Natural Hazards

Hazard management

The bad, the good and the unpredictable: living with volcanoes / part 2

The bad, the good and the unpredictable: living with volcanoes          / part 2

Before continuing, if you haven’t read it yet, catch up with the first part of this blog article by clicking on this link.

The good

Living with volcanoes is not all bad. Volcanoes provide a wealth of natural resources in the form of building materials, hot springs, freshwater and fertile soil. However, there are more hidden aspects, which was the focus of a recent collaboration with an archaeologist. We believe that volcanoes and their landforms provide “cultural services”, which is a component defined by the UN Millennium Ecosystem Assessment as the cultural benefits we gain from ecosystems. These components are the following:

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The bad, the good and the unpredictable: living with volcanoes / part 1

The bad, the good and the unpredictable: living with volcanoes     / part 1

Humans have existed and lived alongside volcanoes for as long as we have been on the planet. For some, this has been beneficial and often, in fact, we can see how indigenous knowledge finds a sustainable approach living with them. However, in some cases, societies cannot cope and are overwhelmed with volcanic eruptions. 

There are many examples from archaeological studies dealing with how ancient civilisations, successfully or unsuccessfully, lived with volcanoes. On one hand, for example, Pre-Colombian villages in Costa Rica were found to be the most resilient to the eruptions of Arenal volcano, managing to cope and survive with many eruptions. The villages were simple societies with egalitarian rules (where people are viewed as having equal rights and opportunities). This meant that they coped faster because everyone had the same duties and rights and were able to help each other without waiting for a ruler to do something for them. On the other hand, more complex chiefdoms in Central America struggled to cope with these events as they had a greater reliance on the built environment, competitive and sometimes hostile political environments and greater population densities [1, 2]. 

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How can remote sensing and wavelet transform unravel natural and anthropogenic ground motion processes?

How can remote sensing and wavelet transform unravel natural and anthropogenic ground motion processes?

Underground energy storage and gas storage in aquifers

In the context of energy transition, massive energy storage is a key issue for the integration of renewable sources into the energy mix. Storing energy in the underground can lead to larger-scale, longer-term and safer solutions than above-ground energy storage technologies. In particular, natural gas storages are designed to address different needs, like a strategic natural gas reserve, the regulation of gas supply and the answer to a seasonal peak heating or electricity demand. Energy companies routinely store gas in underground reservoirs known as “gas aquifers”, which then become gigantic natural tanks for injecting and extracting gases for energy needs. The natural gas is compressed and injected through wells into selected reservoirs, usually constituted of sand layers containing water, which is automatically forced out. The gas is then extracted from the same wells and the water can naturally flow back into the sand, maintaining equilibrium. Natural gas is stored from May to September when the demand is lower and withdrawn from October to April when the demand is higher.

Figure 1 – Location map showing a Sentinel-1 acquisition (2016) in Southwestern France (Aquitaine Basin) (colour image), a 25 km cell used by SMOS satellite (black square) that contains the reservoir isobaths of a gas storage site (red lines).

Integrated monitoring of a gas storage site

For risk prevention and environmental protection purposes, it is essential to check the integrity of the natural reservoirs used for underground storage and how they respond to the annual natural gas injection and extraction cycles. [Read More]

Mapping population dynamics to advance Disaster Risk Management

Mapping population dynamics to advance Disaster Risk Management


Today we have the honour to introduce Sérgio Freire as our guest. Sérgio Freire is a Geographer, currently working as Scientific/Technical Project Manager at the European Commission’s Joint Research Centre (JRC), Directorate E. Space, Security and Migration, Disaster Risk Management Unit, based in Ispra, Italy. His main activities focus on developing applications of the JRC’s Global Human Settlement Layer (GHSL) in the context of disaster exposure, risk, and vulnerability analysis, including modelling population distribution at a range of spatial and temporal resolutions. Current activities also include global mapping and characterisation of human settlements, and developing satellite-based indicators to support monitoring of Sustainable Development Goals.



  1. When we think about disasters, we firstly mean natural hazards characteristics. However, potential harm comes even from vulnerability and exposure. Can you please explain to us what these elements are and which role they play in the risk equation?


In fact, natural hazards are ‘normal’ acts of nature that are part of the living planet that is Earth.

These only make the news and become disasters when they affect people (or property, systems) that display vulnerabilities to those specific phenomena. A strong earthquake in the middle of the Sahara desert may have little or no impacts due to scarce population and settlements, i.e., the absence of exposure. On the other hand, an earthquake of comparable magnitude occurring in cities of dissimilar countries may cause very different impacts and casualties due to the divergent structural vulnerabilities of built-up structures. However, for extreme events or hazards above a certain magnitude, exposure is a major driver of impacts.

Figure 1. Evolution of global population exposed to the highest seismic hazard, by decade. Bars refer to the total population in Modified Mercalli Intensity levels VIII to XII (right axis) and lines refer to percent population change relative to the previous period (left axis) (Source: Freire S., D. Ehrlich, S. Ferri, 2015. Population Exposure and Impacts from Earthquakes: Assessing Spatio-temporal Changes in the XX Century. Computer Modeling in Engineering & Sciences (CMES), SI: ‘Modeling of dangerous phenomena for risk mitigation’. Vol.109(2): 159-182)


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