven in the field, the hydraulic software could be modified to rank
81
pipes, making it easy for utilities to prioritise the pipe to replace or pay more
82
attention.
83 84
Keywords: Discoloration, Hydraulic model, Burst pipe, Velocity, Sediment transport,
85
Re-suspension Potential Method (RPM)
86 87 88 89 90 91 92
93
1.0 Introduction
94
Discoloration at the customer tap is one of the most common causes of customer
95
complaints in a drinking water supply system (DWSS). In Australia, it stands at 60 to
96
80% (Al-Ithari, 2013). Within Australia there is a large variation in customer
97
complaints between the different utilities, ranging from 1.1 to 17.9 complaints per
98
1000 customers with an average of 6 per 1000 customers (Polychronopolous et al.,
99
2003). Discoloured water may contain potentially harmful pathogens and heavy
100
metals (Gauthier et al., 1999; Kris and Hadi, 2008 and Tong et al., 2015). During the
101
discoloration events turbidity increases and is one way of assessing the event.
102
Australian Drinking Water Quality Guidelines (ADWG, 2004), therefore,
103
recommends an acceptable turbidity as below 1 NTU at times of disinfection, but the
104
maximum can reach up to 5 NTU for aesthetic considerations.
105 106
It is well accepted that the sediments or suspended solids must be present before
107
hydraulic events carry them to the customer to cause discoloration events. Suspended
108
solids can come with the treated water or may form due to physical, chemical and
109
microbiological processes within the pipe. For a discoloration event to occur
110
sediments or particles should be present and it should be disturbed and carried away
111
by moving water. The sediments in the system can originate from a number of
112
different sources. It can come directly from the treatment plant, especially treatment
113
with sand filtration where sediment can be introduced in the network (Vreeburg, and
114
Boxall, 2007, Vreeburg et al, 2004). During installations and maintenance work, sand,
115
clay and silt easily enter the system. It can also come from corrosion of unlined cast
116
iron mains which is regarded as a dominant process (Slaats et al, 2002). Peltier et al.,
117
(2003) showed that the absence of suspended solids in nano-filtered water supplied to
118
a distribution system did not immediately result in reduction of sediments but they
119
noted the change in composition, implying the importance of in-pipe processes. In-
120
pipe processes include the formation in the network by precipitation of dissolved
121
minerals (iron, manganese, and calcium) or sediment formation, caused by micro- and
122
macro organisms in the water main (van der Kooij, 2002). The presence of manganese
123
and iron colours the water red, brown, or black (Vreeburg et al., 2004). The loose
124
sediments are rich in organic matter and microbes (Gauthier et al., 1999) and can be
125
easily resuspended.
126 127
The rate of the material layer developed inside the pipe is a function of water quality
128
and hydraulic conditions (Husband and Boxall, 2011). Formation of the sediment is
129
affected by the differences in the ultimate shear stress of layers of material on the wall
130
of pipes made up from iron and plastic pipes (Husband and Boxall, 2010). A shear
131
stress of 1.2 N/m2 was shown to dislodge accumulated layers of the material from the
132
plastic pipes. For the operation and maintenance strategies, they suggested that these
133
pipes should be treated differently to minimize discoloration risk. For example,
134
measures could be implemented to limit or prevent particles from entering or being
135
generated within the network. The shear stress is a function of velocity. The change in
136
velocity (direction or magnitude) can change the shear stress and hence cause the
137
dislodgement of material. The change in velocity is not uncommon in pipes of water
138
supply system where major hydraulic events (break main, flushing etc.) occur in
139
addition to diurnal and seasonal variations. Depending on the ultimate shear stress of
140
the material and the shear stress caused by the disturbance, discolouration material
141
can be mobilised (Wricke et al., 2007; Boxall et al., 2001; Kivit, 2004 and Husband et
142
al., 2008). Water velocities affect the nature and physiological activity on biofilm
143
which eventually dislodge to form sediments (Wricke et al., 2007).
144
145
The velocity at which the sediments mobilise is called re-suspension velocity.
146
Different researchers have adopted different re-supension velocities. Using the
147
sediments collected from the downstream ends of distribution systems, Jayaratne et
148
al., (2004) showed the sediments will start to resuspend between the velocities of 0.07
149
- 0.25 m/s while a complete movement was noted between the velocities of 0.25-0.6
150
m/s. If the particles do not start to move until the velocity is above 0.6 m/s,
151
manganese is likely to be present in the water, possible because of higher density of
152
manganese sediments. The 0.6 m/s velocity translates to 4.71 L/s in a 100 mm
153
diameter pipe which is the majority in a reticulation system. This aligns with the
154
suggestion of Polychronopoulos et al., (2003) to reduce flush flow rate to 5 l/s from a
155
typical 10 l/s, (in a 100 mm pipe 1.28 m/s to 0.64 m/s), or higher to avoid water
156
wastage and extra sediments entrainment from upstream. This also agrees with the
157
suggestion of Qing (2006) to reduce flushing velocity from 1.5 m/s to 0.8~1.0 m/s
158
without compromising the sediment removal efficiency. When evaluating the amount
159
of sediment that has the potential to cause discoloration, Vreeburg (2010) used 0.35
160
m/s above the velocity of water in the pipe. In some smaller pipes of 100 mm
161
diameter, the maximum velocity can be as low as 0.05 m/s. In such cases, the
162
disturbing velocity is only 0.40 m/s.
163 164
Sediment build-up and discoloration in the distribution system are usually dealt with
165
by an aggressive program of water mains flushing through fire hydrants, air-scouring,
166
vacuum, ice pigging technology and pipe replacement (Yarra Valley Water, 2013). In
167
most cases, frequency of complaints determines the need for cleaning the system.
168
Vreeburg and Boxall (2007) proposed the Prediction and control of discolouration in
169
distribution system (PODDS) and the Re-suspension Potential Method (RPM) could
170
support the decision making on the need for maintenance operations. However, to
171
evaluate the amount of sediments in the pipes, RPM needs to be carried out which is
172
laborious.
173 174
The network hydraulic management is a potential strategy in reducing discolouration
175
risk. It is proposed that self-cleaning networks which regularly flushes the sediments
176
as the best strategy (Vreeburg and Boxall, 2007). Adoption of a branch-type network
177
design instead of a looped network is suggested to provide minimum discoloration
178
risk (Subramaniam, 2010). However, in an already built network, it is difficult to
179
reconfigure and hence better management strategies are needed.
