Quantitative volcanic susceptibility analysis of Lanzarote and Chinijo Islands based on kernel density estimation via a linear diffusion process
Risk management stakeholders in high-populated volcanic islands should be provided with the latest high-quality volcanic information. We present here the first volcanic susceptibility map of Lanzarote and Chinijo Islands and their submarine flanks based on updated chronostratigraphical and volcano structural data, as well as on the geomorphological analysis of the bathymetric data of the submarine flanks. The role of the structural elements in the volcanic susceptibility analysis has been reviewed: vents have been considered since they indicate where previous eruptions took place; eruptive fissures provide information about the stress field as they are the superficial expression of the dyke conduit; eroded dykes have been discarded since they are single non-feeder dykes intruded in deep parts of Miocene-Pliocene volcanic edifices; main faults have been taken into account only in those cases where they could modified the superficial movement of magma. The application of kernel density estimation via a linear diffusion process for the volcanic susceptibility assessment has been applied successfully to Lanzarote and could be applied to other fissure volcanic fields worldwide since the results provide information about the probable area where an eruption could take place but also about the main direction of the probable volcanic fissures.
Assessing qualitative long-term volcanic hazards at Lanzarote Island (Canary Islands)
Abstract. Conducting long-term hazard assessment in active volcanic areas is of primary importance for land-use planning and defining emergency plans able to be applied in case of a crisis. A definition of scenario hazard maps helps to mitigate the consequences of future eruptions by anticipating the events that may occur. Lanzarote is an active volcanic island that has hosted the largest (>  1.5 km3 DRE) and longest (6 years) eruption, the Timanfaya eruption (1730–1736), on the Canary Islands in historical times (last 600 years). This eruption brought severe economic losses and forced local people to migrate. In spite of all these facts, no comprehensive hazard assessment or hazard maps have been developed for the island. In this work, we present an integrated long-term volcanic hazard evaluation using a systematic methodology that includes spatial analysis and simulations of the most probable eruptive scenarios.
Velocity moments in alongshore bottom stress parameterizations
The time-averaged alongshore bottom stress is an important component of nearshore circulation models. In a widely accepted formulation the bottom stress is proportional to , the time average of the product of the instantaneous velocity magnitude |u→| and the instantaneous alongshore velocity component υ. Both mean and fluctuating (owing to random, directionally spread waves) velocities contribute to . Direct estimation of requires a more detailed specification of the velocity field than is usually available, so the term is parameterized. Here direct estimates of based on time series of near-bottom currents observed between the shoreline and 8-m water depth are used to test the accuracy of parameterizations. Common parameterizations that are linear in the mean alongshore current significantly underestimate for moderately strong alongshore currents, resulting in overestimation of a drag coefficient determined by fitting modeled (with a linearized bottom stress) to observed alongshore currents. A parameterization based on a joint-Gaussian velocity field with the observed velocity statistics gives excellent overall agreement with the directly estimated and allows analytic investigation of the statistical properties of the velocity field that govern . Except for the weakest flows, depends strongly on the mean alongshore current and the total velocity variance but depends only weakly on the mean wave angle, wave directional spread, and mean cross-shore current. Several other nonlinear parameterizations of are shown to be more accurate than the linear parameterizations and are adequate for many modeling purposes.