An agent-based spatiotemporal integrated approach to simulating in-home water and related energy use behaviour: A test case of Beijing, China

Zhuge, Chengxiang; Yu, Min; Wang, Chunyan; Cui, Yilan; Liu, Yi

doi:10.1016/j.scitotenv.2019.135086

Cited by 16 publications

(11 citation statements)

References 55 publications

(64 reference statements)

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“…Water users are modelled using ABM to analyze and forecast household water demand [31] and to explore the effect of water demand management strategies on household water consumption [32]. Furthermore, [33], which is focused on an area outside Europe, developed an ABM simulating the users' behavior and how it affects energy and water consumption.…”

Section: Resultsmentioning

confidence: 99%

On the Use of Agent Based Modelling for Addressing the Social Component of Urban Water Management in Europe

Koutiva¹,

Makropoulos²

2021

CWEEE

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The paper aimed to provide a review of different tools that estimate how human behavior changes by water management strategies and quantify this change to support the decisions of urban water managers. To support decision makers, it is essential to be able to model the urban water system's human part explicitly and link it to the hydro system's response, rather than only explore the reaction of the system based on scenarios. To do so, tools are needed that can model the human part of the system, explore its reaction to potential changes and dynamically link back this to the techno-environmental model of the water system. This work reviews state-of-the-art ABMs that are publicly available focusing on the human part of the urban water system in Europe. The review leads to the proposals of three pillars for future development of ABMs for urban water management in Europe: end-user enablement; Machine Learning and Artificial Intelligence integration and adversaries modelling.

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Section: Resultsmentioning

confidence: 99%

On the Use of Agent Based Modelling for Addressing the Social Component of Urban Water Management in Europe

Koutiva¹,

Makropoulos²

2021

CWEEE

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“…Other recurrent themes included impacts to stream hydrology [36] and water use conflicts [31] in the context of shifting water availability under future climate (i.e., hydroclimate) and/or population growth (Figure 2). Energy-water ABM applications (3) were all household-level simulations of interrelated water and energy demands generated by daily in-home and out-of-home activities [37][38][39]. The ABM applications that addressed additional sectors or dimensions beyond FEWS were generally equally split between environment (7) and greenhouse gas emissions (7) and one focusing on resource-related conflicts [31] (Table 1).…”

Section: Research Contextmentioning

confidence: 99%

“…A distributed architecture was also needed to better account for the interactions among agents when there was directionality to interactions, such as upstream and downstream water users [31], or producers/consumers in material flow networks between farms, and with their upstream and downstream partners [32]. Accordingly, the ease with which spatial heterogeneity could be represented and integrated with GIS in ABMs was seen as a strength of the approach [38].…”

Section: Justifications For Using Abmmentioning

confidence: 99%

Agent-Based Modeling for Integrating Human Behavior into the Food–Energy–Water Nexus

Magliocca

2020

Land

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The nexus of food, energy, and water systems (FEWS) has become a salient research topic, as well as a pressing societal and policy challenge. Computational modeling is a key tool in addressing these challenges, and FEWS modeling as a subfield is now established. However, social dimensions of FEWS nexus issues, such as individual or social learning, technology adoption decisions, and adaptive behaviors, remain relatively underdeveloped in FEWS modeling and research. Agent-based models (ABMs) have received increasing usage recently in efforts to better represent and integrate human behavior into FEWS research. A systematic review identified 29 articles in which at least two food, energy, or water sectors were explicitly considered with an ABM and/or ABM-coupled modeling approach. Agent decision-making and behavior ranged from reactive to active, motivated by primarily economic objectives to multi-criteria in nature, and implemented with individual-based to highly aggregated entities. However, a significant proportion of models did not contain agent interactions, or did not base agent decision-making on existing behavioral theories. Model design choices imposed by data limitations, structural requirements for coupling with other simulation models, or spatial and/or temporal scales of application resulted in agent representations lacking explicit decision-making processes or social interactions. In contrast, several methodological innovations were also noted, which were catalyzed by the challenges associated with developing multi-scale, cross-sector models. Several avenues for future research with ABMs in FEWS research are suggested based on these findings. The reviewed ABM applications represent progress, yet many opportunities for more behaviorally rich agent-based modeling in the FEWS context remain.