180 181
Hydraulic models of water distribution system have been widely accepted as a
182
management tool within the water utility industry for simulating hydraulic and water
183
quality behaviour in water distribution system networks (Fisher et al., 2011).
184
Depending on flow conditions the suspended particles may be transported or
185
deposited as sedimentary deposits (Slaats et al., 2003). The Particle Suspension
186
Model (PSM) was developed by the Cooperative Research Centre for Water Quality
187
and Treatment (CRCWQT) in Australia. It assumes the settled sediment resuspends
188
when the flow velocity is greater than or equal to the resuspension velocity. The PSM
189
was built on free available EPANET software. PSM software assumes that all
190
sediments are transported with a single re-suspension velocity and a single
191
sedimentation velocity (Jayaratne et al., 2004).
192 193
It takes a lot of computing time to simulate the sediment transport. However, it is
194
logical to assume that the re-suspension velocity of sediments in a pipe is a function
195
of a conditioning velocity (Vc) which is defined as the maximum daily velocity
196
experienced within the pipe prior to the hydraulic event. The concept of this research
197
is based on the fact that suspended particles accumulate in stable layers attached to the
198
pipe walls of the network and is conditioned by the usual daily demand pattern within
199
the network. The strength of these layers is a function of the maximum daily shear
200
stress that relates to the maximum daily velocity pattern. Therefore, there is always a
201
risk of discoloration if the velocity is greater than the conditioning velocity. It should
202
be noted that the magnitude of risk could vary depending on the amount of sediment
203
material present in the pipe and nature (age, origin) of the material, but is not
204
considered.
205 206
In this paper, break main events on five different pipes in different locations of a
207
distribution system were simulated during the daily peak flow period to determine the
208
length of affected pipes – in which the velocity in the pipe would increase more than
209
the conditioning velocity of each pipe. It is assumed, if the method is successfully
210
proven with the field trial, the hydraulic software can be easily modified to rank the
211
pipes based on potential risk.
212 213
2.0 Material and Methods
214
To evaluate the effect of change in velocity, five pipes (Table 1) in a chosen zone,
215
Perth, Western Australia were simulated in EPANET (Figure 1). The zone has an
216
area of about 4.0 km2 and serves about 11,600 customers via Tank A.
217 218
As the normal scenario, the EPANET was run with design daily requirements within
219
the zone to identify the conditioning velocity (Vc) in each pipe. The peak velocity
220
occurred at around 7:00 each day. For the break main event scenario, five simulation
221
runs at 10 L/s flow rate was added between 6:00 to 8:00 to the node that is located
222
downstream of each chosen pipe to increase the chance of highest velocity. For both
223
scenarios, the hydraulic time step for the required results was set to 15 minutes during
224
the operation period (24 hrs). Note that time (0) in the EPANET denote 1:00 am.
225
Table 1 includes the data of these pipes.
226 227
Table 1: Design data of the simulated burst pipes Seq. of the burst pipe
Diameter (mm)
Length (m)
Pipe status
1
99
523.9
Loop
2
99
186.8
Open
3
222
406.4
Open
4
146
193.6
Open
5
99
537.0
Loop
3 5
4 4 2
1
Water tank A
Reservoir A
228 229 230 231 232 233
Figure 1: Simulated break event pipes in the chosen zone of Southern Suburb, Perth, Western Australia
234
2.1 Method to rank pipes for its potential to cause discoloration event
235
To understand the impact more meaningfully, the conditioning velocity Vc for normal
236
(daily) operation and the maximum possible velocity (Vbmax) during the break main
237
event were determined and a ratio of velocity, rv is defined as follows,
rv Vb max V
238
Eq(1)
c
239
The value of rv was calculated to understand the potential velocity increase in each
240
pipe. If it is assumed n number of pipes are affected (0>rv>1), when pipe j is
241
simulated to break, then the potential to cause discoloration complaints is assumed to
242
be proportional to the total affected length (TAL) of pipes; n
TALj li
243
Eq(2)
i 1
244 245
3.0 Results and discussion
246
3.1 Velocity changes from break main event in one pipe
247
The results from normal and break main event scenarios were compared for velocity
248
and head at nodes to understand the impact of a break main event. From the results of
249
burst pipe 1 (Figure 2), the velocities in 185 pipes have increased and in some of these
250
pipes the flows have reversed. At any time when the flow changed its direction
251
and/or magnitude there is a change in energy/shear stress which will drive the
252
sediment to move. All affected pipes (0>rv>1) had velocity increase between 1.1 and
253
13.3 times compared with the normal flow (Figure 3). Majority (80%) of the affected
254
pipes were of 99 mm in diameter which directly supply water to customers with the
255
highest potential to cause customer complaints.
256
Velocity legend 0.010 0.050 0.10 0.20 m/s
r r
r: Reverse
r r r r
r
Noder 76
1 r
r Node 69
r r
Scenario N
Scenario B (pipe 1)
257 258 259 260 261 262
Figure 2: Difference in the velocity values and direction for case of the burst pipe 1 at time 6:00 for normal and break main scenarios. Change in colour shows the change in magnitude. Arrow shows the direction of flow. “r” shows the flow has reversed. 1.2
Vbmax Vc
Velocity (m/s)
1 0.8 0.6 0.4 0.2
263 264 265 266 267 268
1(91mm) 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101(>99mm) 106 111 116 121 126 131 136 141(>200mm) 146 151 156 161 166 171 176 181
0
Pipe No.
Figure 3: Values of the conditional velocity (Vc) and break mean velocity (Vbmax) in (m/s) at time 6:00 in the affected pipes. Pipes are organised in the increasing order of diameter.
269
The most important parameter that determines the flow in pipe is the pressure (or
270
head) at nodes (junctions). The values of the head in all junctions that connect the
271
affected pipes decrease as a result of burst event (Figure 4). This figure shows the
272
decrease in head values during the burst period. Figure 5 represents the difference in
273
head in the junction of the burst pipe 76.
