Building Urban Flood resilience in Kibera, Nairobi
This project (2015-2016) worked with residents of Kibera, local and national authorities and civil society organisations to build the...
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Tactic 19: Participatory Flood Modelling
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Participatory flood modelling (PFM) brings together science and modelling approaches with the knowledge and experiences of stakeholders, fostering participatory decision-making when addressing complex social-ecological challenges. Rather than solely relying on expert-driven data collection, PFM focuses on collaborative discussions, where learning happens through dialogue. Stakeholder involvement can take the shape of active participation, where stakeholders work together to frame problems, set priorities, formulate options, and evaluate the model. The models are co-created through an iterative learning process between modellers and stakeholders.
In Kenya, rapid urbanisation and climate change are increasing flood risk, in a way that disproportionately affects the poorest and most vulnerable communities living in informal settlements. In these settlements, flooding is just one of many climate-related risks, but it is interconnected with larger issues such as poverty, public health, livelihoods, urban fragility, and the social contract (Mitra et al., 2017). In many cases, the high frequency of flooding limits the ability of residents to move beyond just coping with risk towards improving their living conditions (Mulligan, 2019).
Flooding is especially challenging in informal contexts where residents are facing a participation gap in flood management efforts. These neighbourhoods often have contested land ownership, making it difficult for communities to engage in formal decision-making processes. Addressing flood risks in such contexts requires solutions that go beyond top-down, technical fixes towards combining expert knowhow with local knowledge and experience.
The participatory flood modelling approach can support negotiation and dialogue between different stakeholders in order to incorporate community-level information on various hazards, and implement flood management in a consultative, collaborative manner. By integrating the knowledge and experiences of informal settlement residents, it can help create solutions that reflect their specific needs.
The Challenge
Bridging the gap between residents and other stakeholders can foster connections for ongoing review of flooding to inform future flood modelling work and flood risk management.
Stakeholder involvement enables better understanding of the specific context, informing efforts towards holistic flood risk management for more safe and resilient neighbourhoods.
PFM fosters participatory decision-making by working together to frame the problem, set priorities, formulate options, and evaluate the model.
PFM integrates flood risk management to cater for communities which are disproportionately affected by flood risk.
PFM helps bridge the participation gap in flood management to incorporate community knowledge and experience to better address their needs.
The stages of modelling for consideration of the timing of participation, adapted from Basco-Carrera et al. (2017)
Key concepts
Participatory flood modelling (PFM) engages local communities, stakeholders, and experts in the process of developing models to understand, predict, and manage flood risks. It places the focus on collaboration and shared decision-making, ensuring that the voices of those directly affected by flooding are heard. The approach aims to engage stakeholders at key stages throughout the modelling process which includes the in the following stages:
(a) data collection
(b) model definition
(c) model construction
(d) model validation/verification
(e) model use
This approach is especially valuable in vulnerable areas, such as informal settlements, where local residents are often the most affected by floods yet may be excluded from formal decision-making processes.
1. Stakeholder Involvement: PFM actively involves a wide range of stakeholders, including community members, local governments, NGOs, and technical experts. The goal is to integrate local knowledge with scientific data to create a more comprehensive understanding of flood risks for both the technical modelling and subsequent design/ planning process, while engaging institutional actors responsible for FRM and DRM.
2. Collaborative Decision-Making: Unlike traditional flood modelling, where experts typically lead the process, PFM applies collective deliberation. Stakeholders work together to identify problems, set priorities, explore solutions, and evaluate models. This results in shared ownership of both the process and the outcomes.
3. Integration of Local Knowledge: Community members have valuable, place-based knowledge about local hazards and vulnerabilities. PFM incorporates this information, ensuring model relevance and improving accuracy for the specific area. This forms the basis for context-specific solutions which are tailored to reflect the social, environmental, and economic realities of the area involved.
5. Building Capacity: Through PFM, stakeholders, including community members and local institutions, gain knowledge and skills in flood risk management. This capacity-building aspect empowers local people to take active roles in managing and mitigating flood risks over the long term.
