1. A method of managing leakage in a liquid distribution network, comprising: identifying, by the leakage management system, one or more critical nodes from plurality of nodes in each of one or more zones in a network model of a liquid distribution network; connecting, by the leakage management system, a pseudo critical node in the network model, for each of the one or more zones, with the one or more critical nodes of respective zone; determining, by the leakage management system, a target pressure at the pseudo critical node of each of the one or more zones, based on real-time pressure values at the one or more critical nodes in the corresponding zone; and controlling, by the leakage management system, at least one Pressure Reducing Valve (PRV) associated with each of the one or more zones to obtain the target pressure at respective pseudo critical node, for managing leakage in the liquid distribution network.

2. The method as claimed in claim 1 further comprising sectorizing the network model to obtain the one or more zones, wherein sectorizing the network model is performed based on number of PRVs and location of PRVs in the liquid distribution network.

3. The method as claimed in claim 1, wherein identifying the one or more critical nodes in a zone from the one or more zones comprises: identifying a node in the liquid distribution network, associated with at least one of maximum elevation and farthest distance from source of the liquid distribution network, to be one of the one or more critical nodes in the zone; throttling at least one PRV in the zone to obtain a predefined pressure at the identified node; checking for pressure at one or more other nodes, apart from the identified node, to be lesser than a first predefined pressure value; and identifying at least one node from the one or more other nodes, with corresponding pressure lesser than the first predefined pressure value, to be the one or more critical nodes in the zone.

4. The method as claimed in claim 1, wherein identifying the one or more critical nodes in a zone from the one or more zones comprises: monitoring pressure at plurality of nodes in the liquid distribution network in relation to variation in demand associated with the liquid distribution network over a predefined period of time; and identifying one or more nodes from the plurality of nodes, with pressure lesser than a second predefined pressure value, during the predefined period of time, to be the one or more critical nodes.

5. The method as claimed in claim 1, wherein the pseudo critical node is connected in the network model, with corresponding critical nodes in the zone with a predefined elevation and a predefined demand.

6. The method as claimed in claim 5, wherein the predefined elevation is elevation greater than that of the one or more critical nodes in the zone.

7. The method as claimed in claim 5, wherein the predefined demand for the pseudo critical node is minimum value of demand selected to provision flow of liquid in the liquid distribution network towards the pseudo critical node, without generating very low pressures in the network model.

8. The method as claimed in claim 1, wherein the target pressure at the pseudo critical node is determined to maintain minimum value of required pressure at the one or more critical nodes in the corresponding zone.

9. The method as claimed in claim 1, further comprising identifying location of the one or more critical nodes to be location of one or more pressure sensors to be placed in the liquid distribution network, for controlling pressure in the liquid distribution network.

10. A leakage management system for managing leakage in a liquid distribution network, comprises: a processor; and a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, cause the processor to: identify one or more critical nodes from plurality of nodes in each of one or more zones in a network model of a liquid distribution network; connect a pseudo critical in the network model, for each of the one or more zones, with the one or more critical nodes of respective zone; determine a target pressure at the pseudo critical node of each of the one or more zones, based on real-time pressure values at the one or more critical nodes in the corresponding zone; and control at least one Pressure Reducing Valve (PRV) associated with each of the one or more zones to obtain the target pressure at respective pseudo critical node, for managing leakage in the liquid distribution network.

11. The leakage management system as claimed in claim 10 further comprises the processor configured to sectorize the network model to obtain the one or more zones, wherein the network model is sectorized based on number of PRVs and location of PRVs in the liquid distribution network.

12. The leakage management system as claimed in claim 10, wherein the one or more critical nodes in a zone from the one or more zones is identified by: identifying a node in the liquid distribution network, associated with at least one of maximum elevation and farthest distance from source of the liquid distribution network, to be one of the one or more critical nodes in the zone; throttling at least one PRV in the zone to obtain a predefined pressure at the identified node; checking for pressure at one or more other nodes, apart from the identified node, to be lesser than a first predefined pressure value; and identifying at least one node from the one or more other nodes, with corresponding pressure lesser than the first predefined pressure value, to be the one or more critical nodes in the zone.

13. The leakage management system as claimed in claim 10, wherein the one or more critical nodes in a zone from the one or more zones is identified by: monitoring pressure at plurality of nodes in the liquid distribution network in relation to variation in demand associated with the liquid distribution network over a predefined period of time; and identifying one or more nodes from the plurality of nodes, with pressure lesser than a second predefined pressure value, during the predefined period of time, to be the one or more critical nodes.

14. The leakage management system as claimed in claim 10, wherein the pseudo critical node is connected in the network model, with corresponding critical nodes in the zone with a predefined elevation and a predefined demand.

15. The leakage management system as claimed in claim 14, wherein the predefined elevation is elevation greater than that of the one or more critical nodes in the zone.

16. The leakage management system as claimed in claim 14, wherein the predefined demand for the pseudo critical node is minimum value of demand selected to provision flow of liquid in the liquid distribution network towards the pseudo critical node, without generating very low pressures in the network model.

17. The leakage management system as claimed in claim 10, wherein the target pressure at the pseudo critical node is determined to maintain minimum value of required pressure at the one or more critical nodes in the corresponding zone.

