Water Management System Research Articles

Connecting With Building Water System Operators and Managers

Public water systems have access to an abundance of professional expertise and technical resources. Sharing this information with customers who operate and manage building water systems provides numerous benefits.

Problems of precipitation treatment in closed water management systems of industrial enterprises

The article is devoted to solving urgent problems of creating and improving closed water management systems of industrial enterprises. An overview and detailed analysis of the implementation of the federal program “Waste” in the existing regional centers of the Russian Federation is provided. During the analysis, the authors identified and solved the following tasks: justification of the need for the creation of closed water management systems (ZSVH); determination of the subject composition required for the development of SPM; selection of process diagrams and corresponding equipment. The article illustrates the experience of implementing the federal program “Waste” in various regions of the Russian Federation, which testifies to the cooperation of enterprises where industrial waste is generated with enterprises where it is processed and used as raw materials or disposed of. Based on the consideration of the types of industrial effluents and the directions of activities of enterprises, the authors came to the conclusion about the advisability of special treatment of industrial effluents before disposal directly at the site of their formation to obtain a dried final product, which should be carried out in accordance with regulatory requirements in the field of waste management.

Sustainable Development Strategies and Good Agricultural Practices for Enhancing Agricultural Productivity: Insights and Applicability in Developing Contexts—The Case of Angola

In general, agricultural productivity in Angola is low due to the limited awareness among stakeholders regarding sustainable development strategies (DSs) and good agricultural practices (GAPs) that could be adjusted to local crops, soil types, and climatic conditions. A structured approach was followed to develop a systematic literature review (SLR) that can address this gap by examining how DSs and GAPs may be adapted for Angola’s context to encourage sustainable agricultural development. Key steps included the selection and exclusion of literature from primary scientific databases based on specific screening indicators such as the publication date, language, relevance to DSs and GAPs, and geographic focus on developing or developed nations with comparable agricultural challenges. The initial search resulted in 11,392 articles, of which 4257 met the primary selection criteria. After further screening for relevance and availability, 98 articles were shortlisted, and 15 studies were ultimately included for in-depth analysis. This strict screening process ensured the inclusion of studies most applicable to Angola’s agricultural context. The key research findings indicate that certain DSs and GAPs have high adaptability potential for Angola. The findings emphasise practices such as drip irrigation and inorganic fertilisation, which are widely implemented in both developed and developing countries due to their efficiency in resource-limited environments. Additional strategies, such as water management systems, organic composting, and agroforestry practices, demonstrate significant potential to enhance soil fertility, water efficiency, and crop resilience against climate variability. By identifying these practices and strategies, this study provides a basic framework for policymakers in Angola to develop targeted implementation guidelines, fostering sustainable agricultural growth and resilience in the face of climatic challenges. Thus, this review contributes to the scientific and practical understanding of sustainable agriculture in developing countries, offering critical insights that support Angola’s efforts to achieve greater self-sufficiency and economic stability through sustainable agricultural practices.

Simulating Agricultural Water Recycling Using the APEX Model

Irrigation plays a vital role in many agricultural crop production regions. Drainage water recycling (DWR) is a popular irrigation water management system that collects excess water drained from cropland fields and stores it in on-site reservoirs for reuse. The efficacy of these systems varies by location, climate, irrigation frequency, and crop demands. Simulating this system would be beneficial for assessing the impact of water and land management practices on agriculture and natural resources. This study presents the development of computational algorithms for DWR simulation with the Agricultural Policy Environmental eXtender (APEX) model, along with the results for 39 testing sites where both reservoir and drainage systems are adopted. Simulating a DWR system with the revised reservoir module, the APEX model simulates irrigation water reuse ranging between 29% and 93%; sediment reduction of around 66%; nitrogen loss reduction of 23% and 73% for the mineral and organic forms, respectively; and phosphorus loss reduction of 22% and 79% for the soluble and sediment-transported forms, respectively. In conclusion, the results provided by the APEX model for sediment loss reduction align with field data, but discrepancies for nitrogen and phosphorus losses emerged from this test.