6. Co-production of Models: The models in PFM are co-created by both the technical experts and the community. This collaborative production ensures that the models not only rely on technical data but also reflect local experiences and priorities, making them more usable and understandable for the affected communities.
7. Building Communication and Trust: By involving various stakeholders, PFM fosters better communication and trust between communities and institutions. This is crucial in ensuring that flood management solutions are accepted and effectively implemented.
A woman walking with her guide in the informal settlement
Ref: AT2030
How To
Identify key stakeholders for the modelling process.
Define the geographic scope, watersheds and watercourses to be captured in the modelling process:
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Collect resident experiences of flooding: Collecting evidence from residents on previous floods helps identify locations and causes of high flood risk and direct the course of the study. For example, formal and informal infrastructures which impede flow during heavy rains can be pointed out for study.
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Survey of bridges and inline structures: Conducting online surveys supported by local residents which can be completed on handheld devices, to photograph and answer questions to classify, dimension, and geo-tag key hydraulic structures and obstructions including bridges, culverts, pipelines and other major obstructions along the main watercourses. This can enable rapid and accurate representation of structures in the flood model.
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Involve stakeholders, including government institutions, to inform the evolution of the model, such as to cover further areas of interest for the analysis.
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Flood extent maps: Once the initial iteration of the flood model is complete, generate flood extent maps at various scales. These maps will serve as the basis for comparison during the verification process.
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Compare model outputs with local knowledge:
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Community workshops with local residents in flood-prone areas: Provide aerial maps that participants can use to identify familiar landmarks and recall the extent of historical flood events in their neighbourhood. Model outputs can be compared with local knowledge by overlaying the flood extent maps generated by the model with the information provided by residents during the workshops.
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Facilitate Discussion and Trust Building: Encourage participants to share their experiences and insights during the comparison process. Allow them to connect their lived experiences with the science-based outputs of the model. This step is essential for fostering trust in the model’s accuracy.
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Promote Social Learning: Use this process as an opportunity for social learning, where participants develop a deeper understanding of how physical flood risks are interconnected with social and environmental factors. Building this collective knowledge can improve confidence in both the model and future flood mitigation efforts.
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Case Studies
References
https://drive.google.com/drive/folders/1-BvFZmK-HX7f92qPnyll4Sz-BxTgNL3a
Mulligan, Joe, Vera Bukachi, Rodoula Gregoriou, Nilani Venn, Duncan Ker-Reid, Alan Travers, Juma Benard, and Luke O Olang. ‘Participatory Flood Modelling for Negotiation and Planning in Urban Informal Settlements’. Proceedings of the Institution of Civil Engineers - Engineering Sustainability 172, no. 7 (1 September 2019): 354–71. https://doi.org/10.1680/jensu.17.00020.
Kiptum, A., Mwangi, E., Otieno, G., Njogu, A., Kilavi, M., Mwai, Z., MacLeod, D., Neal, J., Hawker, L., O'Shea, T., Saado, H., Visman, E., Majani, B., & Todd, M. C. (2023). Advancing operational flood forecasting, early warning and risk management with new emerging science: Gaps, opportunities and barriers in Kenya. Journal of Flood Risk Management, e12884. https://doi.org/10.1111/jfr3.12884
Bloch, Robin; Jha, Abhas K.; Lamond, Jessica. 2012. Cities and Flooding : A Guide to Integrated Urban Flood Risk Management for the 21st Century. © World Bank. http://hdl.handle.net/10986/2241 Licence: CC BY 3.0 IGO.
Owuor, Martin Ochieng, and Donald Anthony Mwiturubani. ‘Nexus between Flooding Impacts and Coping Strategies in Nairobi’s Settlements’. International Journal of Disaster Risk Reduction 64 (1 October 2021): 102480. https://doi.org/10.1016/j.ijdrr.2021.102480.
Randa O. T., Krhoda O. George, Atela O. Joanes, and Akala Haron. ‘Review of Flood Modelling and Models in Developing Cities and Informal Settlements: A Case of Nairobi City’. Journal of Hydrology: Regional Studies 43 (1 October 2022): 101188. https://doi.org/10.1016/j.ejrh.2022.101188.
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