Urban Water Resources Research Articles

A Bibliometric Analysis of Research Trends in Hazard Mitigation Studies in Korea: Based on Articles from the Journal of Korean Society of Hazard Mitigation

This study conducts a bibliometric analysis to identify research trends in hazard mitigation, based on 3,074 papers published in the Journal of the Korean Society of Hazard Mitigation between 2010 and 2023. The findings revealed that research on climate change and disaster response was the most active, with key topics including natural disaster management, urban water resource management, fire analysis and prevention, and AI-based disaster management. A keyword analysis highlighted “disaster” and “climate change” as having the highest frequency and centrality within the network. Institutional analysis identified the Korea Institute of Civil Engineering and Building Technology as the leading institution in co-authorship, with high research productivity and a key role as an intermediary. The authors’ analysis revealed that certain authors were central to expanding the field through diverse cooperation. These insights highlight the evolution of hazard mitigation research in Korea and offer guidance for future research to tackle emerging challenges in disaster management.

Energy-efficient and reliable coordinated scheduling for water distribution systems: enhancing hydraulic conditions and water quality

ABSTRACT Multi-objective operation optimization of water distribution systems (WDSs) in large metropolitan areas is essential; however, it is complex and time-consuming. Effective and reliable scheduling of WDSs can significantly enhance the efficiency and reliability of urban water resources management, which requires further research. This paper develops an optimization method combining genetic algorithm and multiple criteria analysis that coordinates energy conservation, hydraulic condition improvement, and water age optimization in WDSs. Results showed that the optimal scheduling method could achieve a 23.0, 16.7, and 2.5% decrease in energy consumption, and water supply volume with unsatisfied pressure, and average water age, respectively. To achieve optimal results, this study indicated that it is crucial to properly allocate water supply volume and pressure across multiple drinking water treatment plants. This finding provides important guidance for water utilities in scheduling. Furthermore, the emergency scenario analysis shows that the newly proposed method can significantly enhance the social and economic sustainability of WDSs through the coordinated optimization of energy consumption, hydraulic conditions, and water age.

Environmental Assessment and Restoration of the Hunjiang River Basin Based on the DPSIR Framework

The Hunjiang River, a vital water system in northeastern China, has suffered severe ecological damage due to overexploitation. This study analyzes the basin’s environmental conditions from 2016 to 2020, identifies key restoration factors, and examines practical restoration projects. Investigating five major pollutants (permanganate index, chemical oxygen demand (COD), biochemical oxygen demand, ammonia nitrogen, total phosphorus) in eight sections, the study finds the Xicun section most polluted, mainly from Baishan City’s industrial and domestic discharges. The ammonia nitrogen concentration at the Zian section also shows deterioration. Using a DPSIR (Driving forces, Pressures, State, Impacts, Responses) framework, the study elucidates the relationship between environmental and socio-economic issues. Results indicate that population changes, industrial development, and water resource management have complex ecological impacts. Evaluating the urban water resource carrying capacity with the entropy weight method and correlation coefficient weighting method, the study finds that increasing forest coverage, improving wastewater treatment efficiency, and reducing COD emissions are crucial. Quantitative assessment of integrated protection and restoration projects involving mountains, rivers, forests, farmlands, lakes, and grasslands demonstrates their positive impact. This research reveals the interplay between the ecological environment and social factors, proposes practical restoration measures, and clarifies project effects, providing reliable decision-making schemes for policymakers.

Urban Water Crisis in Kabul City: Key Challenges and Solutions

Water is an essential human need for survival. However, billions globally wake up daily with accessible and affordable clean water. Rapid population growth, urbanization, climate change, precipitation regime changes, industrial development, and environmental degradation increase pressure on urban water resources. As a result, water demand is continuously rising, leading to prominent shortages in many cities in developing and developed countries, regardless of their developmental condition. One such city facing significant water scarcity is Kabul, the capital of Afghanistan, where rapid urbanization has outpaced local water supply infrastructure, resulting in unsustainable exploitation of groundwater resources. This directly threatens the well-being of millions of residents in this city. In anticipation of the exhaustion of local water sources, Kabul will soon need to explore alternative water supply methods, such as inter-basin water transfers, to meet the growing demand. This paper aims to offer a broad overview of urban water crises, evaluating the key drivers of water shortages, exploring the specific water crisis facing Kabul, and analyzing previous research, reports, papers, flow data, groundwater data, maps/charts, field observations, surveys, GIS data, and statistical analysis as the methods for this work. So, to combat declining groundwater levels, a sustainable groundwater management approach is crucial. The approach includes water conservation methods, the implementation of efficient irrigation techniques, and the adoption of water pricing mechanisms.

