Engaging diverse stakeholders: practical participatory tools for exposure data collection

Extreme natural events, including earthquakes, tsunamis and floods, can significantly impact communities, causing physical damages, casualties and socio-economic disruptions. In order to mitigate or reduce disaster risk, it is paramount to identify the exposed assets prone to different hazards, and their characteristics.  Exposure assessment consists in collecting the characteristics of population and tangible and intangible assets,  including, but not limited to, buildings and infrastructure. However, exposure is often developed based on the available data (e.g. population and building  census), and does not account for local and expert knowledge held by societal stakeholders. To reduce disaster risk, it is therefore of utmost importance to engage diverse stakeholders so that they can contribute with their expertise. This work  discusses three different methods that involve a wide range of stakeholders in participatory activities and leverage exposure-related knowledge: semi-structured interviews, crowdsourcing and citizen science and capacity development workshops. Each method allows collecting different data types using specific tools, such as semi-structured interviews, questionnaires and interactive web interfaces, to collect exposure-related information, which can be adapted to the specific context. Practitioners, academics, policymakers and emergency managers were involved in exposure development activities at a national and regional scale. Residents, civil protection officers and school students contributed to identifying dominant building typologies collecting information on single buildings. The described methods allow gathering expert and local knowledge held by societal stakeholders, which is often missing in existing exposure datasets (e.g. building census, land use maps). These methods can accommodate different building features relevant for specific hazards (e.g. shape regularity) and be extended to other exposed assets (e.g. infrastructure). Context-dependent storylines were also developed for selected areas prone to floods and coastal hazards, based on the historical, geological and geographical evidence, and presented to societal stakeholders during dissemination activities. Through storylines, we highlight the temporary evolution of exposure identifying potential adaptation and mitigation strategies. We discuss how a wide range of societal stakeholders can contribute to exposure development if enabled in structured, tailored participatory approaches. For each method we identified challenges and opportunities of interacting with societal stakeholders for disaster risk reduction purposes. We also envisage the benefits of integrating the described methods towards a collaborative stakeholder interaction framework for exposure development. This research is a contribution to the project PRIN-PNRR project SMILE: Statistical Machine Learning for Exposure development, funded by the European Union- Next Generation EU, Mission 4 Component 1 (CUP F53D23010780001).