18. The leakage management system as claimed in claim 10, further comprises the processor configured to identify location of the one or more critical nodes to be location of one or more pressure sensors to be placed in the liquid distribution network, for controlling pressure in the liquid distribution network. , Description: TECHNICAL FIELD The present subject matter is related in general to liquid distribution networks, more particularly, but not exclusively to method and system for managing leakage in a liquid distribution network. BACKGROUND A water utility industry is made up of domestic entities responsible for safe and timely distribution of water and other related services, such as water and wastewater treatment. Most of water utilities around the world are under tremendous stress to prevent loss of treated water in the water network. Leakage leads to loss of water, as well as revenue for water utilities. Due to reducing water resources around the world, gap between demand and supply of water is widening. Also, leakage in turn adversely affect said gap, by reducing the amount of supply available for consumer use. Leakage may affect water quality integrity of respective water distribution network by leading to contaminant intrusion into the water distribution network during low pressure conditions. Aging infrastructure, frequent pressure fluctuations, low structural strength at joints of the water distribution network, theft and so on, may leads to water loss from the water distribution network as leakage. Such problems may not be faced in water distribution networks but may also be faced any liquid distribution network. It may be known that pressures in the liquid distribution network have a direct relationship with leakages in the liquid distribution network. In case of a network with cracks or breakage in the pipes, or loose joints, increased pressures in the network will lead to loss of excess water through these apertures. Also, very high pressures in the liquid distribution network may lead to breakages and burst in pipelines. Hence, pressure reduction may be used to check pipe bursts. Also, pressure management is found to reduce consumption in water network efficiently. Some of common methods for reducing leakage in the liquid distribution network include pressure management and pipe replacement. Leakages are completely removed when pipes are replaced, unlike as in pressure management where it is only reduced. However, with respect to cost, installation time and Operation and Maintenance (O&M) activity, pressure management is better than pipe replacement. Especially if there are only background leaks in the liquid distribution network. Pressure management in the liquid distribution network is a widely used active leak control protocol for reduction of leakages in the liquid distribution network, especially background leakages in the water network. Reduction of pressure in the liquid distribution network can aid in reduction in the leakage. Pressure management in the liquid distribution network may be achieved by installing Pressure Reducing Valves (PRVs) in the liquid distribution network. The PRVs helps in reducing the water pressure in the liquid distribution network. The pressure at downstream node of a PRV will be equal to setting of the PRV and help in reducing overall pressure of the downstream network of the PRV. Pressure management may be a fixed outlet pressure profile-based pressure management or electronically operated control for pressure management. In fixed outlet pressure profile method, the downstream pressure setting is maintained as a constant value regardless of varying upstream pressures. To alter the pressure, the valve must be adjusted manually by changing the pressure setting on the valve. Electronically operated pressure controls may be performed using approaches including time modulation-based approach, flow modulation-based approach and remote node modulation-based approach. Out of said approaches, the remote node modulation is most popular and widely used approach. The remote node modulation is also known as critical node approach. In the remote node modulation-based approach, the pressures at the critical node of the liquid distribution network i.e., node with minimum pressure is monitored using a pressure sensor. Based on pressure at the critical node, the control PRV is regulated, such that the critical node pressure is minimal. But, such approaches may not help in maintaining a minimum pressure across the liquid distribution network, including the critical node, for demand satisfaction. Some of existing systems disclose to manage leakages disclose by sectorizing the liquid distribution network to multiple zones, and minimize average zonal pressures and pressure variability within a zone. Such systems provide controlling conditions within a liquid conduit system. Every single zone is controlled by one or more actuator valves. Minimization techniques may be used for minimization of the average zonal pressures and the pressure variability within a zone. However, such systems may be regarded as multi-objective approach and may be computationally expensive. Also, such systems depends on minimization of average zonal pressures in a network and real time field application of such systems may be a challenge. The information disclosed in this background of the disclosure section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art. SUMMARY In an embodiment, the present disclosure relates to a method of managing leakage in a liquid distribution network. For managing the leakage, initially, one or more critical nodes from plurality of nodes in each of one or more of zones in network model of the liquid distribution network, are identified. A pseudo critical node in the network model is connected, for each of the one or more zones, with the one or more critical nodes of respective zone. A target pressure is determined at the pseudo critical node of each of the one or more zones, based on real-time pressure values at the one or more critical nodes in the corresponding zone. At least one Pressure Reducing Valve (PRV) associated with each of the one or more zones is controlled to obtain the target pressure at respective pseudo critical node, for managing leakage in the liquid distribution network. In an embodiment, the present disclosure relates to a leakage management system for managing leakage in a liquid distribution network. The leakage management system comprises a processor and a memory communicatively coupled to the processor. The memory stores processor-executable instructions, which, on execution, cause the processor to manage the leakage. Initially, one or more critical nodes from plurality of nodes in each of the one or more zones in network model of the liquid distribution network, are identified. A pseudo critical node in the network model is connected, for each of the one or more zones, with the one or more critical nodes of respective zone. A target pressure is determined at the pseudo critical node of each of the one or more zones, based on real-time pressure values at the one or more critical nodes in the corresponding zone. At least one Pressure Reducing Valve (PRV) associated with each of the one or more zones is controlled to obtain the target pressure at respective pseudo critical node, for managing leakage in the liquid distribution network. The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description. BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, serve to explain the disclosed principles. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and regarding the accompanying figures, in which: Figure 1 shows exemplary environment of a leakage management system for managing leakage in a liquid distribution network, in accordance with some embodiments of the present disclosure; Figure 2 shows a detailed block diagram of a leakage management system for managing leakage in a liquid distribution network, in accordance with some embodiments of the present disclosure; Figure 3a-3f show exemplary embodiments for managing leakage in a liquid distribution network, in accordance with some embodiments of the present disclosure; Figures 4a-4b show exemplary embodiments for managing leakage in a liquid distribution network, in accordance with some embodiments of the present disclosure; Figure 5a shows a flow diagram illustrating method for managing leakage in a liquid distribution network, in accordance with some embodiments of present disclosure; Figures 5b and 5c show a flow diagrams illustrating methods for identifying one or more critical nodes in a liquid distribution network, in accordance with some embodiments of present disclosure; and Figure 6 illustrates a block diagram of an exemplary computer system for implementing embodiments consistent with the present disclosure. It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether such computer or processor is explicitly shown. DETAILED DESCRIPTION In the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however that it is not intended to limit the disclosure to the forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternative falling within the spirit and the scope of the disclosure. The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device or method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or method. The terms “includes”, “including”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device or method that includes a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “includes… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or method. In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings that form a part hereof, and in which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense. Present disclosure system and method for managing leakage in a liquid distribution network using pressure management approach. A pseudo-critical node-based pressure management is implemented by introducing a pseudo critical node in the network model of the liquid distribution network. By determining target pressure at the pseudo critical node, Pressure Reducing Valves (PRVs) associated with each of one or more zones of the liquid distribution network is controlled, by which the pressure is managed, and leakage is reduced. Figure 1 shows an exemplary environment 100 of a leakage management system 101 associated with a liquid distribution network 102. The liquid distribution network 102 may be configured to provision distribution of liquid in a physical environment. In an embodiment, the liquid distribution network 102 may be a water distribution network, sewer system, storm system or the like. The liquid distribution network 102 also be configured to monitor distribution of the liquid in the physical environment. Source of the liquid distribution network 102 may be connected to consumers via plurality of interconnected branches and joints. Each of the consumers may be denoted as a node in the liquid distribution network 102. In an embodiment, the liquid distribution network 102 may include plurality of nodes with are interconnected with each other and to the source of the liquid distribution network 102. Pressure and flow of the liquid at each of the plurality of nodes is monitored in the liquid distribution network 102. Along with monitoring the pressure and the flow, the liquid distribution network 102 may implement leak detection systems for detecting leakages of liquid in the liquid distribution network 102. Regular monitoring of leakage is essential in the liquid distribution network 102. Along with regular monitoring, managing of detected leakages help in efficient distribution of the liquid. The leakage management system 101 may be configured to manage the detected leakage in the liquid distribution network 102. The leakage management system 101 may include a processor 104, I/O interface 105 and a memory 106. In some embodiments, the memory 106 may be communicatively coupled to the processor 104. The memory 106 stores instructions, executable by the processor 104, which on execution, may cause the leakage management system 101 to manage leakage in the liquid distribution network 102. In an embodiment, the memory 106 may include one or more modules 107 and data 108. The one or more modules 107 may be configured to perform the steps of the