Towards real-time eruption forecasting in the Auckland Volcanic Field: application of BET_EF during the New Zealand National Disaster Exercise ‘Ruaumoko’

The Auckland Volcanic Field (AVF) is a young basaltic field that lies beneath the urban area of Auckland, New Zealand’s largest city. Over the past 250,000 years the AVF has produced at least 49 basaltic centers; the last eruption was only 600 years ago. In recognition of the high risk associated with a possible future eruption in Auckland, the New Zealand government ran Exercise Ruaumoko in March 2008, a test of New Zealand’s nation-wide preparedness for responding to a major disaster resulting from a volcanic eruption in Auckland City. The exercise scenario was developed in secret, and covered the period of precursory activity up until the eruption. During Exercise Ruaumoko we adapted a recently developed statistical code for eruption forecasting, namely BET_EF (Bayesian Event Tree for Eruption Forecasting), to independently track the unrest evolution and to forecast the most likely onset time, location and style of the initial phase of the simulated eruption. The code was set up before the start of the exercise by entering reliable information on the past history of the AVF as well as the monitoring signals expected in the event of magmatic unrest and an impending eruption. The average probabilities calculated by BET_EF during Exercise Ruaumoko corresponded well to the probabilities subjectively (and independently) estimated by the advising scientists (differences of few percentage units), and provided a sound forecast of the timing (before the event, the eruption probability reached 90%) and location of the eruption. This application of BET_EF to a volcanic field that has experienced no historical activity and for which otherwise limited prior information is available shows its versatility and potential usefulness as a tool to aid decision-making for a wide range of volcano types. Our near real-time application of BET_EF during Exercise Ruaumoko highlighted its potential to clarify and possibly optimize decision-making procedures in a future AVF eruption crisis, and as a rational starting point for discussions in a scientific advisory group. It also stimulated valuable scientific discussion around how a future AVF eruption might progress, and highlighted areas of future volcanological research that would reduce epistemic uncertainties through the development of better input models.     

Bayesian event tree for eruption forecasting (BET_EF) at Vesuvius,Italy: a retrospective forward application to the 1631 eruption

Reliable forecasting of the next eruption at Vesuvius is the main scientific factor in defining effective strategies to reduce volcanic risk in one of the most dangerous volcanic areas of the world. In this paper, we apply a recently developed probabilistic code for eruption forecasting to new and independent historical data related to the pre-eruptive phase of the 1631 eruption. The results obtained point out three main issues: (1) the importance of “cold” historical data (according to Guidoboni 2008) related to pre-eruptive phases for evaluating forecasting tools and possibly refining them; (2) the BET_EF code implemented for Vesuvius would have forecasted the 1631 eruption satisfactorily, marking different stages of the pre-eruptive phase; (3) the code shows that pre-eruptive signals that significantly increase the probability of eruption were likely detected more than 2 months before the event.     

Probabilistic eruption forecasting at short and long time scales

Any effective volcanic risk mitigation strategy requires a scientific assessment of the future evolution of a volcanic system and its eruptive behavior. Some consider the onus should be on volcanologists to provide simple but emphatic deterministic forecasts. This traditional way of thinking, however, does not deal with the implications of inherent uncertainties, both aleatoric and epistemic, that are inevitably present in observations, monitoring data, and interpretation of any natural system. In contrast to deterministic predictions, probabilistic eruption forecasting attempts to quantify these inherent uncertainties utilizing all available information to the extent that it can be relied upon and is informative. As with many other natural hazards, probabilistic eruption forecasting is becoming established as the primary scientific basis for planning rational risk mitigation actions: at short-term (hours to weeks or months), it allows decision-makers to prioritize actions in a crisis; and at long-term (years to decades), it is the basic component for land use and emergency planning. Probabilistic eruption forecasting consists of estimating the probability of an eruption event and where it sits in a complex multidimensional time–space–magnitude framework. In this review, we discuss the key developments and features of models that have been used to address the problem.     

