Vanessa Speight

Daily pressure traces used to calculate the median supply hours across the piped network. Intermittent water supply (IWS) affects over one billion people worldwide, resulting in unequal delivery of piped drinking water. Limited data from operational networks constrain our understanding of the processes driving this inequality. This study utilised 12 pressure loggers, measuring at 15-min intervals over 30 days, to reveal the spatio-temporal pressure distribution across multiple supply cycles in an operational IWS network in Lahan, Nepal. A new statistical method for defining supply hours was developed to characterise highly variable supply conditions, deconstructing the monolithic concept of ‘supply hours’. Comparison with other network parameters identified key physical drivers of supply inequality: distance from the nearest source governed the duration of ‘high-pressure’ supply hours, while network elevation drove ‘low-pressure’ supply hours. The study provides new evidence of the importance of the draining phase in IWS cycles, showing that in this network, the lowest elevations receive continuous supply due to localised water pooling. Finally, the findings highlight challenges in designing network improvements; interventions such as network zoning could inadvertently reduce supply hours in certain locations. Network managers must therefore account for localised conditions to avoid negatively impacting water access for vulnerable consumers.

Graphical abstract illustrating the study design and key findings using icons and arrows. On the left, three rounded rectangles each labelled Catchment 1, Catchment 2, and Catchment 3 contain house icons representing domestic households. A vertical dark teal bar connects all three catchments with the label No hospital input, indicating the absence of hospital wastewater inputs. A large horizontal arrow points right from the catchments into a central box labelled Domestic Wastewater Treatment. Inside this box, three dark grey squares represent the sequential treatment stages: primary sedimentation, trickling filter, and sludge tank. Below the treatment box, four icons depicting racks of test tubes are labelled IN (influent), PS (primary sedimentation), EF (effluent), and SL (sludge), connected by downward arrows showing the sampling points. Beneath the sampling point icons, a row of bacteria and DNA double-helix icons illustrates the progressive reduction in microbial and genetic material through treatment: large bacteria and large red DNA helices at IN reduce in size at PS, become very small at EF, while SL shows bacteria and DNA helices again at moderate size. On the right, two dark teal boxes display the key findings in white text: the upper box reads ARGs persisting despite treatment: aadA7, blaOXY, qepA; the lower box reads Candidate biomarkers: aadA7, sul1_2, blaOXA48. Wastewater surveillance is increasingly used to monitor antimicrobial resistance (AMR) at community scales. This study aimed to (1) assess AMR removal across treatment stages, (2) identify persistent versus responsive antimicrobial resistance genes (ARGs), and (3) characterise resistome profile of a wastewater treatment plant (WWTP) in Northeast England with no hospital inputs. Analyses included physicochemical profiling, microbial culturing, and high-throughput quantitative polymerase chain reaction targeting ARGs. Presumptive extended spectrum β-lactamase (ESBL)-producing Escherichia coli were effectively reduced by over two logs in the WWTP, although viable ESBL E. coli was still present in effluent. Comparative analyses revealed significant reductions along treatment stages for most ARGs. However, some ARGs, such as aadA7, blaOXY, and qepA, showed no significant reduction, indicating some ARGs persist through treatment, an important consideration for future monitoring programmes. The resistome profiles from three sub-catchments were similar, with only one ARG (lnuC) showing significant variation. This suggests that domestic-only catchments without hospital inputs may exhibit relatively uniform ARG profiles, although these results are specific to the WWTP studied and requires further validation. Finally, three ARGs, aadA7, sul1_2, and blaOXA48 were identified as potential biomarkers for AMR monitoring in WWTP, based on their abundance, strong correlation patterns, and clinical relevance.

1. A municipal water supply system is a complex assembly of hydraulic components designed to bridge the gap between source and consumer. Fundamentally, these systems operate through one of two deli...

