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In the UK, decision makers use hydraulic model outputs to inform funding, connection consent, adoption of new drainage networks and planning application decisions. Current practice requires the application of design storms to calculate sewer catchment performance metrics such as flood volume, discharge rate and flood count. With flooding incidents occurring more frequently than their designs specify, hydraulic modelling outputs required by practice are questionable. The main focus of this paper is the peakedness factor (ratio of maximum to average rainfall intensity) of design storms, adjudging that this is a key contributor to model bias. Hydraulic models of two UK sewer catchments were simulated under historical storms, design storms and design storms with modified peakedness to test bias in modelling outputs and the effectiveness of peakedness modification in reducing bias. Sustainable drainage systems (SuDS) were implemented at catchment scale and the betterment achieved in the modelling outputs was tested. The proposed design storm modification reduced the bias that occurs when driving hydraulic models using design storms in comparison with historical storms. It is concluded that SuDS benefits are underestimated when using design rainfall because the synthetic rainfall shape prevents infiltration. Thus, SuDS interventions cannot accurately be evaluated by design storms, modified or otherwise.

Urban water security levels will be threatened during the next few years due to new development pressures combined with the climate emergency and increasing population growth in cities. In the UK, London’s planning authorities have a target of more than half a million households for the next 10 years. This new housing will increase the current impacts on urban consumer demand, flood risk, and river water quality indicators. In our previous work, we developed a new concept for urban Water Neutrality (WN) inside an integrated urban planning sustainability framework called CityPlan to deal with water stress and urban complexity issues. This framework integrates the UK’s planning application process with systemic design solutions and evaluation, all being spatially represented in a GIS platform. With the new digital era, there is a constantly increasing number of spatial datasets that are openly available from different sources, but most of them are disaggregated and difficult to understand by key urban stakeholders such as Local Planning Authorities, housing developers, and water companies. Moreover, there are several Multi-Criteria Decision Support Tools (MCDST) that address water management challenges in the literature; but there is still little evidence of one that evaluates the impacts and opportunities to allocate water neutral urban developments.In this work, we expand the CityPlan framework and present an innovative fully data-driven approach to test WN indicators at different urban scales. WaNetDST integrates GIS spatial data with a series of rules for development impact and offset opportunity based on the current properties of the urban land. This integration is linked to a new scoring system from expert advice that maps strategic areas for water neutral interventions and links the most impactful zones with others more prone to be intervened. The tool connects different urban scales with a series of case study areas: from city (i.e., London), to borough (i.e., Enfield), and to urban development scale (i.e., Meridian Water Development). In the end, WaNetDST visually compares the need for housing vs. green spaces and the trade-offs between new housing vs. retrofitting existing infrastructure, providing a series of maps that guide the planning decision-making process in an integrated way. The results from CityPlan might potentially change the decision-making process for LPAs and housing developers and open a new dialogue between boroughs inside the same city, providing a novel and automated system for WN trade-offs and linking data-driven design with future planning decisions

Climate change-related phenomena are putting an enormous strain on cities’ infrastructure, human livelihoods, public health and citizens well-being. This, together with the increase in urban growth and urbanization, results in an expansion of urban hazards - including water scarcity, disease transmission and consequent social issues.To address this complexity in an urban design context we introduce a Systemic Design (SyD) framework for Multifunctional Nature-based Solutions (NBS) to rethink and contribute to the planet’s health and people’s quality of life. The SyD approach focuses on context knowledge creation (environmental, climatic, social…) that includes perspectives from the point of view of multiple stakeholders, maps its key features, and analyses alternatives for exploiting different design options. Exploratory or suitability modelling supports all these steps.The examples here presented are part of the multidisciplinary project euPOLIS focused on climate change adaptation and on enhancement of public health and citizen’s well-being through the implementation of nature-based solutions (NBS). Although diversity of the size and the scale of presented case studies, the systematic baseline analysis have revealed that there are several shared conditions, such as an immediate need for improvement of existing green spaces, mitigation of direct and indirect UHI effect and refinement of maintenance systems.A mapping of the local features, and variety of specific spatial and social conditions in public spaces studied in euPOLIS’s Cities (Belgrade, Gladsaxe, Lodz and Pireas) gives synthetic prospects to better understand the potential effectiveness of Blue-Green Infrastructure (BGI) solutions (design options) in relation to their wider ecosystem and citizens’ concerns. This leads to a systematic assessment of possible future scenarios of different scales (local, urban, regional…) and allows an examination of possible steps to better define locally specific variables, evaluation and validation of benefits to reduce existing vulnerability, and to improve community’s liveability. The systemic design approach allows to explore the main drivers of urban development, climate change mitigation and urban resilience. In this way, it also supports decisions for further planning stages and anticipates actions for the management of the multifaceted hazards of the entire urban system.

