Towards urban resilience through Sustainable Drainage Systems: A multi-objective optimisation problem

Design and hydrologic performance estimation of highway filter drains using a novel analytical probabilistic model

Sustainable drainage systems (SuDS) are nature-based methods of managing urban stormwater runoff. Although they are widely used, some SuDS, such as highway filter drains (HFDs), are understudied with respect to sizing and performance. For the first time, we developed an analytical probabilistic model (APM) that can be used to design and estimate the hydrologic performance of HFDs. Unlike the conventionally used design-storm based or continuous simulation approaches, our APM can directly calculate the runoff capture ratios of HFDs using closed-form analytical equations. Validation of the APM presented here shows that it is robust and reliable. The relative differences between the APM-estimated and continuous simulation-determined runoff capture ratios for all the simulated design cases are less than 8.5%.

Optimized strategies of green and grey infrastructures for integrated control objectives of runoff, waterlogging and WWDP in old storm drainages

Frequent waterlogging occurs in old high-density urban areas where the sewage is inappropriately connected to storm drainages, resulting in serious wet weather discharge pollution (WWDP). To address urban waterlogging and runoff, the optimization of green infrastructures (GIs) and grey infrastructures (GRs) has been proposed to improve rainwater management efficiency. However, most strategies neglect WWDP and fail to achieve integrated control of runoff, waterlogging, and discharge pollution. In the present study, a new optimization method was introduced to identify optimal solutions for renovating outdated storm drainage systems, considering the management of discharge pollution in wet weather. A case study in Shanghai, China was conducted to demonstrate the application of the method. The cost-benefit index (CBI) of optimized GIs (0.06) was lower than that of optimized GRs (2.78) under 22.2 mm rainfall (no runoff and WWDP), but the costs of the former were only half those of the latter. In a 5-year return period storm (no waterlogging), optimized GIs had a significantly higher CBI (2.85 times) compared to optimized GRs, costing only 44 % of the latter. When WWDP reached the control objective (COD≤70 mg/L), the optimized GIs needed to be further optimized with GRs. The CBI of optimized GI-GRs was higher than GRs by 2.50, and the cost was 58% of the latter. In areas with frequent low-intensity rainfall, optimized GIs and GRs should be selected based on local cost or benefit requirements for drainage reconstruction. In high-intensity storm-prone areas, the optimized GI-GR combination should be selected for drainage reconstruction. The proposed method can compensate for the shortcomings of existing optimization methods in controlling WWDP for the reconstruction of old storm drainages.

Machine learning-based surrogate model assisting stochastic model predictive control of urban drainage systems

Quantifying the uncertainty of stormwater inflow is critical for improving the resilience of urban drainage systems (UDSs). However, the high computational complexity and time consumption obstruct the implementation of uncertainty-addressing methods for real-time control of UDSs. To address this issue, this study developed a machine learning-based surrogate model (MLSM) that maintains high-fidelity descriptions of drainage dynamics and meanwhile diminishes the computational complexity. With stormwater inflow and controls as inputs and system overflow as the output, MLSM is able to fast evaluate system performance, and therefore stochastic optimization becomes feasible. Thus, a real-time control strategy was built by combining MLSM with the stochastic model predictive control. This strategy used stochastic stormwater inflow scenarios as input and aimed to minimize the expected overflow under all scenarios. An ensemble of stormwater inflow scenarios was generated by assuming the forecast errors follow normal distributions. To downsize the ensemble, representative scenarios with their probabilities were selected using the simultaneous backward reduction method. The proposed control strategy was applied to a combined UDS of China. Results are as follows. (1) MLSM fit well with the original high-fidelity urban drainage model, while the computational time was reduced by 99.1%. (2) The proposed strategy consistently outperformed the classical deterministic model predictive control in both magnitude and duration dimensions of system resilience, when the consumed time compatible is with the real-time operation. It is indicated that the proposed control strategy could be used to inform the real-time operation of complex UDSs and thus enhance system resilience to uncertainty.

