Journal of Water and Sustainable Development

Abstract Top-down, supply-oriented solutions in Iran’s water governance have proven ineffective, and the era of one-size-fits-all prescriptions has come to an end. Water challenges are inherently local; therefore, policy-making must be built upon local pilots as living laboratories for institutional learning. Small, gradual successes can restore trust and generate social support. Simultaneous empowerment of both society and government, along with a redistribution of power in favor of smallholders, rural women, and marginalized communities, is an unavoidable necessity. Technological and developmental responses that appear successful on the surface can, through a “reflexive risk spiral,” lead to the exacerbation of crises or the emergence of new risks. Hence, a transition toward “reflexive, risk-informed, and resilient development” is required. Data are never neutral; they are inherently political. The processes of selecting what to measure, how to distribute and interpret data are all defined within the field of power. Without independent and accountable institutions, as well as public access to raw data, no technical innovation can generate transparency, and advanced technologies will only reproduce existing inequalities.

Abstract Iran is a land where the formation of its civilization is tied to a deep understanding of water limitations and the necessity of adapting to arid and semi-arid climates. Historical experiences of water management in this land show that sustainability and protection of water resources have always been the result of a balance between exploitation and conservation. However, in recent decades, increasing climate pressures, growing demand, developing economic activities, and more complex inter-sectoral relationships have presented water governance with challenges that require approaches beyond traditional decision-making tools. In such a context, artificial intelligence, as one of the outstanding achievements of the data age, has provided a new opportunity to improve the quality of water governance.

Abstract The water crisis has evolved from a limited geographical challenge to a global issue with multiple economic, environmental, social and even security dimensions in recent decades. Population growth, urbanization, climate change and rising levels of prosperity have all led to an increase in demand for water resources, while the supply of these resources is facing serious constraints due to natural constraints and environmental degradation. In the meantime, the agricultural sector, as the largest consumer of freshwater, plays a key role in the formation and management of this crisis.

Abstract The smart irrigation market, as one of the emerging and rapidly growing sectors in agriculture and water resources management, has attracted considerable attention in recent years. This technology enables optimized and automated irrigation through the use of intelligent devices and systems such as sensors, weather- and soil-moisture-based controllers. The primary objective of these systems is to reduce water losses and improve water use efficiency. The growing demand for smart irrigation technologies is driven by water scarcity, climate change, population growth, and the increasing need for higher food production. Moreover, technological advancements such as the Internet of Things (IoT), machine learning (ML), and big data analytics play a crucial role in optimizing irrigation processes and reducing operational costs. The smart irrigation market is projected to reach USD 3.94 billion by 2029, with a compound annual growth rate (CAGR) of 16.2%. Market growth is influenced by government policies, financial incentives, and investments in research and development. However, challenges such as high initial investment costs and connectivity issues in rural areas remain major barriers to the widespread adoption of this technology. International studies indicate that smart irrigation systems can reduce water consumption by 20–50% and increase water use efficiency by up to approximately 44%, highlighting their effectiveness as a viable solution for addressing water scarcity and enhancing irrigation system performance.

Abstract Microbial contamination of water and the increasing emergence of antibiotic-resistant bacteria have posed unprecedented challenges to global public health. Current water treatment methods, despite their advantages, face limitations such as the production of harmful byproducts and reduced efficacy against antibiotic-resistant strains. In the alarming situation of increasing antibiotic resistance, bacteriophages (phages) serve as a powerful line of defense and a vital alternative. Bacteriophages are viruses that have a protein core with a nucleic acid called a capsid and a thin, fiber-like tail. Phage proteins bind to specific receptors on the surface of target bacteria, conferring high specificity to them. Some phages have a broad host range and can recognize multiple receptors on different bacterial species and genera. This review examines the potential of bacteriophages as an alternative to antibiotics and a complement to traditional water treatment methods. This systematic review collected and analyzed research from the past 15 years sourced from reputable scientific databases. The extracted data were categorized and analyzed based on the applications of bacteriophages in wastewater treatment. According to the findings, key advantages of phages include high specificity (precise targeting of pathogens without harming beneficial flora), ability to self-replicate in the presence of the host, ability to destroy biofilms and affect antibiotic-resistant bacteria, making them a powerful tool in combating the microbial resistance crisis. The ultimate conclusion of this review is that, despite existing barriers, the transition from purely chemical methods towards "phage therapy" in water treatment is not merely a possibility but an increasing necessity for ensuring water safety in the age of antibiotic resistance. Future advances in phage engineering and the development of smart phage cocktails will facilitate the operational implementation of this strategy on an industrial scale.