Using computational fluid dynamics and deep learning for leak detection and localization in a smart water management system

Water leakages in distribution systems offer significant challenges, resulting in water loss, infrastructure damage, and environmental hazards. As urban populations grow and water resources become scarcer, water management systems’ efficiency becomes increasingly important. Traditional leak detection methods are inadequate and labour-intensive, making them unsuitable for large-scale infrastructure. In addition, limitations in the data representing pipes of varying diameters and materials under various leak scenarios leads to complexity in automatic water leak detection and localization. In response to this challenge, this research effort combines Computational Fluid Dynamics (CFD) and Deep Learning (DL) to enhance leak detection and localization. The study simulates water flow in pipes of varying diameters and materials under various leak scenarios using CFD. Consequentially deep learning models like the Bi-Layered ReLU Encoder + Softmax and Tri-Layered ReLU Encoder + Softmax are trained and tested. The results indicate improvements in detection accuracy by 2.4% and localization by 5.6%, highlighting the potential of this hybrid approach to enhance the reliability and efficiency of water management systems, ultimately promoting water conservation and reducing infrastructure damage.

Prediction of Sediment Transport and Deposition in the Stone Buddha Temple Reservoir Based on HD and ST Bidirectional Coupling Model

Reservoirs deliver vital ecological services, including water storage and drainage. However, these functions are increasingly compromised by the dual pressures of climate change and human activities. Among the most pressing concerns is reservoir sedimentation, highlighting the urgency of investigating hydrodynamic sediment scouring. This study focuses on the plain reservoirs of Liaoning Province, using the Shifo Temple Reservoir as a case study. An optimized sediment scouring scheme was developed based on the reservoir’s hydrodynamic characteristics to improve water and sediment management. A coupled hydrodynamic and sediment transport (ST) model was constructed to simulate runoff dynamics and sediment distribution within the Liao he River Basin, while the MIKE21 model was applied to simulate the interaction between the hydrodynamics and sediment transport. The study analyzed groundwater dynamics across different runoff scenarios, seasons, and representative years, offering a scientific foundation for optimizing water and sediment allocation strategies. The results demonstrated a strong correlation between simulated and observed data during validation, confirming the accuracy of the hydrodynamic simulations. Utilizing the coupled HD and ST modules, the study proposed a sediment transfer scheme. The analysis revealed that flow rates between 165 and 190 m3/s significantly enhance sediment scouring in the long term (2029–2039) compared to the short term (2024–2029), effectively reducing sedimentation, minimizing deposition length, and lowering silt removal costs. The findings offer critical insights for predicting reservoir evolution and conducting risk assessments, thereby contributing to the sustainable management and ecological restoration of water systems in Liaoning Province.

Real-Time Pipeline Fault Detection in Water Distribution Networks Using You Only Look Once v8.

Detecting faulty pipelines in water management systems is crucial for ensuring a reliable supply of clean water. Traditional inspection methods are often time-consuming, costly, and prone to errors. This study introduces an AI-based model utilizing images to detect pipeline defects, focusing on leaks, cracks, and corrosion. The YOLOv8 model is employed for object detection due to its exceptional performance in detecting objects, segmentation, pose estimation, tracking, and classification. By training on a large dataset of labeled images, the model effectively learns to identify visual patterns associated with pipeline faults. Experiments conducted on a real-world dataset demonstrate that the AI-based model significantly outperforms traditional methods in detection accuracy. The model also exhibits robustness to various environmental conditions such as lighting changes, camera angles, and occlusions, ensuring reliable performance in diverse scenarios. The efficient processing time of the model enables real-time fault detection in large-scale water distribution networks implementing this AI-based model offers numerous advantages for water management systems. It reduces dependence on manual inspections, thereby saving costs and enhancing operational efficiency. Additionally, the model facilitates proactive maintenance through the early detection of faults, preventing water loss, contamination, and infrastructure damage. The results from the three conducted experiments indicate that the model from Experiment 1 achieves a commendable mAP50 of 90% in detecting faulty pipes, with an overall mAP50 of 74.7%. In contrast, the model from Experiment 3 exhibits superior overall performance, achieving a mAP50 of 76.1%. This research presents a promising approach to improving the reliability and sustainability of water management systems through AI-based fault detection using image analysis.

Influence of Sustainable Agriculture Practices, Water Management, and Organic Seedling Availability on Yields in Bandung Regency Organic Farms

This study investigates the impact of organic seedling availability, sustainable agriculture practices, and water management on the yields of organic farms in Bandung Regency. Using a quantitative approach, data were collected from 230 organic farmers and analyzed using Structural Equation Modeling (SEM) with Partial Least Squares (PLS). The results reveal that all three factors significantly and positively affect farm yields. Water management had the strongest influence, followed by organic seedling availability and sustainable agriculture practices. These findings highlight the critical role of resource management in enhancing the productivity of organic farms. The study suggests that improving access to organic seedlings, promoting sustainable farming techniques, and investing in efficient water management systems can lead to better farm performance and sustainability. The research offers practical insights for policymakers and agricultural stakeholders seeking to optimize organic farming in the region.