274
For the case of reverse flow as an example, at time 6:00, the flow in the pipe between
275
the two junctions (76 and 69) of a pipe 1 (Figure 2) was considered. In the daily
276
operation scenario, the flow direction was from node 76 to node 69 (Head at 76 is
277
higher than that at 69) while it was in opposite direction (Head at 76 is lower than that
278
at 69) during break main event (Figure 5). 92 Head (m)
91 90 Head at Vc
89
Head at Vbmax
88
2 5 8 11 14 17 20 23 26 29 32 35 38 41 44 47 50 53 56 59 62 65 68 71 74 77 80 83 Burst node 1 88 91 94 97 100 103
87
Junctions ID
279 280 281 282
Figure 4: Hydraulic head pressures (m) at time 6:00 in all affected nodes for normal and break main event scenarios 93
Head at Vbmax Head at Vc
Head (m)
92 91 90 89 88
Time (hr)
283 284 285 286
Figure 5: Hydraulic head pressures (m) in node 76 for normal and break main event scenarios at time 6:00
287
3.2 Effect of other induced break main events
288
Similar to Pipe 1, four other pipes were simulated to break by introducing 10 L/s at
289
stipulated nodes and the results showed the impact vary depending on the location
20:15
19:30
18:45
18:00
17:15
16:30
15:45
15:00
14:15
13:30
12:45
12:00
11:15
10:30
9:45
9:00
8:15
7:30
6:45
6:00
5:15
4:30
3:45
3:00
2:15
1:30
0:45
0:00
87
290
(loop or open) and diameter of the pipe. All affected pipes for each break are shown
291
in Figure 6 with different colour and the results are summarized in Table 2. Breaking
292
of a 99 mm diameter pipe had the maximum impact, but the impact varied depending
293
on the location of the pipe. The percentage of affected area ranged between 8% and
294
17.5% of the total analysed area giving a clear indication of ranking among the
295
limited number of pipes analysed.
296 297
Larger diameter pipes (146 or 222 mm) had less impact compared to 99 mm diameter
298
pipes, mainly because same break main flow (10 L/s) as that of 99 mm diameter pipe
299
induced less velocity changes in the large diameter pipe itself.
300 301
An increase in velocity and inverse in flow direction resulted in additional dynamic
302
forces and decrease in a shear strength. This strength, and hence sediments layer state,
303
is dictated by the shear stresses imposed by hydraulic conditions.
304 305 3
306
5
307 4
308
2
309 310 311 312 313 314 315 316
1
Pipe 1 Pipe 4
Figure 6: Affected pipes for each burst pipe (rv>2)
Pipe 2 Pipe 3 Pipe 5
317 318
Table 2: Effect of the burst event within study area for each hypothetical burst pipe arranged according to the area affect Burst pipe
Without direction change With reverse flow
ID
rv>1
Dia (mm)
1
99
185
TAL (m) 21,489
2
99
183
5
99
4 3
Affected area
rv>2
Rank
km2
%
12
TAL (m) 928
0.7
17.5
1
56
TAL (m) 5,440
21,203
55
5,421
12
928
0.6
15
2
95
9,441
27
2,549
4
419
0.32
8
3
146
133
12,549
19
1,590
6
799
0.13
3.25
4
222
117
13,676
15
2,410
0
0
0.13
3.25
5
No.*
No.
No.
319
*No. refers to the “Affected number of pipes”.
320
The pipes with low daily maximum hydraulic forces, such as loops (pipes 1 and 5) or
321
other low flow pipes (2, 3 and 4) will have low strength characteristics and high
322
discolouration potential because they are usually located in the downstream ends of
323
the systems where majority of the customers are located. The occurrence of
324
disequilibria hydraulic conditions (burst or increased demand) may expose the layers
325
to shear stress in excess of their conditioned cohesive strength and lead to a
326
mobilisation of the cohesive layers, resulting in a discolouration event. Various
327
researchers have considered many other aspects of deposition and movement of
328
sediments: Age, nature or origin of sediments (Vreeburg and Boxall, 2010; Gauthier
329
et al., 1997); a fixed sedimentation or a resuspension velocity (Jayaratne et al., 2004)
330
or other ways of modelling (Husband and Boxall, 2010; 2011; Kris and Hadi, 2008 );
331
or the topography (Polychronopolous et al., 2003).
332
estimate of the potential to cause discolouration without considering other aspects as
333
these can vary within a system or across different distribution systems. It should be
334
noted that the actual discoloration will be less than that is calculated by this approach
Our approach provides an
335
for any given broken pipe. In summary, pipes can be ranked depending on their
336
potential to cause discoloration event, using only hydraulic software.
337 338
3.3 Implication for discoloured water complaints management
339
The results showed the same hydraulic disturbance in different pipes can impact
340
significantly differently. For the discolouration to occur there should be sediment
341
within the pipe. This paper only analyses the potential with the assumption that if the
342
water velocity in a pipe experiences more than the historically experienced maximum
343
velocity there should be a chance to cause discoloration event. It is possible that there
344
exist some stable layers that need much more disturbance than that is assumed in this
345
article. This needs further field validation, but the simulation has shown there can be a
346
pipe which causes the vast impact when broken. Such pipe or area in which this
347
occurs can be easily identified and targeted with the suggested approach. Hence, if a
348
water utility is considering the pipe replacement then this type of simple hydraulic
349
modelling can assist in ranking the pipes. Current work involved laborious analysis of
350
the network. However, if hydraulic software can be appropriately modified, this
351
analysis can be easily carried out to rank many pipes.
352 353
4.0 Conclusion
354
Discolouration is associated with mobilisation of accumulated particles from within
355
distribution networks. The impact of each burst event depends on the burst pipe
356
diameter. The burst pipes with smaller diameter (99 mm) had regions of influence
357
ranging from 17.5% to 3.25% of the study area (4.0 km2). Significantly different
358
impacts indicate that there is a benefit to identify the critical pipe which causes the
359
most discolouration risk. A particular pattern regarding the location of most critical
360
pipe could not be established in this research and needs further work.
361
Acknowledgement
362
The authors would like to acknowledge Water Corporation of Western Australia to
363
allow us to run the hydraulic model of the system presented in this paper.
364
365 366
References
367
Al-Ithari A., 2013. Evaluating and Improving the Tools for Predicting Discolouration
368
Event in Potable Water Supply System. Ph.D. thesis. School of Mechanical
369
Engineering-Department of Civil Engineering, Curtin University.
370
Australian
371
http://www.nhmrc.gov.au/_files_nhmrc/publications/attachments/eh34_adwg_11_06.
372
Boxall, J.B., Saul, A.J., Skipworth, P.J., 2001. A novel approach to modelling
373
sediment movement in distribution mains based on particle characteristics. Water
374
Software Systems, pp. 263-273.