Abstract The Persian Gulf Water Transfer Project is one of the largest infrastructure initiatives in Iran’s water sector, implemented to provide drinking water and support export-oriented industrial development. Despite the stated benefits, the project has faced criticisms and opposition from environmental specialists, social activists, and some scientific institutions. This study aims to identify the main roots of social conflicts surrounding the project and to propose a participatory governance model based on sustainable development. A qualitative research approach was adopted, employing document analysis of official and media sources alongside semi-structured interviews with key stakeholders. Data were analyzed using thematic analysis with MAXQDA software. The research framework is grounded in sustainable development across economic, social, and environmental dimensions, as well as participatory governance theories. Findings indicate that the primary roots of conflict include competing stakeholder interests, lack of transparency in policymaking, disregard for alternative options, and public distrust. In addition, significant challenges were identified across all three dimensions of sustainable development. The importance of this study lies in presenting a context-specific participatory governance model that emphasizes multi-stakeholder dialogue, transparency of information, and collective decision-making. This model can contribute to improving policymaking and project management in water transfer initiatives within Iran and similar local contexts. However, due to the specific socio-political characteristics of the Persian Gulf Water Transfer Project, the findings are not necessarily generalizable to other projects, serving primarily as guidance for policymakers in comparable initiatives.

Abstract In recent years, Environmental Non-Governmental Organizations (ENGOs) have emerged as key actors in promoting non-formal water education. However, the lack of standardized, context-specific, and multidimensional evaluation tools to assess the quality of Environmental Education (EE) provided by these organizations has created a significant gap in their learning systems and continuous improvement processes. This study aims to design and validate a comprehensive, localized checklist for evaluating the quality of EE in Iranian ENGOs. The research adopted an exploratory mixed-methods approach, conducted in two phases. In the first phase, qualitative content analysis of documents and interviews with 15 experts led to the extraction of a preliminary framework consisting of 7 main criteria and 13 sub-criteria. In the second phase, a modified Delphi technique involving 6 experts was employed for content validation (using CVR and CVI indices), while statistical analysis was used to assess the tool’s reliability (via Cronbach’s alpha and exploratory factor analysis). The results demonstrated that the final checklist exhibits high reliability (α = 0.91) and a coherent factor structure. This tool can be utilized for both internal and external evaluations of the quality of EE provided by ENGOs, offering a robust foundation for enhancing organizational learning, evidence-based decision-making, and strengthening collaboration between governmental and civil institutions.

Abstract Sewage projects are among the most important urban infrastructure facilities that bring about appropriate living conditions and increased social welfare for the people. In this regard, the present study was conducted to investigate the feasibility of implementing a wastewater project in the study area adjacent to the Caspian Sea in the cities of Babol and Amirkola. The results obtained showed that by examining the above options in terms of environmental, social, economic and technical factors, including seven criteria (ease of project implementation, compliance with technical standards, public satisfaction with the desired option, improvement of public health and hygiene, endangerment of water and soil quality in the region, investment cost of each alternative plan) and giving them points, and considering the goals of sustainable development, the option of implementing the complete collection network, transmission line and wastewater treatment plants in Babol and Amirkola with the highest score is the priority. Given the increasing trend of population growth in the cities of Babol and Amirkola, the traditional wastewater disposal system, due to long-term environmental pollution, will not be responsive to the region’s sanitary and environmental needs. The option of constructing a collection network and wastewater treatment to common national environmental standards for the study area has been identified as the superior choice, and it will have significant impacts on the health and environmental status of this city and its surrounding areas. Furthermore, by recovering wastewater and utilizing it in agriculture, water wastage, especially in water-scarce regions, can be prevented. Thus, the implementation of this project is environmentally justified.

