Realising smarter stormwater management: A review of the barriers and a roadmap for real world application.

Effective management of stormwater systems is necessary for protection of both the built and natural environments. However, stormwater management is facing multiple, growing challenges, including climate change, ageing infrastructure, population growth, urbanisation, environmental concerns, regulatory and institutional changes and public awareness. While the potential of 'smart', internet-of-things enabled stormwater management systems to address these challenges is increasingly being recognised, with considerable evidence in literature for the benefits of more data-driven approaches, implementation to date remains low. This paper, therefore, provides a comprehensive review of the potential barriers to adoption of smarter stormwater management practices that require addressing, and provides a roadmap for real world application. Barriers related to all elements of stormwater management, from the asset sensing to the data analytics and online optimisation, are identified. Technical challenges discussed include the availability and reliability of technologies, technological and physical limitations, decision making, uncertainty and security. Technical barriers are rapidly reducing and there is increasing evidence in the academic literature of the efficacy of smart technologies. However, socio-economic barriers remain a significant challenge, and issues such as trust and lack of confidence, resistance to change, expense, and lack of knowledge and guidance are reviewed. A 'smart stormwater management wheel' that provides a flexible and iterative approach for implementing smart functionality is also presented. Whilst acting as a roadmap, this aims to facilitate a structured methodology for overcoming barriers and benchmarking progress, and may be used to explore trade-offs and relationships between differing levels of implementation for each of the constituent technologies in a smart stormwater system.

Dynamic population normalisation in wastewater-based epidemiology for improved understanding of the SARS-CoV-2 prevalence: a multi-site study.

Wastewater-based epidemiology (WBE) is a valuable tool for monitoring the circulation of COVID-19. However, while variations in population size are recognised as major sources of uncertainty, wastewater SARS-CoV-2 measurements are not routinely population-normalised. This paper aims to determine whether dynamic population normalisation significantly alters SARS-CoV-2 dynamics observed through wastewater monitoring, and whether it is beneficial or necessary to provide an understanding of COVID-19 epidemiology. Data from 394 sites in England are used, and normalisation is implemented based on ammoniacal nitrogen and orthophosphate concentrations. Raw and normalised wastewater SARS-CoV-2 metrics are evaluated at the site and spatially aggregated levels are compared against indicators of prevalence based on the Coronavirus Infection Survey and Test and Trace polymerase chain reaction test results. Normalisation is shown, on average, to have a limited impact on overall temporal trends. However, significant variability in the degree to which it affects local-level trends is observed. This is not evident from previous WBE studies focused on single sites and, critically, demonstrates that while the impact of normalisation on SARS-CoV-2 trends is small on average, this may not always be the case. When averaged across many sites, normalisation strengthens the correlation between wastewater SARS-CoV-2 data and prevalence indicators; however, confidence in the improvement is low.

Moving to a future of smart stormwater management: A review and framework for terminology, research, and future perspectives.

Stormwater hazards are a significant threat across the globe. These are continuing to increase in line with urbanisation and climate change, leading to a recognition that the historic paradigm of passive management using centralised infrastructure is insufficient to manage future hazards to our society, environment, and economy. The cross-sector Internet of Things revolution has inspired a new generation of smart stormwater management systems which offer an effective, cost beneficial and adaptive solution to enhance network capacities and reduce hazards. However, despite growing prominence within research, this technology remains under-utilised, in a large part due to fragmented and inconsistent alignment and terminology, obscuring the strategic co-ordination of research. We respond to this through systematically reviewing the terminology, practice and trajectory for smart stormwater management and developing a framework which can be applied to both coordinate and understand the existing research landscape, as well as identifying key research gaps for future development. We find that literature almost universally agrees that smart technology is, or will be, beneficial to stormwater management and that technology has reached partial maturity in terms of quantity management, although this has not yet transferred to water quality. However, research is dominated by proof-of-concept modelling studies, with limited practical application beyond real time control of large assets, individual pilot studies and monitoring. We recommend that future research explores and evidences the substantial benefits likely through expanding current implementation towards a coordinated, decentralised, and optimised catchment-scale approach.

Building knowledge of university campus population dynamics to enhance near-to-source sewage surveillance for SARS-CoV-2 detection.

Wastewater surveillance has been widely implemented for monitoring of SARS-CoV-2 during the global COVID-19 pandemic, and near-to-source monitoring is of particular interest for outbreak management in discrete populations. However, variation in population size poses a challenge to the triggering of public health interventions using wastewater SARS-CoV-2 concentrations. This is especially important for near-to-source sites that are subject to significant daily variability in upstream populations. Focusing on a university campus in England, this study investigates methods to account for variation in upstream populations at a site with highly transient footfall and provides a better understanding of the impact of variable populations on the SARS-CoV-2 trends provided by wastewater-based epidemiology. The potential for complementary data to help direct response activities within the near-to-source population is also explored, and potential concerns arising due to the presence of heavily diluted samples during wet weather are addressed. Using wastewater biomarkers, it is demonstrated that population normalisation can reveal significant differences between days where SARS-CoV-2 concentrations are very similar. Confidence in the trends identified is strongest when samples are collected during dry weather periods; however, wet weather samples can still provide valuable information. It is also shown that building-level occupancy estimates based on complementary data aid identification of potential sources of SARS-CoV-2 and can enable targeted actions to be taken to identify and manage potential sources of pathogen transmission in localised communities.

COVID-19 and the UK water sector: Exploring organizational responses through a resilience framework.

The unprecedented scale and impact of the COVID-19 pandemic have required organizations to adapt all facets of their operations. The impact on the UK water sector extends beyond engineering and treatment processes, with social, economic and environmental consequences. Semi-structured interviews were conducted with executives from 10 UK water companies to investigate the organizational response to the pandemic, and how their response impacted operational delivery. The Safe and SuRe framework was used to structure interview questions and analysis. Emergent themes of changes to customer behaviour, changes to operational practices and industry collaboration were mapped onto the framework and a ripple effect map developed. Lessons learnt highlight a failure to adequately prepare for the scale of the threat, the success of sector-level collaboration and a need to embrace new ways of working.

COVID-19 and the water sector: understanding impact, preparedness and resilience in the UK through a sector-wide survey.

The COVID-19 pandemic led to drastically altered working practices. During the UK lockdown, a questionnaire was distributed to water professionals to understand their experiences and perceptions of organisational response. Findings were evaluated on the measures of mitigation, adaptation, coping and learning. Employees' perceived there were adequate procedures to mitigate a threat, partly due to preparations for Brexit. Participants quickly adapted, with eighty-four percent working from home. Coping was experienced at an individual and sector level. IT issues and care responsibilities made it harder for individuals to cope, but good communication and signposting of support helped. Eighty percent felt able to continue their usual role, implying coping mechanisms were effective. At the sector level, coping involved the ability to meet an increased water demand with a remote workforce. Lessons learned highlight the importance of communication and collaboration. Future crisis plans should prepare for prolonged crises of international magnitude and multiple threats.