Tectonically driven deposition and landscape evolution within upland incised valleys: Ambra Valley fill,Pliocene–Pleistocene,Tuscany, Italy

Sedimentation in the upstream reaches of incised valleys is predominantly of alluvial origin and, in most cases, independent from relative sea‐level or lake‐level oscillations. Preserved facies distributions record the depositional response to a combination of allogenic factors, including tectonics, climate and landscape evolution. Tectonics drive fluvial aggradation and degradation through local changes in gradient, both longitudinal and transverse to the valley slope. This article deals with a Pliocene–Pleistocene fluvial valley fill developed in the north‐eastern shoulder of the Siena Basin (Northern Apennines, Italy). Evolution of the valley was not influenced by sea‐level or lake‐level changes and morphological and depositional evolution of valley resulted from extensional tectonics that gave rise to normal and oblique‐slip faults orthogonal and parallel to the valley axis. Data from both field observations and geophysical study are interpreted to develop a comprehensive tectono‐sedimentary model of coeval longitudinal and lateral tilting of the developing alluvial plain. Longitudinal tilting was generated by a transverse, upstream‐dipping normal fault that controlled the aggradation of fining‐upward strata sets. Upstream of the fault zone, valley back‐filling generated an architecture similar to that of classic, sea‐level‐controlled, coastal incised valleys. Downstream of the fault zone, valley down‐filling was related to an overwhelming sediment supply sourced and routed from the active fault zone itself. Lateral tilting was promoted by the activity of a fault oriented parallel to the valley axis, as well as by different offsets along near orthogonal faults. As a result, the valley trunk system experienced complex lateral shifts, which were governed by interacting fault‐generated subsidence and by the topographic confinement of progradational, flank‐sourced alluvial fans.     

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.     

Homotopy Perturbation Method‐Based Analytical Solution for Tide‐Induced Groundwater Fluctuations

The groundwater variations in unconfined aquifers are governed by the nonlinear Boussinesq's equation. Analytical solution for groundwater fluctuations in coastal aquifers under tidal forcing can be solved using perturbation methods. However, the perturbation parameters should be properly selected and predefined for traditional perturbation methods. In this study, a new dimensional, higher‐order analytical solution for groundwater fluctuations is proposed by using the homotopy perturbation method with a virtual perturbation parameter. Parameter‐expansion method is used to remove the secular terms generated during the solution process. The solution does not require any predefined perturbation parameter and valid for higher values of amplitude parameter A/D, where A is the amplitude of the tide and D is the aquifer thickness.     

Performance of “G-Pisa” ring laser gyro at the Virgo site

The ring laser gyroscope ??G-Pisa?? has been taking data inside the Virgo interferometer central area with the aim of performing high sensitivity measurements of rotations in the vertical as well as in the horizontal orientation. We discuss the main characteristics of the instrument, describing its mechanical design and presenting the measured sensitivity limit. By applying a simple effective model for the laser gyroscope, we show that the stability of the sensor above 10?s of integration time is mainly limited by backscattering effects. The horizontal rotation rate signal is also compared with the signals recorded by the Virgo environmental monitoring system and by a biaxial mechanical tiltmeter rigidly fixed on top of the gyrolaser mounting frame.     

A maritime decision support system to assess risk in the presence of environmental uncertainties: the REP10 experiment

The aim of this work is to report on an activity carried out during the 2010 Recognized Environmental Picture experiment, held in the Ligurian Sea during summer 2010. The activity was the first at-sea test of the recently developed decision support system (DSS) for operation planning, which had previously been tested in an artificial experiment. The DSS assesses the impact of both environmental conditions (meteorological and oceanographic) and non-environmental conditions (such as traffic density maps) on people and assets involved in the operation and helps in deciding a course of action that allows safer operation. More precisely, the environmental variables (such as wind speed, current speed and significant wave height) taken as input by the DSS are the ones forecasted by a super-ensemble model, which fuses the forecasts provided by multiple forecasting centres. The uncertainties associated with the DSS’s inputs (generally due to disagreement between forecasts) are propagated through the DSS’s output by using the unscented transform. In this way, the system is not only able to provide a traffic light map (run/not run the operation), but also to specify the confidence level associated with each action. This feature was tested on a particular type of operation with underwater gliders: the glider surfacing for data transmission. It is also shown how the availability of a glider path prediction tool provides surfacing options along the predicted path. The applicability to different operations is demonstrated by applying the same system to support diver operations.     