present disclosure using the data 108, to manage the detected leakage in the liquid distribution network 102 as disclosed in the present disclosure. In an embodiment, each of the one or more modules 107 may be a hardware unit which may be outside the memory 106 and coupled with the leakage management system 101. The leakage management system 101 may be implemented in a variety of computing systems, such as a laptop computer, a desktop computer, a Personal Computer (PC), a notebook, a smartphone, a tablet, e-book readers, a server, a network server, and the like. For managing the leakage in the liquid distribution network 102, the leakage management system 101 may be configured to sectorize a network model of the liquid distribution network 102 into one or morezones. The network model may be mathematical model of the liquid distribution network 102. The network model may be used to analyze hydraulic behavior in the liquid distribution network 102. The network model for the liquid distribution network 102 may be determined using one or more techniques, known to a person skilled in the art. In an embodiment, the leakage management system 101 may be configured to determine the network model for the liquid distribution network 102. In an embodiment, the liquid distribution network 102 may implement a dedicated system for determining the network model of the liquid distribution network 102. The determined network model may be communicated with the leakage management system 101 for managing the leakage in the liquid distribution network 102. Using the network model, the liquid distribution network 102 may be sectorized into the one or morezones. In an embodiment, the liquid distribution network 102 may be sectorized based on number of PRVs and location of PRVs in the liquid distribution network 102. In an embodiment, the sectorization may be in such a way that each zone of the one or more zones may include at least one PRV. In an embodiment, the one or more zones may be formed by considering impact of PRVs on the plurality of nodes of the liquid distribution network 102. Each zone may include a single PRV or plurality of PRVs. In an embodiment, the network model received by the leakage management system 101 may already be sectorized or the network model may include a single zone. In such case, the step of sectorization may not be performed by the leakage management system 101. Upon sectorization, the leakage management system 101 may be configured to identify one or more critical nodes from plurality of nodes in each of the one or more zones. In an embodiment, the one or more critical nodes may be referred to as nodes which have major impact or are majorly impacted, due to leakages in the liquid distribution network 102. Leakage may be managed efficiently by managing pressure at the one or more critical nodes in the liquid distribution network 102. In an embodiment, the leakage management system 101 may be configured to identify the one or more critical nodes in a zone from the one or more zones by initially identifying a node in the liquid distribution network 102 which is associated with at least one of maximum elevation and farthest distance from source of the liquid distribution network 102. Such identified node may be referred to as one of the one or more critical nodes. Further, the leakage management system 101 may be configured to throttle at least one PRV in the zone to obtain a predefined pressure at the identified node. Upon throttling, pressure at one or more other nodes, apart from the identified node, is checked to be lesser than a first predefined pressure value. At least one node from the one or more other nodes, with corresponding pressure lesser than the first predefined pressure value is identified to be the one or more critical nodes in the zone. The initially identified node along with the nodes associated with pressure lesser than the first predefined pressure value constitute the one or more critical nodes of the zone. In an embodiment, the leakage management system 101 may be configured to identify the one or more critical nodes in a zone from the one or more zones by monitoring pressure at plurality of nodes in the liquid distribution network 102. The pressure may be in relation to variation in demand associated with the liquid distribution network 102 over a predefined period of time. Further, one or more nodes with pressure lesser than a second predefined pressure value, during the predefined period of time, may be identified to be the one or more critical nodes. In an embodiment, the leakage management system 101 may be configured to identify location of the one or more critical nodes to be location of one or more pressure sensors to be placed in the liquid distribution network 102. By placing the one or more pressure sensors at the location of the one or more critical nodes, accurate measurement and effective controlling of pressure in the liquid distribution network 102 may be achieved. Upon identifying the one or more critical nodes for each of the one or more zones, the leakage management system 101 may be configured to connect a pseudo critical node in the network model with the one or more critical nodes of respective zone. Each of the one or more zones may be associated with a pseudo critical node. In an embodiment, the pseudo critical node may be connected in the network model with a predefined elevation and a predefined demand. In an embodiment, the predefined elevation is elevation greater than that of the one or more critical nodes in the zone. In an embodiment, the predefined demand for the pseudo critical node is minimum value of demand selected to provision flow of liquid in the liquid distribution network 102 towards the pseudo critical node, without generating very low pressures in the network model. Further, the leakage management system 101 may be configured to determine a target pressure at the pseudo critical node of each of the one or more zones, based on real-time pressure values at the one or more critical nodes in the corresponding zone. In an embodiment, the target pressure at the pseudo critical node is determined to maintain minimum value of required pressure at the one or more critical nodes 209 in the corresponding zone. One or more techniques, known to a person skilled in the art, may be implemented to determine the target pressure. Upon determining the target pressure, the leakage management system 101 may be configured to control at least one PRV associated with each of the one or more zones. The leakage management system 101 controls the at least one PRV to obtain the target pressure at respective pseudo critical node. By obtaining the target pressure at the respective pseudo critical node, leakage at each of the one or more zones in the liquid distribution network 102 may be minimized and managed. In an embodiment, the leakage management system 101 may be a dedicated server or a cloud-based server in communication with the liquid distribution network 102. The leakage management system 101 may communicate with the liquid distribution network 102 via a communication network 103. The communication network 103 may include, but is not limited to, a direct interconnection, , a Peer to Peer (P2P) network, Local Area Network (LAN), Wide Area Network (WAN), wireless network (e.g., using Wireless Application Protocol), Controller Area Network (CAN), the Internet, Wi-Fi, and such. In an embodiment, the leakage management system 101 may be associated with plurality of liquid distribution networks, to manage the leakages at each of the liquid distribution networks. In an embodiment, the leakage management system 101 may communicate with each of the liquid distribution networks, via dedicated communication network. In an embodiment, the leakage management system 101 may be integral part of the liquid distribution network 102. The I/O interface 105 of the leakage management system 101 may assist in transmitting and receiving data. Received data may include, but is not limited to, the network model, real-time pressure values and so on. Transmitted data may include, but is not limited to, location and information of identifies one or more critical nodes, controlling of the at least one PRV and so on. One or more other data, which is associated with managing the leakage, may be received and transmitted via the I/O interface 105. Figure 2 shows a detailed block diagram of the leakage management system 101 for managing leakage in the liquid distribution network 102, in accordance with some embodiments of the present disclosure. The data 108 and the one or more modules 107 in the memory 106 of the leakage management system 101 may be described herein in detail. In one implementation, the one or more modules 107 may include, but are not limited to, a sectorization module 201, a critical node identification module 202, a pseudo critical node connection module 203, a target pressure determination module 204, a pressure sensor location identification module 205, a PRV control module 206 and one or more other modules 207, associated with the leakage management system 101. In an embodiment, the data 108 in the memory 106 may include network data 208, critical node data 209 (also referred to as one or more critical nodes 209), pseudo critical node data 210, real-time pressure data 211, target pressure data 212, PRV control data 213, predefined pressure data 214, pressure sensor location data 215 and other data 216 associated with the leakage management system 101. In an embodiment, the data 108 in the memory 106 may be processed by the one or more modules 107 of the leakage management system 101. In an embodiment, the one or more modules 107 may be implemented as dedicated units and when implemented in such a manner, said modules may be configured with the functionality defined in the present disclosure to result in a novel hardware. As used herein, the term module may refer to an Application Specific Integrated Circuit (ASIC), an electronic circuit, a Field-Programmable Gate Arrays (FPGA), Programmable System-on-Chip (PSoC), a combinational logic circuit, and/or other suitable components that provide the described functionality. The leakage management system 101 may be associated with the liquid distribution network 102 of any network configuration. The network configuration may be based on number of plurality of nodes, connectivity of each of the plurality of nodes with other nodes and source, demand values and elevation associated with the plurality of nodes and so on. Consider Figure 3a which shows an exemplary representation of the liquid distribution network 102. The liquid distribution network 300a may include a PRV 301 and plurality of nodes including a first node 302.1, a second node 302.2, a third node 302.3, a fourth node 302.4, a fifth node 302.5, a sixth node 302.6, a seventh node 302.7, a eight node 302.8, a ninth node 302.9 and a tenth node 302.10 (together referred to as the plurality of nodes 302.1….302.10). For the liquid distribution network 300a, the leakage management system 101 may be configured to manage the leakage in the liquid distribution network 300a. In an embodiment, the management of leakage include to minimize the leakage in the liquid distribution network 300a. The leakage may be minimized by maintaining the pressure at optimal values. Hence, pressure management may in-turn aid in management of leakage. In an embodiment, the liquid distribution network 300a may include one or more PRVs which are type of safety valves used to control or limit the pressure in the liquid distribution network 300a. Building-up of pressure, which may create upset in process of distribution, may be avoided by throttling the PRVs. For managing the leakage in the liquid distribution network 300a, the sectorization module 201 may be configured to sectorize the liquid distribution network 300a into the one or more zones. For sectorization, the sectorization module 201 may obtain the network data 208 associated with the liquid distribution network 300a. In an embodiment, the network data 208 may include but not limited to, network model, available demand and flow data, network connectivity data, number of PRVs, location of PRVs and so on of the liquid distribution network 300a. The network data 208 may be received from the liquid distribution