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“…Three types of simulation modelling approaches are commonly used to explore urban water management and governance: urban water metabolism [7], [8], agent-based [9] and system dynamics modelling [10]- [12]. The metabolism-based modelling approach overcomes issues commonly encountered by independent modelling of the components of the urban water system (water supply, wastewater and surface water collection) by providing an integrated approach that considers the interconnection and interdependencies between water flows and other fluxes in urban systems including wastewater, energy and material.…”

Section: Introductionmentioning

confidence: 99%

“…Agent-Based Modelling has been used as well, but also with limitations e.g. in providing a comprehensive and cross-sectoral analysis of complex urban systems and in the analysis of future evolution through 'what-if' scenarios [9]. The System Dynamics Modelling approach is able to incorporate both the dynamic evolution of the urban system as well as social conditions such as stakeholders' priorities and goals.…”

Section: Introductionmentioning

confidence: 99%

Further Development of the Ebbsfleet Water Management System Dynamics Model: Adjusting Representation of Processes and System Boundaries, Incentivising Stakeholder Re-Engagement, and Exploring Potential for University Teaching

Krivtsov

Pagano

Ahilan

et al. 2021

WIT Transactions on Ecology and the Environment

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Sustainable urban water management must address interconnected social, technical and environmental issues. Modelling helps us understand these interconnections and provides a tool to analyse interactions between the urban water system and alternative management strategies. Models may be used to simulate not only the effects of climate, social and economic changes, but also the impacts of technological innovations, and different policy interventions. This paper reports an update of the Ebbsfleet Water Management System Dynamics Model (SDM) that explores sustainable urban water management. The model is open-source compiled using Vensim software, which is free for non-commercial use. This paper demonstrates that the current SDM and the modelling approach are open to adjustment, which is illustrated by introducing a link between water tariffs and environmental awareness. The increase in water tariffs leads not only to the obvious increase in water bills, but also to an increase in Environmental Awareness, and consequently, to increases in the use of water efficiency devices, grey water acceptability, and grey water reuse. A range of further modifications is suggested, including expanding representation of sustainable drainage systems (SuDS) to consider resultant improvements in stormwater quality as well as quantity. This would recognise the indirect benefits of improved stormwater quality on biodiversity in the River Ebbsfleet, which is the receiving watercourse. This study intends to encourage knowledge transfer, by facilitating and incentivising the use and further development of the SDM by stakeholders and a wider community of end-users, including practitioners, academics and the public. While SDM is particularly suited to analysis of indirect relations, benefits and trade-offs among system constituents, other approaches provide viable alternatives and we discuss the potential for re-implementing our findings in other interactive modelling software packages and programming languages. We also explore the scope for linking the adapted SDM to other models. Finally, we consider the utility of the Ebbsfleet SDM in teaching, learning and knowledge transfer. We conclude that students, practitioners and other stakeholders could not only enhance their understanding of urban water management complexity, but also gain valuable system modelling skills based on using the SDM to support kinaesthetic learning. Ultimately, society benefits when the level of knowledge and analytical thinking skills of its members are enhanced.

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An agent-based spatiotemporal integrated approach to simulating in-home water and related energy use behaviour: A test case of Beijing, China

Cited by 16 publications

References 55 publications

On the Use of Agent Based Modelling for Addressing the Social Component of Urban Water Management in Europe

On the Use of Agent Based Modelling for Addressing the Social Component of Urban Water Management in Europe

Agent-Based Modeling for Integrating Human Behavior into the Food–Energy–Water Nexus

Further Development of the Ebbsfleet Water Management System Dynamics Model: Adjusting Representation of Processes and System Boundaries, Incentivising Stakeholder Re-Engagement, and Exploring Potential for University Teaching

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