2020
DOI: 10.18174/sesmo.2020a17938
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Tracing resilience, social dynamics and behavioral change: a review of agent-based flood risk models

Abstract: Climate change and rapid urbanization exacerbate flood risks worldwide. The recognition of the crucial role that human actors play in altering risks and resilience of flood-prone cities triggers a paradigm shift in climate risks assessments and drives the proliferation of computational models that include societal dynamics. Yet, replacing a representative rational actor dominant in climate policy models with a variety of behaviorally-rich agents that interact, learn, and adapt is not straightforward. Focusing … Show more

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Cited by 21 publications
(17 citation statements)
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“…Incorporating social complexities into formal models is nontrivial (Taberna et al, 2020). For example, the Earth System and Integrated Assessment Models (ESMs and IAMs) are key in understanding coupled dynamics of climate and socioeconomic systems on the macro-scale, but they do not include human behavior on the micro-scale (Beckage et al, 2020).…”
Section: Methods and Models To Assess Social Tipping Pointsmentioning
confidence: 99%
See 1 more Smart Citation
“…Incorporating social complexities into formal models is nontrivial (Taberna et al, 2020). For example, the Earth System and Integrated Assessment Models (ESMs and IAMs) are key in understanding coupled dynamics of climate and socioeconomic systems on the macro-scale, but they do not include human behavior on the micro-scale (Beckage et al, 2020).…”
Section: Methods and Models To Assess Social Tipping Pointsmentioning
confidence: 99%
“…Worst-case scenarios may exceed adaptive capacities even in the wealthiest countries, as demonstrated by the 2003 heat wave in Europe, or by recent Hurricanes in the United States. ABMs are increasingly applied to study agents' adaptation behavior to various climate hazards, including floods (Yang et al, 2018;Taberna et al, 2020), droughts (Barreteau et al, 2014), wildfires (Spies et al, 2017), and climate-driven migration (Entwisle et al, 2016). Furthermore, ABMs go beyond modeling the behavior of individual actors to capture changes in social institutions in response to climate-driven hazards (Abebe et al, 2019;de Koning and Filatova, 2020).…”
Section: Methods and Models To Assess Social Tipping Pointsmentioning
confidence: 99%
“…The MSD research community must position itself to take advantage of the explosive growth of emerging data resources, algorithmic innovations, and analytic advances that facilitate model‐based insights. Modeling frameworks have been rapidly evolving in how they capture dynamic and adaptive representations of human actors, infrastructures, and natural systems, as well as in how they account for the uncertainties surrounding them (Filatova et al., 2013; Herman et al., 2020; Knox et al., 2018; Morris et al., 2018; Taberna et al., 2020; Trindade et al., 2020; Turner et al., 2020; Yoon et al., 2021). These advances enable new scientific hypotheses by diversifying theoretical problem framings across a broader array of disciplinary perspectives.…”
Section: Msd Research Gaps and Aspirationsmentioning
confidence: 99%
“…Recently, reviews specific to the use of ABMs in the area of FRMA have been published by Aerts (2020), Taberna et al (2020), Zhuo and Han (2020), and Simmonds et al (2020). Aerts (2020) compared trends among other system dynamic models and discussed the decision-making process associated with human behaviour.…”
Section: Introductionmentioning
confidence: 99%
“…Aerts (2020) compared trends among other system dynamic models and discussed the decision-making process associated with human behaviour. Taberna et al (2020), looked at ABM implementation across disciplines (from an economic and a flood viewpoint) and sheds light on different spatio-temporal scales, and the learning process in agents to change adaptive behaviour. Zhuo and Han (2020), identified spatial distributions of the studies, different ABM platforms, their applications and advantages.…”
Section: Introductionmentioning
confidence: 99%