Global resilience analysis of combined sewer systems under continuous hydrologic simulation

Managing and reducing combined sewer overflow (CSO) discharges is crucial for enhancing the resilience of combined sewer systems (CSS). However, the absence of a standardised resilience analysis approach poses challenges in developing effective discharge reduction strategies. To address this, our study presents a top-down method that expands the existing Global Resilience Analysis to quantify resilience performance in CSS. This approach establishes a link between threats (e.g., rainfall) and impacts (e.g., CSOs) through continuous and long-term simulation, accommodating various rainfall patterns, including extreme events. We assess CSO discharge impacts from a resilience perspective by introducing eight new metrics. We conducted a case study in Fehraltorf, Switzerland, analysing the performance of three green infrastructure (GI) types (bioretention cells, green roofs, and permeable pavements) over 38 years. The results demonstrated that GI enhanced all resilience indices, with variations observed in individual CSO performance metrics and their system locations. Notably, in Fehraltorf, green roofs emerged as the most effective GI type for improving resilience, while the downstream outfall displayed the highest resilience enhancement. Overall, our proposed method enables a shift from event-based to continuous simulation analysis, providing a standardised approach for resilience assessment. This approach informs the development of strategies for CSO discharge reduction and the enhancement of CSS resilience.

Community values on governing urban water nature-based solutions in Sydney, Australia

Since the needs and expectations of communities towards their urban environments often vary, landscape management strategies can often be prone to fail in the absence of social considerations. It is therefore incumbent on policy-makers to investigate and attempt to reconcile diverse community perceptions toward the natural and built environment for more equitable governance. This is of particular interest when planning and managing nature-based solutions (NBS) for river protection. We considered this challenge in understanding human values, perceptions and behaviour in a multilayered ecosystem that includes waterways, NBS, green open spaces, and a built environment. This paper analyses perceptions and behaviour around a public urban park next to the Georges River in Sydney Australia, utilizing a proxy-based approach and a mixed-method comprising community surveys and behavioural mapping. The results showed that while users perceive the significance of the urban river environment differently, naturalistic (ecological), humanistic (recreational) and utilitarian (well-being) values are dominant. Urban river catchments are highly valued for recreational purposes, with a strong perception of potential flooding hazards. Through exploring the literature, we recognized that the dominancy of leisure-related values around urban river catchments can be generalized to similar cases worldwide. While NBS, as an urban stormwater management solution, address some user values (e.g., naturalistic) around urban river catchments, they may lack further delivery of humanistic and utilitarian values due to the poor integration with recreational and cultural spaces. It was also the case around the Georges River, where low prominence of cultural features was observed. We concluded that NBS development around Georges River and other urban river catchments should incorporate socio-cultural considerations and community values, in particular the ones related to leisure. The gaps between users' beliefs and behaviour do not greatly challenge governance, provided that the decision-makers utilise these gaps for optimising management actions.

Designing coupled LID-GREI urban drainage systems: Resilience assessment and decision-making framework

As flooding risks rise in urban areas, research suggests combining low impact development (LID) and grey infrastructure (GREI) in urban drainage systems. Several frameworks have been proposed to plan such coupled systems, but there is not a comprehensive framework to assess their resilience under diverse failure scenarios and sources of uncertainty. This study proposes a framework which considers both technological and operational resilience. Technological resilience has to do with the performance of the system under extreme loads. Operational resilience has to do with the performance and long-term efficiency of the system after structural damage or degradation, using appropriate probability distributions to quantify the likelihood of failures. The proposed framework is based on an optimization and multi-criteria decision-making platform. It improves on previous research, which lacked consideration of uncertainty in resilience over the life span. We also apply the proposed framework to a real-world test case, and find that in a high-density urban area, a coupled system is more cost-effective than GREI alone. Furthermore, decentralized systems with greater flexibility show significantly better technological and operational resilience. The proposed framework can better support decision-making for planning robust and cost-effective urban drainage systems, particularly in highly urbanized areas.

Battle of centralized and decentralized urban stormwater networks: From redundancy perspective

Recent research underpinned the effectiveness of topological decentralization for urban stormwater networks (USNs) during the planning stage in terms of both capital savings and resilience enhancement. However, how centralized and decentralized USNs' structures with various degrees of redundancy (i.e., redundant water flow pathways) project resilience under functional and structural failure remains an unresolved issue. In this work, we present a systemic and generic framework to investigate the impact of adding redundant flow paths on resilience based on three strategies for optimal centralized versus decentralized USNs. Furthermore, a tailored graph-theory based measure (i.e., eigenvector centrality) is proposed to introduce redundant paths to the critical locations of USNs. The proposed framework is then applied to a real large-scale case study. The results confirm the critical role of layout decentralization under both functional (e.g., extreme precipitation events), and structural failure (e.g., pipe collapse). Moreover, the findings indicate that the implementation of redundant paths could increase resilience performance by up to 8% under functional failure without changing the network's major structural characteristics (i.e., sewer diameters, lengths, and storage capacity), only by leveraging the effective flow redistribution. The scheme proposed in this study can be a fruitful initiative for further improving the USNs' resilience during both planning and rehabilitation stages.