During COP14 in 2022, Ramsar Convention commended 25 cities around the world for their efforts to protect urban wetlands. With the development of cities and the increase in land demand, the trend is to reduce the number of open blue spaces. Yet when preserved and sustainably used, urban nature-based solutions in the form of constructed wetlands could provide water management benefits including water quality regulation and flood mitigation. However, these water management benefits have rarely been evaluated at a catchment scale, and the mechanisms behind them are not fully understood, both of which hinder effective integrated constructed wetlands planning. We aim to explore the impact of wetland changes on water quality and quantity at the catchment scale. This study firstly evaluates the benefits by analysing the monitoring water quantity and quality datasets before and after the wetland construction in Enfield catchment, London. To understand the mechanisms behind the benefits, we build a Water Systems Integration Modelling framework (WSIMOD) to simulate the catchment-scale water cycle. This model is validated against monitoring river flow and water quality data. The constructed wetlands are then conceptualised and integrated into the WSIMOD, and their interactions with the catchment water cycle are simulated. Scenarios are constructed to analyse the impacts of different configurations and sizes of the constructed wetlands on the catchment water cycle. The results show that urban wetlands play a role in flood detention and water quality purification of watershed water resources at the catchment scale. Scattered small wetlands can more effectively reduce the impact of a flood under the same total wetland area. The results provide useful insights into the planning of constructed wetlands for maximising the water management benefits at a catchment scale. Future studies could focus on representing the interaction between the quantity and quality of water in a wetland with biodiversity and leveraging this representation to design interventions to improve biodiversity.

The potential to deliver better, more efficient and sustainable cities has motivated recent research on Digital Twins (DTs) that seek to support planning decisions by displaying analytical evidence to inform collaborative design actions. Prior research identifies different types of DT tools and gives recommendations for their use, but it has not been grounded in engaged research that co-designs DTs with planning users from the context description and problem formulation stage. We report on a research project to co-create DTs with local government planners to visualize interactions between water resources and housing development. We describe co-creating two different DTs starting from the context and problem for water management and assess the steps against these three categories. While engaging with the field we built on prior studies to identify a set of categories relevant to co-creating and assessing DTs: context, governance, spatial and technical definition. By recording the steps of the DT design process, and contrasting the results with the theoretical proposals, we develop a three-step framework for the co-creation of DTs. This step-by-step framework, illustrated by examples, provides a contribution to the literature on the co-design of DT, and we conclude by discussing implications for practitioners and areas for further research.

The water cycle is highly interconnected; water fluxes in one part depend on physical and human processes throughout. For example, rivers are a water supply, a receiver of wastewater, and an aggregate of many hydrological, biological, and chemical processes. Thus, simulations of the water cycle that have highly constrained boundaries may miss key interactions that create unanticipated impacts or unexpected opportunities. Integrated environmental models aim to resolve the issue of boundary conditions, however they have some key limitations, and we find a significant need for a parsimonious, self-contained suite that is accessible and easy to setup. With this in mind, we have developed the WSIMOD – a Python package that allows for the representation of the water system’s demands and impacts of multiple sectors and actors’ decisions within a single tool, which is considered beneficial to increasing a shared understanding of system performance and for more collaborative and coherent decisions on integrated water resources, water quality and flood management. The WSIMOD is a self-contained software package that includes modelled representations of key physical and infrastructure elements of the water cycle (urban and rural), with each type of modelled element generically described as a component. Components are written in such a way that any component can interact with any other component. This enables a flexible representation of a water system that is needed to accommodate the wide variety of different built/natural infrastructure configurations and scales. We will showcase how the WSIMOD tool has been developed and successfully tested through a range of applications in the UK, including integrated analysis of urban water systems, catchment water management and urban water neutrality.

Nature-based solutions (NBS) have co-benefits for water availability, water quality, and flood management. However, searching for optimal integrated urban-rural NBS planning to maximise co-benefits at a catchment scale is still limited by fragmented evaluation. This study develops an integrated urban-rural NBS planning optimisation framework based on the CatchWat-SD model, which is developed to simulate a multi-catchment integrated water cycle in the Norfolk region, UK. Three rural (runoff attenuation features, regenerative farming, floodplain) and two urban (urban green space, constructed wastewater wetlands) NBS interventions are integrated into the model at a range of implementation scales. A many-objective optimization problem with seven water management objectives to account for flow, quality and cost indicators is formulated, and the NSGAII algorithm is adopted to search for optimal NBS portfolios. Results show that rural NBS have more significant impacts across the catchment, which increase with the scale of implementation. Integrated urban-rural NBS planning can improve water availability, water quality, and flood management simultaneously, though trade-offs exist between different objectives. Runoff attenuation features and floodplains provide the greatest benefits for water availability. Regenerative farming is most effective for water quality and flood management, though it decreases water availability by up to 15% because it retains more water in the soil. Phosphorus levels are best reduced by expansion of urban green space to decrease loading on combined sewer systems, though this trades off against water availability, flood, nitrogen and suspended solids. The proposed framework enables spatial prioritisation of NBS, which may ultimately guide multi-stakeholder decision-making, bridging the urban-rural divide in catchment water management.

At a time of system shocks, significant underlying challenges are revealed in current approaches to delivering infrastructure, including that infrastructure users in many societies feel distant from nature. We set out a research agenda on systems approaches to infrastructure, drawing on ten years of interdisciplinary work on operating infrastructure, infrastructure interventions and lifecycles. Research insights and directions on complexity, systems integration, data-driven systems engineering, infrastructure life-cycles, and the transition towards zero pollution are summarised. This work identifies a need to better understand the natural and societal impacts of infrastructure interventions under uncertainty. We argue for a change in current approaches to infrastructure: starting from the natural environment and its resources, encompassing societal use of infrastructure and the supporting infrastructure assets and services. To support such proposed new systems approaches to infrastructure, researchers need to develop novel modelling methods, forms of model integration, and multi-criteria indicators.