Service reservoirs (SRs) are critical assets within drinking water distribution systems, yet water service providers (WSPs) lack methods for in-service performance assessment. Using data from 17 SRs and 2 WSP, a novel framework assessing SR integrity and mixing characteristics is developed and validated. While single-parameter analysis yields limited insights, combining level and flow data enabled mass balance calculations to detect integrity issues such as leaks and ingress up to 3 months before the scheduled inspections. Hydraulic residence time calculations, based on flow and level data, identified SRs operating beyond their recommended range with water age, sedimentation, and disinfectant residual consequences. By comparing hydraulic to cross-correlation residence times, calculated using inlet and outlet conductivity data, SRs exhibiting short-circuiting were identified. These were linked to poor mixing behaviour, creating zones of reduced disinfectant residual and higher bacteriological risk. An operational trial was subsequently conducted that demonstrated that by enhancing the SR level cycling, an approach highlighted by self-organising map analysis of data from 329 SRs, a 33% improvement in mixing was obtained. This new framework, using standard network data, facilitates WSPs to transition from reactive and periodic assessment of SRs to proactive and effective real-time smart water infrastructure management.

Diagram showing a three-layer framework where datasets feed intermediary processes that support business applications, linked through graph relationships to integrate fragmented data in water distribution systems. The water industry faces increasing challenges in ensuring efficient and sustainable delivery of safe drinking water through ageing infrastructure while meeting operational, regulatory, and customer demands. Large volumes of data are generated but are stored and utilised in disconnected silos. Such fragmentation limits the potential for comprehensive analysis, informed decision-making, and operational optimisation. To better understand the impact of this fragmentation, we developed a three-layer data and process connectivity framework, a novel graph-database-driven approach designed to identify, analyse, and address gaps in data utilisation and data process efficiency. The framework systematically maps critical data flows and reveals interdependencies between data, intermediary processes, and business applications. We validated the framework through a case study with Scottish Water, constructing a graph comprising 127 nodes and 911 relationships across water distribution data and processes. Using node centrality measures, relationship-based graph querying, and impact simulations, we demonstrate how this approach exposes inefficiencies, uncovers overlooked data relationships, and generates actionable insights for process integration. The findings highlight the potential of graph-database-driven approaches to overcome data fragmentation, bridge silos, and enable more data-driven and strategically optimised operations, with applicability across the wider water sector and other industries.

The water sector needs advances in a range of thematic areas to deliver sustainable water systems in a future characterised by climate change, population growth, and ageing infrastructure. Individual innovations will not be enough to deliver the step-change required. A multitude of sociotechnical advances in water management exist, however the real innovation challenge lies in understanding and demonstrating how combinations of these solutions can be deployed to deliver resilient and adaptive urban water systems. These combinations, or ‘silver baskets’, need to be tailored to local needs and context and work synergistically with existing infrastructure. The scale at which the solutions will be deployed ranges from individual domestic applications to city-wide infrastructure, across potential water qualities ranging from black water for reuse and resource recovery to ultra-pure potable water. This paper describes the results from a structured set of workshops across five years with UK water sector stakeholders from more than 250 organisations to develop potential future scenarios and pathways towards each one for urban water systems. While there is value in the resulting ‘silver baskets’, arguably there is more value in building skills through the process of collectively envisioning future options, transition pathways and drivers, and understanding the range of possibilities and combinations to deliver sustainable water futures across an entire country’s water sector. The study concluded that all water futures lie on, and can be considered and planned for on, a continuum from centralised to decentralised, despite the variety and complexity of the pathways, contexts, situations and pressures leading to them.

The present study explored the incorporation of health-related organisms within drinking water biofilms and bulk water quality using benchtop-scale distribution systems. The annular reactors simulated the dead-end pipes of distribution systems with low shear stress but maintained a chlorine residual and formed young biofilms on plastic surfaces. Spiked coliforms and Escherichia coli were introduced to the annular reactors after 1 month of growth. Although initially detected in the spike, the coliforms were inactivated in the bulk water phase, likely due to environmental stresses, such as nutrient starvation and residual chlorine. Also, coliform incorporation within biofilm was only detected in a single coupon in the reactor 24 h post-spike (with 100% lake water), suggesting they were not incorporated or under the detection limit.

Modelling consumer demand under intermittent water supply (IWS) is an unresolved challenge. To understand withdrawal behaviours in more detail, fifty-six smart meters were installed in households across an IWS network in Lahan, Nepal. The most frequent withdrawal type was small withdrawals (median two litres), while large tank-filling-type behaviours contributed significantly to a household’s overall water consumption. Behaviour was highly heterogeneous; households with large storage tanks tended to practice tank-filling behaviour significantly more than those without. Consequently, a one-size-fits-all approach to consumer demand modelling may not always be appropriate and could lead to unrealistic predictions of supply inequality.