375
Fisher, I., G. Kastl, A. Sathasivan and V. Jegatheesan (2011) Suitability of chlorine
376
decay models for planning and management of water distribution systems: A Review,
377
Critical Reviews in Environmental Science and Technology. 41(20), pp 1843-1882
378
Gauthier, V., Portal, J.M., Rosin, C., Block, J.C., Cavard, J. and Gatel, D., 1997. How
379
good are water distribution systems for transport of particulate matter? Proc. Am.
380
Water Works Assoc., Water quality Technology Conference, Denver, Co., USA.
381
Gauthier, V., Portal, J-M., Yvon, H., Rosin, C., Block, J-C., Lahoussine, V.,
382
Benabdallah, S., Cavard, J., Gatel, D. and Fass, S., 2001. Characterization of
383
suspended particles and deposits in drinking water reservoirs. Water Science and
384
Technology: Water Supply, Vol. 1, No. 4, pp. 89-94.
385
Gauthier, V., B. Gérard, JM. Portal, JC. Block, D. Gatel, 1999. Organic matter as
386
loose deposits in a drinking water distribution system, Water Research, Volume 33,
387
Issue 4, Pages 1014-1026, ISSN 0043-1354.
Drinking
Water
Guideline
(ADWG),
2004.
388
Huiyan Tong, Peng Zhao, Hongwei Zhang, Yimei Tian, Xi Chen, Weigao Zhao, Mei
389
Li, 2015. Identification and characterization of steady and occluded water in drinking
390
water distribution systems, Chemosphere, Volume 119, Pages 1141-1147.
391
Husband, P. S. and Boxall, J. B., 2010. Field Studies of Discoloration in Water
392
Distribution Systems: Model Verification and Practical Implications. Journal of
393
Environmental Engineering, Vol. 136, No. 1, pp. 86–94.
394
Husband, P. S. and Boxall, J. B., 2011.Asset deterioration and discolouration in water
395
distribution systems. Water Research, Vol. 45, pp. 113–124.
396
Husband, P. S., Boxall, J. B., and Saul A. J., 2008.Laboratory studies investigating the
397
processes leading to discolouration in water distribution networks. Water Research,
398
Vol. 42, pp. 4309–4318.
399
Jayaratne A, Ryan G, Grainger C, Wu J, Noui-Mehidi M N, 2004. Modelling of
400
particles in water supply systems. Water, Vol. 31, No. 8, AWA.
401
Kivit C. F. T., 2004. Origin and behaviour of particles on drinking water networks. M.
402
Sc. Thesis report. Civil Engineering, Delft University of Technology.
403
Kris, J. and Hadi, Ghawi A., 2008.CFD Investigation of particle deposition and
404
resuspension in a drinking water distribution system. Slovak Journal of Civil
405
Engineering, Vol. 1, pp. 1-7.
406
Neilands K., Bernats M., and Rubulis J., 2012. Accumulation and modelling of
407
particles in drinking water pipe fittings. Drinking Water Engineering and Science,
408
Vol. 5, pp. 47–57.
409
Peltier, S., Cotte, M., Gatel, D., Herremans, L., Cavard, J., 2003.Nanofiltration:
410
improvements of water quality in a large distribution system. Water Science and
411
Technology: Water Supply, Vol. 3, No.1-2, pp. 193-200.
412
Polychronopolous, M, Dudley K, Ryan, G, Hearn J., 2003. Investigation of factors
413
contributing to dirty water events in reticulation systems and evaluating of flushing
414
methods to remove deposited particles, Water Science and Technology: Water Supply,
415
Vol. 3, No.1-2, pp. 295-306.
416
Qing W., 2006. Drinking water distribution system sediment resuspension
417
characteristics study - New application of Jar test. M. Sc. Thesis. Department of Water
418
Management Faculty of Civil Engineering. Delft University of Technology.
419
Slaats P.G.G, Rosenthal L.P.M, Vreeburg J.H.G., 2003. Processes involved in the
420
generation of discoloured water. AwwaRF 2003.
421
Subramaniam V., 2010. Addressing discoloration of drinking water problems in
422
distribution systems. Discolouration of drinking water: an old problem clarified,
423
Water 21.
424
Vreeburg, J., 2010. Discoloration in drinking water systems: The role of particles
425
clarified. IWA Publishing, London, UK.
426
Vreeburg, J.H.G. and Boxall, J. B., 2007. Discolouration in potable water distribution
427
systems: A review. Water research. Vol. 41, pp. 519-529.
428
Wricke B., Henning L., Korth A., Vreeburg J., Schaap P., Osterhus S., Juhna T.,
429
Hammes F., and Coelho S., 2007. Particles in relation to water quality deterioration
430
and
431
https://www.techneau.org/fileadmin/files/Publications/Publications/Deliverables/D5.5
432
.1.pdf
433
Yarra Valley water. Drinking water quality report 2012/2013.
434
http://www.yvw.com.au/yvw/groups/public/documents/document/yvw1004001.pdf
435 436
problems
in
the
network.
Techneau,
28.
S0957-5820(16)30155-0 http://dx.doi.org/doi:10.1016/j.psep.2016.08.002 PSEP 843
To appear in:
Process Safety and Environment Protection
Received date: Revised date: Accepted date:
7-12-2015 1-8-2016 2-8-2016
Please cite this article as: Al-Bedyry, Najah Kadhim, Sathasivan, Arumugam, AlIthari, Afrah Jaber, Ranking Pipes in Water Supply Systems Based on Potential to Cause Discoloured Water Complaints.Process Safety and Environment Protection http://dx.doi.org/10.1016/j.psep.2016.08.002 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1
Highlights
2
Conditioning velocity is the historical daily maximum velocity in a pipe.
3
Affected pipe experienced a higher velocity than the conditioning velocity.
4
The total affected length (TAL) of pipes for each broken pipe was used to rank.
5
Smaller the diameter of the broken pipe, more the TAL.
6
The method can guide the utilities when prioritising the pipe to replace/repair.
