Sustainable Water Management in Smart Cities

• Altering patterns of water usage

• Creating local forecasts for variations in weather trends

• Establishing and activating service and acceptance standard;

• Creating contingency plans for severe occurrences

• Improving the water system to satisfy water requirements.

There is a call to adopt new strategies and technologies, developing future scenarios regarding rising water demand and stress, which indicates the urgency for available digital water solutions. In Europe, the sustainable European framework for a water-smart society involves a fundamental change in how our future society will be structured and managed in relation to water (Wu and Rahman 2017).

There are critical challenges in water management that continue to grow in the face of urbanization, climate change, and increasing water demand.

2. Core Concepts of Smart Cities 

The main goal of smart cities in water management is to ensure adequate water supply to users at an affordable price while maintaining water quality standards. Because of scarce water resources, managing and distributing water is a challenging task. This includes the critical process of Water Resources Allocation. To guarantee the sensible and sustainable utilization of water resources, the Smart Water Management System aims to achieve several key objectives, as follows:

• Preventing Water Waste: Crucial for conserving water supplies, particularly in agricultural and industrial practices. Methods such as precision agriculture, intelligent irrigation, and automated water meters assist in reducing waste (Gade et al., 2021).

• Effective Water Distribution: Intelligent sensors and pressure control devices guarantee ideal water distribution throughout communities, structures, and industries, fulfilling needs efficiently.

• Efficient Water Leak Management: Each year, millions of liters are lost because of leaks in pipes. Automated water meters and leak detection systems assist in reducing losses and avoiding disasters, This is crucial for managing Water Leakage Distribution Networks. These sophisticated monitoring systems gain significant advantages from the application of machine learning to analyze pressure and flow data. By leveraging this information, systems such as AI leak detection play a crucial role in minimizing losses and preventing potential disasters.

• Effective Water Reuse: Treatment of wastewater and desalination enables the recycling of water for industrial and sanitation purposes, alleviating pressure on fresh water resources.

• Safe Drinking Water Supply: Guarantees clean, treated water for drinking to avert illnesses, employing filtration systems, desalination facilities, and secure storage solutions.

• Secure Data and Financial Integrity: In addition to monitoring water quality, smart cities can harness distributed ledger technology. The integration of Blockchain in Water Management holds great promise for boosting transparency and security in areas like water rights trading, consumption data recording, and maintaining supply chain integrity. The immutable nature of blockchain ensures that data from smart sensors remains secure and tamper-proof, fostering trust between utility providers and consumers.

Smart cities can handle the above-mentioned objectives with information and communication technology (ICT) and the Internet of Things (IoT). The overarching field of Hydroinformatics and its Applications in Water Science uses this ICT framework that functions as the nervous system of the urban environment. Sophisticated data networks, rapid internet, and cloud technology facilitate smooth communication among devices, systems, and individuals. This interlinking serves as the foundation for real-time data gathering, analysis, and decision-making procedures that enhance urban functions and water systems (Bouramdane et al., 2023). The IoT, a system of linked devices equipped with sensors and software, empowers smart cities by enabling data-driven analysis and automation. For instance, smart irrigation devices that modify watering according to live data and IoT enhance efficiency and resource use (Bellini et al. 2022). IOT allows for the tracking of water quality, consumption measurement, and leak detection in smart homes, offering a monitoring platform and raising awareness for both users and managers (Okol and Kabaso 2024).

3. Addressing Water Scarcity in Smart Cities

The world is rapidly becoming urbanized. Between 1950 and 2020, the worldwide urban population rose from 0.8 billion (29.6%) to 4.4 billion (56.2%) and is expected to hit 6.7 billion (68.4%) by 2050. Water scarcity—when demand surpasses supply—is a crucial factor influencing water security and has a direct impact on the health and wellbeing of city residents, urban environmental conditions, and economic growth. Currently, numerous urban populations worldwide are experiencing water shortages. It is anticipated that population growth, urbanization, and socioeconomic development will lead to a 50–80% rise in demand for urban industrial and domestic water over the next thirty years (He et al. 2021). Simultaneously, climate change will influence the geographical distribution and timing of water resources. We can manage water scarcity through terrestrial and Groundwater Quantity Monitoring Methods.

