Implementation of an intelligent drinking water supply system using GIS mapping and smart metering for reliable water supply management

Water scarcity is one of the major issues faced in developing nations like India. The major objective is to make better-quality sources of drinking water available to the populace. For the various development endeavours and for the continuation of life, water is the fundamental basis of life. In order to meet the constant increase in demand, it is important to use water resources methodically, consistently, and wisely in the real world. Due to rising population and resource demands, water is now in short supply in many parts of the world. Water pollution has exacerbated the issue. India is experiencing a freshwater shortage as a result of ineffective management of the nation's water resources and environmental damage. Many regions of India are suffering from a freshwater shortage. However, its size and intensity vary according to the season. A supply check is necessary in order to maintain the water's quality.

Effective planning and decision-making at various levels are essential when resources are scarce. In today's high-tech world, gathering and combining various pieces of information into a usable format is essential for effective decision-making. A geographic information system (GIS) enables users to bring all types of information based on the geographic and locational components of the data. GIS enables you to perform previously unachievable tasks such as making maps, integrating data, visualising scenarios, resolving difficult issues, outlining compelling arguments, and coming up with workable solutions. Using the threshold values of various groundwater quality parameters, the groundwater quality index can be easily calculated, and the results are simple to understand.

However, one of the major issues with the traditional Water Quality Indices (WQIs) (for both surface water and groundwater) is that they fail to deal with the uncertainty and subjectivity that are inherent in the assessment of environmental problems (Silvert 2000), especially while classifying water quality near the parameter-threshold boundary. To overcome this subjectivity and to incorporate environmental uncertainty in the groundwater quality evaluation process, the application of artificial intelligence (AI)-based computational methods is highly recommended (Maiti et al. 2013; Patki et al. 2015; Bagherzadeh et al. 2018; Salari et al. 2018). The available AI methods can be classified into two broad categories: (a) symbolic AI, and (b) computational AI. The former mainly deals with the development of a knowledge-based system, while the latter deals with the development of a behavior-based system (Chau 2006). Computational AI includes neural networks, genetic algorithm, fuzzy systems, etc. Among various computational AI methods, fuzzy logic (FL) is extensively used to deal with complex water-related environmental problems (McKone & Deshpande 2005; Ghosh & Mujumdar 2006), owing to its capability to deal with non-linearity and uncertainty involved in environmental systems (Chanapathi et al. 2019). In addition to this, FL serves as an effective tool for conveying the results to the public and beneficiaries in a much more understandable linguistic format (Li et al. 2018).

It displays power system characteristics as spatial coordinates. Distribution network information is divided into two categories: static data and dynamic data. Dynamic data are instantaneous information of voltage, current, reactive power, active power, power factor, etc., which can be retrieved using various metering devices such as advanced metering infrastructure (AMI), fast recorders, and data loggers. Static data includes information about poles, transformers, switchgear, etc., which can be retrieved using a global positioning system.

Rajendran et al. (2019) deal with the fundamental geochemical analysis of groundwater at specific locations using statistical and/or graphical methods. These studies also highlight the need for an effective methodology to evaluate groundwater quality on a larger scale. More than that, GIS makes it possible to model scenarios to test various hypotheses and visually identify results to find/identify the outcome that meets the needs of the stakeholders. GIS and related technologies are now acknowledged as helpful tools for natural resource inventorying studies and management due to their capacity to combine geographically referenced data from various subject areas to aid in the processing, interpretation, and analysis of such data.

GIS definition: A computer-based system for storing and modifying geographic data. ‘An organised collection of database, application, hardware, software, and trained manpower capable of capturing, manipulating, managing, and analysing the spatial reference database and production of output both in tabular and map form’ is a commonly used definition of GIS. A more general definition of GIS is a tool that enables users to edit data, create interactive queries, and analyse spatial data.

Benefits of GIS over other information systems: The main purposes of GIS are decision-making and question-answering. In order to manage geographic data, a GIS, like other information systems, offers the following four sets of capabilities: (i) input, (ii) data management, (iii) manipulation and analysis, and (iv) output.