Urban Water Management in Milan Metropolitan Area, a review

The increasing rate of urbanisation and extreme climatic events represent a constant threat for urban water resources management. In recent decades, Milan Metropolitan Area (Lombardy Region, Northern Italy) has been affected by a) frequent extreme rainfall events, responsible for the flooding of major surface water courses, and b) groundwater management problems, both from a quantitative (i.e. interaction with underground infrastructures) and qualitative point of view. Moreover, the increasing use of groundwater geothermal systems also requires further considerations. This work analyses the literature available in the area regarding surface floods, groundwater quantity, quality, and temperature. Finally, a discussion is provided to understand a) which approaches could promote an effective management of both surface water and groundwater resources b) which points of contact emerge between these two aspects of the urban water cycle, and c) which possible urban interventions could contribute to an integrated and functional management of water resources, also reducing some current issues.

Nitrate removal by a novel aerobic denitrifying Pelomonas puraquae WJ1 in oligotrophic condition: Performance and carbon source metabolism

Reducing nitrate contamination in drinking water has become a critical issue in urban water resource management. Here a novel oligotrophic aerobic denitrifying bacterium, Pelomonas puraquae WJ1, was isolated and purified from artificial lake sediments. For the first time, excellent aerobic denitrification capabilities were demonstrated. At a carbon-to‑nitrogen ratio of 5.0, strain WJ1 achieved 100.0 % nitrate removal and 84.92 % total nitrogen removal within 24 h, with no nitrite accumulation. PCR amplification and sequencing confirmed the presence of the denitrification genes napA, nirS, and nosZ in the strain. The nitrogen balance demonstrated that approximately 74.95 % of the initial nitrogen was eliminated as gaseous products under aerobic conditions. Furthermore, carbon balance analysis showed that most electron donors from strain WJ1 were directed towards oxygen, with limited availability for nitrate reduction. A combination of bio-ECO analysis and network modeling indicated that strain WJ1 has robust metabolic capabilities for diverse carbon sources and exhibits high adaptability to complex carbon environments. Overall, Pelomonas puraquae WJ1 removed approximately 45.89 % of the nitrates in raw water, demonstrating significant potential for practical applications in oligotrophic denitrification.

Investigation and Validation of Split-Window Algorithms for Estimating Land Surface Temperature from Landsat 9 TIRS-2 Data

Land surface temperature (LST) is important in a variety of applications, such as urban thermal environment monitoring and water resource management. In this paper, eleven candidate split-window (SW) algorithms were adapted to Thermal Infrared Sensor-2 (TIRS-2) data of the Landsat 9 satellite for estimating the LST. The simulated dataset produced by extensive radiative transfer modeling and five global atmospheric profile databases was used to determine the SW algorithm coefficients. Ground measurements gathered at Surface Radiation Budget Network sites were used to confirm the efficiency of the SW algorithms after their performance was initially examined using the independent simulation dataset. Five atmospheric profile databases perform similarly in training accuracy under various subranges of total water vapor. The candidate SW algorithms demonstrate superior performance compared to the radiative transfer equation algorithm, exhibiting a reduction in overall bias and RMSE by 1.30 K and 1.0 K, respectively. It is expected to provide guidance for the generation of the Landsat 9 LST using the SW algorithms.

Study on Large-Scale Urban Water Distribution Network Computation Method Based on a GPU Framework

Large-scale urban water distribution network simulation plays a critical role in the construction, monitoring, and maintenance of urban water distribution systems. However, during the simulation process, matrix inversion calculations generate a large amount of computational data and consume significant amounts of time, posing challenges for practical applications. To address this issue, this paper proposes a parallel gradient calculation algorithm based on GPU hardware and the CUDA Toolkit library and compares it with the EPANET model and a model based on CPU hardware and the Armadillo library. The results show that the GPU-based model not only achieves a precision level very close to the EPANET model, reaching 99% accuracy, but also significantly outperforms the CPU-based model. Furthermore, during the simulation, the GPU architecture is able to efficiently handle large-scale data and achieve faster convergence, significantly reducing the overall simulation time. Particularly in handling larger-scale water distribution networks, the GPU architecture can improve computational efficiency by up to 13 times. Further analysis reveals that different GPU models exhibit significant differences in computational efficiency, with memory capacity being a key factor affecting performance. GPU devices with larger memory capacity demonstrate higher computational efficiency when processing large-scale water distribution networks. This study demonstrates the advantages of GPU acceleration technology in the simulation of large-scale urban water distribution networks and provides important theoretical and technical support for practical applications in this field. By carefully selecting and configuring GPU devices, the computational efficiency of large-scale water distribution networks can be significantly improved, providing more efficient solutions for future urban water resource management and planning.

