Early Warning is one of the most important components of Disaster Risk Reduction – and one of the most successful!

In this blog to mark the International Day of Disaster Risk Reduction (October 13), HSC Coordinator Tom Ansell dives into the role of ‘Early Warning’ systems and policies as part of Disaster Risk Reduction initiatives. They fit within greater DRR programming to make sure that people are warning in advance and can take precautions, or other measures, to prepare for an upcoming shock or hazard. The 2004 Asian Tsunami highlighted the need for more early warning systems for countries with Pacific and Indian Ocean coasts – these systems were triggered earlier this year after an 8.8 magnitude earthquake off the coast of Russia.

Photo Credit: UNDRR

Introduction – DRR on multiple levels

Managing the risks to people’s lives and livelihoods before, during and after a disaster (whatever the cause) requires looking beyond just ‘responding to a disaster’. Since the 1990’s, and the UN’s ‘International Decade for Natural Disaster Reduction’, attitudes towards the disaster cycle have matured and within many emergency management agencies there is some reference to several ‘phases’ of a disaster in a ‘cycle’. For example, the Australian Emergency Management Agency refers to the ‘prevention, preparedness, response, recovery’ phases (now considered a bit old fashioned!). The ‘risk management approach’ is currently the most modern frame for disaster preparation for and responding to a disaster, which focuses on risks rather than timelines: “establish contexts, identify risks, analyse risks, assess risks, treat risks” – and repeat!

Risks are themselves a mixture of hazards/shocks (something that might cause a disaster), vulnerability (socioeconomic conditions that might exacerbate the hazard), exposure (how close people, livelihoods, etc, are to the hazard), and coping capacity (the resources and protocols in place to manage risk).

It’s all put together as the following formula:

Risk = Hazard x Vulnerability x Exposure
Coping capacity

To make a risk assessment, practitioners consider the severity of a risk, and the likelihood of it occurring, to make a compound ‘score’. Disaster Risk Management involves activities, policies, procedures and so on to mitigate risks (DRR), often by reducing vulnerabilities or exposure, or by increasing coping capacity.

So a systematic approach to DRR will approach all of these various components. It’s easy to see why knowing about a hazard early might make it easier to protect people and livelihoods. Or, in technical language: Early Warning increases coping capacity, by giving more time to prepare for a hazardous situation (by taking anticipatory action), thereby decreasing exposure! Within the humanitarian sector, programmes and interventions around this are usually referred to as Early Warning, Early Action (EWEA). Ideally, these activities should be contextual, appropriate, ‘people-centred’, community-based and/or managed, and inclusive.

What do Early Warning systems look like?

What an early warning system looks like is completely dependent on the context and hazard in question. The logic behind most early warning systems, though, is monitoring a hazard (say, a river level) and then triggering information sharing and next steps once a certain level of immediacy has been reached.

For example, the Syria Civil Defence (the White Helmets) co-developed an app-based early warning system for airstrikes, military activities, and knock-on emergencies during the Syrian civil war. A central command room processes incoming reports of, say, jets taking off from an air base, and then sends a warning via app and SMS to mobile phones in the region, with instructions to take cover. Prior to this system, early warnings of air strikes were spotted by people in watch-towers, and communicated by word of mouth and a walkie-talkie radio network, which led to delays in warning people about incoming danger. This app-based system could be used to warn of other incoming hazards, for example a particularly violent winter storm, upstream flooding, or seismic activity. The Netherlands utilizes a similar system for all manner of hazards, NL-Alert.

But whilst tech-enabled Early Warning systems have grown in the last 15 years, there are plenty of contexts where word-of-mouth, radio broadcasting, or an emergency network (the ‘telephone tree’ method) is the most effective way of getting information to people in time to evacuate, take precautions, or otherwise prepare. For example, if there is a river close to a community that periodically floods, people ‘upstream’ can monitor river levels, and spread the words to communities ‘downstream’ if there is particularly high water. This is also the case for knowledge passed down through the generations: if a particular species of animal usually leaves just before a violent storm, for example, this can serve as the ‘trigger’ to warn people.

Early Warning systems are equally useful for slow-onset disasters. An example here is part of the Productive Safety Net Programme (PSNP) in Ethiopia, which is designed to reduce the risk of famine during poor harvests by offering cash-for-work and cash transfers for people that mainly rely on local agriculture for income and to maintain access to food. The programme is ‘activated’ when drought has been detected for a certain number of months, depending on the region.

Early Warning for Tsunami since 2004

On 26 December 2004, a large underwater earthquake off the coast of Indonesia triggered 50-metre high waves that killed over 220,000 people, as well as leaving more than 2 million people homeless in 15 countries. At the time, Indonesia was not considered an especially high-risk country for tsunami, meaning that the at the time there was little monitoring of underwater seismic activity, or sea level surface. The Pacific Tsunami Warning Centre was only able to find out about the impending disaster through internet news stories about devastation in Thailand (itself also unprepared for underwater earthquakes or tsunami at the time), and so couldn’t warn countries with Indian Ocean costs in time.

Following the destruction of the 2004 tsunami, national governments, UN agencies, and NGOs all put renewed efforts into reducing exposure to tsunami and oceanic hazards. At an intergovernmental level, the tsunami sped up development and adoption of the Hyogo Framework for Risk Reduction (now surpassed by the Sendai Framework). At a national level, Thailand created a multi-hazard oceanic early warning system, with tsunami detection buoys and information sharing with Indonesian, Australian, and Indian detection buoys. These signals are sent to a national coordination centre, whereupon various operating procedures are activated. A warning is then broadcast in five languages by fax, SMS, through ‘warning box’ speakers, radio relay towers, public tannoys, social media and through radio and TV warnings. The system will be developed further to give direct to mobile phone warnings in the coming decades.