7 8 9 10 11
12
Graphical abstract
13 3
14
5
4 4
15 2
16 1
Water tank A
17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38
Study area with hypothetical burst pipes showing
Reservoir A
39
Ranking Pipes in Water Supply Systems Based on Potential to Cause
40
Discoloured Water Complaints
41 42 43 44
Najah Kadhim Al-Bedyry, Department of Civil Engineering, College of Engineering,
45
Babylon University,
46
Babylon, Iraq, [email protected]
47
Arumugam Sathasivan, School of Computing, Engineering and Mathematics,
48
University of Western Sydney, Locked Bag 1797, Penrith NSW 2751, Australia
49
Corresponding author: [email protected]
50
(Phone: 61-02-4736-0941, Fax: 61-02-47360833)
51
Afrah Jaber Al-Ithari, Caledonian College of Engineering, Al Hail South, Sultanate of
52
Oman, [email protected]
53 54 55 56 57 58 59 60 61 62 63 64 65 66
67
ABSTRACT
68 69
A novel concept to rank pipes based on the potential (risk) to cause discoloured water
70
complaints when broken is presented. A fixed re-suspension velocity for all sediments
71
was used previously to model sediment transport. However, there is always a risk of
72
sediment re-suspension and discoloration, if the velocity caused by hydraulic
73
disturbance is greater than the conditioning velocity- the maximum daily velocity
74
historically experienced in a pipe before the disturbance. In a full scale system, five
75
pipes of different diameters (99 - 222 mm) and locations (loop or open) were
76
simulated to break (break main flow at 10L/s) and the hydraulic response was
77
analysed using hydraulic software. The total affected length of the pipes where
78
velocity was more than the conditioning velocity was used for ranking. In general,
79
breakage of a smaller diameter pipe (100 mm diameter) caused more widespread
80
disturbance. If proven in the field, the hydraulic software could be modified to rank
81
pipes, making it easy for utilities to prioritise the pipe to replace or pay more
82
attention.
83 84
Keywords: Discoloration, Hydraulic model, Burst pipe, Velocity, Sediment transport,
85
Re-suspension Potential Method (RPM)
86 87 88 89 90 91 92
93
1.0 Introduction
94
Discoloration at the customer tap is one of the most common causes of customer
95
complaints in a drinking water supply system (DWSS). In Australia, it stands at 60 to
96
80% (Al-Ithari, 2013). Within Australia there is a large variation in customer
97
complaints between the different utilities, ranging from 1.1 to 17.9 complaints per
98
1000 customers with an average of 6 per 1000 customers (Polychronopolous et al.,
99
2003). Discoloured water may contain potentially harmful pathogens and heavy
100
metals (Gauthier et al., 1999; Kris and Hadi, 2008 and Tong et al., 2015). During the
101
discoloration events turbidity increases and is one way of assessing the event.
102
Australian Drinking Water Quality Guidelines (ADWG, 2004), therefore,
103
recommends an acceptable turbidity as below 1 NTU at times of disinfection, but the
104
maximum can reach up to 5 NTU for aesthetic considerations.
105 106
It is well accepted that the sediments or suspended solids must be present before
107
hydraulic events carry them to the customer to cause discoloration events. Suspended
108
solids can come with the treated water or may form due to physical, chemical and
109
microbiological processes within the pipe. For a discoloration event to occur
110
sediments or particles should be present and it should be disturbed and carried away
111
by moving water. The sediments in the system can originate from a number of
112
different sources. It can come directly from the treatment plant, especially treatment
113
with sand filtration where sediment can be introduced in the network (Vreeburg, and
114
Boxall, 2007, Vreeburg et al, 2004). During installations and maintenance work, sand,
115
clay and silt easily enter the system. It can also come from corrosion of unlined cast
116
iron mains which is regarded as a dominant process (Slaats et al, 2002). Peltier et al.,
117
(2003) showed that the absence of suspended solids in nano-filtered water supplied to
118
a distribution system did not immediately result in reduction of sediments but they
119
noted the change in composition, implying the importance of in-pipe processes. In-
120
pipe processes include the formation in the network by precipitation of dissolved
121
minerals (iron, manganese, and calcium) or sediment formation, caused by micro- and
122
macro organisms in the water main (van der Kooij, 2002). The presence of manganese
123
and iron colours the water red, brown, or black (Vreeburg et al., 2004). The loose
124
sediments are rich in organic matter and microbes (Gauthier et al., 1999) and can be
125
easily resuspended.
126 127
The rate of the material layer developed inside the pipe is a function of water quality
128
and hydraulic conditions (Husband and Boxall, 2011). Formation of the sediment is
129
affected by the differences in the ultimate shear stress of layers of material on the wall
130
of pipes made up from iron and plastic pipes (Husband and Boxall, 2010). A shear
131
stress of 1.2 N/m2 was shown to dislodge accumulated layers of the material from the
132
plastic pipes. For the operation and maintenance strategies, they suggested that these
133
pipes should be treated differently to minimize discoloration risk. For example,
134
measures could be implemented to limit or prevent particles from entering or being
135
generated within the network. The shear stress is a function of velocity. The change in
136
velocity (direction or magnitude) can change the shear stress and hence cause the
137
dislodgement of material. The change in velocity is not uncommon in pipes of water
138
supply system where major hydraulic events (break main, flushing etc.) occur in
139
addition to diurnal and seasonal variations. Depending on the ultimate shear stress of
140
the material and the shear stress caused by the disturbance, discolouration material
141
can be mobilised (Wricke et al., 2007; Boxall et al., 2001; Kivit, 2004 and Husband et
142
al., 2008). Water velocities affect the nature and physiological activity on biofilm
143
which eventually dislodge to form sediments (Wricke et al., 2007).
144
145
The velocity at which the sediments mobilise is called re-suspension velocity.
146
Different researchers have adopted different re-supension velocities. Using the
147
sediments collected from the downstream ends of distribution systems, Jayaratne et
148
al., (2004) showed the sediments will start to resuspend between the velocities of 0.07
149
- 0.25 m/s while a complete movement was noted between the velocities of 0.25-0.6
150
m/s. If the particles do not start to move until the velocity is above 0.6 m/s,
151
manganese is likely to be present in the water, possible because of higher density of
152
manganese sediments. The 0.6 m/s velocity translates to 4.71 L/s in a 100 mm
153
diameter pipe which is the majority in a reticulation system. This aligns with the
154
suggestion of Polychronopoulos et al., (2003) to reduce flush flow rate to 5 l/s from a
155
typical 10 l/s, (in a 100 mm pipe 1.28 m/s to 0.64 m/s), or higher to avoid water
156
wastage and extra sediments entrainment from upstream. This also agrees with the
157
suggestion of Qing (2006) to reduce flushing velocity from 1.5 m/s to 0.8~1.0 m/s
158
without compromising the sediment removal efficiency. When evaluating the amount
159
of sediment that has the potential to cause discoloration, Vreeburg (2010) used 0.35
160
m/s above the velocity of water in the pipe. In some smaller pipes of 100 mm
161
diameter, the maximum velocity can be as low as 0.05 m/s. In such cases, the
162
disturbing velocity is only 0.40 m/s.