Assessing the Impact of Agricultural Practices and Urban Expansion on Drought Dynamics Using a Multi-Drought Index Application Implemented in Google Earth Engine: A Case Study of the Oum Er-Rbia Watershed, Morocco

Drought monitoring is a critical environmental challenge, particularly in regions where irrigated agricultural intensification and urban expansion pressure water resources. This study assesses the impact of these activities on drought dynamics in Morocco’s Oum Er-Rbia (OER) watershed from 2002 to 2022, using the newly developed Watershed Integrated Multi-Drought Index (WIMDI), through Google Earth Engine (GEE). WIMDI integrates several drought indices, including SMCI, ESI, VCI, TVDI, SWI, PCI, and SVI, via a localized weighted averaging model (LOWA). Statistical validation against various drought-type indices including SPI, SDI, SEDI, and SMCI showed WIMDI’s strong correlations (r-values up to 0.805) and lower RMSE, indicating superior accuracy. Spatiotemporal validation against aggregated drought indices such as VHI, VDSI, and SDCI, along with time-series analysis, confirmed WIMDI’s robustness in capturing drought variability across the OER watershed. These results highlight WIMDI’s potential as a reliable tool for effective drought monitoring and management across diverse ecosystems and climates.

Novel drainage pipeline breakages detection based on MEMS inertial sensor: From mechanism to application

Urban water environment pollution is a global concern, in developing countries, sewage infiltration resulting from urban drainage pipelines breakage is an essential element in the urban groundwater pollution and the recurrence of black odor water bodies, it is crucial to accurately and efficiently detection and localisation of urban drainage pipelines breakage to protect the urban water resources. In this paper, a device for detecting defects in drainage pipelines was developed and assembled using microelectromechanical systems (MEMS) inertial sensors as the core components, and the improved cumulative sum (CUSUM) model was used for anomalous detection of the pitch angle of the device's movement along the course of the pipeline as a method of detecting pipeline breakage. In the laboratory simulation of drainage pipeline tests, the CUSUM peaks (0.709, 1.102, 3.038, 7.990) for the case of external water infiltration rates into the pipeline at the point of pipe breakage (2.9%, 4.6%, 5.8%, 9.2%), and for the cases of sewer exfiltration rates in the pipeline of 4.2% and 6.4% (0.760, 1.382). CFD simulations of the water flow in the laboratory pipeline show a high degree of overlap between the trend of the water surface near the point of breakage and the anomalous fluctuations in the pitch angle of the device motion in the laboratory tests. Finally, the authors tested the device on municipal drains in the city of A. The results demonstrated the reliability and high accuracy of the device. The device enables to improve the ecological quality of urban water environment by accelerating the rate of defect detection in urban drainage pipelines and reducing the detection expenses.

Urbanization-induced spatial and temporal patterns of local drought revealed by high-resolution fused remotely sensed datasets

