Intermittent water supply is one of the impediments which gets in the way of achieving the Millennium Development Goals in developing countries. In India no city provides 24×7 continuous water supply to their residents. There have been many endeavours to achieve this most challenging task. But the high population density coupled with unplanned distribution system and laxity in water loss management has been the reasons that are not allowing achieving this important hallmark.
INTRODUCTION
India is the seventh largest country by geographical area and, the second most populous country. It is estimated that half of the Indian population will live in urban areas by 2050. Despite mammoth efforts of governments, a large portion of urban population especially poor still lack potable water supply. In India, 86 % urban population has access to safe drinking water, but only 63 % have access to the tapped water. Even though a target of 135 liters per capita per day (LPCD) has been set, average per capita water supply ranges between 57 to 160 LPCD. In slum areas, the average supply attains a lower value of mere 27 LPCD, which results in poor level of service constituting serious health risks. One of the important causes of poor service in many South Asian cities is the intermittent water supply. Presently no Indian city gets 24×7 water supply. Status of water supply in terms of per capita supply and hours of supply of some of Indian cities is shown in Table. Even though urban access to water and sanitation is better than rural, meeting the ever increasing demand from urban areas along with protecting the environment is a daunting task and is certain to emerge as one of the most serious challenges in times to come (indiawaterportal.org).
The fundamental objective of an urban water service is to supply adequate and safe wholesome water efficiently and effectively at an affordable price so that the citizens are released from the drudgery of seeking their daily water. In case of India and other developing countries, water service providers do not meet this basic objective due to an intermittent water supply, which is a piped water supply system that delivers water to its users for less than 24 hours in a day. 24×7 continuous, pressurised water supply overcomes shortcomings of intermittent supply and ensures customer convenience and benefits the poor. Continuous high quality water supply system has a number of benefits.
OBJECTIVE OF PRESENT STUDY
Objective of this article is to describe the methodology that is best suited in Indian scenario which is required to achieve 24×7 continuous water supply. The approach can help cities in India and in developing countries to enhance public health of the poor masses and thus attain Millennium Development Goals set by the United Nations.
APPROACH AND THE CASE STUDY
Badlapur city (Figure 1) in Mumbai Metropolitan Area has a population of 0.16 million. It has an assured water source (Figure 2) of Ulhas river. Ample water is available to meet future demand; water supply rate is 170 liters per capita per day (LPCD).
Population of the city spread over an area of 68 square kilometers.
There are 11,700 house connections in total 34 wards of the city. Before embarking upon the hydraulic model initiative, the system was operated in an intermittent mode and water was supplied in various zones for three hours a day.
Demerits of the present system are as follows:
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Individual domestic storage is inevitable;
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For housing societies, individual building etc., underground storage tanks are required;
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Water supply in a limited time span leads to possibility of ‘no supply’ to poor hamlets;
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Due to intermittent water supply, pipelines remain as hollow conduit in no supply time zones;
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Possibility of injection of contaminated water through joints/leakages in no supply period;
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Consumer’s tendency to prefer fresh water, and therefore, to let away the balance storage.
Stages Adopted for Transformation to 24×7 Water Supply System
The scheme is under intermittent operation mode since last decade. A large number of property connections have been issued without proper hydraulic study of the network. As a result, the daily operation of water supply is carried out by operating the valves zone wise. A fleet of valve operators are required to perform this job. The system which is, therefore, being operated as an intermittent supply mode is performing low.
When it was decided to convert this intermittent system into 24×7 system, a holistic approach was adapted. Achieving continuous water supply is culmination of combined efforts of various strategies adopted for improving the water supply. The action plan of transformation is shown in Figure 3. Satellite image was procured and the entire city was digitised. The map showing road network, house properties (with house ID number) etc. was prepared in AutoCad drawing which was then used as backdrop of the hydraulic model. City Development Plan (CDP) was obtained from the Municipal Council. Water distribution network was plotted on CDP in AutoCad which was then superimposed on the digitised map. Population was forecasted by the density method.
Water distribution pipe network of Badlapur city was divided into 10 Operation Zones (OZ). Each OZ is further sub-divided into 3 to 4 District Metering Area (DMA)s so that each DMA contained not more than 1000 connections. Property survey was carried out to determine the number of people residing in all 28,000 houses. Thus demand at nearest node was computed which was then compared with the earlier population figure computed by the density method.
Distribution network has been simulated using latest WaterGem software and hydraulic model was prepared. The data was validated and the pipe network was calibrated.
The Model
Modeling of the transformation of intermittent to 24×7 systems is a critical part of designing for successful operations of OZ and DMAs so that the distribution system serves the community reliably, safely and efficiently 24 hours in a day. The hydraulic model gives commanding knowledge of the water infrastructure, and helps to take informed decisions. Modeling is defined as a mathematical description of a real-world system.
Maps and records: System maps help in understanding the water distribution networks. These maps illustrate wide range of system characteristics such as pipeline alignment, elevations of nodes, location of tanks, reservoirs and valves etc.
A vast data, describing real-world network system, is collected before building a model. The maps are tested for accuracy and were corrected and synchronised with the GPS system. The source of the barrage, along with the Ulhas river is shown on the drawing. Water transmission pipelines were then skeletonised, marked and the positions of water treatment plants, master balancing tanks and the elevated service reservoirs and the entire distribution system in the Badlapur city were plotted on the AutoCad drawing. This drawing was then converted to the Drawing Exchange Format (DXF) format and was used as a backdrop of the WaterGems scaled drawings as shown in Figure 4.
