The Fukushima Dai-ichi disaster has shown the importance of evaluating cascading effects in disaster management, as the impact of a triggering hazard may generate different sequences of events (event trees) that result in physical, social or economic disruption. The models of the Snowball’s Decision Support System are able to assess the impacts of a sequence of interdependent disasters on the elements exposed (population, buildings, grids) and to define a set of possible mitigation strategies. In a scenario that involves cascading effects, the choice of the most appropriate mitigation strategy is articularly challenging, as it involves multiple conflicting objectives and several variables to be taken in consideration.
The aim of the decision algorithm is to support the decision maker in the choice of the best mitigation strategy, according to its expected impacts and his/her priorities.
The objective is fulfilled by means of a Multi-Criteria Decision Making algorithm, which allows the decision maker to enter his/her priorities as a set of weights on a number of criteria and to suggest the best mitigation strategy according to this input and the impact assessment of the Snowball’s models. Through the comparison of different starting times of mitigation strategies, the decision algorithm is also able to support the decision maker in the choice of the best timing for the intervention, which is crucial when cascading effects are taken into account. The results of the algorithm, a ranking and class assignment of mitigation strategies, are easy to interpret for the decision maker, and at the same time convey a proxy of uncertainty in the form of probability distributions, obtained through an ensemble approach.
The results of the decision algorithm are displayed on the Snowball’s dashboard, in order to allow an easier utilization and the direct interaction with the decision maker.