A long-term volcanic hazard event tree for Teide-Pico Viejo stratovolcanoes (Tenerife,Canary Islands)

We propose a long-term volcanic hazards event tree for Teide-Pico Viejo stratovolcanoes, two complex alkaline composite volcanoes that have erupted 1.8–3 km³ of mafic and felsic magmas from different vent sites during the last 35 ka. This is the maximum period that can be investigated from surface geology and also represents an upper time limit for the appearance of the first phonolites on that volcano. The whole process of the event tree construction was divided into three stages. The first stage included the determination of the spatial probability of vent opening for basaltic and phonolitic eruptions, based on the available geological and geophysical data. The second, involved the analysis of the different eruption types that have characterised the volcanic activity from Teide during this period. The third stage focussed on the generation of the event tree from the information obtained in the two previous steps and from the application of a probabilistic analysis on the occurrence of each possible eruption type. As for other volcanoes, the structure of the Teide-Pico Viejo Event Tree was subdivided into several steps of eruptive progression from general to more specific events. The precursory phase was assumed as an unrest episode of any geologic origin (magmatic, hydrothermal or tectonic), which could be responsible for a clear increase of volcanic activity revealed by geophysical and geochemical monitoring. According to the present characteristics of Teide-Pico Viejo and their past history, we started by considering whether the unrest episode would lead to a sector collapse or not. If the sector collapse does not occur but an eruption is expected, this could be either from the central vents or from any of the volcanoes' flanks. In any of these cases, there are several possibilities according to what has been observed in the period considered in our study. In the case that a sector collapse occurs and is followed by an eruption we considered it as a flank eruption. We conducted an experts elicitation judgement to assign probabilities to the different possibilities indicated in the event tree. We assumed long term estimations based on existing geological and historical data for the last 35 Ka, which gave us a minimum estimate as the geological record for such a long period is incomplete. However, to estimate probabilities for a short term forecast, for example during an unrest episode, we would need to include in the event tree additional information from the monitoring networks, as any possible precursors that may be identified could tell us in which direction the system will evolve. Therefore, we propose to develop future versions of the event tree to include also the precursors that might be expected on each path during the initial stages of a new eruptive event.     

Tephra fallout hazard assessment at the Campi Flegrei caldera (Italy)

Tephra fallout associated with renewal of volcanism at the Campi Flegrei caldera is a serious threat to the Neapolitan area. In order to assess the hazards related with tephra loading, we have considered three different eruption scenarios representative of past activity: a high-magnitude event similar to the 4.1 ka Agnano-Monte Spina eruption, a medium-magnitude event, similar to the ∼3.8 ka Astroni 6 eruption, and a low-magnitude event similar to the Averno 2 eruption. The fallout deposits were reconstructed using the HAZMAP computational model, which is based on a semi-analytical solution of the two-dimensional advection–diffusion–sedimentation equation for volcanic tephra. The input parameters into the model, such as total erupted mass, eruption column height, and bulk grain-size and components distribution, were obtained by best-fitting field data. We carried out tens of thousands simulations using a statistical set of wind profiles, obtained from NOAA re-analysis. Probability maps, relative to the considered scenarios, were constructed for several tephra loads, such as 200, 300 and 400 kg/m². These provide a hazard assessment for roof collapses due to tephra loading that can be used for risk mitigation plans in the area.     