System Simulation
While making hydraulic model, various components of the network such as reservoir, tanks, pipelines and valves etc. are required to be simulated. The term simulation refers to the process of imitating the behaviour of one system through functions of another. In the present approach, the term simulation represents the behaviour of the real system (model) mathematically.
Here simulation is used to represent dynamics of existing and proposed networks in the Badlapur city, which helps to predict the system response while transforming the system into 24×7.
Modeling of Base Scenario and Child Scenario of OZs and DMAs
The transformation study involves modeling and the various possibilities of demarcating the operation zones and DMAs.
Infrastructure of entire city water supply including those of all pipelines and the valves are plotted on the backdrop drawing. Then the network is calibrated with respect to field information. Demarcating the operation zones have been carried out with respect to anticipated consumer behaviour and storage capacities. Further the demarcation of DMAs and the improvement measures are modeled.
Operational Zone: Schematic arrangement of a big sector of distribution system called as operational zone is shown in Figure 5.
Source supplies water to the water treatment plant. Treated water is stored into balancing reservoir, which supplies water to various service reservoirs. OZs are demarcated from the consideration of critical study of storages of the service reservoirs and consumer withdrawal pattern. A service reservoir supplies water to the operational zone. The operational zones are the most strategic blocks for transformation into 24×7 system. Badlapur city is divided into 10 such operational zones.
Need of Alternatives: In the simulation study vast datasets need to be created and handled, large numbers of model runs are required and also recording of their results. It is not possible to create various data files to edit input data in each data file. Working either with many data files or editing frequently with single data file is confusing, inefficient and susceptible to the human errors. Hence, to solve this problem alternative data sets are kept with single model data file. The alternative data sets individually represent exclusive information on network. For the purpose of present study of 24×7 three alternative datasets (Figure 7) are considered. They are namely, (a) Active Topology– Physical representation of the system and its properties; (b) Demand – Various types of demands of the network; (c) Operation – Valves, their setting and operations.
Now to depict the actual/expected behaviour of the system, various scenarios are created. Scenario represents a set of models that describe character of network under specifi ed conditions. They are created for the present working conditions as well as for future population. Formation of Base Scenario: Modeling the base scenario is carried out to represent the actual functioning of the system before taking up any improvements. It is most critical and time consuming step. It involves modeling the entire transmission and distribution networks, the valve operations as set in the fi eld. All the three alternatives of active topology, demand and the operational alternatives are made available to the base scenario (Figure 7).
Once the Base Scenario is prepared and appropriately calibrated then it is suitably divided in OZs. The base scenario is then separated into various child scenario (Figure 8) for each operation zone by making elements of other operation zones inactive and making active the elements of the operation zone under consideration. Thus all child scenarios of active topology of all zones are built. All the three child alternatives of active topology, demand and the operational alternatives are formed from the base alternatives for each OZ and are again made available to their respected scenarios. The hydraulic network of scenario of each OZ is then solved and the results are checked as shown in Figure 9.Figure 9: r unning the model.
MODELING AND MANAGEMENT OF DMAS
Every DMA is hydraulically discrete (isolable) from adjoining area. It is fed with water from single point, the fl ow and pressures at key locations are continuously metered and measured, which give indication of extent of leakages as well as high fl ow rates. Leakages are then repaired; some pipes and ailing valves and old property connections in worst part of the distribution networks are replaced. Suitable control measures are adopted to keep a check on high fl ow rates. The DMA is then set for 24×7 continuous water supplies.
All the three child alternatives of active topology, demand and the operational alternatives for DMA are again derived from the base alternatives of each OZ (which were earlier derived from the base alternatives of entire city) and are again made available to their respected scenarios of DMA. The hydraulic network of scenario of each DMA is then solved and the results are checked. The present study is focused on the leakage rates by comparing the model results with the actual results in fi eld.
The model was used for taking decisions in fi eld. According to the model design OZ and DMAs are made hydraulically discrete at site of work. As per analysis carried out by the hydraulic model, new pipelines are laid, some old pipes are replaced. Using DMA methodology non revenue water (NRW) for each OZ and DMA was worked out. The OZ and DMA where NRW is maximum (profusely leaking) were tackled fi rst for leak detection and repair. Toll free contact number is provided for consumer redressal. 8 Wards out of 34 Wards tackled in fi rst phase for 24×7 water supply system. Rest of the areas will be covered in two phases. The results of the initiative pre-project and post-project are shown in Table 2.
SUMMARY
- A hydraulic model for transforming intermittent water supply to 24×7 continuous water supply was prepared for the fi rst time in India which is used for the city of Badlapur.
- The model described simulated behaviour of system and particularly helped Maharashtra Jeevan Pradhikaran (MJP) engineers to hydraulically isolate the operation zones (OZ) as well as district metering areas (DMA).
Merely by hydraulically discreting OZ and DMAs, and repairing visible leaks, they were able to transform water supply of 8 wards (out of 34 wards) into 24×7 continuous water supply. - The model so prepared has been proved to be very useful tool for metering strategy.The number of costly bulk meters used for determining net night fl ow are optimised by this unique model. INR eight million were saved using this model.
- Using the model for transformation to 24×7 system helped MJP to increase revenue and improve service delivery.
- The approach presented in this article can help cities in India and in developing countries to achieve 24×7 continuous water supply.
REFERENCES
- Chary, 2005, “24- Hour Water Supply: A Goal Achievable?”, Nagari, A Publication of ASCI,Hyderabad.
- Haested, Walski and et al, “Advanced Water Distribution Modeling and Management,” Haested Methods, First Edition, 2003.
- A Report of World Bank, October 2005.
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