Abstract In this experimental study, the discharge coefficient of flow over rectangular broad-crested weirs was examined under two conditions: solid and porous (gabion). For the porous weir, eight tests were conducted with effective lengths of 30 cm and 60 cm, using three gradations with mean particle diameters of 11 mm, 19 mm, and 28 mm. Initially, under free-flow conditions downstream of the weir, discharge coefficients for solid and gabion weirs were calculated and compared. Additionally, variations in velocity profiles and Reynolds shear stress distributions within the hydraulic domain of the weir were evaluated. The analysis of the water surface profile demonstrated that increasing gabion particle size reduced resistance to flow, thereby requiring a greater discharge to achieve fully overtopping conditions. Conversely, at constant discharge, increasing the weir length enhanced hydraulic resistance, leading to a higher upstream head. Examination of discharge coefficients revealed an increasing trend with longer weir lengths at equal discharges. On average, coefficients for porosities of 38%, 42%, and 45% were 0.74, 0.82, and 0.89 for the 30 cm weir, and 0.95, 1.00, and 1.20 for the 60 cm weir, respectively, whereas the solid weir yielded a coefficient of about 0.38. Furthermore, by applying a multivariable correlation equation and employing a gene expression programming (GEP) model based on dimensional analysis, an efficient predictive relationship for discharge over gabion weirs was developed, achieving a coefficient of determination of 98%.

Abstract The increasing water stress at both global and national levels, particularly in countries such as Iran, has shown that linear and single‑dimensional approaches to urban water management are no longer capable of addressing the existing complex challenges. In this context, adopting a circular economy approach and aligning water supply and demand management strategies in an integrated manner has emerged as a strategic necessity. This research aims to design a strategic framework for aligning urban water supply and demand management with the circular economy approach. In today's world, the growing challenges of water scarcity and limited water resources necessitate a review of traditional management models and a shift toward innovative and sustainable approaches. The circular economy, as a new paradigm, provides the opportunity to create alignment between supply strategies and demand management. In this research, using the thematic analysis method, 91 scientific articles published between 2015 and 2024 were examined. The research results led to the identification of five main dimensions (resource and infrastructure management strategies, circular economy strategies, demand and consumption management strategies, planning and policy-making strategies, and stakeholder participation and collaboration strategies), 26 components, and 62 indicators. This framework can serve as a guide for policymakers and urban water specialists in designing and implementing strategies aligned with circular economy principles and provide the foundation for achieving sustainable water resource management.

Abstract Food security is a fundamental pillar of sustainable development, and its realization requires effective and accountable governance throughout the entire food supply chain. A review of previous national studies indicates that food security governance in the country has predominantly focused on improving productivity, while facing challenges such as weak conceptual definitions of food security, constraints on transparency and stakeholder engagement, and the absence of integrated policy mechanisms. Adopting a systems approach and employing system dynamics, this study proposes a conceptual framework as an innovative tool for analyzing and improving water and food governance. The framework enables the assessment of key institutions, their interrelationships, and the effectiveness of existing policies based on data and empirical evidence, thereby helping to identify institutional bottlenecks and develop corrective scenarios. The tool highlights the interdependence of food production on scarce water resources and underscores the need to link water and food governance.  The results of implementing the current status scenario indicate that food availability exceeds 80%, while the access index varies between 60% and 90%. However, water extraction at a rate of 50% above sustainable levels highlights the unsustainability of production. Furthermore, with a daily food consumption of 4 kilograms, the nutritional health index fluctuates between 43% and 63%, indicating an unfavorable nutritional status. Overall, the focus of current policies on increasing production, without regard for nutritional health and resource sustainability, has placed the country's food security in a precarious position and led to the degradation of production resources. Therefore, the implementation of innovative approaches to enhance food security sustainability is essential.

