It is crucial to forecast the water demand accurately for supplying water efficiently and stably in a water supply system. In particular, accurately forecasting short-term water demand helps in saving energy and reducing operating costs. With the introduction of the Smart Water Grid (SWG) in a water supply system, the amount of water consumption is obtained in real-time through a smart meter, which can be used for forecasting the short-term water demand. The models widely used for water demand forecasting include Autoregressive Integrated Moving Average, Radial Basis Function-Artificial Neural Network, Quantitative Multi-Model Predictor Plus, and Long Short-Term Memory. However, there is a lack of research on assessing the performance of models and forecasting the short-term water demand in the SWG demonstration plant. Therefore, in this study, the short-term water demand was forecasted for each model using the data collected from a smart meter, and the performance of each model was assessed. The Smart Water Grid Research Group installed a smart meter in block 112 located in YeongJong Island, Incheon, and the actual data used for operating the SWG demonstration plant were adopted. The performance of the model was assessed by using the Residual, Root Mean Square Error, Normalized Root Mean Square Error, Nash–Sutcliffe Efficiency, and Pearson Correlation Coefficient as indices. As a result of water demand forecasting, it is difficult to forecast water demand only by time and water consumption. Therefore, as the short-term water demand forecasting models using only time and the amount of water consumption have limitations in reflecting the characteristics of consumers, a water supply system can be managed more precisely if other factors (weather, customer behavior, etc.) influencing the water demand are applied.

A model that computes the per-unit process energy consumption, energy intensity, CO₂ emission, and CO₂ intensity of water treatment plants is developed. This model is used to estimate the total energy consumption of six water treatment plants in Seoul Metropolitan City (SMC), which is comprised 80–85% for finished water pumping, 6–10% for ozone disinfection, 2–4% for rapid mixing, and 1–3% for non-process loads. The model results are validated against actual data for 2020 and 2021. The net energy consumption considering renewable energy production and use is then calculated, and the corresponding level of CO₂ emissions is predicted. Four scenarios based on the projected water requirements for the year 2045 were evaluated as follows: increased energy efficiency in finished water pumping (Scenario 1), increased renewable energy production in water treatment plants (Scenario 2), increased energy efficiency in raw water pumping (Scenario 3), and reduced water supply per capita (Scenario 4). Compared to a baseline do-nothing scenario (Scenario 0), the net energy consumption is reduced by 3.57%, 2.61%, 3.42%, and 4.67% for Scenarios 1–4, respectively. Scenario 4, which is a water-driven approach, is best for reducing CO₂ emissions, while Scenario 1 and 3, which are energy-driven approaches, are more effective at reducing CO₂ intensity.

Substantial greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs) increase the global warming potential, underscoring the importance of addressing their role in GHG mitigation. This study proposes a strategy development approach that analyzes unit-process-based energy consumption, direct and indirect GHG emissions, and scenario impacts to create integrated water–energy–GHG solutions. The analysis of four WWTPs in Seoul Metropolitan City (SMC) identified aeration as the most energy-intensive process, consuming over 40% of the total energy. In addition, substantial GHG emissions were observed, with total indirect emissions surpassing direct emissions. To address these challenges, five future scenarios targeting 2050 were developed and analyzed: (1) replacing aeration diffusers, (2) reducing wastewater production, (3) adjusting treatment levels, (4) increasing renewable energy production, and (5) integrating all measures. Scenario 1 proved most effective in reducing energy and GHG emission intensity, Scenario 4 achieved high energy self-sufficiency, and Scenario 5 enabled some plants to achieve net-zero energy and carbon conditions. The approach proposed in this study provides actionable insights to support carbon neutrality through targeted water–energy–GHG strategies.