London aims to build more than half a million households over the next 10 years to cope with the growing demand for housing in the UK. In this future scenario, urban water security levels will be threatened due to new development pressures combined with the climate emergency and exponential population growth in the city. In addition to this, there is a lack of agreement between the policy and decision-making sectors to decide what can be accepted as a sustainable urban development project and which are the physical and decision boundaries inside the city (i.e., while boroughs and wastewater zones present decision boundaries, new urban developments have physical boundaries only). In our previous work, we developed a new concept for urban Water Neutrality (WN) inside an operational framework called CityPlan to frame the concerns about rising water stresses in cities. This framework integrates spatial data with an integrated urban water management model, enabling urban design at systems level and delivering a new index that assesses possible future scenarios. Despite several studies related to WN, little evidence is yet available in the literature of how urban water neutrality can be achieved at different urban scales and if results might vary depending on the scale studied.In this work, we expand the CityPlan framework and present an innovative evaluation approach that sets several urban indicators to be tested at different urban scales. As part of the evaluation toolkit of CityPlan, we also develop the Water Efficiency Certificate (WEC) by boroughs using two novel criteria: the Housing Age Indicator (HAI) and the Device Efficiency Score (DES). The WEC evaluates the current situation of household water consumption and can be used to support predictions of water consumption under different scenarios, to study the potential for retrofitting existing residential buildings, and to develop water-efficient households. In the end, the full development of the CityPlan framework will provide a clear vision to contextualise water neutrality in urban water systems and its key role in urban water security at different urban scales.

Cities are open living systems, which rely on the confluence of multiple layers of infrastructure and corresponding services. The interaction among these components is made even more complex by the demands of businesses and governments, together with constraints arising from ecological and environmental considerations. Climate change-related phenomena are putting an enormous strain on cities’ infrastructure, basic services, human livelihoods, public health and well-being. In many parts of the world concerns mount in regard to the scarcity of resources and growing risk of natural disasters (heat waves, urban flooding, droughts). The converse also holds true, cities are major contributors to climate change through greenhouse gas emissions, notwithstanding other sources of pollution. This, together with the increase in urban growth and urbanization, results in an expansion of urban hazards - including water pollution, disease spread and issues with food security. Despite these pressing issues, we are witnessing an almost paradoxical mismatch between the needs of future cities and the practices currently used in numerous urban projects. A wholesale re-thinking of existing urban design methods at systems level (Systemic Design), is therefore not only necessary, but also provides significant opportunities to explore critical aspects of Blue-Green Infrastructure (BGI) and systematic assessment of possible future scenarios of different scales (local, urban, regional…). Nature-based solutions (NBS) are at the very core of the conception and development of BGI and provide a range of ecosystem services including alleviation of flood risk, mitigation of climatic effects, increase in biodiversity and amenity values, improvements in water quality, and further, rather more intangible benefits related to the residents’ health and wellbeing.In this work we provide a systemic design as an innovative and integrated approach, based on ecology and ecological design, which introduces the systematic context analysis (environmental, climatic, historic…). A GIS-based mapping of the context, produced in relation to the functional purpose, can give us synthetic prospects to better understand the potential effectiveness of BGI solutions (design options) in relation to their wider ecosystem. The systemic design approach allows an examination of possible steps to reduce actual cities vulnerability and to explore the main drivers of urban development, climate change mitigation and urban resilience. In this way, the systemic design approach also supports decisions for further planning and anticipates actions for the management of the multifaceted hazards of the entire urban system.

Globally, urban areas will face multiple water-related challenges in the near future. The main challenges are intensified droughts leading to water scarcity, increased flood risk due to extreme rainfall intensification, increased total water demand due to an increasing urban population, amplified urban heat island intensities due to urban sprawl, and reduction in urban carbon sink due to plant water stress. Urban greening is an excellent option for mitigating flood risk and excess urban heat. Meanwhile, rainwater harvesting (RWH) systems can cope with water supply needs and urban water management. In this study, we investigated how urban greening and RWH can work together to mitigate the aforementioned risks. We evaluate the joined-up management approach under climate projections for 30 cities in the USA spanning a variety of climates, population densities and urban landscapes. By incorporating a new RWH module in the urban ecohydrological model UT&C and flexible operational rules of reusing harvested water for domestic use and urban green space irrigation, we tested 4 intervention approaches: control, RWH installation, urban greening supported by RWH, and urban greening supported by traditional irrigation (i.e., supplying via mains water). Each intervention approach was evaluated using our adapted version of UT&C and forced by the last generation convection-permitting model simulations of current (2001-2011) and end-of-century (RCP8.5) climate from Weather Research and Forecasting (WRF). The volume of RWH is assumed to be 2000L per household for all cities. Results showed that neither urban greening nor RWH could contribute significantly to reducing the expected increase in canyon temperature, because of the strong change in background climate (i.e., increases in average atmospheric temperature). However, RWH alone can sufficiently reduce the intensifying surface flood risk and effectively enhance water conservation, and urban greening can significantly increase the carbon sink of cities especially in dry regions, and if supported by traditional irrigation. Those results vary with the background climate: the benefits of urban greening, either supported by RWH or traditional irrigation, on canyon temperature reduction and carbon sink improvement increased with average air temperature and decreased with wetness index respectively; the benefits of RWH on runoff reduction and water conservation are both positively dependent on local annual precipitation.