The collection, archiving, and analysis of objects and phenomena where geographic location is a significant characteristic or essential to analysis are other areas where GIS is designed for use. The distinctive capabilities of GIS are spatial searching and the overlay of (map) layers. For instance, a GIS can combine maps of crop potential and ground/surface water conditions to create a map of crop/land suitability on a temporal and spatial basis. GIS is a cutting-edge and excellent planning tool for resource managers and decision makers because real-world situations are complex (for example, in agriculture, data on land, soil, crop, climate, hydrology, forestry, livestock, fisheries, and social and economic parameters are required for decision-making), and physical computing capacity to manipulate data is low and time-consuming. Thus, the configuration of modern information technology revolves around GIS.

Major GIS tasks: Six key types of tasks are carried out by GIS

• Data input: Conversion of paper maps to digital format, vector processing, and image classification.

• Manipulation: Prior to integration, all of the information must be converted to the same resolution scale.

• The spatial and attribute databases are used in management.

• Query and viewing: Once the database is ready, users can use GIS to perform any query on the data, such as finding out where soils with the land types MHL and clay-textured soils are located.

• Analysis: GIS has a wide range of effective tools for creating ‘what-if’ scenarios.

• Visualisation and printing: Creating maps, legends, symbols, and other related materials, as well as providing printers with the ability to print them.

GIS also allows for thorough infrastructure management and makes it simpler to monitor and maintain infrastructure in real time by mapping the entire water network, including pipes, valves, and storage facilities. As a result, there is less waste and better resource allocation. It also supports the analysis of consumption patterns, distribution optimisation, and demand understanding across various regions. By identifying affected areas and planning urgent measures, GIS facilitates quick response during emergencies or disasters. As a result, it aids in the effective and sustainable management of water supply systems for communities. It also aids in data integration, visualisation, future planning, and environmental impact assessment.

A modern method of observing and managing water use in communities is the AMI in the water supply. To improve the effectiveness and accuracy of water metering, it is necessary to integrate cutting-edge technologies such as smart meters, communication networks, and data analytics. On each individual water connection, smart meters are installed, and they can monitor water usage frequently or in real time. These devices enable automated data collection and transmission to centralised data repositories, which helps utilities better track usage patterns, identify leaks, and manage billing.

The ability of AMI to deliver real-time and nearly real-time data on water consumption is its main advantage. Utilities are better able to spot unusual usage patterns, potential leaks, and unauthorised usage by looking at consumption patterns and trends. Water utilities can take quick action to reduce water losses and boost system effectiveness thanks to early leak detection. By giving customers usage-specific data, improving customer satisfaction, and encouraging a culture of water conservation, AMI also enables more accurate and transparent billing based on actual consumption.

AMI also supports two-way communication, which enables utilities to remotely control and manage meters, create alerts, and alter prices in response to demand peaks or other circumstances. In order to encourage customers to reduce their water use during peak hours, utilities can use demand-based pricing strategies. AMI in water supply ultimately plays a critical role in promoting sustainable water management, reducing water waste, and guaranteeing a consistent water supply to communities while providing utilities and customers with useful information and data.

Integrating GIS and smart metering infrastructure (SMI) into water supply systems is a practical way to improve water management. For organising, analysing, and visualising geographic data about demand zones, natural water sources, and water infrastructure, GIS provides a spatial framework. The effectiveness of data collection from smart meters is increased by AMI technology, which permits real-time or nearly real-time monitoring of water consumption at the individual consumer level. GIS and AMI work together to create a comprehensive platform that makes use of spatial data and offers accurate usage information to improve operational effectiveness and decision-making.

In addition, this integration enables predictive analytics, which forecasts future water demand by combining geographic data from GIS and historical consumption data from AMI. Utilities can use these forecasts to proactively plan for capacity expansions, manage distribution networks efficiently, and ensure sufficient water supply during peak demand periods. Thus, the integration of GIS and AMI plays a crucial role in optimising water supply systems by enabling a data-driven approach to decision-making, ultimately raising the overall efficiency, sustainability, and resilience of water supply operations.

The minimum speed required for a minimum flow of 9.72 m³/d corresponding to the maximum WL condition is 52.87% of the rated speed. A single pump with speed variation can be operated for discharge up to approximately 22.0 m³/d, without exceeding the rated speed. Up to about 22.0 m³/d, it is preferable to operate a single pump for less power consumption as seen from values for KW per m³/d. For flow exceeding 22.0 m³/d, two pumps shall have to be operated as the power drawn for a single pump operation leaves an inadequate margin. It is desirable to operate two pumps for less power consumption, for flow above 22.0 m³/d, and the variation in speed, head, efficiency, and power for the given discharge for feeder main 3 is detailed in Table 3 and Figure 7.