Urbanization has exerted considerable impacts on urban water systems and ecological environments, yet its effects on local meteorological drought remain under-explored. The primary challenge to local-scale drought analysis is the scarcity of meteorological datasets with sufficient spatial and temporal resolution. To address the research gap, we initially proposed a two-step fusion framework, integrating both surface (i.e., gridded data)-surface and point (i.e., in-situ data)-surface fusion. The framework was applied to generate daily precipitation and average/maximum/minimum air temperature at a 1 km resolution through the integration of high-resolution remotely sensed datasets across the Yangtze River Basin (YRB), China. The final fused data demonstrated excellent performance, achieving a PCC (RMSE) of 0.806 (5.414 mm/day), 0.993 (1.138 °C), 0.987 (1.443 °C), and 0.988 (1.376 °C) for precipitation and average/maximum/minimum air temperature, respectively. A comparison of our fused data with CPC, ERA5-Land, CMFD, CHIRPS, IMERG, and TMPA products confirmed its capability in capturing local-scale meteorological dynamics by improving spatial resolution from 0.1°-0.25° to 1 km. Utilizing these high-resolution datasets, we quantified urbanization's impacts on local drought across 52 major cities in the YRB. We found that urbanization significantly magnified extreme Standardized Precipitation Evapotranspiration Index (SPEI) and drought severity in 69.2% and 61.5% of these cities, respectively. The effects of urbanization on extreme SPEI were amplified by the increase of urbanization rates, with a slope of −0.24 (p < 0.05). To further examine the spatial patterns of urbanization-induced local drought, we proposed a drought spatial field identification method, utilizing it in three representative urban regions: Chengdu, Wuhan, and the Yangtze River Delta. Our findings revealed that urbanization led to more intense peak drought intensity and average drought severity. In addition, urban drought fields showed lower effective radius, indicating more concentrated drought towards urban regions. While urbanization is projected to continue alongside rapid population growth in the future, the advanced application of remote sensing data and technology in this study not only improves our understanding of urban water resource challenges but also equips urban planners with the necessary data to develop effective drought mitigation strategies.

Groundwater monitoring infrastructure: Evaluation of the shallow urban and coastal network in Ōtautahi Christchurch

Study regionŌtautahi Christchurch, New Zealand Study focusUrban shallow groundwater monitoring networks are becoming widespread in New Zealand and globally. A reliable groundwater monitoring infrastructure is important to develop knowledge on water table aquifers in coastal cities like Ōtautahi Christchurch. Previous investigations have shown shallow groundwater vulnerability to salinisation and contamination in urban settings, and shallow groundwater exacerbates flooding from climate change and the impact of rising sea levels. New hydrological insights for the regionFollowing the 2010–2011 Canterbury earthquake sequence, shallow groundwater data acquisition and the establishment of a geotechnical database in Ōtautahi Christchurch provided unprecedented information on subsurface conditions. The installation of the groundwater monitoring infrastructure opened the field of New Zealand-based urban hydrogeological studies, including continuous measurements of groundwater levels. This study presents the hydrogeological context of Ōtautahi Christchurch, provides an overview of seismic impacts on groundwater, and documents the monitoring network’s development. Methods for assessing the monitoring network included field surveys and digital information review. The overall good condition and robustness of the network mean the dataset held by the city and regional councils should be more widely used to benefit the community. Implications for researchers and network asset managers mean that the maintenance and availability of the data should be prioritised. Records from urban shallow groundwater monitoring networks are becoming an essential source of information to manage urban water resources under climate change and sea-level rise conditions.

Rethinking Urban Water Management Through Drivers-Pressures-States-Impacts-Responses Framework Application in Chennai, India

Cities suffering water scarcity are projected to increase in the following decades. However, the application of standardized indicator frameworks for assessing urban water resource management problems is on an early stage. India is expected to have the highest urban population facing water scarcity in the world by 2050. In this study, the authors assess how the Drivers-Pressures-States-Impacts-Responses framework, a causal framework adopted by the European Environment Agency, can contribute to evaluate water management challenges in cities and apply it to Chennai, India´s fourth-largest urban agglomeration. The framework proved to be a helpful tool for the evaluation of water management challenges in cities by disentangling relationships between environmental indicators and structuring dispersed data that allows a better understanding for policymakers. The main drivers identified in Chennai were population growth and economic development which generated impacts such as loss of aquatic ecosystems, low water table, low water quality, and reduction of biodiversity and human health. As a response, better urban planning, projects for new water infrastructure, and water bodies restoration have been implemented. Nevertheless, Chennai keeps facing difficulties to achieve proper water management. The severe hit of the COVID-19 pandemic on the Indian economy and its future management will be key for achievements related to water management.

Assessment of land use transformations and its impact on fluctuations in groundwater quality in Chengalpattu district, Tamil Nadu

ABSTRACT This study examines land use transformations and their impact on groundwater quality fluctuations in Chengalpattu district, Tamil Nadu. Chengalpattu is a rapidly urbanizing coastal region in South India. Landsat 5 and 9 satellite imagery were utilized to create land use land cover (LULC) maps for 2011 and 2021, with overall accuracies of 82.20% and 85.71%, respectively. The analysis showed significant growth in built-up and fallow lands due to urbanization, which has altered LULC. Groundwater Quality Index (GQI) was generated using seven groundwater quality parameters, adhering to World Health Organization (WHO) standards. The mean GQI showed slight fluctuations during pre- and post-monsoon periods, with a declining trend in pre-monsoon seasons. The study area predominantly experiences moderate groundwater quality, with fewer areas of low and high quality. The findings indicate that land use transformation significantly impacts groundwater quality, emphasizing the need for sustainable urban planning and water resource management in the region.