Graph partitioning algorithms separate nodes of a graph into clusters, resulting in a smaller graph that maintains the connectivity of the original. In this study we use graph partitioning to produce reduced complexity sewer networks that can be simulated by a novel urban hydrology model. We compare a variety of algorithms, including spatial clustering, spectral clustering, heuristic methods and we propose two novel methods. We show that the reduced network that is produced can provide accurate simulations in a fraction of the time (100-1000x speed up) of typical urban hydrology models. We address some likely use cases for this approach. The first is enabling a user to pre-specify the desired size of the resultant network, and thus the fidelity and speed of simulation. The second is enabling a user to preserve desired locations that must remain in their own cluster, for example, locations with complex hydraulic structures or where monitoring data exists. The third is a case where detailed sewer network data is not available and instead the network must be simulated hundreds of times in a random sampling of network parameters, something that is only possible with the speed gains that our method allows. We envisage that this reduced complexity approach to urban hydrology will transform how we operate and manage sewer systems, enabling a far wider range of model applications than are currently possible, including optimisation and scenario analysis.

Sustainable development is becoming increasingly urgent in the post-COVID recovery and climate crisis era. Despite this need, the water management scientific community is still deciding how to comprehensively represent and assess the role of humans within the hydrological cycle. An explanation may be found in numerous examples where water managers are often challenged when their decisions, policies, and interventions lead to a range of unintended consequences that cause increased pressures on the environment, which have been described by socio-hydrological paradoxes. If the paradoxes are seen as the main obstacles hindering sustainable development in the context of water management, then investigating their mechanisms and understanding logic may help us to reveal unintended system responses and define guiding principles critical for designing robust and sustainable water management plans. We analyse the socio-hydrological paradoxes from a systems perspective and assume that water management decisions and plans developed adopting a linear thinking and goals-focused approach are likely to neglect consequential effects which occur throughout the wider system. This definition enables us to rename the phenomena into water management paradoxes, which might be fundamentally related to systems’ complexity and unexpected behaviour arising from internal feedbacks along with external driving forces that generate nonlinear outcomes which are inconsistent with the expected results or responses from inputs and actions within the system.To find solutions for the water management paradoxes, we hypothesise that they can be described in the context of three feedback mechanisms, which define the purpose of systems water management (SYWM) as coordination of development and water infrastructure with environmental management to improve the quality of life. We argue that the lack of consideration, integration and coordination of the SYWM meta-model loops will result in one of the water management paradoxes. As a solution, we propose three paradox archetypes that form the basis for guiding principles for systems water management. We suggest that environmental capacity indicators should be used in whole-system performance evaluation. The meta-model emphasises the need to better understand the baseline and development scenarios in the context of water neutrality, which is crucial for informing development decisions, including trade-offs in resource and infrastructure planning and operation. We encourage the use of a SYWM meta-model and proposed principles as a guide for analysing, modelling, and assessing human-water systems, thus creating an evidence base of case studies to demonstrate the meta-model’s applicability to solving water management paradoxes. In doing so, we hope to move towards the design of water systems that will support post-COVID recovery and enable long-term sustainable development.

Managing river water quality at critical checkpoints that have significant impacts on water use is important for sustainable catchment development. This requires managing the whole multi-catchment systems upstream of a critical checkpoint. Concepts of systems headroom (deficit below permit) and excess (extra above permit) have been used to distinguish sub-catchments’ roles in pollution contribution. Based on the concepts, we propose a three-phase management approach. In the first phase, we frame the headroom and excess at temporal, spatial, and source domains and evaluate them to investigate the systems mechanisms. The evaluation is by simulating physical processes a semi-distributed integrated model (CatchWat-SD). We apply the model to 12 sub-catchments that make up the Upper Thames river basin and validate it using monitoring data. In the second phase, we incorporate the evaluated headroom and excess in loads allocation to develop a strategy that coordinates systems headroom for more efficient and realistic interventions. In the last phase, we validate the strategies by simulating the scenarios that coordinate headroom at different domains and evaluating them in water quality improvement, efficiency, temporal steadiness, spatial homogeneity, and practical feasibility. Results show that dry seasons, downstream catchments and urban sources generally have more excess. Thus, more target loads reduction is allocated to dry season, downstream catchments and urban sources in the fully coordinated scenario. The higher degree of headroom coordination a strategy achieves, the better performance this strategy generally obtains in all five metrics. This study emphasises the need to incorporate headroom in loads reduction allocation, which helps to more efficiently improve systems water quality performance with a more realistic degree of intervention. The whole procedure can be further expanded to water quality management at multiple checkpoints for sustainable management in large catchments.

In the UK, decision-makers use hydraulic model outputs to inform funding, connection consent, adoption of newdrainage networks and planning application decisions. Current practice requires the application of design storms tocalculate sewer catchment performance metrics such as flood volume, discharge rate and flood count. With floodingincidents occurring more frequently than their designs specify, hydraulic modelling outputs required by practice arequestionable. The main focus of this paper is the peakedness factor (ratio of maximum to average rainfall intensity)of design storms, adjudging that this is a key contributor to model bias. Hydraulic models of two UK sewercatchments were simulated under historical storms, design storms and design storms with modified peakedness totest bias in modelling outputs and the effectiveness of peakedness modification in reducing bias. Sustainabledrainage systems (SuDS) were implemented at catchment scale and the betterment achieved in the modelling outputswas tested. The proposed design storm modification reduced the bias that occurs when driving hydraulic modelsusing design storms in comparison with historical storms. It is concluded that SuDS benefits are underestimated whenusing design rainfall because the synthetic rainfall shape prevents infiltration. Thus, SuDS interventions cannotaccurately be evaluated by design storms, modified or otherwise.