Quantifying volcanic ash fall hazard to electricity infrastructure

Quantifying the potential ash fall hazards from re-awakening volcanoes is a topic of great interest. While methods for calculating the probability of eruptions, and for numerical simulation of tephra dispersal and fallout exist, event records at most volcanoes that re-awaken sporadically on decadal to millennial cycles are inadequate to develop rigorous forecasts of occurrence, much less eruptive volume. Here we demonstrate a method by which eruption records from radiocarbon-dated sediment cores can be used to derive forecasting models for ash fall impacts on electrical infrastructure. Our method is illustrated by an example from the Taranaki region of New Zealand. Radiocarbon dates, expressed as years before present (B.P.), are used to define an age-depth model, classifying eruption ages (with associated errors) for a circa 1500–10 500 year B.P. record at Mt. Taranaki (New Zealand). In addition, data describing the youngest 1500 years of eruption activity is obtained from directly dated proximal deposits. Absence of trend and apparent independence in eruption intervals is consistent with a renewal model using a mix of Weibulls distributions, which was used to generate probabilistic forecasts of eruption recurrence. After establishing that interval length and tephra thickness were independent in the record, a thickness–volume relationship (from [Rhoades, D.A., Dowrick, D.J., Wilson, C.J.N., 2002. Volcanic hazard in New Zealand: Scaling and attenuation relations for tephra fall deposits from Taupo volcano. Nat. Hazards, 26:147–174]) was inverted to provide a frequency–volume relationship for eruptions. Monte Carlo simulation of the thickness–volume relationship was then used to produce probable ash fall thicknesses at any chosen site. Several critical electrical infrastructure sites in the Taranaki Region were analysed. This region, being the only gas and condensate-producing area in New Zealand, is of national economic importance, with activities in and around the area depending on uninterrupted power supplies. Forecasts of critical ash thicknesses (1 mm wet and 2 mm dry) that may cause short-circuiting, surges or power shutdowns in substations show that the annual probabilities of serious impact are between ~ 0.5% and 27% over a 50 year period. It was also found that while large eruptions with high ash plumes tend to affect “expected” areas in relation to prevailing winds, the direction impacts of small ash falls are far less predictable. In the Taranaki case study, areas out of normal downwind directions, but close to the volcano, have probabilities of impact for critical thicknesses of 1–2 mm of around half to 60% of those in downwind directions and therefore should not be overlooked in hazard analysis. Through this method we are able to definitively show that the potential ash fall hazard to electrical infrastructure in this area is low in comparison to other natural threats, and provide a quantitative measure for use in risk analysis and budget prioritisation for hazard mitigation measures.     

Improved age estimates for Holocene Ko-g and Ma-f~j tephras in northern Japan using Bayesian statistical modelling

The Ko-g and Ma-f~j tephras are two key isochronous marker layers in northern Japan, which are from the largest Plinian eruptions of Komagatake volcano (VEI = 5) and Mashu caldera (VEI = 6), respectively. Despite extensive radiocarbon studies associated with the two tephras, individual calibrated results show considerable variations and thus accurate ages of these important eruptions remain controversial. Bayesian statistical approaches to calibrating radiocarbon determinations have proven successful in increasing accuracy and sometimes precision for dating tephras, which is achieved through the incorporation of additional stratigraphic information and the combination of evidence from multiple records. Here we use Bayesian approaches to analyse the proximal and distal information associated with the two tephra markers. Through establishing phase and deposition models, we have taken into account all of the currently available stratigraphic and chronological information. The cross-referencing of phase models with the deposition model allows the refinement of eruption ages and the deposition model itself. Using this we are able to provide the most robust current age estimates for the two tephra layers. The Ko-g and Ma-f~j tephras are hereby dated to 6657-6505 (95.4%; 6586±40, μ±σ) cal yr BP, and 7670-7395 (95.4%; 7532±72, μ±σ) cal yr BP, respectively. These updated age determinations underpin the reported East Asian Holocene tephrostratigraphic framework, and allow sites where the tephra layers are present to be dated more precisely and accurately. Our results encourage further applications of Bayesian modelling techniques in the volcanically active East Asian region.     

Revisiting the 1669 Etnean eruptive crisis using a cellular automata model and implications for volcanic hazard in the Catania area

Cellular Automata provide an alternative approach to standard numerical methods for modelling some complex natural systems, the behaviour of which can be described in terms of local interactions of their constituent parts. SCIARA is a 2-D Cellular Automata model which simulates lava flows. It was tested on, validated by, and improved on several Etnean lava events such as the 1986–1987 eruption and the first and last phase of the 1991–1993 event. With respect to forecasting the surface covered by the lava flows, the best results were acceptable. The model has been used to determine hazard zones in the inhabited areas of Nicolosi, Pedara, S. Alfio and Zafferana (Sicily, Italy). The main goal of the current work in the Etnean area from Nicolosi to Catania has been the verification of the volcanic hazard effects of an eruptive crisis similar to the event that occurred in 1669. The simulation uses the volcanic data of the 1669 eruption with present-day morphology. Catania has been affected by some historical Etnean events, the most famous one being the 1669 eruption, involving 1 km³ of lava erupted over the course of 120 days. The simulation of ephemeral vents and the use of different histories within the experiments have been crucial in the determination of a new hazard area for Catania. In fact, during the simulation the city was never affected without the introduction of ephemeral vents, proving the fact that lava tubes played a fundamental role in the 1669 Catania lava crisis.     