Abstract Estimating the economic value of water plays a fundamental role in the efficient management of water resources and in making informed decisions for water supply planning. It is regarded as one of the main pillars in resource allocation, the design of pricing systems, and the development of sustainable water markets. In this study, the economic value of water was estimated using the Residual Value Method, based on data from the Statistical Center of Iran’s Census plan for industrial enterprises with 10 or more employees during the years 2002 to 2019. The results indicate that the economic value of water varies significantly across major industrial sectors in the Zayandeh-Rud Basin, with an average value of 5,254,702 rials per cubic meter, based on the producer price index, for the year 2024. These findings can be considered in the economic assessments of water supply projects for large industries in the basin. Furthermore, according to the research results, the average cost of water in the industrial production process was less than 0.2% of total production costs, and the ratio of this cost to the economic value of water estimated to be below 0.02. These findings highlight the necessity for a review of the industrial water pricing system, the enhancement of statistical data quality in the industrial sector, and the incorporation of the true economic value of water into water allocation and investment policies in the country.

Abstract The Internet of Things (IoT), through real-time monitoring and data analysis, enhances the sustainability of urban water systems and guides cities towards smart management and sustainable water supply. In this regard, the present research study has been prepared with the aim of meta-analyzing the role of the Internet of Things in the future of urban water systems in Tehran metropolis. The research approach is a systematic and structural meta-analysis, which is applied in terms of objective and descriptive-analytical in terms of methodology, based on bibliometrics and Delphi. In the first part, through systematic analysis, 388 articles retrieved from the Scopus database were identified and analyzed using VOSviewer software. In the second, structural part, 14 key indicators were analyzed using the MICMAC technique, and future scenarios were identified with the Scenario Wizard software. The statistical population comprises experts in the fields of water and urban planning, from whom 60 individuals were selected as the statistical sample using purposive sampling. The results indicate the dominance of research output from India (30.9%), China (8.5%), and the United States (7.2%). The primary research areas investigated include water quality monitoring, leak detection, smart metering, and demand management, while future challenges encompass data security, privacy, and interoperability between systems. The results of the structural analysis showed that smart irrigation has the highest influence and water infrastructure monitoring has the highest susceptibility, highlighting the key role of technology and infrastructure in urban water management. The scenarios indicated that only through the synergy of smart technologies, data analysis, and cybersecurity can high efficiency and equitable access to water be achieved in Tehran metropolis. Therefore, future predictive analyses, increased connectivity, and IoT integration are essential for optimizing water resource management and ensuring its long-term sustainability.

Abstract Drought, as a natural and creeping phenomenon, is considered one of the most important climate challenges in arid and semi-arid regions, including Iran. Given the context of climate change and the increased severity of drought events, a dynamical analysis is crucial for effective water resource management. This study aimed to investigate the probabilistic behavior and drought dynamics within the Mashhad Plain. To achieve this, the Markov Chain model was applied to a 127-year time series of precipitation and mean temperature data. The core innovation lies in employing the Twelve-Fold Hydrologic Time Series method. By analyzing the data across twelve annual time scales, this approach facilitated a more comprehensive and precise characterization of drought features, effectively revealing long-duration events often masked in conventional annual analyses. The results derived from the transition probability matrix indicated that extreme climatic states (severe drought and extreme wet periods) exhibit significant persistence, whereas intermediate states (moderate drought and moderate wet periods) are inherently more transient. Furthermore, the calculation of the steady-state distribution provided a clear perspective on the long-term behavior of the climatic system. The findings reveal that, in the long run, the combined probability of residing in drought states (severe and moderate), totaling 42%, is higher than the probability of residing in wet states (38%). These results yield invaluable insights for strategic, long-term planning in water resource management and facilitate effective adaptation strategies against future climatic conditions in arid and semi-arid regions.