The phrase 'smart irrigation' has been characterized within the global idea of smart cities, regarding water scarcity and the necessity for efficient water use. Intelligent irrigation encompasses a set of methods and standards focused on effective irrigation management, necessitating precise assessment of plant water needs and maximal efficiency of irrigation systems to reduce water waste and ensure optimal utilization of water resources (Canales-Ide et al. 2019). Smart irrigation consists of 5 main steps, including gathering and analyzing data, sensor setup, system design and integration, irrigation controller configuration, monitoring and optimization.

Collecting and evaluating data involves assembling details such as temperature, humidity, precipitation, wind speed, and solar radiation from nearby weather stations. And, even more importantly, soil moisture data that establish ideal moisture levels for various plant species and pinpoint regions with differing soil conditions. Next, examine the particular water needs of vegetation in the urban green areas. And evaluating the existing water supply and possible constraints.

Sensor installation involves placing sensors across the irrigation areas to assess soil moisture content at various depths. Set up weather stations to gather real-time meteorological information. Observe water flow to detect leaks and enhance irrigation supply. Irrigation controller selection involves picking a smart irrigation controller that can analyze data from sensors and modify watering schedules accordingly, as well as creating a network to send data from the sensors to the controller. Additionally, irrigation zones can be classified according to plant species, soil characteristics, and water requirements to enhance efficiency. In the final stages, users can observe irrigation efficiency, detect possible problems, and record water consumption. Consistently assess data and adjust irrigation schedules as required. Carry out regular upkeep on sensors, controllers, and irrigation systems.

4. Addressing Water Quality in Smart Cities

Population growth leads to increased environmental pollution, further deteriorating water quality. This enables us to assess and monitor water quality through advanced technologies such as IoT. Remote sensing revolutionizes water quality assessment and monitoring by providing high-level data.A unified collection of products, solutions, and systems that allows for the remote and ongoing monitoring, diagnosing, and optimizing of every element of the water distribution network is referred to as a Smart Water Grid (Savic 2015). It assists in prioritizing and handling maintenance problems. The smart water grid employs wireless sensor networks and IoT alongside various electronic communication devices and routing protocols to provide continuous real-time data from multiple sites. The gathered data is beneficial for enhancing the performance of the water distribution system. It also gives significant information to the final users. Therefore, the intelligent water grid offers significant enhancement by displaying real-time data and enabling authorities to assess the information and make required actions promptly (Baanu and Babu 2021). These sensors usually assess water temperature, pressure, level, quality, and contamination metrics such as total dissolved solids (TDS), pH levels, and turbidity with a core controller having built-in Wi-Fi module. The sensor connectors are inserted into the water that needs testing. The Analog-to-Digital Converter (ADC) will process the sensor values, and the core controller will read these values to upload them to the cloud. The values will be continuously monitored by verifying if the sensor value exceeds the threshold or not. If the sensor reading exceeds the threshold, it will be conveyed to the relevant end user for additional action. If the sensor value is below the threshold, then the parameters are re-evaluated for an alternate water source (Lakshmikantha et al .2021).

Another aspect of water quality monitoring is wastewater management. Wastewater treatment is employed to remove contaminants from waste or sewage and convert them into water that can be repurposed for various applications (known as water recovery) or introduced back into the water supply, bringing with it an associated environmental effect. Intelligent cities can additionally aid in wastewater treatment via a multi-steps strategy. For instance, Bins are fitted with sensors to track waste levels and, when full, send alerts to optimize collection schedules and minimize unnecessary trips. Artificial intelligence can sort recyclables such as paper, plastics, and metals more effectively than human methods. Waste that cannot be recycled is incinerated to create electricity or heat, reducing landfill reliance, while organic waste is treated to yield biogas and natural fertilizers (Poonkuzhali et al. 2024). Intelligent cities create systems to securely deconstruct and recycle electronic waste, reclaiming precious resources and reducing ecological impact. Dashboards in real-time and predictive analytics offer insights into trends in waste, allowing improved resource distribution and enhancing recycling in smart cities. Mobile applications and online services motivate residents to sort waste and recycle correctly by using gamification and rewards.