• False: It is a procedure to ensure that pressure is sufficient within the designed DMA only after closing all valves (IVs) and letting water pass through its district meter.

• True: It is a procedure to ensure that pressure is sufficient outside the designed DMA after closing all IVs and letting water pass through its district metre.

• False: This procedure is done during nighttime when the pressure is high.

Required data

• Supply, Bulb Volume (BV), Non-revenue water (NRW), and Water Supply Corporation (WSC) can be obtained from historical data.

• Minimum NFR and pressure are obtained through actual activity (Table 4).

Night user is computed from actual activity equations

• Physical losses = Q_avg = Q_min × (P_min/P_avg)

• Commercial losses = NRW volume-physical losses

A new era in water supply management has begun with the integration of GIS mapping and cutting-edge metering technologies, producing notable results. The availability and accuracy of water-related data have significantly improved as a result of these technological advancements. Decision-makers now have easy access to real-time consumption insights, ensuring they have the most recent data available for efficient decision-making. This level of data accuracy has significant ramifications for water resource management since it enables planners and managers to react quickly to changing demand dynamics.

One cannot overestimate the importance of GIS models in this situation. Visualising the spatial and temporal patterns of water demand has shown to be impossible without these models. Decision makers can strategically distribute resources and infrastructure by mapping these patterns, which will maximise the distribution of water resources. For instance, resources can be swiftly transferred to maintain a consistent supply to areas in need during periods of peak water demand or in reaction to localised shortages. In addition, the use of GIS mapping in urban planning procedures has transformed city planning. It enables the strategic placement of water supply infrastructure, minimising the need for expensive expansion projects and encouraging water-wise land-use regulations.

Advanced metering technologies have also significantly increased the effectiveness of managing the water supply. These systems have the benefit of remote monitoring, making it possible to track water usage in real time and quickly find leaks or anomalies. By reducing water losses within distribution networks, this proactive method not only conserves water resources but also generates significant cost savings. Rapid response to such abnormalities reduces resource waste and operational interruptions, emphasising the revolutionary effects of advanced metering on water delivery systems.

Beyond improving infrastructure, the use of GIS technology has greatly improved the knowledge, expertise, and capabilities of those who study and work with water resources. It equips them with powerful analytical tools to investigate a variety of water management solutions. Professionals can come up with novel solutions to complex problems involving water resources by utilising data-driven insights. The improvement of these skills helps make projects for managing water resources more effective overall.

However, despite these incredible developments, the cyclical nature of droughts continues to be a problem, and climate change is making them more often and more severe. GIS mapping and cutting-edge metering technology have made it possible to better prepare for and respond to drought situations in this area. These developments give us the resources we need to monitor droughts proactively, develop early warning systems, and allocate scarce resources. As a result, water supply systems have shown enhanced resilience and dependability even in the face of drought difficulties.

The integration of modern metering technology with GIS mapping has proven crucial in improving the administration of water supply systems. With the help of these tools, a new era of data precision has begun, allowing decision makers to react quickly and successfully to shifting demand trends. The use of GIS in urban planning has cleared the floor for more sustainable and water-efficient city designs in addition to optimising resource allocation. Advanced metering has resulted in lower operating expenses and a smaller environmental impact. In addition, these advances have increased the general resilience of water supply systems in the face of climatic problems in addition to improving the abilities of water resource professionals. To ensure the long-term sustainability of water supplies, reduce the effects of droughts, and satisfy the rising water demands of expanding populations while protecting this priceless natural resource for future generations, it is imperative to continue investing in these technologies.

In conclusion, population growth and the ongoing effects of droughts on irrigated agriculture are the main causes of the rising demand for water resources. To solve the imbalance between water supply and demand, modern metering technology and GIS mapping deployment offer a potential solution. These techniques offer precise information on the spatial and temporal patterns of water usage, facilitating efficient water resource planning and management. The findings of this study demonstrate the beneficial effects of GIS technology on urban planning, the effectiveness of the water supply, and the development of professional abilities among those involved in the management of water resources. It decreases water losses and enhanced system efficiency is the inclusion of modern metering systems. To ensure sustainable and reliable water supply systems, it is essential that governments, municipalities, and water agencies continue to invest in these technologies. It can better manage the water resources, lessen the consequences of droughts, and meet our communities expanding water needs, all while protecting the natural resource for the future.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.