163 164
Sediment build-up and discoloration in the distribution system are usually dealt with
165
by an aggressive program of water mains flushing through fire hydrants, air-scouring,
166
vacuum, ice pigging technology and pipe replacement (Yarra Valley Water, 2013). In
167
most cases, frequency of complaints determines the need for cleaning the system.
168
Vreeburg and Boxall (2007) proposed the Prediction and control of discolouration in
169
distribution system (PODDS) and the Re-suspension Potential Method (RPM) could
170
support the decision making on the need for maintenance operations. However, to
171
evaluate the amount of sediments in the pipes, RPM needs to be carried out which is
172
laborious.
173 174
The network hydraulic management is a potential strategy in reducing discolouration
175
risk. It is proposed that self-cleaning networks which regularly flushes the sediments
176
as the best strategy (Vreeburg and Boxall, 2007). Adoption of a branch-type network
177
design instead of a looped network is suggested to provide minimum discoloration
178
risk (Subramaniam, 2010). However, in an already built network, it is difficult to
179
reconfigure and hence better management strategies are needed.
180 181
Hydraulic models of water distribution system have been widely accepted as a
182
management tool within the water utility industry for simulating hydraulic and water
183
quality behaviour in water distribution system networks (Fisher et al., 2011).
184
Depending on flow conditions the suspended particles may be transported or
185
deposited as sedimentary deposits (Slaats et al., 2003). The Particle Suspension
186
Model (PSM) was developed by the Cooperative Research Centre for Water Quality
187
and Treatment (CRCWQT) in Australia. It assumes the settled sediment resuspends
188
when the flow velocity is greater than or equal to the resuspension velocity. The PSM
189
was built on free available EPANET software. PSM software assumes that all
190
sediments are transported with a single re-suspension velocity and a single
191
sedimentation velocity (Jayaratne et al., 2004).
192 193
It takes a lot of computing time to simulate the sediment transport. However, it is
194
logical to assume that the re-suspension velocity of sediments in a pipe is a function
195
of a conditioning velocity (Vc) which is defined as the maximum daily velocity
196
experienced within the pipe prior to the hydraulic event. The concept of this research
197
is based on the fact that suspended particles accumulate in stable layers attached to the
198
pipe walls of the network and is conditioned by the usual daily demand pattern within
199
the network. The strength of these layers is a function of the maximum daily shear
200
stress that relates to the maximum daily velocity pattern. Therefore, there is always a
201
risk of discoloration if the velocity is greater than the conditioning velocity. It should
202
be noted that the magnitude of risk could vary depending on the amount of sediment
203
material present in the pipe and nature (age, origin) of the material, but is not
204
considered.
205 206
In this paper, break main events on five different pipes in different locations of a
207
distribution system were simulated during the daily peak flow period to determine the
208
length of affected pipes – in which the velocity in the pipe would increase more than
209
the conditioning velocity of each pipe. It is assumed, if the method is successfully
210
proven with the field trial, the hydraulic software can be easily modified to rank the
211
pipes based on potential risk.
212 213
2.0 Material and Methods
214
To evaluate the effect of change in velocity, five pipes (Table 1) in a chosen zone,
215
Perth, Western Australia were simulated in EPANET (Figure 1). The zone has an
216
area of about 4.0 km2 and serves about 11,600 customers via Tank A.
217 218
As the normal scenario, the EPANET was run with design daily requirements within
219
the zone to identify the conditioning velocity (Vc) in each pipe. The peak velocity
220
occurred at around 7:00 each day. For the break main event scenario, five simulation
221
runs at 10 L/s flow rate was added between 6:00 to 8:00 to the node that is located
222
downstream of each chosen pipe to increase the chance of highest velocity. For both
223
scenarios, the hydraulic time step for the required results was set to 15 minutes during
224
the operation period (24 hrs). Note that time (0) in the EPANET denote 1:00 am.
225
Table 1 includes the data of these pipes.
226 227
Table 1: Design data of the simulated burst pipes Seq. of the burst pipe
Diameter (mm)
Length (m)
Pipe status
1
99
523.9
Loop
2
99
186.8
Open
3
222
406.4
Open
4
146
193.6
Open
5
99
537.0
Loop
3 5
4 4 2
1
Water tank A
Reservoir A
228 229 230 231 232 233
Figure 1: Simulated break event pipes in the chosen zone of Southern Suburb, Perth, Western Australia
234
2.1 Method to rank pipes for its potential to cause discoloration event
235
To understand the impact more meaningfully, the conditioning velocity Vc for normal
236
(daily) operation and the maximum possible velocity (Vbmax) during the break main
237
event were determined and a ratio of velocity, rv is defined as follows,
rv Vb max V
238
Eq(1)
c
239
The value of rv was calculated to understand the potential velocity increase in each
240
pipe. If it is assumed n number of pipes are affected (0>rv>1), when pipe j is
241
simulated to break, then the potential to cause discoloration complaints is assumed to
242
be proportional to the total affected length (TAL) of pipes; n
TALj li
243
Eq(2)
i 1
244 245
3.0 Results and discussion
246
3.1 Velocity changes from break main event in one pipe
247
The results from normal and break main event scenarios were compared for velocity
248
and head at nodes to understand the impact of a break main event. From the results of
249
burst pipe 1 (Figure 2), the velocities in 185 pipes have increased and in some of these
250
pipes the flows have reversed. At any time when the flow changed its direction
251
and/or magnitude there is a change in energy/shear stress which will drive the
252
sediment to move. All affected pipes (0>rv>1) had velocity increase between 1.1 and
253
13.3 times compared with the normal flow (Figure 3). Majority (80%) of the affected
254
pipes were of 99 mm in diameter which directly supply water to customers with the
255
highest potential to cause customer complaints.
