Document Type : Original Article


1 Department of Water, Wastewater and Environmental Engineering, Faculty of civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran

2 Department of Water Resources Engineering, Faculty of civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran


One of the challenges facing water and wastewater companies around the world is water loss from water distribution networks following after burst and leakage, which imposes high economic, social and environmental costs on these companies. So every year, a large part of the budget of water and wastewater companies is allocated for repair and rehabilitation of the pipe network. Therefore, knowing the burst frequency will help to estimate network leakage and select appropriate management strategies for leakage. Various factors affect the failure of water distribution pipes, one of the most important factors of these is water pressure. Therefore, the development of models to predict precisely failure based on effective factors is necessary to achieve optimal leakage management in water distribution networks.
Materials and methods:
In the present study, using a developed model and Pressure and burst field data analysis in urban water distribution network, the relationship between pressure and burst rate for a district of Tehran has been determined. The study area has 516 km of main pipelines that include many types of material like polyethylene, ductile iron, steel, PVC and asbestos cement. Both polyethylene and ductile iron pipes were selected for the investigation because they consist 93 percent of the network length. After collecting and revising the statistics and information about the burst and pressures recorded during the years 1386 to 1395, we calculate the average zone point and the pressure index at this point and assigning it to the whole area. At last the pressure-burst relation for each material of the pipes were presented individually. The prediction model of the failure consists of two parts including independent and dependent parts which the pressure parameter is linked through a power component to the failure rates. In this study, the maximum daily pressure at the average zone point was used as a pressure index in the pressure-burst relationship.
Results and discussion:
Pressure-burst relationship for polyethylene and ductile iron based on maximum daily pressure index is presented separately. In the obtained relationships for comparison, both average of maximum daily pressure and maximum of maximum daily pressure values were used. The results of this study showed that in the dependent pressure part, average of maximum daily pressure index presents a more accurate result in comparison with the maximum of maximum daily pressure index and has a higher correlation coefficient. The cause of the inappropriateness of the maximum of maximum daily pressure can be temporary and impermanent overload in one or more days of the year. As it may not really have caused a failure but has been involved in the calculation; therefore, this index does not have an accurate prediction of burst.  Also, the relations are obtained for two condition with a power pressure of 3 and an unknown situation, which indicates that, in the case of unknown power, higher correlation coefficients are obtained such that for polyethylene the power is equal to 3 and Correlation coefficient = 0.97 and for ductile iron, the power was equal to 2.7 and  correlation coefficient =0.99.
According to the obtained relationships, it can be concluded that the pressure-burst model could well predict the number of failure of main pipes in the water distribution networks. The results also showed that the pressure variations affect on burst frequency in the polyethylene more than the ductile iron and The exponent of pressure in the failure prediction model is also depends on the pipe material and is larger for polyethylene in comparison with ductile iron material, and the average of maximum daily pressure index was a more accurate indicator in the failure prediction model. According to the result of this paper we can improve pressure management and rehabilitation strategies for reduction burst frequency. By applying accurate pressure management and Awareness of material susceptibility to burst, it is possible to reduce failure rate and consequently, water loss.


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