Modelling Community Disaster Resilience: A Participatory Approach

Tariq, Hisham

Abstract

Due to the increasingly complex nature of climate change impacts, decision-makers such as local government practitioners and community members need more inclusive tools to assess their communities' resilience to environmental risks and natural hazards. The implementation of the whole-of-society approach from international organisations like the United Nations Office for Disaster Risk Reduction (UNDRR), the Global Network of Civil Society Organisations for Disaster Reduction (GNDR) and the Disaster Emergency Committee (DEC) demands a more participatory and subjective approach to defining and evaluating community resilience to disasters. Each stakeholder group brings a different perspective to understanding their resilience issues, which typically cause significant debate or conflict on the policies needed to improve the community's resilience for long-term sustainable development and growth. The multi-disciplinary nature of resilience issues requires innovative techniques that can help capture multiple perspectives, the dynamic nature of community resilience at the local level, and the complexity of hazard impacts on a short- and long-term basis. This research aims to improve community resilience measurement by developing a novel Participatory Approach to Modelling Community Resilience to natural disasters associated with a simulation model that can be adapted and customised according to stakeholder specifications.

This research first analysed the key features and characteristics of 36 community disaster resilience (CDR) frameworks in the literature, which led to the clustering of six critical resilience dimensions (i.e. Physical, Health, Economic, Environmental, Social and Governance) with a library of 86 resilience indicators, composed of 360 measures. These indicators and measures were categorised into three community capacities (Anticipatory, Absorptive, and Restorative) and used as the basis for operationalising a CDR model according to the needs of the stakeholders. To overcome the objective and static nature of the current CDR frameworks, this research introduced a novel participatory approach which is comprised of two Phases: 1) Systems Thinking and Mapping to develop an understanding of community resilience with the target stakeholder groups of a disaster risk reduction intervention and determine the key dimensions of indicators (from the library) for the measurement of resilience capacities as parameters; and 2) System Design and Modelling, to use the parameters to formulate a System Dynamics (SD) model of community resilience over time, test and validate the SD model of Community Resilience with stakeholders’ group in a case study. The case study implements the two-phased modelling approach developed in the research to model the impact of flash flooding disaster events in the Budni Nala neighbourhood in the City of Peshawar, Pakistan – a country ranked 8th in the World Climate Risk Index in 2023. The case study evaluates the Participatory Approach to Modelling Community Resilience with three stakeholder groups, Academics, Practitioners and Community members working on local resilience issues.

The first phase of the research uses Systems Thinking to customise the CDR framework according to stakeholder needs. Phase 1 uses 19 interviews to develop Causal Loop Diagrams of resilience issues to determine the dimensions to include in the model and 68 Q-Sort interviews, a methodology for ranking preferences, among the three stakeholder groups for developing a Community Capacity Index to model in the case study. The Capacities Index measures the resilience levels within the community dynamically over time as the community grows or falters. Phase 2 System Design and Modelling uses System Dynamics simulation modelling to develop the model of Community Resilience, using the dimensions and capacities identified in Phase 1, and to test and validate the model using three Focus Group Discussions with 18 participants drawn from the three stakeholder groups participating in the case study.

The SD model simulated three scenarios in the case study community to investigate the impact of disaster magnitude, relief delivery duration, and investment in adaptive capacity levels on community resilience over a one-year period. The three scenarios showed that improving communities' adaptive capacity can improve overall system resilience through different pathways: building physical infrastructure such as retention ponds, debris clearance to keep the waterways clear, and building up local capacity for preparedness and mitigation through training or increasing funds for preparedness and mitigation. This study's adaptable framework and participatory modelling approach demonstrate how greater stakeholder engagement in selecting the resilience indicators can better understand the local context of communities' risks, contribute to better intervention design, and improve mitigation and preparedness strategies.

• Thesis Type: Thesis
• Deposit Date: Jun 21, 2024
• Publicly Available Date: Jul 29, 2024
• Award Date: Jun 28, 2024