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Table 1a: Score table for leakage frequency, normalised to: no./100 meter /10 year


From [no./100 m/10 year]

To [no./100 m/10 year ]

Score (LF)

3.5

1000

6

1.7

3.5

5

1.2

1.7

4

0.7

1.2

3

0.7

1.2

2

0

0.7

1



Pipe age

Age in it self is not considered to cause an increase in probability for leakages to occur. Age is anyway an important factor for the model and it must be determined for all water mains in the distribution network. In the software tool, age either serve as secondary information in order to classify another parameter (as is the case for the Pipe Material parameter), or is used indirectly to estimate an otherwise undetermined parameter (as is the case for the Excavation Method)


About 1/3 of the water mains in the pilot area lack information on age, therefore this information had to be established. This was done by gathering the public work veterans from the municipalities around a map. Thereby it was possible to determine with sufficient certainty the age of water mains for which this information was lacking.

Pipe material (PM)
Pipe material is considered to be another important probability parameter for identifying water mains for rehabilitation. This parameter uses age as a secondary parameter to give an indirect indication on type of joints and corrosion protection.
For municipal water mains, information on material is generally available, while information on type of joints and corrosion protection are missing.
Table 2: Score table for material



Material

From year

To Year

Score (PM)

Gray cast iron

0

1913

5

Gray cast iron

1914

1940

4

Gray cast iron

1941

1960

3

Gray cast iron

1961

1970

2

Ductile cast iron

1960

1974

2

Ductile cast iron

1975

2010

1

Iron (type unknown)

0

1913

5

Iron (type unknown)

1914

1940

4

Iron (type unknown)

1941

1960

3

Iron (type unknown)

1961

1968

2

Steel

0

1960

4

Steel

1961

1970

2

Steel

1971

2010

1

PVC

0

1973

4

PVC

1974

1978

2

PVC

1979

2010

1

PE

0

1973

4

PE

1974

2010

1

PEL

0

2010

4

Unknown1)

0

1913

5

Unknown1)

1914

1940

4

Unknown1)

1941

1960

3

Unknown1)

1961

1974

2

Unknown1)

1975

2010

1

Asbestos

0

1970

3

Asbestos

1971

2010

2

1) When the project started the type of material for some of the water mains were unknown, but during the project a discussion and assumption was made, and at the end of the project, the material type was established for all water mains in the pilot area.

Excavation method (PEM)
When the use of excavator was introduced, the handling of the water mains became less careful, resulting in increased damage to the pipe and the pipe protection. New directions and improved pipe protection have reduced this problem, and it is believed that this problem is minor today. Generally information about excavation method is not registered in the GIS system or any other easily available source. Age is therefore used as an indirect method to determine the method of trenching that had been used.
Table 3: Score table for excavation method


Excavation method

From year

To Year

Score (PEM)

Digging by hand

0

1950

0

Digging by excavator

1951

1975

3

Digging by excavator

1976

1980

1

Digging by excavator

1981

2010

0

Placement method (PPM)
It is generally considered that placement method is an important parameter in forecasting the probability for leakage. Unfortunately very little information is registered over time about placement method. Furthermore age is not a good indirect parameter, because varying techniques have been used during most of the times. However, for a single and important t
Figure 3: Pipes supported by wooden planks
echnique, some information may be drawn from the information of cause for the leakages, namely the use of wooden planks to support the pipe-ends before backfilling the trench.


Table 4: Score table for Placement method



Method

Score (PPM)

Pipes supported by wooden planks

5

It is clear that further development of this parameter may improve the model. Indicating where wooden planks have been used would improve the model considerably. The use of wooden planks has two serious consequences: a) Source of organic material that promote SRB corrosion under anaerobic soil conditions, b) When the wood deteriorates and rots the pipe foundation is destroyed and the risk of pipe fractures increase.



Consequence criteria

These parameters are used to define the importance of a water main section. It is clear that the more important a water main is with regard to how many people that are served, the type of customers, the possibility for rerouting the water supply etc. the sooner the water main should be rehabilitated.


