
Despite her nickname of 'Mother' Nature, it has long been understood that sometimes, in some places, she can show a less maternal face: earthquakes, volcanoes, tsunamis, drought, tornados, winter storms, forest fires, floods… are events which many of us may have to face. The Industrial era has added other threats such as chemical or nuclear leakage or dam failures. Such incidents occur daily around the globe and all too often the consequences can be severe in terms of loss of life and damage to or destruction of property.
Early Warning Systems to warn the population in the event of one of these natural and industrial disasters have evolved over the years: The basic functionalities of such systems consist of (1) detecting the event and (2) quickly warning the people. Some dedicated systems have been developed and deployed for volcanoes, earthquake and tsunamis; the detection element is not perfect, and further studies still have to be performed, but they have proven to be effective in many situations. Industrial risks, resulting from human activities are more easily detected, and where systems exist, the early warning of the population has proved to be efficient. However, there are still many examples where an incident can be detected, but there are no means to warn the people at risk.
Early Warning, is to contact the population as soon as possible in case of a major incident which may impact them: to be efficient however, this works best if people are well prepared and trained to react to the warning messages they receive. Awareness of potential threats and of the actions to be carried out in case one of them occurs are key requirements to make Early Warning systems effective. Moreover, the infrastructures have to be built to reduce the impacts of the incident (such as shelters for hurricanes, evacuation routes for volcanoes…). Thus, the foundation for Early Warning is effective preparation.
However, early warning systems monitor one threat and they alert the population in a small area. There are dedicated systems for tsunamis with earthquake sensors, and usually sirens installed along the sea shore. Around chemical plants, warning systems are installed which are able to warn people a few kilometres around the plant.
Given these intrinsic problems, the enhancement of the quality of the information provided by the sensors and the efficiency of the sirens network will still not solve all the problems:
- A disaster may be bigger than planned for in the contingency procedures, and the threat may expand far beyond the area where dedicated warning systems are installed. For instance, the Chernobyl explosion released radioactive material over most of Europe. Thus, multi-country aspects have to be solved.
- Multiple hazards may occur at the same time in the same area, and their combination may not be detected, or even if they are, their combined impact may not be evaluated correctly: for instance, in the case of a high-speed wind blowing over a chemical plant where toxic gas is diffused into the atmosphere. Thus, multi-hazards aspects have to be addressed.
- An opportunity to expand the area where warning messages are received is by the use of mass-media telecommunication or information systems (TV, mobile phone…). Another enhancement plans to use several of these means in parallel to reach more people, wherever they are and whatever they are doing. Thus, multi-channel aspects are seen as a key enhancement.
Being warned in time usually means being able to reduce the impacts of the incident on population and property, but these impacts will not be eradicated completely: the quick reaction of the authorities to evacuate, to provide first-aid, to secure areas and to organise long-term operations are key points in damage limitation. This starts by authorities being informed about the initial effects of the incident, and more generally on the situation. Rapidly deployable networks for first responders are one of the technical solutions to reduce the impacts of disasters on population and property.
Figure 1 : The three-phase disaster time model
