VOLCANBOX uses HASSET (Sobradelo et al., 2013; Sobradelo and Martí, 2015; Bartolini et al., 2016) to conduct temporal analysis. It is a probabilistic tool based on Bayesian methodology that has been developed for long- and short-term hazard assessment and eruption forecasting. It is built on an event tree structure, that use Bayesian inference to estimate the probability of occurrence of a future volcanic scenario. It also evaluates the most relevant sources of uncertainty in the corresponding volcanic system. Each node of the event tree represents a step and contains a set of possible branches (the outcomes for that particular category). The nodes are alternative steps from a general prior event, state or condition that move towards increasingly specific subsequent events and a final outcome. HASSET accounts for the possibility of (i) flank eruptions (as opposed to only central eruptions) and monogenetic volcanism, (ii) geothermal or tectonic unrest (as opposed to only magmatic unrest), and (iii) felsic or mafic lava composition (or the absence composition data), as well as (iv) certain volcanic hazards as possible outcomes of an eruption, and (v) the extent of each hazard.

 ST-HASSET, is a modified version of HASSET to use the time evolution of unrest indicators in the volcanic short-term hazard assessment. It complements long-term hazard assessment with continuous monitoring data when the volcano goes into unrest. It is based also on Bayesian Inference and transforms different pre-eruptive monitoring parameters into a common probabilistic scale for comparison among unrest episodes from the same volcano or from similar ones. This allows identifying common pre-eruptive behaviours and patterns. ST-HASSET is especially designed to assist experts and decision makers as a crisis unfolds, and allows detecting sudden changes in the activity of a volcano.