Leak detection and leak localization in a smart water management system using computational fluid dynamics (CFD) and deep learning (DL)

Leak detection and leak localization in a smart water management system using computational fluid dynamics (CFD) and deep learning (DL)

Smart Building Digital Twin for Interior Water Distribution System Management

Abstract. A smart campus integrates the Internet of Things, artificial intelligence, and real-time sensor data to optimize campus functions and create a context-aware decision-support platform for effective campus management. A crucial aspect of a smart campus is the water distribution system, which faces several challenges due to bursts, leaks, and water quality issues. This study uses Digital Twin technology to address these challenges through real-time monitoring, detection, and management of campus water distribution networks. A building-level digital twin is developed for the interior water networks of the Daphne Cockwell Complex at Toronto Metropolitan University. The major components include a 3D network model capable of analysis and simulations, a smart water management system, and real-time visualization. A 3D static model of the interior water utility network is created using the Industrial Foundation Class data. The semantic and topological models based on graph models are developed for network analysis. The models are integrated into the ESRI ArcGIS Pro to facilitate BIM-GIS integration. A dynamic model is created by incorporating automatic meter readings based on IoT. Combined with the 3D model of the utility network, the digital twin monitors and visualizes building water consumption, facilitating anomaly detection and real-time maintenance by the facilities management department. This study provides practical guidance for managing water distribution systems in university buildings, with potential applications in other complex environments. Future work aims to develop a system for detecting complex event processes by integrating different utilities.

A review of the knowledge structure and trends in research on the interlinkages between the rule of law and environmental sustainability

AbstractThe interplay between nature and human activities is important for both human well‐being and the health of our planet. The rule of law is central to maintaining harmony between environmental needs and human endeavors. Since the early 1990s, particularly after the Earth Summit in 1992, there has been an increased interest in the relationship between environmental sustainability and legal frameworks. This has led to a significant expansion in the field, encompassing a wide array of research. Despite the field's growth, there is still a lack of review papers that explore its knowledge structure and evolution. This study aims to conduct a comprehensive bibliometric analysis of the literature by employing the Visualization of Similarities (VOS) viewer software. We identify key thematic areas within the field, highlight influential authors and journals, and specify major contributing countries and institutions. The findings show that the initial focus was on limited themes, which later gave way to an acknowledgment of the multidimensional nature of the subject. Certain themes, such as environmental emissions and governance, retain prominence. Among the focal themes, sustainability, climate change, and democracy are particularly influential in shaping the field's trajectory. Despite this evolution, certain aspects of both concepts, such as waste and water management, fundamental rights and justice system, and the importance of socio‐economic factors, remain underrepresented. This study offers valuable insights into the linkage between the rule of law and environmental sustainability themes and the associated themes.

A Case Study on Sustainable Energy Use from Ballast Water Management System in Transport Vessels

A Case Study on Sustainable Energy Use from Ballast Water Management System in Transport Vessels

Actionable human–water system modelling under uncertainty

Abstract. This paper develops an actionable interdisciplinary model that quantifies and assesses uncertainties in water resource allocation under climate change. To achieve this objective, we develop an innovative socio-ecological grand ensemble that combines climate, hydrological, and microeconomic ensemble experiments with a widely used decision support system for water resource planning and management. Each system is populated with multiple models (multi-model), which we use to evaluate the impacts of multiple climate scenarios and policies (multi-scenario, multi-forcing) across systems so as to identify plausible futures where water management policies meet or miss their objectives and to explore potential tipping points. The application of the methods is exemplified by a study conducted in the Douro River basin (DRB), an agricultural basin located in central Spain. Our results show how marginal climate changes can trigger non-linear water allocation changes in the decision support systems (DSSs) and/or non-linear adaptive responses of irrigators to water shortages. For example, while some irrigators barely experience economic losses (average profit and employment fall by < 0.5 %) under mild water allocation reductions of 5 % or lower, profit and employment fall by up to 12 % (∼ 24 ×) when water allocation is reduced by 10 % or less (∼ 2×). This substantiates the relevance of informing the potential natural and socio-economic impacts of adaptation strategies and related uncertainties for identifying robust decisions.

What is the status of the European Union's water resources and sanitation services when sustainable development goals are evaluated?