network 300a and stored in the memory 106. Such network data 208 may be used for sectorization of the liquid distribution network 300a into one or more zones. In an embodiment, the one or more zones may be formed based on number and location of PRVs in the network. Pressures in each zone in the liquid distribution network 300a may be controlled by the respective PRV or PRVs. For the liquid distribution network 300a, PRV 301 is configured to control pressure in the liquid distribution network 300a and at the plurality of nodes 302.1….302.10. Consider, the plurality of nodes 302.1….302.10 along with the PRV 301 is identified to be a zone. Upon sectorization, the critical node identification module 202 may be configured to identify one or more critical nodes 209 from plurality of nodes in each of the one or more zones. In an embodiment, a critical node is defined as a node with minimum pressure at any instance of time. In an embodiment, the critical node may be related as a node with highest elevation and is farthest from the source. In the liquid distribution network 102, selecting a single critical node may be very difficult. There may be more than one node which have similar pressures in the liquid distribution network 102. Selecting one of these nodes as critical node and carrying out management of the leakage, as proposed in the present disclosure, may lead to pressures below acceptable range at the other node . Also, for instances when the critical node changes based on demand variation, it will be difficult to identify a single critical node. Hence, the critical node identification module 202 is configured to consider possible parameters to identify all the one or more critical nodes 209 in the liquid distribution network 102. One of the approach proposed herewith includes the critical node identification module 202 to identify a node based on topographical factors. In this approach, first iteration includes to identify node with maximum elevation and farthest distance from the source to be a critical node. Consider the liquid distribution network 300a shown in Figure 3b, the eight node 302.8 may be associated with highest elevation and farthest from source. Hence, the eight node 302.8 may be identified as a critical node. Further, the critical node identification module 202 may be configured to throttle the PRV 301 of the zone to obtain a predefined pressure at the eight node 302.8 i.e., the critical node of the zone. Upon throttling, pressure at the other nodes i.e., nodes 302.1-302.7, 302.9 and 302.10 is checked. In an embodiment, the pressure is checked to be lesser than the first predefined pressure value. Nodes which are associated with pressure lesser than the first predefined pressure value may be identified as other critical nodes. In case, there are no nodes with pressure lesser than the first predefined pressure value, it may be decided that there are no conflicting critical nodes in the liquid distribution network 102. If one or more nodes are identified to be associated with the pressure lesser than the first predefined value, it may be decided that there are more than one critical node in the liquid distribution network 300a. Figure 3c illustrates the liquid distribution network 300a with the ninth node 302.9 to be additional critical node. Hence, for the liquid distribution network 300a, the eight node 302.8 and the ninth node 302.10 may be identified to be the one or more critical nodes 209. In an embodiment, when the eight node 302.8 and the ninth node 302.10 are identified to be the one or more critical nodes 209, the critical node identification module 202 may be configured to throttle the PRV 301 of the zone to obtain the predefined pressure at the eight node 302.8 and the ninth node 302.9 i.e., the one or more critical nodes 209 of the zone. Pressure at other nodes i.e., nodes 302.1-302.7 and 302.10 are checked to be associated with pressure lesser than the first predefined pressure value. By which additional critical nodes are identified in the liquid distribution network 300a. Once the additional critical nodes are identified, the process of throttling the PRV to obtain the predefined pressure value and identifying the additional critical nodes is repeated, until no additional critical nodes are identified for the liquid distribution network 300a. Other approach to identify the one or more critical nodes 209 proposed in the present disclosure is based on demand variability, i.e., diurnal variation of demand in the liquid distribution network 102. The critical node identification module 202 is configured to obtain demand pattern and uncertainty associated demands of the liquid distribution network 102. Such data may be derived from monthly consumption data and supply data associated with the zone. If the liquid distribution network 102 is instrumented with Automated Meter Reading (AMR), estimation of nodal demands may be derived from readings of the AMR. In case, the liquid distribution network 102 is not equipped with AMR, the nodal demands may be estimate from historical data associated with the liquid distribution network 102. In an embodiment, pressure at the plurality of nodes in the liquid distribution network 102 may be monitored for the predefined period of time. In an embodiment, the predefined period of time may be 24 hours. Further, at each time period, a node with the minimum pressure or pressure lesser than the second predefined pressure value may be selected as a critical node. For every hour the value of the base demand at the nodes may be different and demand values are to be estimated from the demand data and the supply data. If the critical node remains the same for every time period, it means there are no conflicting critical node in the zone. In an embodiment, the first predefined pressure value and the second predefined pressure value may be selected to optimum minimum values of pressure in the liquid distribution network 102. The first predefined pressure value and the second predefined pressure value may be stored as the predefined pressure data 214. In an embodiment, final set of one or more critical nodes 209 may be identified using both the proposed approaches or either of the approaches. Consider for the liquid distribution network 300a, the one or more critical nodes 209 identified using both the approach is the eight node 302.8 and the ninth node 302.9, as shown in Figure 3c. In case the liquid distribution network 102 include one or more zones, the critical node identification module 202 may be configured to identify the one or more critical nodes 209 for each of the one or more zones. In an embodiment, at least one of proposed approaches, for identifying the one or more critical nodes 209, may be performed on each of the one or more zones. In an embodiment, the pressure sensor location identification module 205 may be configured to identify location of the one or more critical nodes 209 to be location of one or more pressure sensors to be placed in the liquid distribution network 102. By placing the one or more pressure sensors at the location of the one or more critical nodes 209, accurate measurement and effective controlling of pressure in the liquid distribution network 102 may be achieved. Identified location may be stored as the pressure sensor location data 215 in the memory 106. For the liquid distribution network 300a, the one or more pressure sensors may be placed as the eight node 302.8 and the ninth node 302.9. Upon identifying the one or more critical nodes 209, the pseudo critical node connection module 203 may be configured to connect a pseudo critical node in every zone in the network model. For a particular zone, upon identifying the one or more critical nodes 209 in the zone, the pseudo critical node in the zone is connected to the identified one or more critical nodes 209 of the zone. In an embodiment, elevation and demand of the pseudo critical node may be selected such a way that, the pseudo critical node remains as a node with minimum pressure at any hydraulic instance. Hence, the pressure at the pseudo-critical node may also be defined as a function of all pressures at the one or more critical nodes 209 and represented as provided in equation 1 below: P(CN*) = f(PCN1, PCN2, PCN3,…… PCNn) ………. (1) where, P(CN*) is simulated pressure at the pseudo critical node; and PCN1, PCN2, PCN3…… PCNn are pressures at the one or more critical nodes 209 in the liquid distribution network 102. In an embodiment, the predefined demand for the pseudo critical node is minimum value of demand selected to provision flow of liquid in the liquid distribution network 102 towards the pseudo critical node, without generating very low pressures in the network model. In an embodiment, the location, elevation, demand and other data associated with the pseudo critical node may be stored as the pseudo critical node data 210 in the memory 106. Figure 3d illustrates exemplary connection of a pseudo critical node 303 with the one or more critical nodes 302.8 and 302.9. Consider for the liquid distribution network 300a, the one or more critical nodes 209 may be identified to be the fifth node 302.5, the eight node 302.8 and the ninth node 302.9 as shown in Figure 3e. The pseudo critical node 303 may be connected with the fifth node 302.5, the eight node 302.8 and the ninth node 302.9 i.e., the one or more critical nodes 209, such that the pseudo critical node 303 is associated with minimal value of the demand. Consider the liquid distribution network 300b with two PRVs 301.1 and 301.3 as shown in Figure 3f. Based on the network data 208 of the liquid distribution network 300b, the liquid distribution network 300b may be sectorized to form a single zone comprising the two PRVs and the plurality of nodes 302.1….302.10. The one or more critical nodes 209 may be identified to be the fifth node 302.5, the eight node 302.8 and the ninth node 302.9. An exemplary connection of the pseudo critical node 303 with the one or more critical nodes 209 is shown in Figure 3f. Further, the target pressure determination module 204 may be configured to determine a target pressure at the pseudo critical node of each of the one or more zones. The target pressure may be determined based on real-time pressure values at the one or more critical nodes 209 in the corresponding zone. In an embodiment, the target pressure determination module 204 may be configured to receive the real-time pressure values of the one or more critical nodes 209 and store the real-time pressure values as the real-time pressure data 211 in the memory 106. In an embodiment, the real-time pressure values may be received from one or more pressure sensors placed at the one or more critical nodes 209. One or more techniques, known to a person skilled in the art, may be implemented to determine the target pressure using the real-time pressure data 211. In an embodiment, the target pressure at the pseudo critical node is determined such that minimum value of required pressure at the one or more critical nodes 209 is maintained in the corresponding zone. In an embodiment, the target pressure of the pseudo critical node of each of the one or more zones is determined. Such target pressure may be stored as the target pressure data 212 in the memory 106. Upon determining the target pressure, the PRV control module 206 may be configured to control at least one PRV associated with each of the one or more zones. In an embodiment, the PRV control module 206 may be configured to formulate a target optimization control function for each of the one or more zones. In an embodiment, said function may be represented as equation 2 given below: min?(f)=1/2 ?(P_(cr,t)-P_target)?^2 ………. (2) where P_(cr,t) is pressure at the pseudo critical node at time “t”; P_targetis the target pressure. Consider a liquid distribution networks 400a and 400b as shown in Figures 4a and 4b, respectively. Upon the sectorization, consider Figure 4a where each zone includes a single PRV. First zone 402.1 of the liquid distribution network 400a includes a PRV 403 and plurality of nodes. The target optimization control function as illustrated in equation 2 may be considered for controlling the PRV 403 of the first zone 402.1. However, such controlling may be subjected to condition indicated in equation 3 given below: X_lower^1