Indonesia, meanwhile, has developed a network of 553 seismographs, as well as using oceanographic modelling and local hazard mapping for low-lying coastal areas. Once this network detects seismographic activity, procedures include public announcements, vertical evacuation routes, and evacuation signage.

Outside of the Pacific region, the destruction of the 2004 tsunami impelled Caribbean governments to put together the Tsunami and other Coastal Hazards Warning System for the Caribbean Sea and Adjacent Regions (ICG/CARIBE EWS), a multi-hazard coastal early warning system, and since 2011 have integrated the CARIBE WAVE exercise, which simulates a tsunami or underwater earthquake evacuation. In 2024, over 700,000 people were ‘evacuated’ during the exercise.

Unfortunately, well-functioning early warning systems are not enough to completely mitigate the risk of a large disaster, as the 2011 Tohoku earthquake and tsunami demonstrates. More than 20,000 people died during the quake and 39-metre tsunami wave, with knock-on effects including the Fukushima Daichi nuclear accident, despite Japan having a well-developed tsunami early warning system. The worth of all of this preparation work was evident this July, though. An 8.8 magnitude offshore earthquake occurred off the coast of Russian Kamchatka, triggering early warning systems and causing precautionary policies in several countries (including Japan, Indonesia, Russia, and China), including evacuations. The earthquake did cause tsunami-like waves, though did not have the same destructive force as the 2004 tsunami.

Conclusion – early warning as part of a multi-level DRR framework

Early warning systems, then, are a key part of reducing disaster risk, especially to climactic and environmental hazards. But we shouldn’t equate that with completely eradicating risks, or indeed think that early warning is the only part of risk management and reduction that should be concentrated on. Early warning systems work best as part of a full multi-level DRR framework, with training and education on detecting hazards, well-developed protocols for early action, evacuation, or other mitigation measures; and a general policy to reduce societal vulnerability through equitable policies, reducing socio-economic inequalities, and strong governance structures.

Opinions expressed in Bliss posts reflect solely the views of the author of the post in question.

 

About the Author

Tom Ansell

Tom Ansell is the coordinator and programme manager of The Hague Humanitarian Studies Centre, and the Coordinator of the International Humanitarian Studies Association. He has a study background in religion and conflict transformation, as well as an interest in disaster risk reduction, and science communication and societal impact of (applied) research.

 

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1 Comment
  • Name Said LOUKIL
    14 October 2025

    Les systèmes d’alerte précoce sont essentiels mais doivent être intégrés à une stratégie globale de réduction des risques. L’intelligence artificielle (IA) peut grandement améliorer leur efficacité, tout en soulevant des défis à surmonter.
    Voici une synthèse des avantages, inconvénients, et améliorations possibles grâce à l’IA dans les systèmes d’alerte précoce (SAP) :

    ✅ Avantages des systèmes d’alerte précoce
    – Sauvegarde des vies et des biens : En anticipant les catastrophes (cyclones, inondations, sécheresses), ils permettent des évacuations et des mesures d’atténuation.
    – Réduction des pertes économiques : Moins de dégâts matériels grâce à une meilleure préparation.
    – Renforcement de la résilience communautaire : Les SAP favorisent la prise de conscience et la mobilisation locale.
    – Adaptabilité multi-risques : Ils peuvent être configurés pour divers types de dangers (géophysiques, climatiques, sanitaires).

    ⚠️ Inconvénients et limites actuelles
    – Inégalités d’accès : Certaines communautés n’ont pas les moyens technologiques ou linguistiques pour recevoir les alertes.
    – Fiabilité des données : Les systèmes peuvent manquer de précision ou être basés sur des données incomplètes.
    – Réponse humaine inadéquate : Même avec une alerte, les réactions peuvent être mal coordonnées ou trop lentes.
    – Dépendance technologique : Risque de défaillance si les infrastructures sont touchées par la catastrophe elle-même.

    🤖 Améliorations possibles avec l’intelligence artificielle
    – Prédiction plus fine et en temps réel : L’IA peut analyser des volumes massifs de données météorologiques, géospatiales et sociales pour anticiper les risques avec plus de précision.
    – Personnalisation des alertes : Grâce au traitement du langage naturel, l’IA peut adapter les messages d’alerte à la langue, au niveau d’éducation et au contexte local des populations.
    – Détection précoce automatisée : L’IA peut surveiller en continu les capteurs, images satellites et réseaux sociaux pour détecter les signaux faibles d’un danger imminent.
    – Optimisation des protocoles d’évacuation : En croisant les données de mobilité, d’infrastructure et de densité humaine, l’IA peut proposer des plans d’évacuation plus efficaces.
    – Retour d’expérience intelligent : L’IA peut analyser les réponses passées pour améliorer les futurs protocoles et renforcer la résilience collective.

    🔄 Vers une approche intégrée
    L’alerte précoce ne doit pas être isolée : elle doit s’inscrire dans une stratégie de réduction des risques de catastrophe (RRC) incluant :
    – Formation communautaire et éducation à la détection des dangers.
    – Protocoles clairs et inclusifs pour l’action rapide.
    – Politiques équitables pour réduire la vulnérabilité sociale.
    – Gouvernance participative et intersectorielle.
    Said LOUKIL Retraité, TOUJOURS, engagé….

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