Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/29548
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dc.contributor.authorHarbach, LM-
dc.contributor.authorGroen, D-
dc.contributor.authorJahani, A-
dc.contributor.authorSuleimenova, D-
dc.contributor.authorGhorbani, M-
dc.contributor.authorXue, Y-
dc.contributor.editorFranco, L-
dc.contributor.editorde Mulatier, C-
dc.contributor.editorPaszynski, M-
dc.contributor.editorKrzhizhanovskaya, VV-
dc.contributor.editorDongarra, JJ-
dc.contributor.editorSloot, PMA-
dc.date.accessioned2024-08-13T16:12:51Z-
dc.date.available2024-08-13T16:12:51Z-
dc.date.issued2024-06-28-
dc.identifierORCiD: Derek Groen https://orcid.org/0000-0001-7463-3765-
dc.identifierORCiD: Alireza Jahani https://orcid.org/0000-0001-9813-352X-
dc.identifierORCiD: Diana Suleimenova https://orcid.org/0000-0003-4474-0943-
dc.identifierORCiD: Yani Xue https://orcid.org/0000-0002-7526-9085-
dc.identifier31-
dc.identifier.citationHarbach, L.M. et al. (2024) 'A Conceptual Approach to Agent-Based Modelling of Coping Mechanisms in Climate-Driven Flooding in Bangladesh', in Franco, L. et al. (eds.) Computational Science – ICCS 2024. ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part III. (14834 LNCS) Cham: Springer Nature, pp. 421 - 428. doi: 10.1007/978-3-031-63775-9_31.en_US
dc.identifier.isbn978-3-031-63774-2 (pbk)-
dc.identifier.isbn978-3-031-63775-9 (ebk)-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/29548-
dc.description.abstractBangladesh stands as a prime example of a nation exceptionally vulnerable to the adverse effects of climate change. Its low-lying coastal and deltaic landscape predisposes it to frequent flooding, a challenge exacerbated by a significant portion of its population grappling with poverty. The country is already experiencing the impacts of climate change, including more frequent and severe flooding that has led to the displacement of millions of people and has intensified existing social and economic challenges. Despite these formidable challenges, Bangladesh has also emerged as a global leader in climate resilience and preparedness, having made significant progress in reducing cyclone-related deaths and protecting its population from the consequences of climate change. Notably, non-governmental organisations, like our partners Save the Children, are keen to explore how they can support the most vulnerable communities by establishing the efficacy of current coping strategies for sustained resilience against climate change. To facilitate this, we are in the process of creating an agent-based model that examines the coping mechanisms adopted in response to climate-induced flooding in Bangladesh. This paper presents the initial phase of developing a multiscale conceptual model tailored to understanding this complex situation.en_US
dc.format.extent421 - 428-
dc.format.mediumPrint-Electronic-
dc.language.isoen_USen_US
dc.publisherSpringer Natureen_US
dc.relation.ispartofseriesLecture Notes in Computer Science;vol 14834-
dc.rightsCopyright © 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-63775-9_31 (see: https://www.springernature.com/gp/open-science/policies/book-policies).-
dc.subjectconceptual modelen_US
dc.subjectagent based modelen_US
dc.subjectforced migrationen_US
dc.subjectBangladeshen_US
dc.subjectfloodingen_US
dc.subjectinternally displaced peopleen_US
dc.subjectcoping mechanismsen_US
dc.subjectclimate changeen_US
dc.titleA Conceptual Approach to Agent-Based Modelling of Coping Mechanisms in Climate-Driven Flooding in Bangladeshen_US
dc.typeConference Paperen_US
dc.date.dateAccepted2024-04-01-
dc.identifier.doihttps://doi.org/10.1007/978-3-031-63775-9_31-
dc.relation.isPartOfComputational Science – ICCS 2024. ICCS 2024-
pubs.place-of-publicationCham-
pubs.publication-statusPublished-
pubs.volume14836 LNCS-
dc.identifier.eissn1611-3349-
dc.rights.licensehttps://www.springernature.com/gp/open-science/policies/book-policies-
dc.rights.holderThe Author(s), under exclusive license to Springer Nature Switzerland AG-
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