Claims:We claim: 1. A method of managing leakage in a liquid distribution network, comprising: identifying, by the leakage management system, one or more critical nodes from plurality of nodes in each of one or more zones in a network model of a liquid distribution network; connecting, by the leakage management system, a pseudo critical node in the network model, for each of the one or more zones, with the one or more critical nodes of respective zone; determining, by the leakage management system, a target pressure at the pseudo critical node of each of the one or more zones, based on real-time pressure values at the one or more critical nodes in the corresponding zone; and controlling, by the leakage management system, at least one Pressure Reducing Valve (PRV) associated with each of the one or more zones to obtain the target pressure at respective pseudo critical node, for managing leakage in the liquid distribution network. 2. The method as claimed in claim 1 further comprising sectorizing the network model to obtain the one or more zones, wherein sectorizing the network model is performed based on number of PRVs and location of PRVs in the liquid distribution network. 3. The method as claimed in claim 1, wherein identifying the one or more critical nodes in a zone from the one or more zones comprises: identifying a node in the liquid distribution network, associated with at least one of maximum elevation and farthest distance from source of the liquid distribution network, to be one of the one or more critical nodes in the zone; throttling at least one PRV in the zone to obtain a predefined pressure at the identified node; checking for pressure at one or more other nodes, apart from the identified node, to be lesser than a first predefined pressure value; and identifying at least one node from the one or more other nodes, with corresponding pressure lesser than the first predefined pressure value, to be the one or more critical nodes in the zone. 4. The method as claimed in claim 1, wherein identifying the one or more critical nodes in a zone from the one or more zones comprises: monitoring pressure at plurality of nodes in the liquid distribution network in relation to variation in demand associated with the liquid distribution network over a predefined period of time; and identifying one or more nodes from the plurality of nodes, with pressure lesser than a second predefined pressure value, during the predefined period of time, to be the one or more critical nodes. 5. The method as claimed in claim 1, wherein the pseudo critical node is connected in the network model, with corresponding critical nodes in the zone with a predefined elevation and a predefined demand. 6. The method as claimed in claim 5, wherein the predefined elevation is elevation greater than that of the one or more critical nodes in the zone. 7. The method as claimed in claim 5, wherein the predefined demand for the pseudo critical node is minimum value of demand selected to provision flow of liquid in the liquid distribution network towards the pseudo critical node, without generating very low pressures in the network model. 8. The method as claimed in claim 1, wherein the target pressure at the pseudo critical node is determined to maintain minimum value of required pressure at the one or more critical nodes in the corresponding zone. 9. The method as claimed in claim 1, further comprising identifying location of the one or more critical nodes to be location of one or more pressure sensors to be placed in the liquid distribution network, for controlling pressure in the liquid distribution network. 10. A leakage management system for managing leakage in a liquid distribution network, comprises: a processor; and a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, cause the processor to: identify one or more critical nodes from plurality of nodes in each of one or more zones in a network model of a liquid distribution network; connect a pseudo critical in the network model, for each of the one or more zones, with the one or more critical nodes of respective zone; determine a target pressure at the pseudo critical node of each of the one or more zones, based on real-time pressure values at the one or more critical nodes in the corresponding zone; and control at least one Pressure Reducing Valve (PRV) associated with each of the one or more zones to obtain the target pressure at respective pseudo critical node, for managing leakage in the liquid distribution network. 11. The leakage management system as claimed in claim 10 further comprises the processor configured to sectorize the network model to obtain the one or more zones, wherein the network model is sectorized based on number of PRVs and location of PRVs in the liquid distribution network. 12. The leakage management system as claimed in claim 10, wherein the one or more critical nodes in a zone from the one or more zones is identified by: identifying a node in the liquid distribution network, associated with at least one of maximum elevation and farthest distance from source of the liquid distribution network, to be one of the one or more critical nodes in the zone; throttling at least one PRV in the zone to obtain a predefined pressure at the identified node; checking for pressure at one or more other nodes, apart from the identified node, to be lesser than a first predefined pressure value; and identifying at least one node from the one or more other nodes, with corresponding pressure lesser than the first predefined pressure value, to be the one or more critical nodes in the zone. 13. The leakage management system as claimed in claim 10, wherein the one or more critical nodes in a zone from the one or more zones is identified by: monitoring pressure at plurality of nodes in the liquid distribution network in relation to variation in demand associated with the liquid distribution network over a predefined period of time; and identifying one or more nodes from the plurality of nodes, with pressure lesser than a second predefined pressure value, during the predefined period of time, to be the one or more critical nodes. 14. The leakage management system as claimed in claim 10, wherein the pseudo critical node is connected in the network model, with corresponding critical nodes in the zone with a predefined elevation and a predefined demand. 15. The leakage management system as claimed in claim 14, wherein the predefined elevation is elevation greater than that of the one or more critical nodes in the zone. 16. The leakage management system as claimed in claim 14, wherein the predefined demand for the pseudo critical node is minimum value of demand selected to provision flow of liquid in the liquid distribution network towards the pseudo critical node, without generating very low pressures in the network model. 17. The leakage management system as claimed in claim 10, wherein the target pressure at the pseudo critical node is determined to maintain minimum value of required pressure at the one or more critical nodes in the corresponding zone. 18. The leakage management system as claimed in claim 10, further comprises the processor configured to identify location of the one or more critical nodes to be location of one or more pressure sensors to be placed in the liquid distribution network, for controlling pressure in the liquid distribution network. , Description: TECHNICAL FIELD The present subject matter is related in general to liquid distribution networks, more particularly, but not exclusively to method and system for managing leakage in a liquid distribution network. BACKGROUND A water utility industry is made up of domestic entities responsible for safe and timely distribution of water and other related services, such as water and wastewater treatment. Most of water utilities around the world are under tremendous stress to prevent loss of treated water in the water network. Leakage leads to loss of water, as well as revenue for water utilities. Due to reducing water resources around the world, gap between demand and supply of water is widening. Also, leakage in turn adversely affect said gap, by reducing the amount of supply available for consumer use. Leakage may affect water quality integrity of respective water distribution network by leading to contaminant intrusion into the water distribution network during low pressure conditions. Aging infrastructure, frequent pressure fluctuations, low structural strength at joints of the water distribution network, theft and so on, may leads to water loss from the water distribution network as leakage. Such problems may not be faced in water distribution networks but may also be faced any liquid distribution network. It may be known that pressures in the liquid distribution network have a direct relationship with leakages in the liquid distribution network. In case of a network with cracks or breakage in the pipes, or loose joints, increased pressures in the network will lead to loss of excess water through these apertures. Also, very high pressures in the liquid distribution network may lead to breakages and burst in pipelines. Hence, pressure reduction may be used to check pipe bursts. Also, pressure management is found to reduce consumption in water network efficiently. Some of common methods for reducing leakage in the liquid distribution network include pressure management and pipe replacement. Leakages are completely removed when pipes are replaced, unlike as in pressure management where it is only reduced. However, with respect to cost, installation time and Operation and Maintenance (O&M) activity, pressure management is better than pipe replacement. Especially if there are only background leaks in the liquid distribution network. Pressure management in the liquid distribution network is a widely used active leak control protocol for reduction of leakages in the liquid distribution network, especially background leakages in the water network. Reduction of pressure in the liquid distribution network can aid in reduction in the leakage. Pressure management in the liquid distribution network may be achieved by installing Pressure Reducing Valves (PRVs) in the liquid distribution network. The PRVs helps in reducing the water pressure in the liquid distribution network. The pressure at downstream node of a PRV will be equal to setting of the PRV and help in reducing overall pressure of the downstream network of the PRV. Pressure management may be a fixed outlet pressure profile-based pressure management or electronically operated control for pressure management. In fixed outlet pressure profile method, the downstream pressure setting is maintained as a constant value regardless of varying upstream pressures. To alter the pressure, the valve must be adjusted manually by changing the pressure setting on the valve. Electronically operated pressure controls may be performed using approaches including time modulation-based approach, flow modulation-based approach and remote node modulation-based