Biomonitoring of water quality and catchment management are often disconnected, due to mismatching scales. Considerable effort and money are spent each year on routine reach-scale surveying across many sites, particularly in countries like the UK, where nationwide sampling has been conducted using standardised techniques for many decades. Most of these traditional freshwater biomonitoring schemes focus on pre-defined indicators of organic pollution to compare observed vs expected subsets of common macroinvertebrate indicator species. Other taxa, including many threatened species, are often ignored due to their rarity, as are many invasive species, which are seen as undesirable despite becoming increasingly common and widespread in freshwaters, especially in urban ecosystems. Both these types of taxa are often monitored separately for reasons related to biodiversity concerns rather than for gauging water quality. Repurposing such data could therefore provide important new biomonitoring tools that can help catchment managers to directly link the water quality they aim to control with the biodiversity they are trying to protect. Here we used extensive data held in the England Non-Native and Rare/Protected species records that track these two groups of species as a proof-of-concept for linking catchment scale management of freshwater ecosystems and biodiversity to a range of potential drivers across England. We used national land use (Centre for Ecology and Hydrology land cover map) and water quality indicator (Environment Agency water quality data archive) datasets to predict, at the catchment scale, the presence or absence of 48 focal threatened or invasive species of concern routinely sampled by the English Environment Agency, with a median accuracy of 0.81 area under the receiver operating characteristic curve. A variety of water quality indicators and land-use types were useful in predictions, highlighting that future biomonitoring schemes could use such complementary measures to capture a wider spectrum of drivers and responses. In particular, the percentage of a catchment covered by freshwater was the single most important metric, reinforcing the need for space/habitat to support biodiversity, but we were also able to resolve a range of key environmental drivers for particular focal species. We show how our method could inform new catchment management approaches, by highlighting how key relationships can be identified and how to understand, visualise and prioritise catchments that are most suitable for restoration or water quality interventions. The scale of this work, in terms of number of species, drivers and locations, represents a significant step towards forging a new approach to catchment management that enables managers to link drivers they can control (water quality and land use) to the biota they are trying to protect (biodiversity).

Land use planning regulates surface hydrological processes by adjusting land properties with varied evapotranspiration ratios. However, a dearth of empirical spatial information hampers the regulation of place-specific hydrological processes. Therefore, this study proposed a Local Land Use Planning framework for EvapoTranspiration Ratio regulations (ETR-LLUP), which was tested for the developments of spatially-varied land use strategies in the Dongjiang River Basin (DRB) in Southern China. With the first attempt at integrating the Emerging Hot Spots Analysis (EHSA) with the Budyko framework, the spatiotemporal trends of evapotranspiration ratios based on evaporative index and dryness index, from 1992 to 2018, were illustrated. Then, representative land-cover types in each sub-basin were defined using Geographically Weighted Principal Component Analysis, in two wet years (1998 and 2016) and three dry years (2004, 2009, and 2018), which in turn were identified using the Standard Precipitation Index. Finally, Geographically Weighted Regressions (GWRs) were used to detect spatially-varied relationships between land-cover proportions and evaporative index in both dry and wet climates. Results showed that the DRB was consistently a water-limited region from 1992 to 2018, and the situation was getting worse. We also identified the upper DRB as hotspots for hydrological management. Forests and croplands experienced increasingly water stress compared to other vegetation types. More importantly, the spatial results of GWR models enabled us to adjust basin land use by 1) expanding and contracting a combination of ‘mosaic natural vegetation’ and ‘broadleaved deciduous trees’ in the western and eastern parts of the basin, respectively; and 2) increasing ‘broadleaved evergreen trees’ in the upstream parts of the basin. These spatially-varied land use strategies based on the ETR-LLUP framework allow for place-specific hydrological management during both dry and wet climates.

The main objective of the transdisciplinary and arts-based research project “The Art of Arriving: Reframing ‘Refugee Integration’” is to explore the transformative potential of the arts for the sociology of migration and integration. By creating a real-world laboratory where sociologists accompany artists as they create, and recipients while they interpret aesthetic expressions, the project focuses on the process of refugees’ arriving. The aim is to examine if and how the meaning-making processes involved in creating and interpreting art can foster alternative views about “refugee integration” and extend or even revise the traditional sociological toolkit for understanding integration. The article discusses the methodological implications of the planned transdisciplinary multimethod approach by paying particular attention to the different logics of knowledge production in science and the arts. Additionally, it sheds light on the benefits associated with the mutual translation between sociology and various fields of art, which is mediated through the process of creating and interpreting aesthetic expressions in the context of refugee migration.

Designing engineering systems for flexibility is of utmost importance for future generations of systems designers and operators. As a core system property, flexibility provides systems owners and operators with the ability to respond easily and cost-effectively to future changes. It contributes to improved economic value, sustainability and resilience by enabling systems to adapt and reconfigure in the face of uncertainty in operations, markets, regulations, and technology. The field of Flexibility in Design has steadily evolved over the last two decades, emerging from the area of Real Options Analysis, which focuses on quantifying the value of flexibility in large-scale, irreversible investment projects. Flexibility in Design goes further by developing and evaluating novel design methods and computational procedures to enable flexibility as a systematic value enhancement mechanism in engineering systems. This chapter provides an overview of how the field has developed over time as well as design frameworks, methods and procedures to support such design activities in practice. It discusses important challenges and limitations with supporting case studies in aerospace, automotive, energy, real estate, transportation, and water management. The chapter highlights key future directions for research, involving sustainability and resilience, data-driven real options, empirical studies and simulation games, machine learning, digital twin modelling, and 3D virtualization.