An integrated framework for waterfront development to recognize nature-based solutions (NBS) in urban areas: evaluating the condition of two projects in Bangladesh

ABSTRACT Nature-based solutions (NBS) often suggest improving the degraded urban environment through the implementation of projects for revitalizing water bodies and adjacent areas. Among various concepts of developing waterfront urban spaces, ‘water sensitive urban design (WSUD)’ asks for integrated design and management of urban water resources and water cycle, following a holistic approach. This research proposes a framework that assimilates the components of WSUD with the concept of ‘integrated urban water management (IUWM)’ that mainly focuses on governance, management, and stakeholders' engagement. This integrated approach emphasizes the need for developing a holistic framework for the management of planning and design of waterfront development projects. The framework includes detailed criteria for water sensitive approach and acts as a holistic checklist for evaluating or designing waterfront development projects. Such comprehensive guidelines that includes planning, governance, and design challenges are rare in the current body of literature. To test the framework, the research conducts a comparative study among two waterfront projects in Bangladesh and through a scored evaluation based on the proposed framework, reveals the lack of water sensitive planning, design and management processes of the projects, which has narrowed down the scope and the opportunities of practicing NBS through reviving lost urban waterbodies.

Multi-Source Remote Sensing Analysis of Yilong Lake’s Surface Water Dynamics (1965–2022): A Temporal and Spatial Investigation

With the acceleration of global warming and the intensification of anthropogenic activities, numerous lakes worldwide are experiencing reductions in their water surface areas. Yilong Lake, a typical shallow plateau lake located on the Yunnan–Guizhou Plateau in China, serves as a crucial water resource for local human production, daily life, and ecosystem services. Hence, long-term comprehensive monitoring of its dynamic changes is essential for its effective protection. However, previous studies have predominantly utilized remote sensing data with limited temporal resolution, thus failing to reflect the long-term variations in Yilong Lake’s water body. This study employs high temporal resolution monitoring, utilizing multi-source satellite data (e.g., KeyHole, Landsat, HJ-1 A/B) images spanning from 1965 to 2022 to investigate the changes in Yilong Lake’s surface area, analyzing the influencing factors and ecological impacts of these changes. The results indicate that from 1965 to 2022, Yilong Lake’s water surface area decreased by 8.33 km2, with a maximum surface area of 40.49 km2 on January 7, 1986, and a minimum surface area of 10.64 km2 on April 20, 2013. These changes are characterized by three significant phases: (1) a rapid shrinking phase (1965–1979); (2) a fluctuating shrinking period (1986–2016); and (3) an expanding recovery phase (2016–2022). Spatially, the most significant shrinkage was observed along the southern and southwestern shores of the lake. The driving factors varied across different periods: sunshine duration was the dominant influence during the rapid shrinking phase (1965–1979), accounting for 82% of the changes; population and cropland area were the main drive factors during the fluctuating shrinking period (1986–2016), accounting for 56% of the changes; and during the expanding recovery phase (2016–2022), the population accounted for 75% of the changes in the lake’s surface area. Currently, the protection of Yilong Lake depends on water supplementation and strict regulation of outflow, resulting in the lake exhibiting characteristics similar to a reservoir. This long-term investigation provides baseline information for future lake monitoring. Our research findings can also guide decision-makers in urban water resource management and environmental protection, ensuring the scientific and rational use of watershed water resources, effectively curbing the shrinkage of Yilong Lake, and achieving long-term sustainable restoration of the lake’s ecology.