approach. Out of said approaches, the remote node modulation is most popular and widely used approach. The remote node modulation is also known as critical node approach. In the remote node modulation-based approach, the pressures at the critical node of the liquid distribution network i.e., node with minimum pressure is monitored using a pressure sensor. Based on pressure at the critical node, the control PRV is regulated, such that the critical node pressure is minimal. But, such approaches may not help in maintaining a minimum pressure across the liquid distribution network, including the critical node, for demand satisfaction. Some of existing systems disclose to manage leakages disclose by sectorizing the liquid distribution network to multiple zones, and minimize average zonal pressures and pressure variability within a zone. Such systems provide controlling conditions within a liquid conduit system. Every single zone is controlled by one or more actuator valves. Minimization techniques may be used for minimization of the average zonal pressures and the pressure variability within a zone. However, such systems may be regarded as multi-objective approach and may be computationally expensive. Also, such systems depends on minimization of average zonal pressures in a network and real time field application of such systems may be a challenge. The information disclosed in this background of the disclosure section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art. SUMMARY In an embodiment, the present disclosure relates to a method of managing leakage in a liquid distribution network. For managing the leakage, initially, one or more critical nodes from plurality of nodes in each of one or more of zones in network model of the liquid distribution network, are identified. A pseudo critical node in the network model is connected, for each of the one or more zones, with the one or more critical nodes of respective zone. A target pressure is determined at the pseudo critical node of each of the one or more zones, based on real-time pressure values at the one or more critical nodes in the corresponding zone. At least one Pressure Reducing Valve (PRV) associated with each of the one or more zones is controlled to obtain the target pressure at respective pseudo critical node, for managing leakage in the liquid distribution network. In an embodiment, the present disclosure relates to a leakage management system for managing leakage in a liquid distribution network. The leakage management system comprises a processor and a memory communicatively coupled to the processor. The memory stores processor-executable instructions, which, on execution, cause the processor to manage the leakage. Initially, one or more critical nodes from plurality of nodes in each of the one or more zones in network model of the liquid distribution network, are identified. A pseudo critical node in the network model is connected, for each of the one or more zones, with the one or more critical nodes of respective zone. A target pressure is determined at the pseudo critical node of each of the one or more zones, based on real-time pressure values at the one or more critical nodes in the corresponding zone. At least one Pressure Reducing Valve (PRV) associated with each of the one or more zones is controlled to obtain the target pressure at respective pseudo critical node, for managing leakage in the liquid distribution network. The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description. BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, serve to explain the disclosed principles. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and regarding the accompanying figures, in which: Figure 1 shows exemplary environment of a leakage management system for managing leakage in a liquid distribution network, in accordance with some embodiments of the present disclosure; Figure 2 shows a detailed block diagram of a leakage management system for managing leakage in a liquid distribution network, in accordance with some embodiments of the present disclosure; Figure 3a-3f show exemplary embodiments for managing leakage in a liquid distribution network, in accordance with some embodiments of the present disclosure; Figures 4a-4b show exemplary embodiments for managing leakage in a liquid distribution network, in accordance with some embodiments of the present disclosure; Figure 5a shows a flow diagram illustrating method for managing leakage in a liquid distribution network, in accordance with some embodiments of present disclosure; Figures 5b and 5c show a flow diagrams illustrating methods for identifying one or more critical nodes in a liquid distribution network, in accordance with some embodiments of present disclosure; and Figure 6 illustrates a block diagram of an exemplary computer system for implementing embodiments consistent with the present disclosure. It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether such computer or processor is explicitly shown. DETAILED DESCRIPTION In the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however that it is not intended to limit the disclosure to the forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternative falling within the spirit and the scope of the disclosure. The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device or method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or method. The terms “includes”, “including”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device or method that includes a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “includes… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or method. In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings that form a part hereof, and in which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense. Present disclosure system and method for managing leakage in a liquid distribution network using pressure management approach. A pseudo-critical node-based pressure management is implemented by introducing a pseudo critical node in the network model of the liquid distribution network. By determining target pressure at the pseudo critical node, Pressure Reducing Valves (PRVs) associated with each of one or more zones of the liquid distribution network is controlled, by which the pressure is managed, and leakage is reduced. Figure 1 shows an exemplary environment 100 of a leakage management system 101 associated with a liquid distribution network 102. The liquid distribution network 102 may be configured to provision distribution of liquid in a physical environment. In an embodiment, the liquid distribution network 102 may be a water distribution network, sewer system, storm system or the like. The liquid distribution network 102 also be configured to monitor distribution of the liquid in the physical environment. Source of the liquid distribution network 102 may be connected to consumers via plurality of interconnected branches and joints. Each of the consumers may be denoted as a node in the liquid distribution network 102. In an embodiment, the liquid distribution network 102 may include plurality of nodes with are interconnected with each other and to the source of the liquid distribution network 102. Pressure and flow of the liquid at each of the plurality of nodes is monitored in the liquid distribution network 102. Along with monitoring the pressure and the flow, the liquid distribution network 102 may implement leak detection systems for detecting leakages of liquid in the liquid distribution network 102. Regular monitoring of leakage is essential in the liquid distribution network 102. Along with regular monitoring, managing of detected leakages help in efficient distribution of the liquid. The leakage management system 101 may be configured to manage the detected leakage in the liquid distribution network 102. The leakage management system 101 may include a processor 104, I/O interface 105 and a memory 106. In some embodiments, the memory 106 may be communicatively coupled to the processor 104. The memory 106 stores instructions, executable by the processor 104, which on execution, may cause the leakage management system 101 to manage leakage in the liquid distribution network 102. In an embodiment, the memory 106 may include one or more modules 107 and data 108. The one or more modules 107 may be configured to perform the steps of the present disclosure using the data 108, to manage the detected leakage in the liquid distribution network 102 as disclosed in the present disclosure. In an embodiment, each of the one or more modules 107 may be a hardware unit which may be outside the memory 106 and coupled with the leakage management system 101. The leakage management system 101 may be implemented in a variety of computing systems, such as a laptop computer, a desktop computer, a Personal Computer (PC), a notebook, a smartphone, a tablet, e-book readers, a server, a network server, and the like. For managing the leakage in the liquid distribution network 102, the leakage management system 101 may be configured to sectorize a network model of the liquid distribution network 102 into one or morezones. The network model may be mathematical model of the liquid distribution network 102. The network model may be used to analyze hydraulic behavior in the liquid distribution network 102. The network model for the liquid distribution network 102 may be determined using one or more techniques, known to a person skilled in the art. In an embodiment, the leakage management system 101 may be configured to determine the network model for the liquid distribution network 102. In an embodiment, the liquid distribution network 102 may implement a dedicated system for determining the network model of the liquid distribution network 102. The determined network model may be communicated with the leakage management system 101 for managing the leakage in the liquid distribution network 102. Using the network model, the liquid distribution network 102 may be sectorized into the one or morezones. In an embodiment, the liquid distribution network 102 may be sectorized based on number of PRVs and location of PRVs in the liquid distribution network 102. In an embodiment, the sectorization may be in such a way that each zone of the one or more zones may include at least one PRV. In an embodiment, the one or more zones may be formed by considering impact of PRVs on the plurality of nodes of the liquid distribution network 102. Each zone may include a single PRV or plurality of PRVs. In an embodiment, the network model received by the leakage management system 101 may already be sectorized or the network model may include a single zone. In such case, the step of sectorization may not be performed by the leakage management system 101. Upon sectorization, the leakage management system 101 may be configured to identify one or more critical nodes from plurality of nodes in each of the one or more zones. In an embodiment, the one or more critical nodes may be referred to as