Supporting local flood risk decision-making using participatory modelling
Flood risk management is increasingly seeking to involve local stakeholders in decision-making, both to harness and benefit from their tacit knowledge and to devolve responsibility for delivering local-scale, individual and community responses. Current techniques used in flood risk management cen...
| Main Author: | |
|---|---|
| Format: | Thesis (University of Nottingham only) |
| Language: | English |
| Published: |
2017
|
| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/39963/ |
| _version_ | 1848795955318489088 |
|---|---|
| author | Maskrey, Shaun Andrew |
| author_facet | Maskrey, Shaun Andrew |
| author_sort | Maskrey, Shaun Andrew |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Flood risk management is increasingly seeking to involve local stakeholders in decision-making, both to harness and benefit from their tacit knowledge and to devolve responsibility for delivering local-scale, individual and community responses.
Current techniques used in flood risk management centre on a techno-scientific approach, which is well-suited to appraising and modelling hazard, but often inaccessible to those without specialist, technical expertise. This leads to participation that is often limited to infrequent consultation periods, keeping local stakeholders at the periphery of the decision-making process. Their absence from the more technical elements of the process can leave local stakeholders struggling to understand how different options have been identified, appraised and/or prioritised. This can in turn lead to dissatisfaction with process outcomes, lack of support for selected options, and foster distrust in expert practitioners.
This thesis explores how participatory modelling techniques could complement current approaches, facilitating the co-production of models with local stakeholders that explore social constructions of risk, and the vulnerability of different receptors. It identifies the qualities that are sought from participation, including the need to remain highly accessible, yet sufficiently robust to capture the complexities encountered when working at the interface of social and physical systems.
Reporting on two UK case studies, it exemplifies the benefits that two popular techniques, Bayesian networks and system dynamics, can deliver at different stages in the flood risk decision-making process. In each case, the effectiveness of the participatory approach is assessed using an evaluative framework that advances current approaches by including an early assessment of context, as well as a detailed exploration of substantive (user-defined goals), and social change outcomes. The holistic nature of the evaluation framework, and its population with practical criteria bespoke to flood risk management, enhance its transferability between different contexts. The thesis finds that participatory modelling techniques support the collating of diffuse tacit knowledge, building of consensus, strengthening of social networks, and the empowerment of local citizens to become volunteer risk managers; provided that process managers are willing to simplify the techniques to maintain accessibility, and be open to different metrics of success. |
| first_indexed | 2025-11-14T19:40:18Z |
| format | Thesis (University of Nottingham only) |
| id | nottingham-39963 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T19:40:18Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-399632025-02-28T13:39:30Z https://eprints.nottingham.ac.uk/39963/ Supporting local flood risk decision-making using participatory modelling Maskrey, Shaun Andrew Flood risk management is increasingly seeking to involve local stakeholders in decision-making, both to harness and benefit from their tacit knowledge and to devolve responsibility for delivering local-scale, individual and community responses. Current techniques used in flood risk management centre on a techno-scientific approach, which is well-suited to appraising and modelling hazard, but often inaccessible to those without specialist, technical expertise. This leads to participation that is often limited to infrequent consultation periods, keeping local stakeholders at the periphery of the decision-making process. Their absence from the more technical elements of the process can leave local stakeholders struggling to understand how different options have been identified, appraised and/or prioritised. This can in turn lead to dissatisfaction with process outcomes, lack of support for selected options, and foster distrust in expert practitioners. This thesis explores how participatory modelling techniques could complement current approaches, facilitating the co-production of models with local stakeholders that explore social constructions of risk, and the vulnerability of different receptors. It identifies the qualities that are sought from participation, including the need to remain highly accessible, yet sufficiently robust to capture the complexities encountered when working at the interface of social and physical systems. Reporting on two UK case studies, it exemplifies the benefits that two popular techniques, Bayesian networks and system dynamics, can deliver at different stages in the flood risk decision-making process. In each case, the effectiveness of the participatory approach is assessed using an evaluative framework that advances current approaches by including an early assessment of context, as well as a detailed exploration of substantive (user-defined goals), and social change outcomes. The holistic nature of the evaluation framework, and its population with practical criteria bespoke to flood risk management, enhance its transferability between different contexts. The thesis finds that participatory modelling techniques support the collating of diffuse tacit knowledge, building of consensus, strengthening of social networks, and the empowerment of local citizens to become volunteer risk managers; provided that process managers are willing to simplify the techniques to maintain accessibility, and be open to different metrics of success. 2017-07-19 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en arr https://eprints.nottingham.ac.uk/39963/1/170119%20PhD%20v17%20FINAL.pdf Maskrey, Shaun Andrew (2017) Supporting local flood risk decision-making using participatory modelling. PhD thesis, University of Nottingham. participation; stakeholder; modelling; flood risk; bayesian networks; system dynamics |
| spellingShingle | participation; stakeholder; modelling; flood risk; bayesian networks; system dynamics Maskrey, Shaun Andrew Supporting local flood risk decision-making using participatory modelling |
| title | Supporting local flood risk decision-making using participatory modelling |
| title_full | Supporting local flood risk decision-making using participatory modelling |
| title_fullStr | Supporting local flood risk decision-making using participatory modelling |
| title_full_unstemmed | Supporting local flood risk decision-making using participatory modelling |
| title_short | Supporting local flood risk decision-making using participatory modelling |
| title_sort | supporting local flood risk decision-making using participatory modelling |
| topic | participation; stakeholder; modelling; flood risk; bayesian networks; system dynamics |
| url | https://eprints.nottingham.ac.uk/39963/ |