ALBERT

Description: RED SEED stands for Risk Evaluation, Detection and Simulation during Effusive Eruption Disasters, and combines stakeholders from the remote sensing, modelling and response communities with experience in tracking volcanic effusive events. The group first met during a three day-long workshop held in Clermont Ferrand (France) between 28 and 30 May 2013. During each day, presentations were given reviewing the state of the art in terms of (a) volcano hot spot detection and parameterization, (b) operational satellite-based hot spot detection systems, (c) lava flow modelling and (d) response protocols during effusive crises. At the end of each presentation set, the four groups retreated to discuss and report on requirements for a truly integrated and operational response that satisfactorily combines remote sensors, modellers and responders during an effusive crisis. The results of collating the final reports, and follow-up discussions that have been on-going since the workshop, are given here. We can reduce our discussions to four main findings. (1) Hot spot detection tools are operational and capable of providing effusive eruption onset notice within 15 min. (2) Spectral radiance metrics can also be provided with high degrees of confidence. However, if we are to achieve a truly global system, more local receiving stations need to be installed with hot spot detection and data processing modules running on-site and in real time. (3) Models are operational, but need real-time input of reliable time-averaged discharge rate data and regular updates of digital elevation models if they are to be effective; the latter can be provided by the radar/photogrammetry community. (4) Information needs to be provided in an agreed and standard format following an ensemble approach and using models that have been validated and recognized as trustworthy by the responding authorities. All of this requires a sophisticated and centralized data collection, distribution and reporting hub that is based on a philosophy of joint ownership and mutual trust. While the next chapter carries out an exercise to explore the viability of the last point, the detailed recommendations behind these findings are detailed here.

Description: How brain functions degenerate in the face of progressive cell loss is an important issue that pertains to neurodegenerative diseases and basic properties of neural networks. We developed an automated system that uses two-photon microscopy to detect rhythmic neurons from calcium activity, and then individually laser ablates the targets while monitoring network function in real time. We applied this system to the mammalian respiratory oscillator located in the pre-Bötzinger Complex (preBötC) of the ventral medulla, which spontaneously generates breathing-related motor activity in vitro. Here, we show that cumulatively deleting preBötC neurons progressively decreases respiratory frequency and the amplitude of motor output. On average, the deletion of 120 ± 45 neurons stopped spontaneous respiratory rhythm, and our data suggest ≈82% of the rhythm-generating neurons remain unlesioned. Cumulative ablations in other medullary respiratory regions did not affect frequency but diminished the amplitude of motor output to a lesser degree. These results suggest that the preBötC can sustain insults that destroy no more than ≈18% of its constituent interneurons, which may have implications for the onset of respiratory pathologies in disease states.

Description: The integration of satellite data and modeling represents a step toward the next generation of quantitative hazard assessment in response to effusive volcano eruption onset. Satellite-based thermal remote sensing of hotspots related to effusive activity can effectively provide a variety of products suited to timing, locating, and tracking the radiant character of lava flows. Hotspots show the location and occurrence of eruptive events (vents). Discharge rate estimates may indicate the current intensity (effusion rate) and potential magnitude (volume). High-spatial-resolution multispectral satellite data can complement field observations for monitoring the front position (length) and extension of flows (area). Physics-based models driven, or validated, by satellite-derived parameters are now capable of fast and accurate forecast of lava flow inundation scenarios (hazard). Here, we demonstrate the potential of the integrated application of satellite remote-sensing techniques and lava flow models by using a retrospective analysis of the 2004–2005 effusive eruption at Mount Etna in Italy. The lava flow hazard was assessed by using the HOTSAT volcano hotspot detection system, which works with satellite thermal infrared data, and the MAGFLOW lava flow emplacement model, which is able to relate the flow evolution to eruption conditions at the vent. We used HOTSAT to analyze Moderate Resolution Imaging Spectroradiometer (MODIS) and Spinning Enhanced Visible and InfraRed Imager (SEVIRI) data to output hotspot location, lava thermal flux, and effusion rate estimation. This output was used to drive the MAGFLOW simulations of lava flow paths and to continuously update flow simulations. We also show how Landsat-7 Enhanced Thematic Mapper+ (ETM+) and Earth Observing 1 ( EO-1 ) Advanced Land Imager (ALI) images complement the field observations to track the flow front position in time and add valuable data on lava flow advancement with which to validate the numerical simulations. Such integration at last makes timely forecasts of lava flow hazards during effusive crises possible at the great majority of volcanoes for which no monitoring exists.