This study uses a sociology of knowledge perspective to analyse how former Bosnian refugees in Austria have integrated the experiences of ethnicized war and forced migration into their lives over the past three decades. The objective hermeneutical analysis of narrative interviews with Bosnian-Austrians reveals significant differences between former child refugees and those who experienced war and migration as adolescents. From a sociology of knowledge perspective, these differences can be attributed to varying ‘stratifications of experience’: The central crisis in the adolescents’ lives was triggered by experiencing the destruction of their Yugoslavian life-world, which significantly eroded their trust in their social reality’s stability and in their belonging. The former child refugees, however, particularly struggle with their double marginalization. While the former typically manage this crisis through an exaggerated adherence to the ideal of personal performance, the latter draw on collective imaginations of ethnic/national affiliation and try to comply with them.

The interest in visual-based surveillance systems, especially in natural disaster applications, such as flood detection and monitoring, has increased due to the blooming of surveillance technology. In this work, semantic segmentation based on convolutional neural networks (CNN) was proposed to identify water regions from the surveillance images. This work presented two well-established deep learning algorithms, DeepLabv3+ and SegNet networks, and evaluated their performances using several evaluation metrics. Overall, both networks attained high accuracy when compared to the measurement data but the DeepLabv3+ network performed better than the SegNet network, achieving over 90% for overall accuracy and IoU metrics, and around 80% for boundary F1 score (BF score), respectively. When predicting new images using both trained networks, the results show that both networks successfully distinguished water regions from the background but the outputs from DeepLabv3+ were more accurate than the results from the SegNet network. Therefore, the DeepLabv3+ network was used for practical application using a set of images captured at five consecutive days in the study area. The segmentation result and water level markers extracted from light detection and ranging (LiDAR) data were overlaid to estimate river water levels and observe the water fluctuation. River water levels were predicted based on the elevation from the predefined markers. The proposed water level framework was evaluated according to Spearman’s rank-order correlation coefficient. The correlation coefficient was 0.91, which indicates a strong relationship between the estimated water level and observed water level. Based on these findings, it can be concluded that the proposed approach has high potential as an alternative monitoring system that offers water region information and water level estimation for flood management and related activities.

Managing river quality is important for sustainable catchment development. In this study, we present how catchment management strategies benefit from a coordinated implementation of measures that are based on understanding key drivers of pollution. We develop a modelling approach that integrates environmental impacts, human activities, and management measures as three hierarchical levels. We present a catchment water management model (CatchWat) that achieves all three hierarchical levels and is applied to the Cherwell Catchment, UK. CatchWat simulations are evaluated against observed river flow and pollutant data including suspended solids, total nitrogen, and total phosphorus. We compare three competing hypotheses, or framings, of the catchment representation (integrated, urban-only, and rural-only framings) to test the impacts of model boundaries on river water quality modelling. Scenarios are formulated to simulate separate, combined and coordinated implementation of fertiliser application reduction and enhanced wastewater treatment. Results show that models must represent both urban and rural pollution emissions to accurately estimate river quality. Agricultural activities are found to drive river quality in wet periods because runoff is the main pathway for rural pollutants. Meanwhile, urban activities are the key source of pollution in dry periods because effluent constitutes a larger percentage of river flow during this time. Based on this understanding, we identify a coordinated management strategy that implements fertiliser reduction measures to improve river quality during wet periods and enhanced wastewater treatment to improve river quality during dry periods. The coordinated strategy performs comparably to the combined strategy but with higher overall efficiency. This study emphasises the importance of systems boundaries in integrated water quality modelling and simulating the mechanisms of seasonal water quality behaviour. Our key recommendation is that incorporating these mechanisms is required to develop coordinated strategies for river water quality management, that can ultimately lead to more efficient and sustainable catchment management.

Existing, high-fidelity models for sewer network modelling are accurate but too slow and inflexible for modern applications such as optimisation or scenario analysis. Reduced complexity surrogate modelling has been applied in response to this, however, current approaches are expensive to set up and still require high-fidelity simulations to derive parameters. In this study, we compare and develop graph partitioning algorithms to automatically group sections of sewer networks into semi-distributed compartments. These compartments can then be simulated using sewer network information only in the integrated modelling framework, CityWat-SemiDistributed (CWSD), which has been developed for application to sewer network modelling in this study. We find that combining graph partitioning with CWSD can produce accurate simulations 100-1,000x faster than existing high-fidelity modelling. Because we anticipate that many CWSD users will not have high-fidelity models available, we demonstrate that the approach provides reasonable simulations even under significant parametric uncertainty through a sensitivity analysis. We compare multiple graph partitioning techniques enabling users to specify the spatial aggregation of the partitioned network, also enabling them to preserve key locations for simulation. We test the impact of temporal resolution, finding that accurate simulations can be produced with timesteps up to one hour. Our experiments show a log-log relationship between temporal/spatial resolution and simulation time, enabling users to pre-specify the efficiency and accuracy needed for their applications. We expect that the efficiency and flexibility of our approach may facilitate novel applications of sewer network models ranging from continuous simulations for long-term planning to spatially optimising the placement of network sensors.