Improved age modelling and high-precision age estimates of late Quaternary tephras,for accurate palaeoclimate reconstruction

The role of tephrochronology, as a dating and stratigraphic tool, in precise palaeoclimate and environmental reconstruction, has expanded significantly in recent years. The power of tephrochronology rests on the fact that a tephra layer can stratigraphically link records at the resolution of as little as a few years, and that the most precise age for a particular tephra can be imported into any site where it is found. In order to maximise the potential of tephras for this purpose it is necessary to have the most precise and robustly tested age estimate possible available for key tephras. Given the varying number and quality of dates associated with different tephras it is important to be able to build age models to test competing tephra dates. Recent advances in Bayesian age modelling of dates in sequence have radically extended our ability to build such stratigraphic age models. As an example of the potential here we use Bayesian methods, now widely applied, to examine the dating of some key Late Quaternary tephras from Italy. These are: the Agnano Monte Spina Tephra (AMST), the Neapolitan Yellow Tuff (NYT) and the Agnano Pomici Principali (APP), and all of them have multiple estimates of their true age. Further, we use the Bayesian approaches to generate a revised mixed radiocarbon/varve chronology for the important Lateglacial section of the Lago Grande Monticchio record, as a further illustration of what can be achieved by a Bayesian approach. With all three tephras we were able to produce viable model ages for the tephra, validate the proposed ⁴⁰Ar/³⁹Ar age ranges for these tephras, and provide relatively high precision age models. The results of the Bayesian integration of dating and stratigraphic information, suggest that the current best 95% confidence calendar age estimates for the AMST are 4690–4300 cal BP, the NYT 14320–13900 cal BP, and the APP 12380–12140 cal BP.     

Eruption episodes and magma recharge events in andesitic systems: Mt Taranaki,New Zealand

Eruption episodes, where a series of eruption events are generically related, can include the eruption of a wide spectrum of volcanic activity over decadal periods. This paper concentrates on the opening phases of an eruption episode which occurred approximately 1800 yrs BP from Mt Taranaki, New Zealand. These events spanned the eruption of differing bulk compositions and styles from two distinct vent locations; an andesitic sub-plinian eruption from the summit vent and a scoria cone-building eruption of basaltic magma from a satellite vent. Compositional profiles and zoning textures of plagioclase, amphibole and clinopyroxene phenocrysts from the opening andesitic event show evidence of magma mixing and subsequent crystallisation just prior to the initiation of the eruption episode. Titanomagnetite grain morphology and Ti variation suggest that the magma mixing event occurred within a few days to weeks before the eruption acting as a trigger for it. We present a magmatic model which is constrained by the petrological observations and eruptions of the episode. In this model magma differentiation at depth causes its rise and recharging of a mid-crustal magma storage area at 5–7 km. Although the recharging magma differed slightly in oxygen fugacity and temperature, it was compositionally and physically similar enough to the residing andesitic magma to allow efficient mixing. The petrological characteristics described here can be readily observed and enable identification of mixing events in other recent eruption episodes.     

Merging eruption datasets: building an integrated Holocene eruptive record for Mt Taranaki,New Zealand

Acquiring detailed eruption frequency datasets for a volcano system is essential for realistic eruption forecasts. However, accurate datasets are inherently difficult to compile, even if one or more well-dated eruption records are available. A single record typically under-represents the eruption frequency, while combining two or more records may result in an overrepresentation. Although glass compositions have proven to be successful in tephrochronological studies of dominantly rhyolitic tephras; microlitic growth and thin glass shards inhibit their application to andesitic tephras. A method consisting of a combination of two techniques for correlating syn-eruptive deposits is demonstrated on data from the typical andesitic stratovolcano of Mt. Taranaki, New Zealand. Firstly, tentative matches are identified using the radiocarbon age and associated error of each event. Secondly, the compositions of titanomagnetite micro-phenocrysts are used as an independent check, and shown to be a useful correlation tool where age data is available. Using two lake-core records containing tephra layers in an overlapping time-frame, the radiocarbon age-correlation procedure suggested 31 tephra matches. Geochemistry data were available for 15 of these pairs. In three of these cases, the titanomagnetite compositions did not match. Hence, these “paired” tephras were from compositionally distinct magmas and therefore likely represent separate events. An additional three matches were reassigned within the temporal uncertainty limits of the dating procedure, based on better geochemical pairing. The final combined dataset suggests that there have been at least 138 separate ash fall-producing eruptions between 96 and 10 150 years B.P. from Taranaki. Using the combined dataset the mixture of Weibulls renewal model forecasts a probability of 0.52 for an eruption occurring in the next 50 years at this volcano. The present annual eruption probability is estimated at 1.6%. This likelihood is almost double that obtained when relying on a single stratigraphic record.     

