Digital twin (DT) technologies have emerged as a transformative framework in hydrology, enabling adaptive, real-time modeling of water systems through data-driven intelligence. This position article proposes a five-level technological evolution model for hydrological DTs, tracing the field’s progression over the last three decades (1995–2025) from physical models toward autonomous and interconnected systems. Each level is anchored in technological milestones such as web systems, geographical information systems, Internet of Things, artificial intelligence (AI) and immersive environments that collectively enhance the interactivity, intelligence and integration capacity of DT systems. The study introduces a layered implementation framework that links enabling technologies to functional capabilities across the DT life cycle. Drawing from this 30-year synthesis and real-world applications, we illustrate how DTs are being used for flood prediction, watershed management, infrastructure resilience and stakeholder engagement. A cross-level capability matrix is presented to analyze DT levels in terms of data requirements, visualization methods, computational demand, expertise and cost. The study also identifies critical research challenges in data interoperability, AI ethics, cybersecurity and institutional coordination. Recommendations are provided to guide future research, emphasizing open standards, modular architectures, participatory design and public trust. This study presents a vision for hydrological DTs as scalable, intelligent and ethically grounded systems that support climate resilience, disaster mitigation and sustainable water governance.

Access to safe and affordable drinking water remains a major challenge in remote and regional communities, particularly in Australia. In Queensland, raw-water iron (Fe) and manganese (Mn) concentrations can exceed guideline values, reaching up to 13.6 mg/L and 61 mg/L, respectively. This study developed and evaluated KJ25 EcoPellets, a calcined clay–biomass composite produced from locally sourced brick-making clays and agricultural residues, as a potential low-cost medium for Fe and Mn removal. Batch experiments compared KJ25 with conventional media under varying pH, adsorbent dose, initial concentration and contact time. KJ25 demonstrated strong Fe removal and moderate Mn removal under the investigated conditions, generally outperforming the conventional media. Kinetic modelling showed that Fe and Mn uptake were better described by pseudo-first-order and pseudo-second-order models, respectively, with intraparticle diffusion contributing to the time-dependent uptake behaviour. Langmuir modelling provided strong fits for both Fe and Mn, with maximum adsorption capacities of 10.3 and 1.9 mg/g, respectively, highlighting the substantially greater capacity of KJ25 for Fe than Mn. Overall, the results demonstrate the potential of KJ25 EcoPellets as a locally manufacturable, circular-economy-aligned medium for decentralised Fe and Mn treatment, while further validation under real-water and continuous-flow conditions is required before practical drinking-water application.

The proposed Padma Barrage aims to restore freshwater flow to southwestern Bangladesh, but it may also alter sediment transport, distributary connectivity, and river dynamics across the Southern Bengal Delta. Drawing on historical river records, historical maps, published evidence, and the geomorphological evolution of the Padma–Brahmaputra–Meghna system, this Perspective conceptually hypothesizes how altered flow and sediment regimes could affect distributary connectivity, channel migration, erosion, sedimentation, salinity distribution, and the long-term stability of the region. It further argues that the proposed USD 4.1 billion investment warrants assessment beyond its anticipated short-term freshwater benefits, with greater attention to long-term hydrological, geomorphological, ecological, and climate-related consequences. It further calls for consideration of diversified alternatives, including decentralized freshwater storage, large-scale rainwater harvesting, managed aquifer recharge, climate-resilient irrigation, distributary restoration, and basin-scale water management.

England’s water system is under intensifying pressure from scarcity, flooding, pollution, biodiversity loss and climate change, yet the prevailing model of water cycle management remains fragmented, resource-intensive and too often focused on managing symptoms rather than causes. This paper outlines an approach to integrated water cycle management that aligns with the ideas set out by Kate Raworth, in her book “Doughnut economics: seven ways to think like a 21st century economist”. Raworth envisions a just and safe space for society where our economies are geared to ensuring that everyone has the essential resources required to fulfil their human rights but resource use is limited to a level that can be sustained within the limits imposed by "ecological ceilings". This aligns with the research by Johan Rockström and his colleagues at Stockholm Resilience Centre who have developed the concept of nine “Earth system boundaries”, the exceedance of which risks triggering large-scale, abrupt or irreversible environmental change. By reframing water management in England as the stewardship of social-ecological systems to deliver human wellbeing within environmental limits, this paper supports policy momentum created by the Cunliffe Review and the Government’s New Vision for Water, while pushing further towards a genuinely integrated, catchment-based and cross-sectoral approach. Its practical contribution is to translate doughnut thinking into the water context through clear operating principles, measurable outcomes and indicative targets. Doughnut economics, applied within the context of a whole water cycle approach to regulation and governance, has potential to centre human needs (affordability, reliability, amenity) and planetary limits (spills, nutrients, flows, biodiversity) within a single, practical framework. At a time when England needs both renewed public legitimacy and more effective delivery, the paper offers a strategic framework for achieving a safe and just water future that restores rivers, reduces demand, improves resilience and enables prosperity within planetary boundaries.