The climate emergency and population growth threaten urban water security in cities worldwide. Growth, urbanisation, and changes to way of life have increased housing demand, requiring cities such as London to increase their housing stock by more than 15% over the next 10 years. These new urban developments will increase water demand, urban flood risk, and river water pollution levels; therefore, an integrated systems-based approach to development and water management is needed. Water Neutrality (WN) has emerged as a concept to frame the concerns about escalating water stresses in cities. We frame WN as a planning process for new urban developments that aims to minimise impacts on urban water security and offset any remaining stresses by retrofitting existing housing stock. In this work, we present a novel systemic design framework for future urban planning called CityPlan-Water, which guides how WN might be achieved to tackle current and future water pressures at a city scale. CityPlan-Water integrates spatial data with an integrated urban water management model, enabling urban design at a systems level and systematic assessment of future scenarios. We define a Water Neutrality Index that captures how successful a given urban planning scenario is in achieving WN and how multiple interventions could be combined at a city scale to improve WN. Results from CityPlan-Water suggest that it will be necessary to retrofit almost the same number of existing homes with WN design options to completely offset the impact imposed by proposed new developments. Combining options such as water efficient appliances, water reuse systems, and social awareness campaigns can offset the impact of new development on water demand by 70%, while to neutralise potential flood risk and water pollution at a city scale, interventions such as rainwater harvesting and Blue Green Infrastructure need to be added both in new urban developments and 432,000 existing London households. We see CityPlan-Water as a tool that can support the transition of urban planning towards using data-driven analysis to effectively design water neutral housing and drive sustainable development.

Due to the COVID-19 pandemic, citizens of the United Kingdom were required to stay at home for many months in 2020. In the weeks before and months following lockdown, including when it was not being enforced, citizens were advised to stay at home where possible. As a result, in a megacity such as London, where long-distance commuting is common, spatial and temporal changes to patterns of water demand are inevitable. This, in turn, may change where people’s waste is treated and ultimately impact the in-river quality of effluent receiving waters. To assess large scale impacts, such as COVID-19, at the city scale, an integrated modelling approach that captures everything between households and rivers is needed. A framework to achieve this is presented in this study and used to explore changes in water use and the associated impacts on wastewater treatment and in-river quality as a result of government and societal responses to COVID-19. Our modelling results revealed significant changes to household water consumption under a range of impact scenarios, however, significant impacts on pollutant concentrations in household wastewater were only seen in central London. Pollutant concentrations in rivers were shown to be most sensitive in the tributaries of the River Thames, highlighting the vulnerability of smaller rivers and the important role that they play in diluting pollution. Ammonia and phosphates were found to be the pollutants that rivers were most sensitive to because their main source in urban rivers is domestic wastewater that was significantly altered during the imposed mobility restrictions. A model evaluation showed that we can accurately validate individual model components (i.e., water demand generator). A model evaluation showed that we can accurately validate individual model components (i.e., water demand generator) and emphasised need for continuous water quality measurements. Ultimatly, the work provides a basis for further developments of water systems integration approaches to project changes under never-before seen scenarios.

Based on the interplays between land use and water resources, the green and blue infrastructure (GBI) is a central landscape approach for hydrological environment management. However, evidence-based principles of regional GBI planning are not well developed. The Budyko framework is widely used to explore water balance in land-use change studies. It provides a method to relate land use changes and streamflow variations based on two indices – the evaporative index (EI) and the dryness index (DI). Using the Dongjiang River Basin (DJ) as an example, we use the Geographically Weighted Principal Components Analysis (GWPCA) with adaptive kernels to classify the dominant land types based on local spatial variances. Then, we apply the Emerging Hot Spots Analysis (EHSA) to identify spatial-temporal hotspots of EI and DI for the Budyko analysis. From the EHSA, two wet years (1998 and 2016) and three dry years (2004, 2009, and 2018) are focused to investigate how land uses are related to water resources in different climatic conditions. On both catchment and hotspot scales, movements within the Budyko space are observed. These movements illustrate the associations between land use and hydrological response. These data-driven relationships can be used to explain the underlying mechanism of catchment forms (land surface property) and functions (evapotranspiration and runoff) for setting best practices for land use planning. Specifically, our results show that planners should consider to 1) reduce the area of croplands and trees, while increase the extent of grassland and water body on a catchment scale; and 2) increase rain fed croplands, broadleaved evergreen trees, and grasslands in the upstream catchment. Overall, this study highlights the scale considerations in land use planning, and land use strategies are developed based on reanalysis data and remote sensing products for catchment water resources management.

Vegetation, as a fundamental element of urban green infrastructure, plays a vital role in mitigating urban flooding. Green infrastructure performance in mitigating floods depends on plant responses to meteorological forcing. This puts urban green infrastructure in risk under a changing climate. In this study, the resilience and efficiency of London’s green infrastructure under climate change is evaluated. The coupled water and carbon dynamics were evaluated using a mechanistic ecohydrological model forced with the new generation of 2018 UK Climate Projections (UKCP18). It was found that despite overall reductions of runoff production in London under climate change in winter/autumn, current urban green infrastructure in London can lose its efficiency due to the elevated levels of plant water stress unless it operates in an integrated manner with the traditional grey infrastructure drainage system. Plant water stress induced mostly by changes in climate is expected to limit vegetation performance during the end of growing seasons. The negative effects of varying climatic factors on vegetation dynamics can only be partially alleviated by the positive effects of the elevated CO2 concentration level, and are highly uncertain due to the large uncertainty of climate projections.

The urban water-energy nexus sits at the intersection of the global phenomena of water scarcity, energy transitions and urbanisation. Research found that end use dominates the water-energy nexus and that this component plays an important role in urban dynamics, but focussed on the Global North. We investigate the nexus of Mumbai and its long-term resource demand. Our tool is a novel system dynamics model representing the urban water-energy nexus and takes into account characteristics such as intermittent water supply and the presence of slums. We devised scenarios around the Sustainable Development Goals and the Swachh Bharat Mission. The model shows that both can be achieved while saving on future water system infrastructure investments compared to business-as-usual. We find that also in Mumbai end use dominates the nexus. Representing end-use interactions increases expected water demand. This work indicates that globally, sustainable development of infrastructure must consider the urban water-energy nexus.