Description: Using two hypothetical effusive events in the Chaîne des Puys (Auvergne, France), we tested two geographical information systems (GISs) set up to allow loss assessment during an effusive crisis. The first was a local system that drew on all immediately available data for population, land use, communications, utility and building type. The second was an experimental add-on to the Global Disaster Alert and Coordination System (GDACS) global warning system maintained by the Joint Research Centre (JRC) that draws information from open-access global data. After defining lava-flow model source terms (vent location, effusion rate, lava chemistry, temperature, crystallinity and vesicularity), we ran all available lava-flow emplacement models to produce a projection for the likelihood of impact for all pixels within the GIS. Next, inundation maps and damage reports for impacted zones were produced, with those produced by both the local system and by GDACS being in good agreement. The exercise identified several shortcomings of the systems, but also indicated that the generation of a GDACS-type global response system for effusive crises that uses rapid-response model projections for lava inundation driven by real-time satellite hotspot detection – and open-access datasets – is within the current capabilities of the community.

Description: The MAGFLOW model for lava-flow simulations is based on the cellular automaton (CA) approach, and uses a physical model for the thermal and rheological evolution of the flowing lava. We discuss the potential of MAGFLOW to improve our understanding of the dynamics of lava-flow emplacement and our ability to assess lava-flow hazards. Sensitivity analysis of the input parameters controlling the evolution function of the automaton demonstrates that water content and solidus temperatures are the parameters to which MAGFLOW is most sensitive. Additional tests also indicate that temporal changes in effusion rate strongly influence the accuracy of the predictive modelling of lava-flow paths. The parallel implementation of MAGFLOW on graphic processing units (GPUs) can achieve speed-ups of two orders of magnitude relative to the corresponding serial implementation, providing a lava-flow simulation spanning several days of eruption in just a few minutes. We describe and demonstrate the operation of MAGFLOW using two case studies from Mt Etna: one is a reconstruction of the detailed chronology of the lava-flow emplacement during the 2006 flank eruption; and the other is the production of the lava-flow hazard map of the persistent eruptive activity at the summit craters.

Description: GPUSPH is a fully three-dimensional model for the simulation of the thermal and rheological evolution of lava flows that relies on the Smoothed Particle Hydrodynamics (SPH) numerical method. Thanks to the Lagrangian, meshless nature of SPH, the model incorporates a more complete physical description of the emplacement process and rheology of lava that considers the free surface, the irregular boundaries represented by the topography, the solidification fronts and the non-Newtonian rheology with temperature-dependent parameters. GPUSPH follows the very general Herschel–Bulkley rheological model, which encompasses Newtonian, power-law and Bingham flow behaviours, with both constant and temperature-dependent parameters, and can thus be used to explore in detail the impact of rheology on the behaviour of lava flows and on their emplacement. To illustrate this possibility, we present some preliminary applications of the model for studying the rheology of lava flows with different constitutive relationships and thermal regimes using the real topography of the Mt Etna volcano.

Description: The HOTSAT multiplatform system for the analysis of infrared data from satellites provides a framework that allows the detection of volcanic hotspots and an output of their associated radiative power. This multiplatform system can operate on both Moderate Resolution Imaging Spectroradiometer and Spinning Enhanced Visible and Infrared Imager data. The new version of the system is now implemented on graphics processing units and its interface is available on the internet under restricted access conditions. Combining the estimation of time-varying discharge rates using HOTSAT with the MAGFLOW physics-based model to simulate lava flow paths resulted in the first operational system in which satellite observations drive the modelling of lava flow emplacement. This allows the timely definition of the parameters and maps essential for hazard assessment, including the propagation time of lava flows and the maximum run-out distance. The system was first used in an operational context during the paroxysmal episode at Mt Etna on 12–13 January 2011, when we produced real-time predictions of the areas likely to be inundated by lava flows while the eruption was still ongoing. This allowed key at-risk areas to be rapidly and appropriately identified.

Description: 〈span〉Lava flows represent the greatest threat by far to exposed population and infrastructure on Mt. Etna, Italy. The increasing exposure of a larger population, which has almost tripled in the area around Mt. Etna during the past 150 years, has resulted from poor assessment of the volcanic hazard and inappropriate land use in vulnerable areas. Here we quantify the lava flow risk on the flanks of Mt. Etna volcano using a Geographic Information System (GIS)-based approach that integrates the hazard with the exposure of elements at stake. The hazard, which shows the long-term probability related to lava flow inundation, is obtained by combining three different kinds of information: the spatiotemporal probability of new flank eruptive vents opening in the future, the event probability associated with classes of expected eruptions, and the overlapping of lava flow paths simulated by the MAGFLOW model. Data including all exposed elements were gathered from institutional web portals and high-resolution satellite imagery and organized in four thematic layers: population, buildings, service networks, and land use. The total exposure is given by a weighted linear combination of the four thematic layers, where weights are calculated using the Analytic Hierarchy Process (AHP). The resulting risk map shows the likely damage caused by a lava flow eruption and allows rapid visualization of the areas subject to the greatest losses if a flank eruption were to occur on Mt. Etna. The highest risk is found in the southeastern flank due to the combination of high hazard and population density.〈/span〉