nodes which have major impact or are majorly impacted, due to leakages in the liquid distribution network 102. Leakage may be managed efficiently by managing pressure at the one or more critical nodes in the liquid distribution network 102. In an embodiment, the leakage management system 101 may be configured to identify the one or more critical nodes in a zone from the one or more zones by initially identifying a node in the liquid distribution network 102 which is associated with at least one of maximum elevation and farthest distance from source of the liquid distribution network 102. Such identified node may be referred to as one of the one or more critical nodes. Further, the leakage management system 101 may be configured to throttle at least one PRV in the zone to obtain a predefined pressure at the identified node. Upon throttling, pressure at one or more other nodes, apart from the identified node, is checked to be lesser than a first predefined pressure value. At least one node from the one or more other nodes, with corresponding pressure lesser than the first predefined pressure value is identified to be the one or more critical nodes in the zone. The initially identified node along with the nodes associated with pressure lesser than the first predefined pressure value constitute the one or more critical nodes of the zone. In an embodiment, the leakage management system 101 may be configured to identify the one or more critical nodes in a zone from the one or more zones by monitoring pressure at plurality of nodes in the liquid distribution network 102. The pressure may be in relation to variation in demand associated with the liquid distribution network 102 over a predefined period of time. Further, one or more nodes with pressure lesser than a second predefined pressure value, during the predefined period of time, may be identified to be the one or more critical nodes. In an embodiment, the leakage management system 101 may be configured to identify location of the one or more critical nodes to be location of one or more pressure sensors to be placed in the liquid distribution network 102. By placing the one or more pressure sensors at the location of the one or more critical nodes, accurate measurement and effective controlling of pressure in the liquid distribution network 102 may be achieved. Upon identifying the one or more critical nodes for each of the one or more zones, the leakage management system 101 may be configured to connect a pseudo critical node in the network model with the one or more critical nodes of respective zone. Each of the one or more zones may be associated with a pseudo critical node. In an embodiment, the pseudo critical node may be connected in the network model with a predefined elevation and a predefined demand. In an embodiment, the predefined elevation is elevation greater than that of the one or more critical nodes in the zone. In an embodiment, the predefined demand for the pseudo critical node is minimum value of demand selected to provision flow of liquid in the liquid distribution network 102 towards the pseudo critical node, without generating very low pressures in the network model. Further, the leakage management system 101 may be configured to determine a target pressure at the pseudo critical node of each of the one or more zones, based on real-time pressure values at the one or more critical nodes in the corresponding zone. In an embodiment, the target pressure at the pseudo critical node is determined to maintain minimum value of required pressure at the one or more critical nodes 209 in the corresponding zone. One or more techniques, known to a person skilled in the art, may be implemented to determine the target pressure. Upon determining the target pressure, the leakage management system 101 may be configured to control at least one PRV associated with each of the one or more zones. The leakage management system 101 controls the at least one PRV to obtain the target pressure at respective pseudo critical node. By obtaining the target pressure at the respective pseudo critical node, leakage at each of the one or more zones in the liquid distribution network 102 may be minimized and managed. In an embodiment, the leakage management system 101 may be a dedicated server or a cloud-based server in communication with the liquid distribution network 102. The leakage management system 101 may communicate with the liquid distribution network 102 via a communication network 103. The communication network 103 may include, but is not limited to, a direct interconnection, , a Peer to Peer (P2P) network, Local Area Network (LAN), Wide Area Network (WAN), wireless network (e.g., using Wireless Application Protocol), Controller Area Network (CAN), the Internet, Wi-Fi, and such. In an embodiment, the leakage management system 101 may be associated with plurality of liquid distribution networks, to manage the leakages at each of the liquid distribution networks. In an embodiment, the leakage management system 101 may communicate with each of the liquid distribution networks, via dedicated communication network. In an embodiment, the leakage management system 101 may be integral part of the liquid distribution network 102. The I/O interface 105 of the leakage management system 101 may assist in transmitting and receiving data. Received data may include, but is not limited to, the network model, real-time pressure values and so on. Transmitted data may include, but is not limited to, location and information of identifies one or more critical nodes, controlling of the at least one PRV and so on. One or more other data, which is associated with managing the leakage, may be received and transmitted via the I/O interface 105. Figure 2 shows a detailed block diagram of the leakage management system 101 for managing leakage in the liquid distribution network 102, in accordance with some embodiments of the present disclosure. The data 108 and the one or more modules 107 in the memory 106 of the leakage management system 101 may be described herein in detail. In one implementation, the one or more modules 107 may include, but are not limited to, a sectorization module 201, a critical node identification module 202, a pseudo critical node connection module 203, a target pressure determination module 204, a pressure sensor location identification module 205, a PRV control module 206 and one or more other modules 207, associated with the leakage management system 101. In an embodiment, the data 108 in the memory 106 may include network data 208, critical node data 209 (also referred to as one or more critical nodes 209), pseudo critical node data 210, real-time pressure data 211, target pressure data 212, PRV control data 213, predefined pressure data 214, pressure sensor location data 215 and other data 216 associated with the leakage management system 101. In an embodiment, the data 108 in the memory 106 may be processed by the one or more modules 107 of the leakage management system 101. In an embodiment, the one or more modules 107 may be implemented as dedicated units and when implemented in such a manner, said modules may be configured with the functionality defined in the present disclosure to result in a novel hardware. As used herein, the term module may refer to an Application Specific Integrated Circuit (ASIC), an electronic circuit, a Field-Programmable Gate Arrays (FPGA), Programmable System-on-Chip (PSoC), a combinational logic circuit, and/or other suitable components that provide the described functionality. The leakage management system 101 may be associated with the liquid distribution network 102 of any network configuration. The network configuration may be based on number of plurality of nodes, connectivity of each of the plurality of nodes with other nodes and source, demand values and elevation associated with the plurality of nodes and so on. Consider Figure 3a which shows an exemplary representation of the liquid distribution network 102. The liquid distribution network 300a may include a PRV 301 and plurality of nodes including a first node 302.1, a second node 302.2, a third node 302.3, a fourth node 302.4, a fifth node 302.5, a sixth node 302.6, a seventh node 302.7, a eight node 302.8, a ninth node 302.9 and a tenth node 302.10 (together referred to as the plurality of nodes 302.1….302.10). For the liquid distribution network 300a, the leakage management system 101 may be configured to manage the leakage in the liquid distribution network 300a. In an embodiment, the management of leakage include to minimize the leakage in the liquid distribution network 300a. The leakage may be minimized by maintaining the pressure at optimal values. Hence, pressure management may in-turn aid in management of leakage. In an embodiment, the liquid distribution network 300a may include one or more PRVs which are type of safety valves used to control or limit the pressure in the liquid distribution network 300a. Building-up of pressure, which may create upset in process of distribution, may be avoided by throttling the PRVs. For managing the leakage in the liquid distribution network 300a, the sectorization module 201 may be configured to sectorize the liquid distribution network 300a into the one or more zones. For sectorization, the sectorization module 201 may obtain the network data 208 associated with the liquid distribution network 300a. In an embodiment, the network data 208 may include but not limited to, network model, available demand and flow data, network connectivity data, number of PRVs, location of PRVs and so on of the liquid distribution network 300a. The network data 208 may be received from the liquid distribution network 300a and stored in the memory 106. Such network data 208 may be used for sectorization of the liquid distribution network 300a into one or more zones. In an embodiment, the one or more zones may be formed based on number and location of PRVs in the network. Pressures in each zone in the liquid distribution network 300a may be controlled by the respective PRV or PRVs. For the liquid distribution network 300a, PRV 301 is configured to control pressure in the liquid distribution network 300a and at the plurality of nodes 302.1….302.10. Consider, the plurality of nodes 302.1….302.10 along with the PRV 301 is identified to be a zone. Upon sectorization, the critical node identification module 202 may be configured to identify one or more critical nodes 209 from plurality of nodes in each of the one or more zones. In an embodiment, a critical node is defined as a node with minimum pressure at any instance of time. In an embodiment, the critical node may be related as a node with highest elevation and is farthest from the source. In the liquid distribution network 102, selecting a single critical node may be very difficult. There may be more than one node which have similar pressures in the liquid distribution network 102. Selecting one of these nodes as critical node and carrying out management of the