The application of resilience theory in urban development: a literature review

In the complex context of urbanization and climate change, how to improve the resilience of cities to deal with various uncertain and unpredictable threats is a new topic with both theoretical and practical challenges. In this paper, the researches on urban resilience are summarized using the bibliometric analysis combined with the visualization analysis. We provide a systematic and objective review of resilience applied to urban development focusing on its conceptual frameworks, research tendencies, and assessment methods. The analysis results demonstrate that an increasing attention has been given to urban resilience, especially in the field of climate change. The degree of research varies significantly in different countries, with the USA dominating in the number of publications, followed by the UK and China. Scholars' attention to urban resilience in different periods is closely related to the development background and disasters experienced by their countries, but there are also some commonalities. Meanwhile, the multi-dimensional research on urban resilience has been recognized by many scholars. Quantitative assessment tools such as simulation model and optimization model have been widely used to assess the level of urban resilience. Based on this, we put forward the future research trends in this field and provide a potential guide for future application of urban resilience.

A SUDS Planning Decision Support Tool to Maximize Ecosystem Services

In the past years, alternative drainage approaches have emerged, such as Sustainable Urban Drainage Systems (SUDS), to prevent run-off and flooding impacts on the most vulnerable zones of the cities. These systems not only provide the benefit of water regulation but also promote other types of ecosystem services. Several studies have developed optimization tools to assist SUDS selection, location, and design. However, they do not consider a comprehensive set of ecosystem services (e.g., provision, regulation, cultural, and support services). This research proposes a flexible and adaptable methodology to incorporate SUDS in different stages of urban projects using a multi-objective optimization technique to minimize run-off, maximize ecosystem services and minimize cost. The methodology comprises four phases: (1) the preliminary analysis of ecosystem services potentially generated by each SUDS type, (2) the priority and opportunity index quantification, (3) the physical feasibility analysis, and (4) the multi-objective optimization tool implementation. The methodology was successfully applied to three different urban areas of Bogotá city (Colombia). Results evidence that the interaction of the budget constraints and the available area restrict the potential benefits of SUDS implementation. These results are helpful to support different urban planning stages.

Suitability Zoning for Sustainable Drainage Systems (SuDSs): Application in a Basin in Southern Brazil

The objective of this study was to propose a set of procedures to assess areas regarding the suitability of sustainable drainage systems (SuDSs) with application in a basin in the urban area of São Carlos (Brazil). The assessment was based on an analysis of 39 attributes reflecting the infiltration conditions that control the functional and constructive aspects of the systems, including subsurface drainability, stability, and groundwater contamination potential, which control the degree of suitability of each plot of land. The data obtained through engineering geological mapping procedures and physical principles were used to characterize the area, which resulted in the division of the basin into five SuDS suitability zones, ranging from favorable to restrictive. The proposed procedures proved to be efficient for analyzing the suitability of different SuDS types and the zoning of an area into terrain units. This approach can help planners identify the most appropriate SuDS types for a given unit, optimize the efficiency/cost relationship, and foresee potential environmental and construction-related challenges. In other words, this procedure enables the assessment of the suitability of SuDSs for different unit terrain types with inexpensive and environmentally efficient technological procedures and resources and can be applied at a fine geographic scale.

Sustainable Urban Drainage System (SUDS) modeling supporting decision-making: A systematic quantitative review

Decision Support Systems (DSS) for Sustainable Urban Drainage Systems (SUDS) are a valuable aid for SUDS widespread adoption. These tools systematize the decision-making criteria and eliminate the bias inherent to expert judgment, abridging the technical aspect of SUDS for non-technical users and decision-makers. Through the collection and careful assessment of 120 papers on SUDS models and SUDS-DSS, this review shows how these tools are built, selected, and used to assist decision-makers questions. The manuscript classifies the DSS based on the question they assist in answering, the spatial scale used, the software selected, among other aspects. SUDS-DSS aspects that require more attention are identified, including environmental and social considerations, SUDS trains performance and criteria for selection, stochasticity of rainfall, and future scenarios impact. Suggestions for SUDS-DSS are finally offered to better equip decision-makers in facing emerging stormwater challenges in urban centers.