256
Velocity legend 0.010 0.050 0.10 0.20 m/s
r r
r: Reverse
r r r r
r
Noder 76
1 r
r Node 69
r r
Scenario N
Scenario B (pipe 1)
257 258 259 260 261 262
Figure 2: Difference in the velocity values and direction for case of the burst pipe 1 at time 6:00 for normal and break main scenarios. Change in colour shows the change in magnitude. Arrow shows the direction of flow. “r” shows the flow has reversed. 1.2
Vbmax Vc
Velocity (m/s)
1 0.8 0.6 0.4 0.2
263 264 265 266 267 268
1(91mm) 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101(>99mm) 106 111 116 121 126 131 136 141(>200mm) 146 151 156 161 166 171 176 181
0
Pipe No.
Figure 3: Values of the conditional velocity (Vc) and break mean velocity (Vbmax) in (m/s) at time 6:00 in the affected pipes. Pipes are organised in the increasing order of diameter.
269
The most important parameter that determines the flow in pipe is the pressure (or
270
head) at nodes (junctions). The values of the head in all junctions that connect the
271
affected pipes decrease as a result of burst event (Figure 4). This figure shows the
272
decrease in head values during the burst period. Figure 5 represents the difference in
273
head in the junction of the burst pipe 76.
274
For the case of reverse flow as an example, at time 6:00, the flow in the pipe between
275
the two junctions (76 and 69) of a pipe 1 (Figure 2) was considered. In the daily
276
operation scenario, the flow direction was from node 76 to node 69 (Head at 76 is
277
higher than that at 69) while it was in opposite direction (Head at 76 is lower than that
278
at 69) during break main event (Figure 5). 92 Head (m)
91 90 Head at Vc
89
Head at Vbmax
88
2 5 8 11 14 17 20 23 26 29 32 35 38 41 44 47 50 53 56 59 62 65 68 71 74 77 80 83 Burst node 1 88 91 94 97 100 103
87
Junctions ID
279 280 281 282
Figure 4: Hydraulic head pressures (m) at time 6:00 in all affected nodes for normal and break main event scenarios 93
Head at Vbmax Head at Vc
Head (m)
92 91 90 89 88
Time (hr)
283 284 285 286
Figure 5: Hydraulic head pressures (m) in node 76 for normal and break main event scenarios at time 6:00
287
3.2 Effect of other induced break main events
288
Similar to Pipe 1, four other pipes were simulated to break by introducing 10 L/s at
289
stipulated nodes and the results showed the impact vary depending on the location
20:15
19:30
18:45
18:00
17:15
16:30
15:45
15:00
14:15
13:30
12:45
12:00
11:15
10:30
9:45
9:00
8:15
7:30
6:45
6:00
5:15
4:30
3:45
3:00
2:15
1:30
0:45
0:00
87
290
(loop or open) and diameter of the pipe. All affected pipes for each break are shown
291
in Figure 6 with different colour and the results are summarized in Table 2. Breaking
292
of a 99 mm diameter pipe had the maximum impact, but the impact varied depending
293
on the location of the pipe. The percentage of affected area ranged between 8% and
294
17.5% of the total analysed area giving a clear indication of ranking among the
295
limited number of pipes analysed.
296 297
Larger diameter pipes (146 or 222 mm) had less impact compared to 99 mm diameter
298
pipes, mainly because same break main flow (10 L/s) as that of 99 mm diameter pipe
299
induced less velocity changes in the large diameter pipe itself.
300 301
An increase in velocity and inverse in flow direction resulted in additional dynamic
302
forces and decrease in a shear strength. This strength, and hence sediments layer state,
303
is dictated by the shear stresses imposed by hydraulic conditions.
304 305 3
306
5
307 4
308
2
309 310 311 312 313 314 315 316
1
Pipe 1 Pipe 4
Figure 6: Affected pipes for each burst pipe (rv>2)
Pipe 2 Pipe 3 Pipe 5
317 318
Table 2: Effect of the burst event within study area for each hypothetical burst pipe arranged according to the area affect Burst pipe
Without direction change With reverse flow
ID
rv>1
Dia (mm)
1
99
185
TAL (m) 21,489
2
99
183
5
99
4 3
Affected area
rv>2
Rank
km2
%
12
TAL (m) 928
0.7
17.5
1
56
TAL (m) 5,440
21,203
55
5,421
12
928
0.6
15
2
95
9,441
27
2,549
4
419
0.32
8
3
146
133
12,549
19
1,590
6
799
0.13
3.25
4
222
117
13,676
15
2,410
0
0
0.13
3.25
5
No.*
No.
No.
319
*No. refers to the “Affected number of pipes”.
320
The pipes with low daily maximum hydraulic forces, such as loops (pipes 1 and 5) or
321
other low flow pipes (2, 3 and 4) will have low strength characteristics and high
322
discolouration potential because they are usually located in the downstream ends of
323
the systems where majority of the customers are located. The occurrence of
324
disequilibria hydraulic conditions (burst or increased demand) may expose the layers
325
to shear stress in excess of their conditioned cohesive strength and lead to a
326
mobilisation of the cohesive layers, resulting in a discolouration event. Various
327
researchers have considered many other aspects of deposition and movement of
328
sediments: Age, nature or origin of sediments (Vreeburg and Boxall, 2010; Gauthier
329
et al., 1997); a fixed sedimentation or a resuspension velocity (Jayaratne et al., 2004)
330
or other ways of modelling (Husband and Boxall, 2010; 2011; Kris and Hadi, 2008 );
331
or the topography (Polychronopolous et al., 2003).
332
estimate of the potential to cause discolouration without considering other aspects as
333
these can vary within a system or across different distribution systems. It should be
334
noted that the actual discoloration will be less than that is calculated by this approach
Our approach provides an
335
for any given broken pipe. In summary, pipes can be ranked depending on their
336
potential to cause discoloration event, using only hydraulic software.
337 338
3.3 Implication for discoloured water complaints management
339
The results showed the same hydraulic disturbance in different pipes can impact
340
significantly differently. For the discolouration to occur there should be sediment
341
within the pipe. This paper only analyses the potential with the assumption that if the
342
water velocity in a pipe experiences more than the historically experienced maximum
343
velocity there should be a chance to cause discoloration event. It is possible that there
344
exist some stable layers that need much more disturbance than that is assumed in this
345
article. This needs further field validation, but the simulation has shown there can be a
346
pipe which causes the vast impact when broken. Such pipe or area in which this
347
occurs can be easily identified and targeted with the suggested approach. Hence, if a
348
water utility is considering the pipe replacement then this type of simple hydraulic
349
modelling can assist in ranking the pipes. Current work involved laborious analysis of
350
the network. However, if hydraulic software can be appropriately modified, this
351
analysis can be easily carried out to rank many pipes.