leakage, as proposed in the present disclosure, may lead to pressures below acceptable range at the other node . Also, for instances when the critical node changes based on demand variation, it will be difficult to identify a single critical node. Hence, the critical node identification module 202 is configured to consider possible parameters to identify all the one or more critical nodes 209 in the liquid distribution network 102. One of the approach proposed herewith includes the critical node identification module 202 to identify a node based on topographical factors. In this approach, first iteration includes to identify node with maximum elevation and farthest distance from the source to be a critical node. Consider the liquid distribution network 300a shown in Figure 3b, the eight node 302.8 may be associated with highest elevation and farthest from source. Hence, the eight node 302.8 may be identified as a critical node. Further, the critical node identification module 202 may be configured to throttle the PRV 301 of the zone to obtain a predefined pressure at the eight node 302.8 i.e., the critical node of the zone. Upon throttling, pressure at the other nodes i.e., nodes 302.1-302.7, 302.9 and 302.10 is checked. In an embodiment, the pressure is checked to be lesser than the first predefined pressure value. Nodes which are associated with pressure lesser than the first predefined pressure value may be identified as other critical nodes. In case, there are no nodes with pressure lesser than the first predefined pressure value, it may be decided that there are no conflicting critical nodes in the liquid distribution network 102. If one or more nodes are identified to be associated with the pressure lesser than the first predefined value, it may be decided that there are more than one critical node in the liquid distribution network 300a. Figure 3c illustrates the liquid distribution network 300a with the ninth node 302.9 to be additional critical node. Hence, for the liquid distribution network 300a, the eight node 302.8 and the ninth node 302.10 may be identified to be the one or more critical nodes 209. In an embodiment, when the eight node 302.8 and the ninth node 302.10 are identified to be the one or more critical nodes 209, the critical node identification module 202 may be configured to throttle the PRV 301 of the zone to obtain the predefined pressure at the eight node 302.8 and the ninth node 302.9 i.e., the one or more critical nodes 209 of the zone. Pressure at other nodes i.e., nodes 302.1-302.7 and 302.10 are checked to be associated with pressure lesser than the first predefined pressure value. By which additional critical nodes are identified in the liquid distribution network 300a. Once the additional critical nodes are identified, the process of throttling the PRV to obtain the predefined pressure value and identifying the additional critical nodes is repeated, until no additional critical nodes are identified for the liquid distribution network 300a. Other approach to identify the one or more critical nodes 209 proposed in the present disclosure is based on demand variability, i.e., diurnal variation of demand in the liquid distribution network 102. The critical node identification module 202 is configured to obtain demand pattern and uncertainty associated demands of the liquid distribution network 102. Such data may be derived from monthly consumption data and supply data associated with the zone. If the liquid distribution network 102 is instrumented with Automated Meter Reading (AMR), estimation of nodal demands may be derived from readings of the AMR. In case, the liquid distribution network 102 is not equipped with AMR, the nodal demands may be estimate from historical data associated with the liquid distribution network 102. In an embodiment, pressure at the plurality of nodes in the liquid distribution network 102 may be monitored for the predefined period of time. In an embodiment, the predefined period of time may be 24 hours. Further, at each time period, a node with the minimum pressure or pressure lesser than the second predefined pressure value may be selected as a critical node. For every hour the value of the base demand at the nodes may be different and demand values are to be estimated from the demand data and the supply data. If the critical node remains the same for every time period, it means there are no conflicting critical node in the zone. In an embodiment, the first predefined pressure value and the second predefined pressure value may be selected to optimum minimum values of pressure in the liquid distribution network 102. The first predefined pressure value and the second predefined pressure value may be stored as the predefined pressure data 214. In an embodiment, final set of one or more critical nodes 209 may be identified using both the proposed approaches or either of the approaches. Consider for the liquid distribution network 300a, the one or more critical nodes 209 identified using both the approach is the eight node 302.8 and the ninth node 302.9, as shown in Figure 3c. In case the liquid distribution network 102 include one or more zones, the critical node identification module 202 may be configured to identify the one or more critical nodes 209 for each of the one or more zones. In an embodiment, at least one of proposed approaches, for identifying the one or more critical nodes 209, may be performed on each of the one or more zones. In an embodiment, the pressure sensor location identification module 205 may be configured to identify location of the one or more critical nodes 209 to be location of one or more pressure sensors to be placed in the liquid distribution network 102. By placing the one or more pressure sensors at the location of the one or more critical nodes 209, accurate measurement and effective controlling of pressure in the liquid distribution network 102 may be achieved. Identified location may be stored as the pressure sensor location data 215 in the memory 106. For the liquid distribution network 300a, the one or more pressure sensors may be placed as the eight node 302.8 and the ninth node 302.9. Upon identifying the one or more critical nodes 209, the pseudo critical node connection module 203 may be configured to connect a pseudo critical node in every zone in the network model. For a particular zone, upon identifying the one or more critical nodes 209 in the zone, the pseudo critical node in the zone is connected to the identified one or more critical nodes 209 of the zone. In an embodiment, elevation and demand of the pseudo critical node may be selected such a way that, the pseudo critical node remains as a node with minimum pressure at any hydraulic instance. Hence, the pressure at the pseudo-critical node may also be defined as a function of all pressures at the one or more critical nodes 209 and represented as provided in equation 1 below: P(CN*) = f(PCN1, PCN2, PCN3,…… PCNn) ………. (1) where, P(CN*) is simulated pressure at the pseudo critical node; and PCN1, PCN2, PCN3…… PCNn are pressures at the one or more critical nodes 209 in the liquid distribution network 102. In an embodiment, the predefined demand for the pseudo critical node is minimum value of demand selected to provision flow of liquid in the liquid distribution network 102 towards the pseudo critical node, without generating very low pressures in the network model. In an embodiment, the location, elevation, demand and other data associated with the pseudo critical node may be stored as the pseudo critical node data 210 in the memory 106. Figure 3d illustrates exemplary connection of a pseudo critical node 303 with the one or more critical nodes 302.8 and 302.9. Consider for the liquid distribution network 300a, the one or more critical nodes 209 may be identified to be the fifth node 302.5, the eight node 302.8 and the ninth node 302.9 as shown in Figure 3e. The pseudo critical node 303 may be connected with the fifth node 302.5, the eight node 302.8 and the ninth node 302.9 i.e., the one or more critical nodes 209, such that the pseudo critical node 303 is associated with minimal value of the demand. Consider the liquid distribution network 300b with two PRVs 301.1 and 301.3 as shown in Figure 3f. Based on the network data 208 of the liquid distribution network 300b, the liquid distribution network 300b may be sectorized to form a single zone comprising the two PRVs and the plurality of nodes 302.1….302.10. The one or more critical nodes 209 may be identified to be the fifth node 302.5, the eight node 302.8 and the ninth node 302.9. An exemplary connection of the pseudo critical node 303 with the one or more critical nodes 209 is shown in Figure 3f. Further, the target pressure determination module 204 may be configured to determine a target pressure at the pseudo critical node of each of the one or more zones. The target pressure may be determined based on real-time pressure values at the one or more critical nodes 209 in the corresponding zone. In an embodiment, the target pressure determination module 204 may be configured to receive the real-time pressure values of the one or more critical nodes 209 and store the real-time pressure values as the real-time pressure data 211 in the memory 106. In an embodiment, the real-time pressure values may be received from one or more pressure sensors placed at the one or more critical nodes 209. One or more techniques, known to a person skilled in the art, may be implemented to determine the target pressure using the real-time pressure data 211. In an embodiment, the target pressure at the pseudo critical node is determined such that minimum value of required pressure at the one or more critical nodes 209 is maintained in the corresponding zone. In an embodiment, the target pressure of the pseudo critical node of each of the one or more zones is determined. Such target pressure may be stored as the target pressure data 212 in the memory 106. Upon determining the target pressure, the PRV control module 206 may be configured to control at least one PRV associated with each of the one or more zones. In an embodiment, the PRV control module 206 may be configured to formulate a target optimization control function for each of the one or more zones. In an embodiment, said function may be represented as equation 2 given below: min?(f)=1/2 ?(P_(cr,t)-P_target)?^2 ………. (2) where P_(cr,t) is pressure at the pseudo critical node at time “t”; P_targetis the target pressure. Consider a liquid distribution networks 400a and 400b as shown in Figures 4a and 4b, respectively. Upon the sectorization, consider Figure 4a where each zone includes a single PRV. First zone 402.1 of the liquid distribution network 400a includes a PRV 403 and plurality of nodes. The target optimization control function as illustrated in equation 2 may be considered for controlling the PRV 403 of the first zone 402.1. However, such controlling may be subjected to condition indicated in equation 3 given below: X_lower^1