Abstract. One of the most important tasks of modern volcanology is the construction of hazard maps simulating different eruptive scenarios that can be used in risk-based decision making in land-use planning and emergency management. The first step in the quantitative assessment of volcanic hazards is the development of susceptibility maps (i.e., the spatial probability of a future vent opening given the past eruptive activity of a volcano). This challenging issue is generally tackled using probabilistic methods that use the calculation of a kernel function at each data location to estimate probability density functions (PDFs). The smoothness and the modeling ability of the kernel function are controlled by the smoothing parameter, also known as the bandwidth. Here we present a new tool, QVAST, part of the open-source geographic information system Quantum GIS, which is designed to create user-friendly quantitative assessments of volcanic susceptibility. QVAST allows the selection of an appropriate method for evaluating the bandwidth for the kernel function on the basis of the input parameters and the shapefile geometry, and can also evaluate the PDF with the Gaussian kernel. When different input data sets are available for the area, the total susceptibility map is obtained by assigning different weights to each of the PDFs, which are then combined via a weighted summation and modeled in a non-homogeneous Poisson process. The potential of QVAST, developed in a free and user-friendly environment, is here shown through its application in the volcanic fields of Lanzarote (Canary Islands) and La Garrotxa (NE Spain).

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Event tree structures constitute one of the most useful and necessary tools in modern volcanology for assessment of hazards from future volcanic scenarios (those that culminate in an eruptive event as well as those that do not). They are particularly relevant for evaluation of longand short-term probabilities of occurrence of possible volcanic scenarios and their potential impacts on urbanized areas. In this paper, we introduce Hazard Assessment Event Tree (HASSET), a probability tool, built on an event tree structure that uses Bayesian inference to estimate the probability of occurrence of a future volcanic scenario and to evaluate the most relevant sources of uncertainty from the corresponding volcanic system. HASSET includes hazard assessment of noneruptive and nonmagmatic volcanic scenarios, that is, episodes of unrest that do not evolve into volcanic eruption but have an associated volcanic hazard (e.g., sector collapse and phreatic explosion), as well as unrest episodes triggered by external triggers rather than the magmatic system alone. Additionally, HASSET introduces the Delta method to assess precision of the probability Editorial responsibility: E.

Abstract. Long-term hazard assessment, one of the bastions of risk-mitigation programs, is required for territorial planning and for developing emergency plans. To ensure qualitative and representative results, long-term volcanic hazard assessment requires several sequential steps to be completed, which include the compilation of geological and volcanological information, the characterization of past eruptions, spatial and temporal probabilistic studies, and the simulation of different eruptive scenarios. Despite being a densely populated active volcanic region that receives millions of visitors per year, no systematic hazard assessment has ever been conducted in the Canary Islands. In this paper we focus our attention on El Hierro, the youngest of the Canary Islands and the most recently affected by an eruption. We analyze the past eruptive activity (how), the spatial probability (where) and the temporal probability (when) of an eruption on the island. By studying the past eruptive behavior of the island and assuming that future eruptive patterns will be similar, we aim to identify the most likely volcanic scenarios and corresponding hazards, which include lava flows, pyroclastic fallout and pyroclastic density currents (PDCs). Finally, we estimate their probability of occurrence. The end result is the first total qualitative volcanic hazard map of the island.

Deception Island is the most active volcano in the South Shetland Islands and has been the scene of more than twenty identified eruptions over the past two centuries. In this contribution we present the first comprehensive long-term volcanic hazard assessment for this volcanic island. The research is based on the use of probabilistic methods and statistical techniques to estimate volcanic susceptibility, eruption recurrence and the most likely future eruptive scenarios. We perform a statistical analysis of the time series of past eruptions and the spatial extent of their products, including lava flows, fallout, pyroclastic density currents and lahars. The Bayesian event tree statistical method HASSET is applied to calculate eruption recurrence, while the QVAST tool is used in an analysis of past activity to calculate the possibility that new vents will open (volcanic susceptibility). On the basis of these calculations, we identify a number of significant scenarios using the GIS-based VORIS 2.0.1 and