Pressure, flow and flow direction
It is the intension that the selection tool should use hydraulic modelling for the calculation of the consequence of bursts on pressure and water flow to customers. Unfortunately the hydraulic model is not yet fully established (this is an ongoing project), and therefore it has not been possible to get reliable data on pressure and flow to customers affected by broken water mains. In the current version of the tool, the hydraulic model have only been used to calculate how many people have interruptions in their water supply caused by pipe bursts.
Number of people loosing their water supply due to pipe burst (CP)
Table 5: Score table for number of people losing water supply in case of pipe bursts.



People from [no.]

People to [no.]

Score (CP)

101

50000

6

61

100

5

31

60

4

11

30

3

6

10

2

0

5

1


Supply to vulnerable customers. (CVCF)
Vulnerable customers are defined as customers to whom continuous water supply is crucial. Vulnerable customers are divided in 3 categories

Category1: Very vulnerable customers (Hospitals etc.)

Category2: highly vulnerable customers (Food processing business, Schools)

Category3: Vulnerable customers (Hotels and nursery)


The number of vulnerable customers is therefore not used directly, instead a vulnerable customer factor (VCF) is calculated using the following formula:


VCF = 3*Category1 customers + 2* Category2 customers + Category3 customers.
Table 6: Score table for VCF


VCF from [no.]

VCF to [no.]

Score (CVCF)

5

1000

6

3

4

5

1

2

4


Rehabilitation factor (RhF)

Given the score tables, the rehabilitation factor for each water main is calculated according to the following formulas:


Calculating probability score (PS):


Table 7: Default weights for calculating Probability Score (PS)


Weight factor

Symbol

Default value

Leakage frequency

WLI

3

Pipe material weight

WM

1

Placement method

WPM

2

Excavation method

WEM

1

Calculating consequence score (CS):





Table 8: Default weights for calculating Consequence Score (CS)


Weight factor

Symbol

Default value

People

WP

1

Vulnurable Customer Factor (VCF)

WVCF

1


Calculating rehabilitation factor (RhF)





Table 9: Default weights for Rehabilitation factor (RhF)


Weight factor

Symbol

Default value

Risk weight

WPR

1

Probability weight

WPS

2



Results and experiences:
The pilot area
The area “Åssiden” in the city of Drammen was selected as pilot area for testing the water main selection tool. As shown on the map in Figure 4, the water mains were installed in the period for 1950 to 1980. It is known that there are problems in this area with both the water mains and the sewers. This opens up for coordination when the rehabilitation programme is planned.

Figure 4: Pilot area for the selection tool. “Åssiden” In the city of Drammen”
Most pipes are installed between 1950 and 1980.





The result
The result for the calculation is a map Figure 5 with water mains in colours representing the Rehabilitation Factor (RhF) calculated for each water main by the selecting tool and. The results can also be found in a table that in addition includes more details about individual parameter scores.
The rehabilitation factor fall in 5 classes:
1: Very low Rehabilitation is not needed

2: Low


3: Middle Rehabilitation should be included in long term planning

4: High


5: Very High Rehabilitation should seriously be considered on a short term view


Figure 5: Pilot area with water mains coloured according to the calculated Rehabilitation factor. Red circles show areas were the selection tool has identified water mains with a high Rehabilitation Factor (Indicating that the water main should be rehabilitated in a short horizon)


A detailed view Figure 6 on the content of the larger red circle in Figure 5, show an area with 5 water mains with an RhF larger than 4, and therefore candidates for rehabilitation.