Public Policies and Research in Brazil on Urban Sustainability and Water Resources

Objective: The objective is to investigate the national scenario of research on urban sustainability related to water resources in the face of national and international public policies. Theoretical Framework: The conception of the current urban infrastructure will not be sufficient to support the impacts of extreme phenomena predicted for the near future. The incorporation of sustainable technologies that incorporate the concept of ecosystem services is a perspective that envisions the resilience necessary for urban centers to accommodate the socio-environmental and economic structure in the future. Method: The methodology adopted for this research comprises data analysis using a quantitative and qualitative approach, exploring theses and dissertations on the urban sustainability of water resources between 2007 and 2000. Data collection was carried out through a survey of secondary data contained in the institutional repositories of four higher education institutions in Brazil. Results and Discussion: The results revealed that research on urban sustainability is growing in Brazil, but research on urban sustainability related to water resources is recent and few. These results are contextualized in the light of national and international government initiatives, highlighting the implications, relationships, discrepancies and limitations of the study.. Research Implications: The practical and theoretical implications providing insights that can influence research on water problems in urban spaces. These can imply paradigm shifts considering urban sustainability and the impacts of urbanization on water resources. Originality/Value: This study contributes to the literature by presenting research gaps present in higher education institutions in Brazil, in the face of international and national government initiatives. The relevance and value are evidenced by the need for a paradigm shift in order to incorporate the principles of sustainability, specifically considering water resources, due to the growing demand and vulnerability to climate change.

Urban water security in multidisciplinary practices: A case of Lamphun Municipality, Thailand

Urban water security is a multi-faceted water, socioeconomic, and governance challenge. The complexity of translating the holistic approach into policies is an important need for improving water resource management to achieve prosperity, equity, sustainability, and good governance. The city of Lamphun is an example of the practice, which faced drought and major challenges in efficiently distributing water to industrial partners and downstream residents. The purpose of this study was to monitor urban water security and formulate a water management-based urban land use policy for Lamphun Municipality to mitigate water conflicts and ensure access to water for all residents. Therefore, the study examined urban water security using 4 indices: urban water resources, access, risks, and governance. A careful urban land use plan responsible for water security was proposed based on potential surface analysis techniques and public participation. The result of this research would not only guarantee water security, but also promote public participation and sustainable communities.

Assessment of water conservation and water intensification level based on AHP-fuzzy comprehensive evaluation model

Scientific evaluation of water conservation and water intensification level is an important prerequisite for addressing water resource shortage. In the current research, there are problems of confusing evaluation indicator systems and unscientific evaluation results. The paper first constructed the evaluation indicator systems of water conservation and water intensification based on the different connotations of the two, and then evaluated the utilization level of the two respectively by using AHP-fuzzy comprehensive evaluation model. The results indicated that from 2010 to 2022, the level of water conservation and water intensification in Zhengzhou both showed an upward trend, but the conservation level was higher than that of intensification. Therefore, promoting water intensification is the key to realize scientific water use in Zhengzhou in the future. Improving conservation level should prioritize the improvement of agricultural and domestic water use, while enhancing intensification level should prioritize the improvement of comprehensive and ecological water use. Separate evaluation of the two is more conducive to identifying weaknesses in their respective processes. Thus, more targeted and scientific improvement measures can be taken to enhance the level of urban water resource development and utilization.

Predicting Urban Water Consumption and Health Using Artificial Intelligence Techniques in Tanganyika Lake, East Africa

Water quality has significantly declined over the past few decades due to high industrial rates, rapid urbanization, anthropogenic activities, and inappropriate rubbish disposal in Lake Tanganyika. Consequently, forecasting water quantity and quality is crucial for ensuring sustainable water resource management, which supports agricultural, industrial, and domestic needs while safeguarding ecosystems. The models were assessed using important statistical variables, a dataset comprising six relevant parameters, and water use records. The database contained electrical conductivity, pH, dissolved oxygen, nitrate, phosphates, suspended solids, water temperature, water consumption records, and an appropriate date. Furthermore, Random Forest, K-nearest Neighbor, and Support Vector Machine are the three machine learning methodologies employed for water quality categorization forecasting. Three recurrent neural networks, namely long short-term memory, bidirectional long short-term memory, and the gated recurrent unit, have been specifically designed to predict urban water consumption and water quality index. The water quality classification produced by the Random Forest forecast had the highest accuracy of 99.89%. The GRU model fared better than the LSTM and BiLSTM models with values of R2 and NSE, which are 0.81 and 0.720 for water consumption and 0.78 and 0.759 for water quality index, in the prediction results. The outcomes showed how reliable Random Forest was in classifying water quality forecasts and how reliable gated recurrent units were in predicting water quality indices and water demand. It is worth noting that accurate predictions of water quantity and quality are essential for sustainable resource management, public health protection, and ecological preservation. Such promising research could significantly enhance urban water demand planning and water resource management.