In South Korea, in line with the increasing need for a reliable water supply following the continuous increase in water demand, the Smart Water Grid Research Group (SWGRG) was officially launched in 2012. With the vision of providing water welfare at a national level, SWGRG incorporated Information and Communications Technology in its water resource management, and built a living lab for the demonstrative operation of the Smart Water Grid (SWG). The living lab was built in Block 112 of YeongJong Island, Incheon, South Korea (area of 17.4 km², population of 8000), where Incheon International Airport, a hub for Northeast Asia, is located. In this location, water is supplied through a single submarine pipeline, making the location optimal for responses to water crises and the construction of a water supply system during emergencies. From 2017 to 2019, ultrasonic wave type smart water meters and IEEE 802.15.4 Advanced Metering Infrastructure (AMI) networks were installed at 527 sites of 958 consumer areas in the living lab. Therefore, this study introduces the development of SWG core element technologies (Intelligent water source management and distribution system, Smart water distribution network planning/control/operation strategy establishment, AMI network and device development, Integrated management of bi-directional smart water information), and operation solutions (Smart water statistics information, Real-time demand-supply analysis, Decision support system, Real-time hydraulic pipeline network analysis, Smart DB management, and Water information mobile application) through a field operation and testing in the living lab.

Achieving carbon neutrality is a priority in global environmental policies, and South Korea is committed to its 2050 carbon neutrality goal. This study explores methods to reduce carbon emissions in urban water cycle (UWC) systems, which are essential urban infrastructures that consume considerable energy. Focusing on Incheon Metropolitan City (IMC), the research identifies UWC components, estimates energy consumption, and calculates carbon emissions across eight administrative districts. The analysis comprises four water abstraction plants (WAPs), four water treatment plants (WTPs), and eleven wastewater treatment plants (WWTPs). Strategies for carbon reduction involve decreasing water and energy consumption and minimizing emissions from wastewater treatment. This study categorizes management targets as water, energy, and carbon, developing different carbon emissions reduction scenarios. A carbon emission calculation model for WTPs and WWTPs was developed to evaluate energy consumption and carbon emissions across scenarios. Notably, the scenario focusing on renewable energy development and energy efficiency improvements yielded the highest carbon emissions reductions, confirming that the government’s renewable energy initiatives are vital for achieving net-zero emissions in IMC’s UWC systems. Conversely, the scenario prioritizing water use reduction proved less effective, but excelled regarding investment costs. These findings can serve as a model for other cities managing UWC systems while striving for sustainability.

Water and energy are essential resources for human life, and carbon emissions (CEs) occur in tandem with their use. Thus, water, energy, and carbon are closely inter-related. Approximately 4% of the global energy is used in urban water sectors (UWSs), which encompass various processes such as water intake, treatment, and distribution and wastewater collection and treatment, all of which consume significant energy and emit CO₂. Several countries are actively working toward achieving carbon neutrality by 2050–2060. Therefore, increasing energy efficiency and reducing CEs through comprehensive evaluations of UWSs is essential. This study aimed to quantify energy consumption and CEs in UWSs and proposed a methodology for analyzing water–energy–carbon (WEC) links at the city level. By applying it to Incheon Metropolitan City (IMC), we first identified the UWSs and established a WEC database. Based on this database, the WEC consumption and emissions were analyzed by process or administrative district, and visualizations using Sankey diagrams and Geographic Information System Mapping were created to enhance their understandability. In 2021, the UWSs in IMC consumed 308,496,107 kWh of energy, representing 32.7% of the public electricity consumption of IMC, with an average energy intensity of 0.46 and 0.38 kWh/m³ for water supply systems (WSSs) and sewerage systems (SSs), respectively. Their carbon emissions totaled 315,765,358 kg CO₂, accounting for 2.7% of IMC’s total carbon emissions, with an average carbon intensity of 0.21 and 0.58 kg CO₂/m³ for WSSs and SSs, respectively. The proposed methodology was used to comprehensively evaluate WEC consumption and emissions in IMC. It is expected to enable relevant stakeholders to develop measures, such as water reuse and increasing renewable energy usage in water treatment and wastewater treatment plants, to build sustainable UWSs.