The revised European Union (EU) drinking water directive has imposed a stricter norm for lead in drinking water. This has necessitated a reassessment of current and future assets maintained by Dutch drinking water utilities (such as brass-containing appurtenances), primarily from the perspective of lead exposure. Should such components result in a considerable exposure, a consequent widespread rehabilitation would require a significant investment. To quantify exposure to lead from brass components in premise plumbing systems, insights from numerical modeling and laboratory experiments are combined. An important insight is that a lead leaching component present in the kitchen tap poses a much higher exposure in contrast to it being present in the service line. This underlines the need to localize lead leaching components – where is it and who needs to take action to remove it. Subsequently, the robustness and vulnerabilities of profile sampling (a lengthy flushing followed by prolonged stagnation followed by collection of a series of water samples) in localizing lead leaching components are explored. This study has led collectively to two major conclusions for the Dutch drinking water sector: (i) there is no need for accelerated rehabilitation of brass-containing appurtenances such as water meters and shutoff valves and (ii) profile sampling is to be deployed upon measuring norm exceedance.

Riverine ecosystems face interacting environmental, climatic and human pressures that threaten freshwater sustainability. This study assessed the socio-ecological drivers, causal interactions and governance dynamics shaping freshwater vulnerability in Malawi’s Bua River Basin using integrated Drivers–Pressures–State–Impact–Response (DPSIR) and Socio-Ecological Systems (SES) frameworks. Physicochemical water-quality measurements across spatial and seasonal gradients were combined with qualitative field observations. Factorial ANOVA revealed significant seasonal and physicochemical variability (F₂,₅₂ = 21.84, p < 0.0001), with season–parameter interactions showing that hydrological variability affected indicators differently. Weak spatial interactions suggested catchment-wide influences. Key changes included elevated turbidity, riparian vegetation loss, exposed riverbanks and sediment mobilisation, driven by agricultural expansion, domestic activities and hydrological variability. The integrated analysis identified reinforcing feedbacks among livelihood dependence, hydropower-related problems, weak institutional coordination and declining freshwater resilience. Trade-offs emerged where intensified agriculture and freshwater-resource utilisation supported short-term livelihoods while accelerating ecological degradation, whereas riparian protection and local stewardship practices demonstrated potential resilience-supporting synergies. Overall, the findings show that freshwater degradation within the Bua River Basin is driven by interacting hydrological, ecological and socio-economic pressures, highlighting the value of integrated DPSIR and SES approaches for understanding freshwater vulnerability and guiding adaptive governance in tropical river systems.

The development of instrumentation, control and automation (ICA) in water operations during half a century is reviewed, and new challenges are described. The ideal ICA system contains a quality team of people who feel a deep sense of ownership of the system and who are committed to the continuous improvement ethics; an instrumentation system that gathers adequate process variable information; a monitoring system to gather data, process and display the data, detect and isolate measurement faults or process abnormal situations, assist in diagnosis and advice; a control system to meet the goals of the operation.

• • ICA is not one scientific discipline; it combines a multitude of scientific and engineering disciplines, here called a “decathlon” combination.

• • ICA is a hidden technology. It is ubiquitous in most industrial processes, including urban water systems, and reveals how processes are connected. When everything works as intended, it is not noted, but if things go wrong, it will be observed.

• • ICA in the water industry has about 50 years of history and is now well recognized.

• • Computers had become more affordable in the late 1960s. It was recognized that wastewater treatment systems are truly dynamic. All the 14 ICA conferences, from 1973 to 2025, have addressed all aspects of ICA methodology and implementations. The author has had the privilege to participate in all the 14 conferences.

• • Technology push and demand pull not only has led to more advanced operations. The rapid development of process knowledge, machine learning, AI, computing power and communication can realize operation also in a system-wide perspective.