Understanding the NEEDS for ACTING: An integrated framework for applying nature-based solutions in Brazil

Nature-based solutions (NBS) support the provision of multiple benefits for the environment and society. First idealised in 2008, NBS are recommended by worldwide reports and guidelines as strategies to protect, sustainably manage and restore ecosystems. However, their operationalisation is still in the early stages, especially in developing countries, and only a few studies consider their full potential. This article contributes to this context by developing an integrated framework, with spatial and participatory tools, for analysing flood risk mitigation in Brazil. The approach enables a deep understanding of the societal challenges and vulnerabilities of the area (i.e., NEEDS) for subsequently planning the appropriate NBS (i.e., ACTIONS), with the participation of 255 stakeholders of Campina Grande municipality. Results show mappings of flood-prone areas, in which approximately 52% of the flooded areas will see an increase in the future. Hotspots (i.e., hazard, vulnerability, and exposure) are shown and discussed with four application cases. Finally, multiple benefits of seven NBS alternatives are analysed in 53 scenarios of application, in which the higher rates of reductions are found to combined alternatives. The discussion emphasizes the importance of spatially assessing the 'needs' and 'multiple benefits' of NBS, including reducing vulnerabilities and increment of resilience.

Enhancing Uptake of Nature-Based Solutions for Informing Coastal Sustainable Development Policy and Planning: A Malaysia Case Study

Nature-based Solutions (NbS) have been advocated to protect, sustainably manage, and restore natural or modified ecosystems, simultaneously providing human well-being and biodiversity benefits. The uptake of NbS differs regionally with some countries exhibiting greater uptake than others. The success of NbS also differs regionally with varying environmental conditions and social-ecological processes. In many regions, the body of knowledge, particularly around the efficacy of such efforts, remains fragmented. Having an “inventory” or “tool box” of regionally-trialed methods, outcomes and lessons learnt can improve the evidence base, inform adaptive management, and ultimately support the uptake of NbS. Using Malaysia as a case study, we provide a comprehensive overview of trialed and tested NbS efforts that used nature to address societal challenges in marine and coastal environments (here referring to mangroves, seagrass, coral reefs), and detailed these efforts according to their objectives, as well as their anticipated and actual outcomes. The NbS efforts were categorized according to the IUCN NbS approach typology and mapped to provide a spatial overview of IUCN NbS effort types. A total of 229 NbS efforts were collated, representing various levels of implementation success. From the assessment of these efforts, several key actions were identified as a way forward to enhance the uptake of Nature-based Solutions for informing coastal sustainable development policy and planning. These include increasing education, training, and knowledge sharing; rationalizing cooperation across jurisdictions, laws, and regulations; enhancing environmental monitoring; leveraging on existing policies; enabling collaboration and communication; and implementing sustainable finance instruments. These findings can be used to inform the improved application and uptake of NbS, globally.

A novel machine learning application: Water quality resilience prediction Model

Resilience-informed water quality management embraces the growing environmental challenges and provides greater accuracy by unpacking the systems' characteristics in response to failure conditions in order to identify more effective opportunities for intervention. Assessing the resilience of water quality requires complex analysis of influential parameters which can be challenging, time consuming and costly to compute. It may also require building detailed conceptual and/or physically process-based models that are difficult to build, calibrate and validate. This study utilises Artificial Neural Network (ANN) to develop a novel application to predict water quality resilience to simplify resilience evaluation. The Fuzzy Analytic Hierarchy Process method is used to rank water basins based on their level of resilience and to identify the ones that demand prompt restoration strategies. The commonly used 'magnitude * duration of being in failure state' quantification method has been used to formulate and evaluate resilience. A 17-years long water quality dataset from the 22 water basins in the State of São Paulo, Brazil, was used to train and test the ANN model. The overall agreement between the measured and simulated WQI resilience values is satisfactory and hence, can be used by planners and decision makers for improved water management. Moreover, comparative analyses show similarities and differences between the 'level of criticalities' reported in each zone by Environment Agency of the state of São Paulo (CETESB) and by the resilience model in this study.

Nature-Based Solutions and Real-Time Control: Challenges and Opportunities

Nature-based solutions (NBS) as green infrastructures to urban drainage are an effective mitigation strategy both in terms of quantity and quality of runoff. Real-time control (RTC) can complement both flood mitigation and improvement of water quality by controlling elements of the drainage and sewage system. This study assessed the improvement opportunities with RTC of three NBS-related techniques commonly applied in urban drainage with different spatial scales: green roof, bioretention and detention basin and the remaining challenges to integrate both methods. Additionally, our investigations showed that the main difficulties reported involve the planning and monitoring stages of the RTC system. All of the studied devices can benefit from RTC. It is possible to observe that, despite the good results reported in the literature, the application of RTC to NBS studies on urban drainage are very recent. There are several opportunities that can be explored to optimize the performance.