A hybrid approach of artificial neural network and multiple regression to forecast typhoon rainfall and groundwater-level change

ABSTRACT

A forecasting model is developed using a hybrid approach of artificial neural network (ANN) and multiple regression analysis (MRA) to predict the total typhoon rainfall and groundwater-level change in the Zhuoshui River basin. We used information from the raingauge stations in eastern Taiwan and open source typhoon data to build the ANN model for forecasting the total rainfall and the groundwater level during a typhoon event; then we revised the predictive values using MRA. As a result, the average accuracy improved up to 80% when the hybrid model of ANN and MRA was applied, even where insufficient data were available for model training. The outcome of this research can be applied to forecasts of total rainfall and groundwater-level change before a typhoon event reaches the Zhuoshui River basin once the typhoon has made landfall on the east coast of Taiwan.     

Lava effusion — A slow fuse for paroxysms at Stromboli volcano?

The 2007 effusive eruption of Stromboli followed a similar pattern to the previous 2002–2003 episode. In both cases, magma ascent led to breaching of the uppermost part of the conduit forming an eruptive fissure that discharged lava down the Sciara del Fuoco depression. Both eruptions also displayed a ‘paroxysmal’ explosive event during lava flow output. From daily effusion rate measurements retrieved from helicopter- and satellite-based infrared imaging, we deduce that the cumulative volume of lava erupted before each of the two paroxysms was similar. Based on this finding, we propose a conceptual model to explain why both paroxysms occurred after this ‘threshold’ cumulative volume of magma was erupted. The gradual decompression of the deep plumbing system induced by magma withdrawal and eruption, drew deeper volatile-rich magma into the conduit, leading to the paroxysms. The proposed model might provide a basis for forecasting paroxysmal explosions during future effusive eruptions of Stromboli.     

The Breccia Museo formation, Campi Flegrei, southern Italy: geochronology, chemostratigraphy and relationship with the Campanian Ignimbrite eruption

The Breccia Museo is one of the most debated volcanic formations of the Campi Flegrei volcanic district. The deposit, made up of six distinctive stratigraphic units, has been interpreted by some as the proximal facies of the major caldera-forming Campanian Ignimbrite eruption, and by others as the product of several, more recent, independent and localized events. New geochemical and chemostratigraphical data and Ar–Ar age determinations for several units of the Breccia Museo deposits (~39 ka), correlate well with the Campanian Ignimbrite-forming eruption. The chemical zoning of the Breccia Museo deposits is interpreted here to be a consequence of a three-stage event that tapped a vertically zoned trachytic magma chamber. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

BMA集合预报在淮河流域应用及参数规律初探

以淮河流域吴家渡水文站作为试验站点,采用基于贝叶斯平均法(BMA)的集合预报模型处理来源于马斯京根法、一维水动力学方法、BPNN(Back Propagation Neural Network)的预报流量序列,通过分析BMA的参数以及其预报结果,对各方法在淮河典型站点流量预报中的适用性进行验证与分析.经2003—2016年19场洪水模拟检验可知,BMA模型能够有效避免模型选择带来的洪水预报误差放大效应,可以提供高精度、鲁棒性强的洪水预报结果.通过进一步比较各模型统计最优的频率与BMA权重值之间的相关性,发现权重值不适用于对单场洪水预报精度评定,而适用于描述多场洪水预报中,模型为最优的统计频率;基于大量先验信息,提前获取BMA的权重等参数,将是指导模型选择、降低洪水预报不确定性、改进洪水预报技术的有效手段.     

