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Institute of Hazard, Risk and Resilience
IHRR building

Institute of Hazard, Risk and Resilience (IHRR) Themed Mini-Conference: 

Text to left describing conference title, timings, and then people and representations of models, data

Presenting and communicating models and uncertainty with respect to hazard, risk and resilience

Monday 3rd November 2025

  • 14:00 – 16:00 - Engineering E005 & Teams (Register here for Teams Online)

  • 16:00 – 17:00 - networking in the IHRR Hub, W246

Summary: The Institute of Hazard, Risk and Resilience (IHRR) welcomes you to this University-wide event, which will explore the presentation of and communication of models, data, and uncertainty across disciplines and audiences in the context of hazard, risk, and resilience. It will consider quantitative models, visualisations, narratives, and artistic interpretations and how they are presented and shape understanding and decision-making, as well as public trust in science. The talks and discussions will be designed to be accessible and engaging for an interdisciplinary audience, encouraging dialogue between colleagues from the sciences, social sciences, and arts and humanities on how uncertainty is represented, perceived, and translated into action.

14:00 – 14:10: Welcome and scene setting by Bruce Malamud, Director, IHRR 

14:10 – 15:00: 6 minute presentations by panel A speakers and panel A discussion

1. Dr Ivo Pink (ECOMIX Postdoctoral Research Associate, Dept of Geography) "Flood hazard modelling projections for the Karnali River"

2. Dr Ellen Robson (Postdoctoral Research Associate, IHRR) "From slope stability models to design guidelines for road cut slopes in Nepal"

3. Prof Ian Vernon (Professor, Dept of Mathematical Sciences) "Uncertainty quantification"

4. Prof Fausto Guzzetti (Professor of Hazard and Risk, IHRR) "On the communication of probabilistic landslide forecasts" 

Q&A/comments: amongst panel A speakers and then from all participants (Chair: Prof Bruce Malamud)

15:00 – 15:50:  6 minute presentations by panel B speakers and panel B discussion

5. Dr Qian Zhang (Assistant Professor in Engineering Management) "Models for resilient construction supply chain management and construction workers’ health and safety convenience"

6. Dr Alex Brown (Associate Professor in Late Medieval and Early Modern British History, Dept of History) "Modelling historic pandemics: Understanding the Black Death in Medieval England"

7. Prof Jochen Einbeck (Professor, Dept of Mathematical Sciences)  "Statistical modelling in radiation dosimetry — navigating science, notation, and conventions"

8. Prof Stavros Zenios (Professor in Operations Management and Finance, Business School) "Communicating climate models for economic analysis"

Q&A/comments: amongst panel B speakers and then from all participants (Chair: Dr Ellen Robson)

15:50 – 16:00: Closing

16:00 – 17:00: Coffee and Tea (IHRR Research Hub Room, Room W246--first room on left after you enter the IHRR/Geography building) 

Suggested Reading

  • Copernicus climate atlas. Available at: https://atlas.climate.copernicus.eu/atlas: This dashboard visualises the climate projections of the latest generation of climate models and is an example of how the Copernicus program communicates uncertainty.
  • Doyle, E.E., Johnston, D.M., Smith, R. and Paton, D. (2019) Communicating model uncertainty for natural hazards: A qualitative systematic thematic review. International Journal of Disaster Risk Reduction, 33, pp. 449–476. https://doi.org/10.1016/j.ijdrr.2018.10.023
  • Dhungana, A., Doyle, E.E., Prasanna, R. and McDonald, G. (2025) From scientific models to decisions: exploring uncertainty communication gaps between scientists and decision-makers. Environment Systems and Decisions, 45(3). https://doi.org/10.1007/s10669-025-10039-w
  • Emery, A.K. (2014) How to visualise qualitative data [Online] Available at: https://depictdatastudio.com/how-to-visualize-qualitative-data/  [Accessed 29 October 2025]
  • Fathollahzadeh, A., Salmani, I., Morowatisharifabad, M.A., Khajehaminian, M.R., Babaie, J. and Fallahzadeh, H. (2023) Models and components in disaster risk communication: A systematic literature review. Journal of education and health promotion, 12(1), 87 https://doi.org/10.4103/jehp.jehp_277_22 
  • Freihardt, J. and Buchs, R. (2024) Framing effects in disaster risk communication: the case of coastal erosion in the United States. Environmental Hazards, 23(3), 287-305, https://doi.org/10.1080/17477891.2023.2280691
  • Mondini AC, Guzzetti F, Melillo M (2023) Deep learning forecast of rainfall-induced shallow landslides. Nature Communications 14, 2466. https://doi.org/10.1038/s41467-023-38135-y 
  • Mondini AC, Guzzetti F, Melillo M, Pievatolo A (2025) Short to long term space-time prediction of rain-induced landslides under uncertainty. Science of the Total Environment 984, 179453. https://doi.org/10.1016/j.scitotenv.2025.179453
  • Spiegelhalter, D., Pearson, M. and Short, I. (2011) Visualising uncertainty about the future’ Science, 333(6048), pp. 1393–1400. DOI: https://doi.org/10.1126/science.1191181
  • Taylor, F.E., Millington, J.D., Jacob, E., Malamud, B.D. and Pelling, M. (2020) Messy maps: Qualitative GIS representations of resilience. Landscape and Urban Planning, 198, 103771, https://doi.org/10.1016/j.landurbplan.2020.103771
  • The IPCC (2022) Policy Summary, https://doi:10.1017/9781009325844.001. [This report includes good examples of how scientific findings are summarised and communicated to policymakers. It is quite large (300+ pages), but looking at a few sections may provide some useful insights.]
  • The R Graph Gallery (2025) Homepage [Online] Available at: https://www.r-graph-gallery.com/  [Accessed 29 October 2025]. This is an excellent source for how data/models might be visualised in many different ways.
  • Wilke, CO (2021) Fundamentals of Data visualisation [Online] Available at: https://clauswilke.com/dataviz/  [Accessed 29 October 2025]
  • van der Bles, A.M., van der Linden, S., Freeman, A.L.J., Mitchell, J., Galvao, A.B., Zaval, L. and Spiegelhalter, D.J. (2019) Communicating uncertainty about facts, numbers and science, Royal Society Open Science, 6(5), 181870. https://doi.org/10.1098/rsos.181870 
  • Verdinelli S and Scagnoli NI (2013) Data Display in Qualitative Research. International Journal of Qualitative Methods 12: 359-381. [Available online at: https://journals.sagepub.com/doi/pdf/10.1177/160940691301200117]