• • There is an increasing demand for water reuse and circular management of water, and ICA has the potential to play an important role. Systems thinking, involving the complete urban water system cycle, is a great issue today. To succeed here, it is necessary to expand cooperation between problem owners, the water industry and methodology researchers in academia.

Although Canada possesses abundant freshwater resources, uneven water distribution, rapid climate change, deteriorating source water quality, and insufficient water infrastructure put small, rural, and remote (SRR) communities at a risk of water advisories and waterborne disease that is 26 times higher than in cities. Approximately three-quarters of SRR communities are Indigenous, indicating that they are more likely to experience water insecurity than non-Indigenous communities. This review examines key factors exacerbating water insecurity in SRR communities, including: (i) the types and ranges of commonly detected contaminants in source water, (ii) contaminant pathways and associated health risks, and (iii) the performance and challenges of small water systems (SWSs) in Canadian SRR communities. Total coliforms and E. coli in the microbiological category, and arsenic, lead, and manganese in the heavy metals and trace minerals category, had the highest number of occurrences among contaminants reported in dedicated studies. In contrast, fewer studies have investigated contaminants of emerging concern (CECs) and the capacity of SWSs to remove them. Common SWSs such as, multistage sand filtration, roughing filtration, granular activated carbon, chlorination, and ozonation offer relatively simple and affordable decentralized options; however, their long-term performance, operation, maintenance, governance, and social acceptability remain challenging.

This study investigates the use of machine learning based image classification techniques to detect debris blocking of urban waterways. Using a dataset comprising 1089 labelled CCTV images of a trash screen located in Cardiff, UK and a comprehensive re-sampling approach, we investigate not only the ability of selected machine learning algorithms to correctly identify images, but also to evaluate the uncertainty of these algorithms conditional on the datasets presented to them. For each candidate model, we considered two datasets: an imbalanced dataset and an under-sampled dataset. The results demonstrate that the performance of a simple logistic regression model was broadly comparable to that of more advanced machine learning models such as vision transformers. The best performing models (vision transformers and logistic regression) achieved an accuracy of more than 80%, while the NetRes50 model achieved an accuracy in the low 70%. This is an important result that opens the possibility for implementing these techniques as part of an operational real-time flood warning system utilising already existing cameras.

Ensuring easy access to clean and safe drinking water using low-cost technology is essential to mitigate the rising water scarcity in emerging economies. Commercial large-scale desalination technologies need significant investment, making them unsuitable for off-grid and small-scale applications. However, this operation can be carried out using a low-cost desalination technology based on renewable energy, known as the solar still. In this research work, a modified basin solar still (basin solar still + internal mirrors + 8 kg gravel + black ink (400 ppm per litre)) was developed and experimentally tested in Visakhapatnam (17.68°N, 83.22°E), India, to determine its appropriateness for sustainable seawater desalination. It produced 14% to 23% more desalinated water than a conventional basin solar still. In addition, its thermal efficiency was between 41% and 42%, which was significantly greater than other basin solar stills reported in literature. In addition, high-quality desalinated water was generated at a cost that was around three times less than the drinking water offered at Indian Railways kiosks. Moreover, the ability to mitigate significant CO2 emissions while also addressing water scarcity demonstrated that the modified basin solar still continues to contribute effectively to the United Nations Sustainable Development Goal 6 (Clean Water and Sanitation).

Sustainable Development Goal 6.1 seeks universal access to safe drinking water for all by 2030, yet persistent disparities remain even in high-income countries. Indigenous, remote and small communities are disproportionately affected by poor drinking water quality, but comparable evidence to evaluate performance across communities is very limited due to inconsistent monitoring and reporting. To this end, we constructed a community-level meta-panel dataset of 839 communities (4,137 observations) across 4 Australian jurisdictions (Northern Territory, South Australia, Victoria and Western Australia) and Ontario, Canada, over the period 2018–2022. Drinking water quality was assessed using the Australian Drinking Water Guidelines and Canadian Boil Water Advisories. Logistic regression was employed to estimate the probability of accessing good-quality drinking water, with Indigenous status, remoteness, population size and socio-economic condition as key explanatory variables. Results reveal systematic disparities: Indigenous and very remote communities are statistically significantly less likely to have good-quality drinking water than non-Indigenous and regional communities after controlling for other factors. Our findings indicate that structural inequities – rather than geographic or demographic variation alone – are critical determinants of poor drinking water outcomes in small, Indigenous communities in both Australia and Canada.