Cascading effects

Cascading effect research is currently at its early stage. According to Pescaroli and Alexander (2015), “Cascading effects are the dynamics present in disasters, in which the impact of a physical event or the development of an initial technological or human failure generates a sequence of events, [… linked or dependent from each other …], that result in physical, social or economic disruption. Thus, an initial impact can trigger other phenomena that lead to consequences with significant magnitudes. Cascading effects are complex and multi-dimensional and evolve constantly over time. They are associated more with the magnitude of vulnerability than with that of hazards. Low-level hazards can generate broad chain effects if vulnerabilities are widespread in the system or not addressed properly in sub-systems. […]”.

EM-DAT, the International Emergency Events Disaster Database managed by the Centre for Research on the Epidemiology of Disasters (CRED), within the Université catholique de Louvain (UCL)  has been chosen among others by the consortium for the selection and description of past crises characterized by cascading effects because of its 25-year experience in disaster data collection and management but also because its compilation process uses a wide range of sources, including UN agencies, non-governmental organizations, insurance companies, research institutes and press agencies. The data given by those different sources are compared and validated through a systematic validation process in order to ensure data quality and reliability. Additionally, the strength of that database is its standardized methodology applied over time (since the creation of the database in 1988), allowing the data to be comparable over time and space. It contains core data on the occurrence, human effects and economic impact of over 21,800 disasters in the world from 1900 to present. That global disaster database, available to the consortium and most cited worldwide (source: drr.jrc.ec.europa.eu), is globally considered by many authors and research centers the best choice among the available database (Kelman, 2001).

On that basis, past crisis characterized with cascading effects have been selected following a strict multi-criteria selection methodology. Only crises happening between 1986 and 2015, having at least either one associated hazard or one physical disruption of the grids and service networks at risk (power, communication, water/sanitation network) and characterized by at least one social disruption (casualties, injured, homeless, affected) or by an economic disruption (expressed in US$ economic losses) are susceptible to be taken into account in Snowball.

Two separated samples have been highlighted: European events and non-European events; as their respective geographical location highly influence a wide range of factors such as meteorological and socio-economic factors having themselves a strong influence both on the occurrence, type of disasters, and chain of effects caused by the disasters. In Europe, a total of 93 country-events met the selection criteria while there were 1916 country-events for the non-European events selection (N.B. In EM-DAT, events are recorded by country. If an event like the extra-tropical storm Xynthia (2010) affected 10 different countries, there will be 10 entries in the database, we will therefore talk about 10 country-events).

Because the aim is to highlight the possible existing hazard chains and link it to their associated impacts and not to present an exhaustive list of all crisis that had cascading effects and their respective impacts, those selections were both shrinked according to criteria relating to their impacts on the population, built environment, grids, natural environment, economy and their hazard chain.

The eruption of the Icelandic volcano Eyjafjallajokull in April 2010 is well known in the study of cascading effects for its large effects on the European air transportation and the resulting strain on the European train and ferry network. Moreover, life of patients waiting for transplants in Europe was threaten because of delays in the importation of bone marrow from North America and the activities were severely affected (commerce, tourism, culture…). This crisis is a good example of a crisis were the associated event became the main cause of disruption because of the dependencies that the societies established with grids and networks. It affected a large amount of people and caused important economic damages (over 3.6 billion US$), even though the triggering event caused very limited effects.

The famous extra-tropical storm Xynthia affected nine European countries end of February 2010 and is relevant in the analysis of past crises. The storm was associated to a storm surge that resulted in important electric disruptions, leaving respectively in France and in Spain, over a million household and over 100,000 houses without electricity. Moreover, the water/sanitation network was disrupted and the transport network was highly affected (roads, rail, air transportation). The economy suffered, causing over 4 billion US$ economic damages in France only. Finally, the impact to the natural environment is not negligible: natural reserves were destroyed and coastal dunes caused safety disorders. On the other hand, the number of casualties was low, with a total of 66 deaths for all affected countries.

The Tōhoku earthquake of the 11th March 2011 which was followed by a tsunami is considered to be an outstanding example of a cascading disaster. Although only about 100 people died as a direct result of the earthquake, over 19,700 were killed by the ensuing tsunami (Pescaroli and Alexander, 2015; EM-DAT, 2016). This tsunami of up to 30 meters high, caused the destruction of the nuclear plants of Fukushima and engendered the disruption of all 3 grids analyzed. This event was also chosen because of its really high economic impact (210 billion US$) and important destruction on the residential buildings, and land transportation (roads, bridges and railways). This highlights the important negative impacts and increasing vulnerability of the society resulting from the interaction of both natural and technological hazards.

Finally, another well know crisis is the Hurricane Sandy (2012) that mainly affected the USA, Haiti and Cuba. The Hurricane was associated to a long and complex chain of hazard: floods (sea surge), slide (land, mud), cholera and dengue outbreak, fire, transport accident, electricity, communication and water/sanitation networks disruption. Destructions were highly noted to residential, educational and health infrastructures. Damages to the agriculture were particularly important and the transport network was also disrupted. Among the most affected countries, 75 and 54 deaths were reported in Haiti and the USA. This cascading event costed approximately 50 billion US$ to the USA.

The selection and analysis of past crises for the detection of possible event chains and associated impacts represents only a first preparatory and necessary step for the implementation of the theoretical model for cascading events and the associated simulation tool for modeling and simulating cascading effects in crisis situations.