ABSTRACT The denial of household access to running water through service shutoffs is a common practice among water providers, yet the scope and nature of the problem remain poorly understood. This article presents results of the first scoping review and critical analysis of peer‐reviewed research on water shutoffs at the global scale, with the goal of identifying key trends, gaps, and insights across the literature. The results indicate a striking concentration of research emerging from the discipline of geography and based on research in the USA—notably Detroit, Michigan. Drawing on thematic and critical discourse analysis, we identify three primary ways that scholars have understood water shutoffs: (1) as mechanisms for enforcing debt‐driven governance; (2) as technologies of racialization and social discipline; and (3) as sites of social organization and struggle. We argue for new research efforts that examine the production and persistence of water shutoffs in a wider range of geographic settings, and we insist that the problem must be understood within the context of financialized capitalism and its predatory reliance on household social reproduction—in effect, shutoffs produce a new waterless class. We conclude by outlining key priorities of a new research agenda, including the intersection of water shutoffs with health, housing, and climate change, and note the impossibility of achieving universal access to water (SDG 6) without reckoning with utility shutoffs. Ending water shutoffs, we argue, requires new models of infrastructure financing and governance combined with an institutionalized commitment to the human right to water. This article is categorized under: Human Water > Water Governance Human Water > Rights to Water
ABSTRACT The ecotone connecting rivers with their riparian zones represents conditions where fluvial processes, abundant resources and reciprocal energetic subsidies have combined over evolutionary time to create multiple opportunities for niche development in a wide range of organisms. Among them, specialist riverine birds are diverse, conspicuous, and widespread globally, but they remain under‐researched by both river ecologists and ornithologists. Globally, we identify 69 bird species that have evolved specialized lifestyles along high‐gradient, fast‐flowing rivers and here we review (i) spatial patterns in their distribution to identify hotspots of diversity; (ii) major threats to their status and (iii) regions that are candidates for their conservation. Only a few species of specialist riverine birds are well known ecologically, hindering understanding of population trends, distribution, and conservation requirements at regional, continental or global scales. Multiple threats include habitat impairments through dams and other water resource infrastructure; land management for agriculture, forestry and urbanization; invasive non‐native species; pollution from well‐known and emerging sources; and the effects of climate change on flow patterns and thermal regimes. Neither the direct nor indirect effects involved—for example through prey availability or species interactions—have been adequately addressed by ecologists in contrast to birds in terrestrial or marine ecosystems. We identify two urgent needs respectively, (i) to expand interdisciplinary research to understand the ecology of river birds and (ii) to enhance their conservation both through catchment‐scale action and by protecting those regions that support threatened species and large species richness, notably in the tropics and sub‐tropics. This article is categorized under: Water and Life > Nature of Freshwater Ecosystems Water and Life > Stresses and Pressures on Ecosystems Water and Life > Conservation, Management, and Awareness
ABSTRACT Atmospheric water harvesting (AWH) provides a decentralized means of producing water without reliance on conventional sources such as rivers, lakes, or aquifers. While traditionally applied in humanitarian and drinking water contexts, the high quality of AWH‐derived water also makes it attractive for industrial and ultrapure water (UPW) applications, where reducing water footprints is increasingly critical. This review examines three primary AWH technologies with emphasis on their energy requirements, water quality, and potential for integration into industrial systems. Fog harvesting is the lowest‐energy option but is restricted to regions with persistent fog and yields limited volumes. Dew‐point condensation systems are commercially available, supported by cost models, and perform best in high‐humidity environments. Desiccant‐based systems, though still emerging, are adaptable across climates and especially promising for arid or low‐humidity regions. Their energy demand can be significantly reduced by coupling sorbent regeneration with industrial waste heat. For industries such as semiconductors manufacturing, pharmaceuticals, beverage production, and energy, both water quality and energy use are central constraints. Compared to municipal tap water, which requires extensive desalting and chemical treatment for UPW, AWH‐derived water is nearly salt‐free, lowering pretreatment energy demands and cost. Significant challenges remain for AWH energy efficiency to reach an ambitious United States Defense Advanced Research Projects Agency (DARPA) target of 42 kWh/m 3 (~$2/m 3 ), but advances in sorbent materials, hybrid system designs, automation, and waste energy recovery provide realistic pathways. This review outlines a roadmap for AWH to evolve into a viable, scalable, and sustainable supplemental source of UPW, particularly in water‐stressed industrial regions. This article is categorized under: Engineering Water > Sustainable Engineering of Water
ABSTRACT The assessment of flood risk is crucial for sustainable planning, policymaking, and emergency management. Even with recent methodological advancements, flood risk assessment in data‐scarce regions still encounters significant uncertainties. Despite the multitude of available methods and data sources, no context‐specific guidance exists for selecting a suitable combination of methods to map risk in a given data‐scarce area of interest. To address this gap, we conducted a systematic review of 264 studies on flood risk assessment in data‐scarce regions. First, our study reveals diverse interpretations of “risk” and “data scarcity”, deviating from well‐established definitions. We highlight the use of a standardized definition of flood risk to enhance the comparability of findings and improve the reliability of assessments. Second, we conceptualize data scarcity in the flood risk context to support an informed selection of assessment methods. Third, we systematically compile risk indicators, methods, and data sources applied in the context of data scarcity, and we analyze the interplay between methods for mapping the three key risk components, that is, hazard, exposure, and vulnerability. This interplay enables the design of a three‐step approach for identifying an appropriate methodological combination for flood risk assessment in any data‐scarce application context. Through these three key contributions, our review paves the way for more reliable and consistent flood risk assessment and management in data‐scarce regions, facilitating the reduction and mitigation of flood impacts in vulnerable communities across the globe. This article is categorized under: Science of Water > Water Extremes Engineering Water > Planning Water
ABSTRACT Smart water meters (SWMs) are key to modern residential, industrial and agricultural water supply and management systems. enabling accurate real‐time data, timely leak detection, reduced water loss, and improved billing accuracy. High system performance enables better forecasting and optimization, especially in areas with aging infrastructure or growing populations, while resilience against cyber threats ensures safety and security. However, maintaining and managing these assets is challenging, due to data reliability and analytical issues, communication failures, and increasing system complexity This review synthesizes current literature on key challenges, recent innovations, and best practices for efficiently managing and maintaining smart water meter (SWM) assets. We highlight the potential of predictive and condition‐based maintenance supported by asset management, the plan‐do‐check‐act (PDCA) approach alongside tool such as root cause analysis (RCA), reliability‐centered maintenance (RCM), conditioning monitoring or failure modes and effects analysis (FMEA)) in accordance with ISO 55002 to enhance reliability and operational efficiency. We advocate for the adoption of machine learning and internet of things (IoT)‐enabled monitoring to facilitate a shift from reactive to predictive maintenance, which remains underexplored in traditional water management literature. The findings offer valuable insights for water utilities aiming to advance smart water infrastructure through strategic asset management, data frameworks, and capability development. This article is categorized under: Engineering Water > Sustainable Engineering of Water Engineering Water > Planning Water Engineering Water > Methods
