Using system dynamics to support a participatory assessment of resilience

Herrera, Hugo; Kopainsky, Birgit

doi:10.1007/s10669-020-09760-5

“…These methods allow for an explicit description of system processes, enabling the user to obtain concrete, replicable data related to the specific vulnerabilities and adaptive capacities of individual variables within a system. Several authors have explored the concept of quantifiable resilience characteristics through the application of system dynamics (SD) models (e.g., Simonovic and Peck 2013, Candy et al 2015, Gotangco et al 2016, Herrerra 2017, Herrera and Kopainsky 2020 and physically based models (e.g., Fowler et al 2003, Cox et al 2011, Miller-Hooks et al 2012). However, it can be argued that the dynamic nature of complex socioenvironmental systems is most reliably represented using a coupled physical-SD modeling approach because coupled models are able to incorporate the concrete nature of physical data modeling with the connectivity and feedback flow of SD models.…”

Section: Modeling Resiliencementioning

confidence: 99%

Quantifying the transient shock response of dynamic agroecosystem variables for improved socio-environmental resilience

Carper¹,

Alizadeh²,

Adamowski³

et al. 2021

E&S

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In classic resilience thinking, there is an implicit focus on controlling functional variation to maintain system stability. Modern approaches to resilience thinking deal with complex, adaptive system dynamics and true uncertainty; these contemporary frameworks involve the process of learning to live with change and make use of the consequences of transformation and development. In a socio-environmental context, the identification of metrics by which resilience can be effectively and reliably measured is fundamental to understanding the unique vulnerabilities that characterize coupled human and natural systems. We developed an innovative procedure for stakeholder-friendly quantification of socio-environmental resilience metrics. These metrics were calculated and analyzed through the application of discrete disturbance simulations, which were produced using a dynamically coupled, biophysical-socioeconomic modeling framework. Following the development of a unique shock-response assessment regime, five metrics (time to baseline-level recovery, rate of return to baseline, degree of return to baseline, overall post-disturbance perturbation, and corrective impact of disturbance) describing distinct aspects of systemic resilience were quantified for three agroecosystem variables (farm income, watertable depth, and crop revenue) over a period of 30 years in the Rechna Doab basin of northeastern Pakistan. Using this procedure, we determined that farm income is the least resilient variable of the three tested. Farm income was easily diverted from the "normal" functional paradigm for the Rechna Doab socio-environmental system, regardless of shock type, intensity, or duration combination. Crop revenue was the least stable variable (i.e., outputs fluctuated significantly between very high and very low values). Water-table depth was consistently the most robust and resistant to change, even under physical shock conditions. The procedure developed here should improve the ease with which stakeholders are able to conduct quantitative resilience analyses.

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“…Alternatively, upon availability of empirical data, such understanding can be used as a baseline for constructing mathematical and simulation models. Examples include transitions from FCM to Agentbased modelling [33] [34], from CLD to System Dynamics [35], and from conceptual mappings into Discrete-event simulation [36] and Bayesian belief networks [37] models.…”

Section: B Designing a Digitalized Participatory Systemmentioning

confidence: 99%

A Cybernetic Participatory Approach for Whole-Systems Modelling and Analysis, with Application to Inclusive Economies

Hassannezhad¹,

Gogarty²,

O’Connor³

et al. 2021

Preprint

1

0

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Traditional participatory systems modelling demands synchronous time from many experts and face-to-face interaction. This is not always feasible (e.g. recent pandemic) and can restrict which participants can be included. There are additional limitations in the effectiveness of physical paper-based modelling when handling large complex systems with numerous variables and links between them. The key challenge facing practitioners is then how we can retain the benefits of traditional participatory modelling whilst exploiting the advantages of new technologies? This paper contributes to development of an original systematic methodology based on Cybernetic principles. The proposed method, refers to 5X – standing for Expose, Explore, Exploit, Explain, and Expand, offers a fully virtual co-produced environment for better engagement of stakeholders, developing more confidence in systems mapping, and promote knowledge to other policy areas. A primary application of the proposed method in a real policy setting illustrates its capability in generating a shared policy understanding of complex Inclusive Economy system, where there is conflicting or dispersed knowledge about system structure, refining this understanding through online feedback channels, and transferring this understanding to wider policy and academic partners through mutual relationships.

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“…Alternatively, upon availability of empirical data, such understanding can be used as a baseline for constructing mathematical and simulation models. Examples include transitions from FCM to Agentbased modelling [33][34], from CLD to System Dynamics [35], and from conceptual mappings into Discrete-event simulation [36] and Bayesian belief networks [37] models.…”

Section: B Designing a Digitalized Participatory Systemmentioning

confidence: 99%

A Cybernetic Participatory Approach for Whole-Systems Modelling and Analysis, with Application to Inclusive Economies

Hassannezhad¹,

Gogarty²,

O’Connor³

et al. 2021

Preprint

0

View full text Add to dashboard Cite

Traditional participatory systems modelling demands synchronous time from many experts and face-to-face interaction. This is not always feasible (e.g. recent pandemic) and can restrict which participants can be included. There are additional limitations in the effectiveness of physical paper-based modelling when handling large complex systems with numerous variables and links between them. The key challenge facing practitioners is then how we can retain the benefits of traditional participatory modelling whilst exploiting the advantages of new technologies? This paper contributes to development of an original systematic methodology based on Cybernetic principles. The proposed method, refers to 5X – standing for Expose, Explore, Exploit, Explain, and Expand, offers a fully virtual co-produced environment for better engagement of stakeholders, developing more confidence in systems mapping, and promote knowledge to other policy areas. A primary application of the proposed method in a real policy setting illustrates its capability in generating a shared policy understanding of complex Inclusive Economy system, where there is conflicting or dispersed knowledge about system structure, refining this understanding through online feedback channels, and transferring this understanding to wider policy and academic partners through mutual relationships.

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Using system dynamics to support a participatory assessment of resilience

Cited by 28 publications

References 41 publications

Quantifying the transient shock response of dynamic agroecosystem variables for improved socio-environmental resilience

Quantifying the transient shock response of dynamic agroecosystem variables for improved socio-environmental resilience

A Cybernetic Participatory Approach for Whole-Systems Modelling and Analysis, with Application to Inclusive Economies

A Cybernetic Participatory Approach for Whole-Systems Modelling and Analysis, with Application to Inclusive Economies

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