Even when water scarcity and quality issues are not severe in the European Union (EU) countries, the impacts of climate change and external pressures vary across EU nations, leading to different outcomes. Achieving sustainability requires prioritizing the efficient management of water resources and sanitation services. To this end, conducting studies to identify countries needing appropriate measures is essential. This research focuses on evaluating and analysing the situation of water resources and sanitation systems in the European Union, with two specific objectives in mind. The first objective is to compare disparities between Member States (MSs) in a particular year and track their progress over two periods of five and ten years concerning variables related to water resources and sanitation services. By examining these disparities, the study aims to identify which countries have made significant improvements and which require more attention and resources to enhance their water management and sanitation systems. The second objective is to identify the countries best positioned to achieve certain Sustainable Development Goals (SDG 6, SDG 1, SDG 2, SDG 8, SDG 10, SDG 11, SDG 12).The results indicate that the countries best positioned in terms of meeting the SDGs and achieving sustainability in water and sanitation are Luxembourg, the Netherlands, Finland, Sweden, Denmark and Germany. However, in contrast, Romania, Lithuania, and Slovakia face greater challenges, particularly in sanitation. Factors such as economic level and climate change, which impact southern countries more severely (Greece, Spain, Cyprus) where water scarcity is more acute, contribute to these difficulties. Additionally, the lack of information on wastewater management hinders decision-making and the proper management of these wastes.This study analyses the progress and current status of water and sanitation indicators from an environmental perspective for the first time. It introduces variables to assess sustainability in EU countries that are not listed as indicators on the United Nations website, aiming to evaluate compliance with the SDGs.

Historical synthesis of the International Commission on Water Resources Systems

The planning, designing, management, and operation of water systems has been one of the most important activities throughout the history of humankind. However, as a scientific and applied discipline, it evolved about 70 years ago. The International Commission on Water Resources Systems (ICWRS) has primarily focused on developing and implementing improved methods for water resources management for the benefit of society since the 1970s. This paper reviews the history of the Water Resources Systems (WRS) discipline over these six decades after the 100th anniversary of the International Association of Hydrological Sciences (IAHS) and aims to make a synthesis of the history of ICWRS. In the concluding section, an outlook for researchers and decision-makers on the future development of water resource systems research is also provided.

Sustainable Water Management Through Green Infrastructure

This research explores the implementation of sustainable water management practices through green infrastructure (GI) solutions. As urbanization intensifies, traditional water management systems face challenges such as flooding, water pollution, and reduced biodiversity. Green infrastructure, which integrates natural processes into urban planning, offers innovative strategies for stormwater management, water quality enhancement, and habitat restoration. This study examines various GI techniques, including rain gardens, permeable pavements, and green roofs, assessing their effectiveness in mitigating urban water challenges. Case studies from multiple cities demonstrate the benefits of GI in promoting resilience against climate change while enhancing community well-being. The findings underscore the potential of green infrastructure as a viable alternative to conventional water management methods, advocating for its broader adoption in urban environments. Key Words: Sustainable water management, Green infrastructure, Stormwater Management, Urbanization, Climate resilience, Water quality enhancement

Irrigation Water Management and Food Security in Nigeria

Food security remains a persistent challenge in Nigeria, a country with a rapidly growing population and a heavy reliance on rain-fed agriculture. Effective irrigation water management is crucial to improving agricultural productivity and addressing this critical issue, particularly in the face of climate change and increasing water scarcity. This study investigates the current state of irrigation water management and its impact on food security in Nigeria. The research employs a mixed-methods approach, combining an extensive literature review with field surveys, interviews, and focus group discussions with key stakeholders, including farmers, water resource managers, policymakers, and subject matter experts. The findings reveal significant gaps in Nigeria's existing irrigation water management system, including outdated infrastructure, inefficient water distribution, limited access to irrigation technology, and poor coordination among relevant government agencies and agricultural extension services. The study explores the multifaceted relationship between irrigation water management and food security, highlighting the impact of water availability, quality, and accessibility on crop yields, livestock production, and overall agricultural output. The analysis also examines the socioeconomic and environmental implications of poor irrigation water management, such as reduced farm incomes, food price volatility, and environmental degradation. Based on the research findings, the study proposes a comprehensive framework for sustainable irrigation water management in Nigeria. This framework emphasizes the integration of technological innovations, policy reforms, institutional strengthening, and community-based approaches to enhance the efficiency, equity, and resilience of the irrigation system. Key elements of the framework include modernizing irrigation infrastructure, promoting precision agriculture techniques, improving water governance and stakeholder coordination, and enhancing the capacity of farmers and water user associations. The implications of this study are far-reaching, as it provides policymakers, development agencies, and agricultural practitioners with a thorough understanding of the critical role of irrigation water management in achieving food security in Nigeria. The proposed framework offers a roadmap for the implementation of sustainable irrigation practices, which can contribute to increased agricultural productivity, improved rural livelihoods, and enhanced national food security. The findings of this research also offer valuable insights for other developing countries facing similar challenges in the realm of irrigation water management and food security.

