How ancestral insights can strengthen early warnings
Four practical actions to integrate indigenous and local knowledges into early warning system monitoring and forecasting
For generations, many Indigenous peoples and local communities have developed localized methods to antici
Four practical actions to integrate indigenous and local knowledges into early warning system monitoring and forecasting
For generations, many Indigenous peoples and local communities have developed localized methods to anticipate, prepare for, and respond to disasters. Drawing on deep traditional knowledge and experience of their surroundings, they use ecological, hydro-meteorological, and celestial indicators to monitor and forecast environmental changes. These traditional approaches have become central components of some effective early warning systems (EWS), especially when integrated with scientific methods. This powerful combination of traditional and scientific knowledge is already proving successful across the globe.
In Vanuatu, the world's most disaster-prone nation, communities are turning to their ancestral wisdom to build resilience. Facing cyclones, volcanic eruptions and earthquakes every year, Vanuatu's people have relied for centuries on natural signs to predict danger. Traditional knowledge holders observe changes in wind patterns, cloud formations, and animal behavior. This traditional knowledge is now being integrated with modern science through tools like the ClimateWatch App. Local Civil Society Organizations across Vanuatu use the app alongside Provincial Traditional Knowledge calendars to collect valuable environmental data. Through this initiative, communities can systematically document and monitor traditional indicators including animal behavior, plant changes, and celestial signs to enhance early warning capabilities.
In Indonesia's Simeulue Island, "smong" is a traditional warning system for tsunamis, shared in local songs and stories. The word specifically describes the sequence of tsunami warning signs: first an earthquake, then the sea receding, followed by a giant wave. This knowledge originated after a devastating tsunami in 1907 and was preserved through oral traditions. The power of this traditional knowledge was proven during the 2004 tsunami when a 9.2 magnitude earthquake struck and the sea receded, all 70,000 Simeulue residents recognized these ancestral warning signs of smong and immediately fled to higher ground. While devastating waves claimed many lives across the Indian Ocean, the people of Simeulue survived thanks to their preserved traditional warning system.
These traditional methods deliver concrete results saving lives, protecting crops, and building climate resilience. Furthermore, by recognizing and incorporating trusted sources of wisdom, an integrated system can gain the confidence and acceptance of the local community it serves. Yet despite their vital importance for community-based solutions, these important sources of knowledge are often overlooked in early warning systems on a global scale.
To address this gap, UNDRRs Handbook on the use of risk knowledge for multi-hazard early warning systems 2024 offers the four practical actions below to successfully integrate local and indigenous knowledge into monitoring and forecasting activities.
1. Inform
Introduce scientific monitoring and forecasting methods to the local population.
Communities must understand how their local knowledge can validate, support and strengthen forecasting models. This knowledge sharing should emphasize the mutual benefits of combining modern and local knowledge to predict hazards.
2. Consult
Hold key informant interviews with local knowledge holders, community leaders, and local disaster management council members to better understand existing local knowledge systems for hazard monitoring and forecasting.
Community consultations through focus group discussions can reveal key insights on precursors to specific hazards. For example, in Southern Africa, drought forecast data has been collected from local knowledge on trees and plants through structured questionnaires at household level. Convenings such as Regional Climate Outlook Fora enable regional experts and local/national practitioners to discuss scientific forecasts.
3. Involve
Use crowdsourcing platforms to harness community involvement in monitoring hazards and reporting environmental variables.
In Tanzania, community disaster management committees or local volunteers in the Global Facility for Disaster Reduction and Recovery project utilize WhatsApp and Telegram to share real-time flood information and coordinate responses. Malawi uses the Weather Chasers WhatsApp group to gather local knowledge on weather disasters by encouraging community members to share real-time weather observations, which helps verify forecasts and improve EWS. Participatory modeling, such as in Dar-es-Salaam's urban flood management, engages communities directly. Local knowledge holders contribute to defining impact thresholds, ensuring EWS alignment with local contexts.
Local communities should be engaged through an interactive modelling process. In Dar-es-Salaam, Tanzania, local populations are directly engaged in participatory mapping efforts, resulting in more accurate flood models and a more resilient society. Local knowledge holders should also contribute to defining impact thresholds, ensuring EWS alignment with local context.
4. Cooperate
Integrate exposed communities into the process of identifying hazard indicators, drawing on their environmental and scientific knowledge.
Integrated systems depend on cooperation between communities using local forecasting systems and scientific communities. By proposing multiple evidence-based forecasting approaches, systems can foster community ownership and trust.
Building resilient futures by integrating local and Indigenous Knowledges
To draw on all relevant knowledge systems to protect communities, policymakers must recognize local and Indigenous Knowledges as critical resources for disaster resilience. This means providing dedicated funding for community-led early warning initiatives and fostering partnerships between scientific institutions and local knowledge holders.
With climate change set to bring even more unprecedented challenges, this combination of traditional wisdom and modern science will be increasingly vital for effective disaster risk reduction. Success stories worldwide demonstrate that when local knowledge is respected and incorporated, early warning systems become more sustainable, trusted, and impactful, creating stronger, more resilient communities for generations to come.