1

2


Figure 6: Detailed view from the finale calculation. It shows 5 water mains with an RhF score ≥ 4.
The score only indicates which water mains that should be target for rehabilitation on a short time horizon. It’s up to the municipal engineers to decide whether or not the water main should be subject to complete replacement (1) or to point repair (2). The municipal engineer must also decide on the method of rehabilitation (Traditional or No dig)

The calculated rehabilitation factor do not by itself dictate which water main that is the first candidate for rehabilitation, but the rehabilitation factor can be used by the municipalities as an indicator when elaboration rehabilitation project plans. Whether or not a water main should be rehabilitated is still subject to coordination with other infrastructure projects in the same area, as for instance sewer projects or road projects. If no coordination is possible, investigation of the water main should be carried out to reveal whether a “no-dig” method for the rehabilitation is the right choice.
The dispersion of leakages on the water main can reveal whether the water main should be replaced in full, as for instance the water main in circle 1 in Figure 6, or be point repaired as could be the case for the water main in circle 2.

Conclusions

The tool has proved to be a help for the engineers in the water sector. The selection of water mains for rehabilitation has moved from a pure defensive strategy (selecting the water mains with the highest number of leakages) to a slightly more proactive strategy where also water mains with otherwise high probability for a leakage and strategic importance are selected for rehabilitation.


The input is based on readly available information. The only improvement needed in data quality, was to ensure that all water mains had an “age” attribute set, a task that at first might look difficult, but actually showed to be possible through the veterans “workshop”.

Further work

Thought we have established a tool that can be used today, plans exists for future improvements, such as:




  • Extending the model to cover the full area of the region of Drammen. This will need a quality increase of the GIS system, in order to ensure that the water main criteria data, such as age, type of material and dimension are available for all mains in the water distribution network. This will give us more experience with the use of the tool, and ensure that we over time will find the right parameters.



  • Improve the input from hydraulic models. In the current version of the tool, hydraulic modelling is used only to calculate the direction of flow. Calculation of the consequence of water main failures on pressure and flow might add new insight about the consequence factor which then can be used with greater confidence than it is the case today.




  • Improve the quality of the placement parameter. Collecting information about how water mains are actually placed in the trench may improve the predictions on where the next leakage will occur. For instance the mappings of pipes where wooden planks are used as pipe foundation are important. Also, information about the backfill material used might be important.

Long term improvements:


Another improvement which can be done in the future is to coordinate with other utilities as for instance sewer, traffic load, soil conditions, importance of the road etc. This could be done by developing a similar tool for the sewer mains, for roads etc. and then put the result from the different utilities together for a complete rehabilitation program. If then a sewer main is present, and the water main needs rehabilitation, it might be more practical to use a traditional excavation method. If no sewer exists or the sewer is not subject for rehabilitation one might consider using a no-dig method for the rehabilitation of the water main.

References

Farly, M., Trow, S. (2003) Losses in Water Distribution Networks. IWA Publishing. ISBN 1 900222 11 6, 


282 pages.
Le Gauffre P., Laffréchine K., Baur R., Di Federico V., Eisenbeis P., König A., Kowalski M., Sægrov S., Torterotot J.P., Tuhovcak L., Werey C., (2002) Care-W: WP3 – Decision support for annual rehabilitation programmes. D6 – Criteria for the prioritisation of rehabilitation projects. Care-W ( Computer Aided Rehabilitation of Water networks), EU project under the 5th Framework Program, contract no. EVK1-CT-2000-00053. Lyon (F): INSA-URGC, June 2002, 72 pages.
Le Gauffre P., Baur R., Laffréchine K., Miramond, M., (2002) Care-W: WP3 – Decision support for annual rehabilitation programmes. D7 – Survey of multi-criteria techniques and selection of relevant procedures. Care-W ( Computer Aided Rehabilitation of Water networks), EU project under the 5th Framework Program, contract no. EVK1-CT-2000-00053. Lyon (F): INSA-URGC, June 2002, 30 pages.
Moen, A.D., Dupont, R. A., Skaret, J.E., Røren, T., (2008) Practical Regional cooperation in the Water Supply sector between 9 Local Municipalities/Councils. Paper presented to the 6th Nordic Water Supply Conference in Oslo june 2008.
The Municipalities of the Region Drammen (2005). Quality Water - The Master plan for the region of Drammen (2005-2020). 42 pages, (In Norwegian)


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