Flood disasters are considered annual disasters in Malaysia due to their consistent occurrence. They are among the most dangerous disasters in the country. Lack of data during flood events is the main constraint to improving flood monitoring systems. With the rapid development of information technology, flood monitoring systems using a computer vision approach have gained attention over the last decade. Computer vision requires an image segmentation technique to understand the content of the image and to facilitate analysis. Various segmentation algorithms have been developed to improve results. This paper presents a comparative study of image segmentation techniques used in extracting water information from digital images. The segmentation methods were evaluated visually and statistically. To evaluate the segmentation methods statistically, the dice similarity coefficient and the Jaccard index were calculated to measure the similarity between the segmentation results and the ground truth images. Based on the experimental results, the hybrid technique obtained the highest values among the three methods, yielding an average of 97.70% for the dice score and 95.51% for the Jaccard index. Therefore, we concluded that the hybrid technique is a promising segmentation method compared to the others in extracting water features from digital images.

Natural capital plays a central role in urban functioning, reducing flooding, mitigating urban heat island effects, reducing air pollution, and improving urban biodiversity through provision of habitat space. There is also evidence on the role played by blue and green space in improving physical and mental health, reducing the burden on the health care service. Yet from an urban planning and development view, natural capital may be considered a nice to have, but not essential element of urban design; taking up valuable space which could otherwise be used for traditional built environment uses. While urban natural capital is largely recognised as a positive element, its benefits are difficult to measure both in space and time, making its inclusion in urban (re)development difficult to justify. Here, using a London case study and information provided by key stakeholders, we present a system dynamics (SD) modelling framework to assess the natural capital performance of development and aid design evaluation. A headline indicator: Natural Space Performance, is used to evaluate the capacity of natural space to provide ecosystem services, providing a semi-quantitative measure of system wide impacts of change within a combined natural, built and social system. We demonstrate the capacity of the model to explore how combined or individual changes in development design can affect natural capital and the provision of ecosystem services, for example, biodiversity or flood risk. By evaluating natural capital and ecosystem services over time, greater justification for their inclusion in planning and development can be derived, providing support for increased blue and green space within cities, improving urban sustainability and enhancing quality of life. Furthermore, the application of a SD approach captures key interactions between variables over time, showing system evolution while highlighting intervention opportunities.

The upper Ganga Basin in Uttarakhand, India, has high hydropower potential and plays an important role in the development of the state economy. Thus, an accurate knowledge of annual water yield is of paramount importance to this region. This paper deals with use of contemporary water yield estimation models such as the distributed Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and the Lumped Zhang model and their validation to identify the most suited one for water yield estimation in the upper Ganga Basin. In previous studies utilizing these models, water yield was estimated by considering a single value of some important model parameters for the entire basin, which in fact show distributed variation at a finer (pixel) scale. Therefore, in this study, pixel-level computations are performed to assess and ascertain the need for incorporating the spatial variation of such parameters in model applications. To validate the findings, the observed sub-basin discharge data are analyzed with the computed water yield for 4 decades, i.e., 1980, 1990, 2001 and 2015. The results obtained are in good agreement with the water yield obtained at the pixel scale.

Urbanisation and climate change are augmenting the uncertainty surrounding the future state of the world’s water resource and are resulting in cities experiencing growing levels of risk of pluvial flooding. Drainage infrastructure is generally built using the paradigm of ‘predict and optimise’; however, this approach fails to account for erroneous predictions. This can result in drainage systems delivering insufficient levels of flood protection. Irrespective of these uncertainties new drainage systems must be built, and existing ones adapted in such a way that they remain reliable. This work presents a critical analysis of the drivers of change of urban pluvial flooding and the uncertainties surrounding urban flood planning; thereby highlighting the shortcomings of current planning methodologies. Different Decision Making Under Deep Uncertainty (DMDU) frameworks are then explored and it is shown that they offer an improved ability to design reliable urban flood systems regardless of highly uncertain future conditions.

Understanding water user behavior and its potential outcomes is important for the development of suitable water resource management options. Computational models are commonly used to assist water resource management decision making; however, while natural processes are increasingly well modeled, the inclusion of human behavior has lagged behind. Improved representation of irrigation water user behavior within models can provide more accurate and relevant information for irrigation management in the agricultural sector. This paper outlines a model that conceptualizes and proceduralizes observed farmer irrigation practices, highlighting impacts and interactions between the environment and behavior. It is developed using a bottom‐up approach, informed through field experience and farmer interaction in the state of Uttar Pradesh, northern India. Observed processes and dynamics were translated into parsimonious algorithms, which represent field conditions and provide a tool for policy analysis and water management. The modeling framework is applied to four districts in Uttar Pradesh and used to evaluate the potential impact of changes in climate and irrigation behavior on water resources and farmer livelihood. Results suggest changes in water user behavior could have a greater impact on water resources, crop yields, and farmer income than changes in future climate. In addition, increased abstraction may be sustainable but its viability varies across the study region. By simulating the feedbacks and interactions between the behavior of water users, irrigation officials and agricultural practices, this work highlights the importance of directly including water user behavior in policy making and operational tools to achieve water and livelihood security.