Complex effusive events at Kīlauea as documented by the GOES satellite and remote video cameras

 GOES provides thermal data for all of the Hawaiian volcanoes once every 15 min. We show how volcanic radiance time series produced from this data stream can be used as a simple measure of effusive activity. Two types of radiance trends in these time series can be used to monitor effusive activity: (a) Gradual variations in radiance reveal steady flow-field extension and tube development. (b) Discrete spikes correlate with short bursts of activity, such as lava fountaining or lava-lake overflows. We are confident that any effusive event covering more than 10,000 m² of ground in less than 60 min will be unambiguously detectable using this approach. We demonstrate this capability using GOES, video camera and ground-based observational data for the current eruption of Kīlauea volcano (Hawai'i). A GOES radiance time series was constructed from 3987 images between 19 June and 12 August 1997. This time series displayed 24 radiance spikes elevated more than two standard deviations above the mean; 19 of these are correlated with video-recorded short-burst effusive events. Less ambiguous events are interpreted, assessed and related to specific volcanic events by simultaneous use of permanently recording video camera data and ground-observer reports. The GOES radiance time series are automatically processed on data reception and made available in near-real-time, so such time series can contribute to three main monitoring functions: (a) automatically alerting major effusive events; (b) event confirmation and assessment; and (c) establishing effusive event chronology. Received: 12 January 1999 / Accepted: 13 July 1999     

Exploring the limits of identifying sub-pixel thermal features using ASTER TIR data

Understanding the characteristics of volcanic thermal emissions and how they change with time is important for forecasting and monitoring volcanic activity and potential hazards. Satellite instruments view volcanic thermal features across the globe at various temporal and spatial resolutions. Thermal features that may be a precursor to a major eruption, or indicative of important changes in an on-going eruption can be subtle, making them challenging to reliably identify with satellite instruments. The goal of this study was to explore the limits of the types and magnitudes of thermal anomalies that could be detected using satellite thermal infrared (TIR) data. Specifically, the characterization of sub-pixel thermal features with a wide range of temperatures is considered using ASTER multispectral TIR data. First, theoretical calculations were made to define a “thermal mixing detection threshold” for ASTER, which quantifies the limits of ASTER's ability to resolve sub-pixel thermal mixing over a range of hot target temperatures and % pixel areas. Then, ASTER TIR data were used to model sub-pixel thermal features at the Yellowstone National Park geothermal area (hot spring pools with temperatures from 40 to 90 °C) and at Mount Erebus Volcano, Antarctica (an active lava lake with temperatures from 200 to 800 °C). Finally, various sources of uncertainty in sub-pixel thermal calculations were quantified for these empirical measurements, including pixel resampling, atmospheric correction, and background temperature and emissivity assumptions.     

Clarifying the distal to proximal tephrochronology of the Millennium (B–Tm) eruption,Changbaishan Volcano,northeast China

Tephra dispersed during the Millennium eruption (ME), Changbaishan Volcano, NE China provides one of the key stratigraphic links between Asia and Greenland for the synchronization of palaeoenvironmental records. However, controversy surrounds proximal-distal tephra correlations because (a) the proposed proximal correlatives of the distal ME tephra (i.e. B–Tm) lack an unequivocal chronostratigraphic context, and (b) the ME tephra deposits have not been chemically characterized for a full spectrum of element using grain-specific techniques. Here we present grain-specific glass chemistry, including for the first time, single grain trace element data, for a composite proximal sequence and a distal tephra from Lake Kushu, northern Japan (ca. 1100 km away from Changbaishan). We demonstrate a robust proximal-distal correlation and that the Kushu tephra is chemically associated with the ME/B–Tm. We propose that three of the proximal pyroclastic fall units were erupted as part of the ME. The radiocarbon chronology of the Kushu sedimentary record has been utilised to generate a Bayesian age-depth model, providing an age for the Kushu tephra which is consistent with high resolution ages determined for the eruption and therefore supports our geochemical correlation. Two further Bayesian age-depth models were independently constructed each incorporating one of two ice-core derived ages for the B–Tm tephra, providing Bayesian modelled ages of 933–949 and 944–947 cal AD (95.4%) for the Kushu tephra. The high resolution ice-core tephra ages imported into the deposition models help test and ultimately constrain the radiocarbon chronology in this interval of the Lake Kushu sedimentary record. The observed geochemical diversity between proximal and distal ME tephra deposits clearly evidences the interaction of two compositionally distinct magma batches during this caldera forming eruption.