352 353
4.0 Conclusion
354
Discolouration is associated with mobilisation of accumulated particles from within
355
distribution networks. The impact of each burst event depends on the burst pipe
356
diameter. The burst pipes with smaller diameter (99 mm) had regions of influence
357
ranging from 17.5% to 3.25% of the study area (4.0 km2). Significantly different
358
impacts indicate that there is a benefit to identify the critical pipe which causes the
359
most discolouration risk. A particular pattern regarding the location of most critical
360
pipe could not be established in this research and needs further work.
361
Acknowledgement
362
The authors would like to acknowledge Water Corporation of Western Australia to
363
allow us to run the hydraulic model of the system presented in this paper.
364
365 366
References
367
Al-Ithari A., 2013. Evaluating and Improving the Tools for Predicting Discolouration
368
Event in Potable Water Supply System. Ph.D. thesis. School of Mechanical
369
Engineering-Department of Civil Engineering, Curtin University.
370
Australian
371
http://www.nhmrc.gov.au/_files_nhmrc/publications/attachments/eh34_adwg_11_06.
372
Boxall, J.B., Saul, A.J., Skipworth, P.J., 2001. A novel approach to modelling
373
sediment movement in distribution mains based on particle characteristics. Water
374
Software Systems, pp. 263-273.
375
Fisher, I., G. Kastl, A. Sathasivan and V. Jegatheesan (2011) Suitability of chlorine
376
decay models for planning and management of water distribution systems: A Review,
377
Critical Reviews in Environmental Science and Technology. 41(20), pp 1843-1882
378
Gauthier, V., Portal, J.M., Rosin, C., Block, J.C., Cavard, J. and Gatel, D., 1997. How
379
good are water distribution systems for transport of particulate matter? Proc. Am.
380
Water Works Assoc., Water quality Technology Conference, Denver, Co., USA.
381
Gauthier, V., Portal, J-M., Yvon, H., Rosin, C., Block, J-C., Lahoussine, V.,
382
Benabdallah, S., Cavard, J., Gatel, D. and Fass, S., 2001. Characterization of
383
suspended particles and deposits in drinking water reservoirs. Water Science and
384
Technology: Water Supply, Vol. 1, No. 4, pp. 89-94.
385
Gauthier, V., B. Gérard, JM. Portal, JC. Block, D. Gatel, 1999. Organic matter as
386
loose deposits in a drinking water distribution system, Water Research, Volume 33,
387
Issue 4, Pages 1014-1026, ISSN 0043-1354.
Drinking
Water
Guideline
(ADWG),
2004.
388
Huiyan Tong, Peng Zhao, Hongwei Zhang, Yimei Tian, Xi Chen, Weigao Zhao, Mei
389
Li, 2015. Identification and characterization of steady and occluded water in drinking
390
water distribution systems, Chemosphere, Volume 119, Pages 1141-1147.
391
Husband, P. S. and Boxall, J. B., 2010. Field Studies of Discoloration in Water
392
Distribution Systems: Model Verification and Practical Implications. Journal of
393
Environmental Engineering, Vol. 136, No. 1, pp. 86–94.
394
Husband, P. S. and Boxall, J. B., 2011.Asset deterioration and discolouration in water
395
distribution systems. Water Research, Vol. 45, pp. 113–124.
396
Husband, P. S., Boxall, J. B., and Saul A. J., 2008.Laboratory studies investigating the
397
processes leading to discolouration in water distribution networks. Water Research,
398
Vol. 42, pp. 4309–4318.
399
Jayaratne A, Ryan G, Grainger C, Wu J, Noui-Mehidi M N, 2004. Modelling of
400
particles in water supply systems. Water, Vol. 31, No. 8, AWA.
401
Kivit C. F. T., 2004. Origin and behaviour of particles on drinking water networks. M.
402
Sc. Thesis report. Civil Engineering, Delft University of Technology.
403
Kris, J. and Hadi, Ghawi A., 2008.CFD Investigation of particle deposition and
404
resuspension in a drinking water distribution system. Slovak Journal of Civil
405
Engineering, Vol. 1, pp. 1-7.
406
Neilands K., Bernats M., and Rubulis J., 2012. Accumulation and modelling of
407
particles in drinking water pipe fittings. Drinking Water Engineering and Science,
408
Vol. 5, pp. 47–57.
409
Peltier, S., Cotte, M., Gatel, D., Herremans, L., Cavard, J., 2003.Nanofiltration:
410
improvements of water quality in a large distribution system. Water Science and
411
Technology: Water Supply, Vol. 3, No.1-2, pp. 193-200.
412
Polychronopolous, M, Dudley K, Ryan, G, Hearn J., 2003. Investigation of factors
413
contributing to dirty water events in reticulation systems and evaluating of flushing
414
methods to remove deposited particles, Water Science and Technology: Water Supply,
415
Vol. 3, No.1-2, pp. 295-306.
416
Qing W., 2006. Drinking water distribution system sediment resuspension
417
characteristics study - New application of Jar test. M. Sc. Thesis. Department of Water
418
Management Faculty of Civil Engineering. Delft University of Technology.
419
Slaats P.G.G, Rosenthal L.P.M, Vreeburg J.H.G., 2003. Processes involved in the
420
generation of discoloured water. AwwaRF 2003.
421
Subramaniam V., 2010. Addressing discoloration of drinking water problems in
422
distribution systems. Discolouration of drinking water: an old problem clarified,
423
Water 21.
424
Vreeburg, J., 2010. Discoloration in drinking water systems: The role of particles
425
clarified. IWA Publishing, London, UK.
426
Vreeburg, J.H.G. and Boxall, J. B., 2007. Discolouration in potable water distribution
427
systems: A review. Water research. Vol. 41, pp. 519-529.
428
Wricke B., Henning L., Korth A., Vreeburg J., Schaap P., Osterhus S., Juhna T.,
429
Hammes F., and Coelho S., 2007. Particles in relation to water quality deterioration
430
and
431
https://www.techneau.org/fileadmin/files/Publications/Publications/Deliverables/D5.5
432
.1.pdf
433
Yarra Valley water. Drinking water quality report 2012/2013.
434
http://www.yvw.com.au/yvw/groups/public/documents/document/yvw1004001.pdf
435 436
problems
in
the
network.
Techneau,
28.