5. Addressing Flood Management in Smart Cities

Flood management in smart cities is essential for safeguarding lives, assets, and infrastructure, reducing financial losses, promoting sustainable development, and responding to climate change effects while simultaneously improving the resilience of communities and ecosystems against flood threats. Key strategies include both digital monitoring and physical measures like Green Stormwater Management. In general, smart cities approach flood management solutions through one of the following three categories, or a mix of them:

• Big data collection:

  the accumulation of data from various sources along with its analysis and display for aiding decision-making, with technologies like artificial intelligence, augmented reality, and crowdsourcing. It also encompasses the Internet of Things (Bail et al. 2021). The application of big data in disaster management typically relies on the phase of the disaster. Information from stationary and mobile sensors or crowdsourced online data can be utilized for tracking and evaluating exposure and susceptibility to risks. In the midst of a flood, data from social media, mobile devices, and remote sensing can be utilized for an initial evaluation of damages and the reactions of the affected people (Boukerche and Coutinho 2018). Key big data sources include satellite imagery, social media platforms, and crowdsourcing (the collection and analysis of data from various sources to generate pertinent disaster insights). Included after that are sensor networks, simulations, mobile GPS, and call data. Since floods can cut off communication lines in the affected area, such as overhead wires, antennas, and fiber optic networks, it is vital to diversify protocols that rely on various and independent communication infrastructures. Typically, utilizing a vast array of deployed physical items, accessed via the Internet, can provide authorities with accurate situational data (Ray et al. 2017).

  

  • Digital twin:

    A virtual representation of a city that actively reflects all the components that make up the city and enables real-time interaction and data sharing with the physical world. A Digital Twin encompasses five key aspects: data management, visualization, situational awareness, forecasting and planning, as well as integration and collaboration; these elements enable a digital twin to aid and improve flood management in smart urban areas (Shahat et al. 2021). A digital twin can combine real-time and fixed data from various sources. The information can be interpreted and utilized for decision-making support by visualizing and conveying the derived insights. A digital twin is particularly powerful when a feedback loop is utilized, enabling decisions and actions to be relayed back into the digital twin, which then synthesizes the information and establishes suggested subsequent actions (Ford and  Wolf  2020).
    
    

    

• Remote sensing and support:

  Remote sensing revolutionizes water quality assessment and monitoring by providing high-level data. Utilizing aerial or satellite vehicles for observation, data collection, communication, and logistics, along with the integration of various geo-data types obtained from aerial and space surveys to track long-term changes in terrain and evaluate their potential effects (Erdelj et al., 2021). Integrating remote sensing with IoT applications improves both spatial and temporal information by employing sensors to collect data on air temperature, atmospheric pressure, and humidity levels. This allows for crucial insights into Remote sensing for Water Quantity. Unmanned aerial vehicles (UAV), a prime example of Drone Applications in Water, are essential in flood management, proving effective throughout all phases of a flood. They can gather information from hard-to-reach places utilizing cameras and sensors, particularly when interconnected. UAVs serve as communication centers, reestablishing connections disrupted by floods, while some variants can move supplies in and out of impacted areas (Josipovic and Viergutz 2021).

Conclusion

Water management in smart cities is an intriguing concept that engages the attention of hydrologists and urban developers, with key objectives such as avoiding water wastage, guaranteeing safe drinking water, encouraging effective water recycling, and enabling efficient water distribution. The main goals of smart cities include multiple aspects of water management, such as addressing water scarcity, enhancing water quality, and controlling floods. The concept of smart cities is associated with IoT, such as smart sensors, enabling real-time data collection on parameters like water flow, pressure, and quality, facilitating rapid detection of leaks, contamination, or inefficiencies in the distribution network. ICT is a bigger aspect of IoT to handle big data and smooth the communication between various sensors. Digital twins can aid in simulating and forecasting behaviors of the water system , boosting  performance, and preparing for upcoming scenarios. In addition, the idea of smart water management in urban areas not only improves operational effectiveness but also aids sustainability objectives by reducing water wastage, encouraging water conservation, and facilitating the recycling of wastewater. In summary, the collaboration between cutting-edge technologies and sustainable methods in smart cities presents a hopeful route to addressing present-day water management problems and ecological concerns, guaranteeing a more effective, fair, and sustainable utilization of water resources in urban settings.