City Water Resilience Framework: A governance based planning tool to enhance urban water resilience

Saikia, Panchali; Beane, George; Garriga, Ricard Giné; Avello, Pilar; Ellis, Louise A.; Fisher, Sophie; Leten, James; Ruiz-Apilánez, Iñigo; Shouler, Martin; Ward, Robin; Jiménez, Alejandro

doi:10.1016/j.scs.2021.103497

Cited by 57 publications

(27 citation statements)

References 23 publications

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“…The roof of the wedding shop was difficult to find in the first place because the roof was covered by inflammable materials such as green plants. Its fire extinguishing mechanism is as follows: (1) vaporization, heat absorption, and radiation blocking [29]; (2) smoke and dust removal, surface infiltration; (3) three-dimensional movement, horizontal fire extinguishing. Fire extinguishing agent is famous for water and cheap materials; the fire extinguishing mechanism is cooling and asphyxiation, the fire extinguishing effect is good, it is not easy to reignite after fire; under the condition of water supply guarantee, it can be reused, applicable to the wedding dress shops and other shops related to fabric [30].…”

Section: Discussionmentioning

confidence: 99%

Analysis of Characteristics of Fire Incident on 24 July 2021 in Jilin Province, China

Wang

2022

Safety

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At 15:48 on 24 July 2021, a fire accident occurred in Changchun City, Jilin Province, China, resulting in 15 deaths and 25 injuries. After the accident happened, Jilin Province comprehensively organised an emergency rescue, saving more than 100 trapped people. Given the dangers posed by these events, it is recommended that we must strengthen our risk awareness. Combined with the general background and scene of the fire, in this study, we analysed the causes of the accident and described the on-site rescue actions. The direct cause of the accident was an arc fault, and the indirect cause was the dereliction of duty in the laying and installation of the circuit and the subsequent fire supervision. From our case analysis of electrical fires in public buildings, we found that electrical failure, human factors (illegal operation), ageing and short circuits of wires, poor contact of wires, and ignition of other combustibles by electrical appliances are the main factors causing electrical fire accidents in public buildings. To avoid serious fire accidents caused by arc faults, we proposed suggestions to reduce or prevent electric fire accidents caused by arc faults.

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Section: Discussionmentioning

confidence: 99%

Analysis of Characteristics of Fire Incident on 24 July 2021 in Jilin Province, China

Wang

2022

Safety

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“…Resilience is a transformative approach that will bridge the gap between sustainability, climate change, and DR reduction by shifting the focus from prevention to managing, adapting, and bouncing back. , Given the complexity and scale of the problem, particularly as microplastics are ubiquitous, a top-down and bottom-up approach carried out in tandem is necessary to achieve the desired goals. The short-term goals of the strategies are to identify and develop a comprehensive range of actions to reduce risk and mitigate the effects of the risks of microplastics in the WSS.…”

Section: Strategies To Reduce Risk Mitigate Effects and Build Resiliencementioning

confidence: 99%

“…The OECD Principles on Water Governance “acknowledge that good governance is a means to master complexity and manage trade-offs in a policy domain that is sensitive to fragmentation, silos, scale mismatch, negative externalities, monopolies and capital-intensive investment.” The WSS needs to adapt to the multiple stressors, including governance and broader behavioral and structural changes in order to overcome “disciplinary legacies and sectoral fragmentation in the water sector (that) are persistent” …”

Section: Strategies To Reduce Risk Mitigate Effects and Build Resiliencementioning

confidence: 99%

Strategies to Reduce Risk and Mitigate Impacts of Disaster: Increasing Water Quality Resilience from Microplastics in the Water Supply System

Senathirajah,

Palanisami

2023

ACS EST Water

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Microplastics contaminating the water supply system qualifies as a disaster. This has major far-reaching implications, posing significant threats to economic growth and human livelihoods, as well as environmental and human health and well-being. Thus, we need to reduce the risk and mitigate against the effects of microplastics to build resilience and ensure continuity and efficiency of water supply system functions. To date, microplastics in the water supply cycle have not been considered in the context of disaster management. Hence, we provide an understanding of the disaster risk that microplastics pose using a conceptual mathematical framework. Additionally, we enhance understanding of the resilience of the social and physical infrastructure by highlighting hazards that people and infrastructure in the community face. Insights of the social, economic, and other human factors that make them vulnerable highlights capacities required to reduce risk and mitigate impacts. By evaluating the social and physical infrastructure resilience to microplastics in the water supply system and recommending multidisciplinary strategies to build resilience over time, we aim to catalyze action to address the problem. This will also contribute toward achieving targets of the Sendai Framework for Disaster Risk Reduction 2015–2030 and UN Sustainable Development Goals.

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“…The resilience and stability of ecological systems is a concept proposed by Holling (1973), who described it as the "ability of a system to absorb changes of state variables, driving variables, and parameters" (Saikia et al, 2022;Satterthwaite et al, 2020;Woolf et al, 2016). Since sustainability addresses the requirement for a long-term equilibrium among all systems, Ragheb et al (2017) clarified that resilience as a concept is essential for comprehending the notion of sustainability.…”

Section: Climate Change Sdgs and Dimensions Of Urban Resiliencementioning

confidence: 99%

Improvingurban Energyresiliencewith an Integrative Framework Based on Machine Learningmethods

Hassan

Megahed²

2022

A&J

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Introduction:Climate change and global warming are among the greatest challenges facing the world today. A newconcept, known as urban resilience, has been developed in response. There are various approaches to urban resilience. Among them, is the urban energy resilience (UER) approach, which poses a considerable challenge. Machine learning (ML), as an application of artificial intelligence (AI), provides powerful and affordable computing resources, large-scale datamining, advanced algorithms, and real-timemonitoring. However, veryfewstudies have investigated howsuch aspectscan be integrated into urban resilience in general, and UER in particular. Purpose of the study: The study develops an integrative framework that can improve UER, based on ML methods. Methodology: We carried out a bibliometric analysisand a systematic review of UER in accordance with AI concepts, models, and applications. Results:The findings of this study were used to create an integrative framework, based on three hierarchical phases, which effectively addressed the main capabilities of UER, identified its priorities, and shed light on how ML can benefit UER as a whole. Novelty:The framework developed in this study also offers insights in integrating ML methods into UER as strategically as possible, especially in the context of climate change and urban energy systems. This framework can serve as reference for specialistsand decision-makers aiming to expand AI and ML applications to optimize UER.

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City Water Resilience Framework: A governance based planning tool to enhance urban water resilience

Cited by 57 publications

References 23 publications

Analysis of Characteristics of Fire Incident on 24 July 2021 in Jilin Province, China

Analysis of Characteristics of Fire Incident on 24 July 2021 in Jilin Province, China

Strategies to Reduce Risk and Mitigate Impacts of Disaster: Increasing Water Quality Resilience from Microplastics in the Water Supply System

Improvingurban Energyresiliencewith an Integrative Framework Based on Machine Learningmethods

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