Abstract Ensuring the accuracy of precipitation data in arid and semi-arid regions, which inherently face a scarcity of ground monitoring stations, is vital for sustainable water resource management and drought assessment. GPPs offer a promising alternative; however, they suffer from systematic biases and inherent uncertainties in estimating extreme values, limiting their direct application in hydrological models. This study aims to develop and evaluate a machine learning-based fusion model to generate a corrected daily precipitation product (ML-Corrected) and assess its efficacy in improving meteorological drought monitoring in South Khorasan Province, a representative arid and data-scarce region. To this end, four widely used GPPs were utilized alongside four spatiotemporal auxiliary variables (latitude, longitude, month, and day of year) as inputs for a RF model. Daily observational precipitation data from six synoptic stations (2010–2019) served as the target variable for model training and validation. Results indicated that the ML-Corrected product demonstrated absolute statistical superiority over all raw GPPs. In daily precipitation assessment, the ML-Corrected product achieved the highest correlation coefficient (median CC=0.87), the lowest error (median RMSE=0.78 mm/day), and the best success index (median CSI=0.545). More importantly, in drought monitoring assessment, the SPI time series derived from the ML-Corrected product (at both 3-month and 12-month scales) exhibited the highest agreement (median R2 > 0.81) and lowest error (median RMSE < 0.40) compared to observed SPI. These findings prove that the machine learning-based fusion approach acts as an intelligent error corrector, significantly reducing GPP uncertainty and providing a reliable precipitation dataset for water crisis management.

Abstract Over the past years, several concepts in water management have emerged and were further developed. They included approaches for saving water and improving water use efficiency and productivity, sustainable water management strategies, salinity control, remote sensing applications to estimate crop evapotranspiration (ETc), soil moisture, crop yield and land cover, using models as water management tools and for designing reservoirs and dams. The intention was great, but the application of the concepts did not always match the intention. Examples of misunderstandings and misconceptions include incorrect application of deficit irrigation, using water use efficiency instead of water productivity, misunderstanding the water accounting system elements, misuse of the term sustainability, leaching with every irrigation, using the term upscaling instead of aggregation, incorrect use of long-term average flow for designing dams and reservoirs, believing that remote sensing data are direct measurements for ETc or soil moisture and believing that well-calibrated/ validated models do not have inaccuracy and uncertainty in their results. This paper highlights these concepts and their misuse and misunderstandings as well as explains the true meaning and application of each concept. The paper also explains why concepts were misunderstood and suggests approaches to improve the understanding and accurate application of the concepts.

Abstract Water challenges in Iranian cities—particularly in metropolises located in arid and semi-arid climates—have emerged as one of the most critical governance issues. In this context, concepts such as “water-friendly cities” and “water-sensitive cities” have been introduced as innovative urban management approaches that emphasize alignment with natural water cycles, active citizen participation, shifts in decision-makers’ cognitive frameworks, and the reform of consumption patterns. Meanwhile, creative industries, as key drivers of knowledge-based economies and social innovation, hold significant potential to influence water consumption behaviors, foster effective public engagement, and enhance societal awareness. Adopting a conceptual and policy-oriented perspective, this analytical note explores the interconnections between creative industries, water-related behavioral practices, social innovation, and the water-sensitive city paradigm in Iran. With a particular focus on the experience of Mashhad as a major metropolis, the paper examines the city’s capacities and potentials for transitioning toward a water-friendly urban model. The experiences implemented in Mashhad are also reviewed as a model for replication in other cities and as a foundation for consolidation and further development in the coming years, ensuring that amid the country’s immediate priorities, the pressing water challenges of today and tomorrow are not overlooked.