BET_VH: a probabilistic tool for long-term volcanic hazard assessment

In this paper, we illustrate a Bayesian Event Tree to estimate Volcanic Hazard (BET_VH). The procedure enables us to calculate the probability of any kind of long-term hazardous event for which we are interested, accounting for the intrinsic stochastic nature of volcanic eruptions and our limited knowledge regarding related processes. For the input, the code incorporates results from numerical models simulating the impact of hazardous volcanic phenomena on an area and data from the eruptive history. For the output, the code provides a wide and exhaustive set of spatiotemporal probabilities of different events; these probabilities are estimated by means of a Bayesian approach that allows all uncertainties to be properly accounted for. The code is able to deal with many eruptive settings simultaneously, weighting each with its own probability of occurrence. In a companion paper, we give a detailed example of application of this tool to the Campi Flegrei caldera, in order to estimate the hazard from tephra fall.     

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.     

Characterization of organic-rich mineral debris revealed by rapid glacier retreat,Indren Glacier,European Alps

In the summer of 2003 and 2004, characterized by a rapid glacier retreat, a stony surface covered by well-structured organic-rich mineral debris was observed very close to the Indren glacier terminus(Monte Rosa Massif, NW Italy, 3100 m ASL), on an area covered by the glacier tongue till the year before. The origin and type of this organicrich material were investigated, in order to detect their characteristics, potential sources and fate within the foreland system. The deposits were dated using Carbon-14 and analyzed for the chemical characteristics of the organic component, the elemental composition of the mineral fraction and presence of microbial markers. The material, granular and dark in color, had a total organic carbon(TOC) content ranging between 17.4 ± 0.39 and 28.1 ± 0.63 g kg-1 dry weight(dw), significantly higher than the surrounding glacial till(～ 1.4 g kg-1 dw), although only 0.33% of it was in water soluble form. Microbial carbon(C) and nitrogen(N) accounted for 10.6% and 3.13% of TOC and total N, respectively. Dissolved nitrogen(N), mainly present as ammonium, represented 2.40% of the total N. The low aromatic component and large presence of nitrogen(N)-derived compounds suggested that most of the organic carbon(OC) in these organic-rich mineral deposits was derived from microbial cells, although the high average radiocarbon age of about 2900 years may also point to the contribution of aeolian depositions of anthropogenic or natural origin. Elemental composition and the crustal enrichment factor of trace elements in the mineral fraction of the aggregates corroborated the hypothesis that most part of the accumulated material derived from ice meltwater. Some indicators of the colonization of these deposits by microbial communities were also reported, from the abundance of DNA and phylogenetic markers, to the presence of bacterial taxa commonly able to thrive in similar habitats. All these elements suggested that such kind of deposits may have a potential role as energy and nutrient sources in recently deglaciated areas, highlighting the necessity to better understand the processes underlying their formation and their evolution.     

Groundwater flow in the Venice lagoon and remediation of the Porto Marghera industrial area (Italy)

Hydrogeology Journal - This study aims to determine the groundwater flow in a large area of the Venice (northeast Italy) lagoon that is under great anthropogenic pressure, which is influencing the...     

Impact on loss/risk assessments of inter-model variability in vulnerability analysis

Fragility curves (FCs) constitute an emerging tool for the seismic risk assessment of all elements at risk. They express the probability of a structure being damaged beyond a specific damage state for a given seismic input motion parameter, incorporating the most important sources of uncertainties, that is, seismic demand, capacity and definition of damage states. Nevertheless, the implementation of FCs in loss/risk assessments introduces other important sources of uncertainty, related to the usually limited knowledge about the elements at risk (e.g., inventory, typology). In this paper, within a Bayesian framework, it is developed a general methodology to combine into a single model (Bayesian combined model, BCM) the information provided by multiple FC models, weighting them according to their credibility/applicability, and independent past data. This combination enables to efficiently capture inter-model variability (IMV) and to propagate it into risk/loss assessments, allowing the treatment of a large spectrum of vulnerability-related uncertainties, usually neglected. As case study, FCs for shallow tunnels in alluvial deposits, when subjected to transversal seismic loading, are developed with two conventional procedures, based on a quasi-static numerical approach. Noteworthy, loss/risk assessments resulting from such conventional methods show significant unexpected differences. Conventional fragilities are then combined in a Bayesian framework, in which also probability values are treated as random variables, characterized by their probability density functions. The results show that BCM efficiently projects the whole variability of input models into risk/loss estimations. This demonstrates that BCM is a suitable framework to treat IMV in vulnerability assessments, in a straightforward and explicit manner.