Research and application of the method of measuring the effective utilization coefficient of irrigation water on farmland

Abstract Under the guidance of the new water management idea of “water conservation priority, spatial balance, system management, and two-handed effort,” the National Water Conservation Action Plan released in 2019 puts forward the key task requirements of “double control of total intensity,” in which the effective utilization coefficient of irrigation water in farmland is one of the indicators of water intensity control. The effective utilization coefficient of irrigation water is one of the water intensity control indicators. At present, there are practical difficulties in measuring the effective utilization coefficient of irrigation water in farmland, such as the low measurement rate of water consumption in the current irrigation area, the high input equipment and manpower requirements, and the difficulty in accurately measuring the net irrigation water absorbed by crops. Therefore, this paper proposed the method of “field monitoring - remote sensing inversion - a comprehensive analysis of data.” The method of “field monitoring - remote sensing inversion - econometric model construction - comprehensive analysis” was proposed in this paper, which can obtain gross irrigation water utilizing field monitoring, overcome the difficulty of accurate monitoring of net irrigation water using remote sensing, and carried out a comprehensive analysis, to realize the scientific, effective and rapid calculation of effective utilization coefficient of irrigation water. This method was applied to the Meixian District, Guangdong Province, and the research results show that it not only generates reliable measurement data but also alleviates workload. Furthermore, it offers scientific measurement techniques for water use efficiency indicators, facilitating the achievement of “dual control over total volume and intensity.” This paper provides an important technical basis for the rational allocation of water consumption and scientific approval of water use plans and supports the assessment of the effectiveness of water-saving irrigation development and the reasonable evaluation of the water-saving potential of farmland irrigation, thus providing a basis for local government departments at all levels to make planning, scientific decision-making, and macro-management.

Design and implementation of closed-loop water reuse systems in urban and industrial settings for maximizing resource recovery and minimizing waste

Global demand for water while the freshwater sources are diminishing, it is necessary to find feasible solutions based on sustainable usage of resources. The goal is to provide beneficial use of as many resource constituents as possible with as little effluent discharge as possible leveraging innovations in treatment technologies and systems. Parameters of discussion include the operation and efficiency of membrane bioreactors, different kinds of oxidation, and reverse osmosis technologies. Such technologies are instrumental in improving the quality of water as well as enabling recovery of useful resources from the streams of wastewater that are normally obtained from several processes. This paper also assesses the feasibility of resource recovery closed-loop systems to measure its economic benefits determinable by operational expenses, energy usage and possible revenue streams from the recycled materials. Such knowledge synthesizes the findings of prior studies in the literature and emerging technologies that help to support this research and identify the impact that closed-loop water reuse systems can have. This emphasizes on the need to have proper regulatory status and consumer’s involvement for its general adoption and practicable implementation. In the long run, the integration of the systems explained above will definitely advance a sustainable water management system that will help in the stewardship of the environment and ensure that in case of arising challenges globally the country will be able to cope.

Automated Water Regulation Systems for Sustainable Management

Finding new ways to manage water resources becomes even more relevant today, as the growing demand for food globally combines with challenges like climate change and water scarcity. This research paper attempts to discover the automated water regulation systems that utilize advanced technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and data interpretation to upgrade irrigation practices and boost sustainable resource management. By using sensors that keep the soil moisture and the environmental conditions in check, accurate modifications can be made to the irrigation being provided. Keeping a check can help reduce water wastage by up to 30% and increase crop yield by an average of 15%. This study amplifies the productivity of smart meters and the demand for AI-driven prediction models that are capable of providing accurate forecasts and real-time data, both of which are very necessary for efficient water management. However, there exist challenges like the question of data security, high initial costs, and user acceptance. These challenges need to be addressed to make sure that these systems are widely adopted. The considerable potential of the automated water management systems to promote sustainable practices in agriculture and to ensure food security when water scarcity is increasing are highlighted via the findings made in this paper. 1 This paper has been written after taking several research papers written by scholars and professors in this field. Taking into consideration their findings and observations, and incorporating personal observations and the potential results that can be applied, this paper is drafted to recommend practices that will help support vegetation and sustainable practices.