Modeling ground deformations of Panarea volcano hydrothermal/geothermal system (Aeolian Islands, Italy) from GPS data

Panarea volcano (Aeolian Islands, Italy) was considered extinct until November 3, 2002, when a submarine gas eruption began in the area of the islets of Lisca Bianca, Bottaro, Lisca Nera, Dattilo, and Panarelli, about 2.5 km east of Panarea Island. The gas eruption decreased to a state of low degassing by July 2003. Before 2002, the activity of Panarea volcano was characterized by mild degassing of hydrothermal fluid. The compositions of the 2002 gases and their isotopic signatures suggested that the emissions originated from a hydrothermal/geothermal reservoir fed by magmatic fluids. We investigate crustal deformation of Panarea volcano using the global positioning system (GPS) velocity field obtained by the combination of continuous and episodic site observations of the Panarea GPS network in the time span 1995–2007. We present a combined model of Okada sources, which explains the GPS results acquired in the area from December 2002. The kinematics of Panarea volcano show two distinct active crustal domains characterized by different styles of horizontal deformation, supported also by volcanological and structural evidence. Subsidence on order of several millimeters/year is affecting the entire Panarea volcano, and a shortening of 10⁻⁶ year⁻¹ has been estimated in the Islets area. Our model reveals that the degassing intensity and distribution are strongly influenced by geophysical-geochemical changes within the hydrothermal/geothermal system. These variations may be triggered by changes in the regional stress field as suggested by the geophysical and volcanological events which occurred in 2002 in the Southern Tyrrhenian area.     

Investigating on the 1920 Garfagnana earthquake (Mw=6.5): Evidences of site effects in Villa Collemandina (Tuscany,Italy)

This paper presents a comprehensive ground response study for the municipality of Villa Collemandina in Northern Tuscany (Italy). This site was selected following a macroseismic analysis of the 1920 Garfagnana earthquake (M_w=6.5), which, at Villa Collemandina, produced damage and losses that were larger than at any other site near the earthquake epicentre, thus indicating the presence of possible site effects. Hence, both experimental and numerical methods are applied in order to investigate the ground response at different locations within the Villa Collemandina municipality. Results obtained from the spectral analysis of earthquake recordings using the reference site method and those from a 2-dimensional dynamic simulation reveal the presence of site effects due to the buried geomorphology (basin-like effects), allowing us to explain the severe damage and losses produced by the 1920 Garfagnana earthquake. As a further result, horizontal to vertical spectral ratio techniques and 1D soil modelling are proved to be inadequate for an effective characterization of the ground response at sites that, like Villa Collemandina, present a complex local geology.     

Uncertainties in probability of occurrence of strong earthquakes for fault sources in the Central Apennines,Italy

Using the characteristic earthquake model, we calculate the probability of occurrence of earthquakes M _w > 5.5 for individual fault sources in the Central Apennines for the 30-year period (2007–2037). We show the effect of time-dependent and time-independent occurrence (Brownian passage time (BPT) and Poisson) models together with uncertain slip rates and uncertain maximum magnitudes and, hence, uncertain recurrence times. In order to reduce the large prior geological slip rate uncertainty distribution for most faults, we obtain a posterior slip rate uncertainty distribution using a likelihood function obtained from regional historical seismicity. We assess the uncertainty of maximum magnitude by assuming that the uncertainty in fault width and length are described by a normal distribution with standard deviation equal to ±20% of the mean values. We then estimate the uncertainties of the 30-year probability of occurrence of a characteristic event using a Monte Carlo procedure. Uncertainty on each parameter is represented by the 16th and the 84th percentiles of simulated values. These percentiles bound the range that has a 68% probability of including the real value of the parameter. We do these both for the Poisson case and for the BPT case by varying the aperiodicity parameter (α value) using the values 0.3, 0.5, and 0.7. The Bayesian posterior slip rate uncertainties typically differ by a factor of about 2 from the 16th to the 84th percentile. Occurrence probabilities for the next 30 years at the 84th percentile typically range from 1% to 2% for faults where the Poisson model dominates and from 2% to 21% where one of the BPT models dominates. The uncertainty in occurrence probability under the time-dependent hypothesis is very large, when measured by the ratio of the 84th to the 16th percentile, frequently being as much as two orders of magnitude. On the other hand, when measured by standard deviation, these standard deviations range from 2% to 6% for those faults whose elapsed time since previous event is large, but always 2% or less for faults with relatively recent previous occurrence, because the probability of occurrence is always small.     

Adjoint free four-dimensional variational data assimilation for a storm surge model of the German North Sea

In this paper, a data assimilation scheme based on the adjoint free Four-Dimensional Variational(4DVar) method is applied to an existing storm surge model of the German North Sea. To avoid the need of an adjoint model, an ensemble-like method to explicitly represent the linear tangent equation is adopted. Results of twin experiments have shown that the method is able to recover the contaminated low dimension model parameters to their true values. The data assimilation scheme was applied to a severe storm surge event which occurred in the North Sea in December 5, 2013. By adjusting wind drag coefficient, the predictive ability of the model increased significantly. Preliminary experiments have shown that an increase in the predictive ability is attained by narrowing the data assimilation time window.     

Rainfall-induced shallow landslides: a model for the triggering mechanism of some case studies in Northern Italy

The article relates the main findings of a recent investigation aimed at modeling the triggering of shallow landslides. A simplified model for assessing the safety factor of potentially unstable slopes, directly related with rainfall trends, was developed. Based on the geometric characteristics of the slope, the geotechnical properties, and strength parameters of the soil, the model makes it possible to define a safety factor of a slope as a function of time. The model is based on the limit equilibrium method and takes into account the seepage of underground water. The safety factor is, in turn, related to the seasonal rainfall. The model was applied on a local scale to some historical cases which had occurred recently in Northern Italy. The paper shows how the results of the application of the model on a local scale achieve a good agreement between the instability condition and the real date of each considered event.     

Forest Fire Alert System: a Geo Web GIS prioritization model considering land susceptibility and hotspots – a case study in the Carajás National Forest,Brazilian Amazon

To increase the monitoring potential of forest fires, an alert classification methodology using satellite-mapped hotspots has been established to help forest managers in the prioritization of which hotspot to be verified in the field, thus potentially improving the distribution of fire-fighting resources. A computer application was developed based on web-distributed geographical information technology whose main function is to interact automatically generated satellite hotspots and risk areas indicated in fire-susceptibility maps and classify them into five alert levels. The location of the hotspots is available continuously every 4 h, and a susceptibility map is produced daily through map algebra algorithm, which uses static (topography, vegetation and land use) and dynamic (weather) variables. Every process runs through automated geoprocessing routines. The methodology was tested during the dry period of 2007 in the Carajás National Forest, in the Brazilian Amazon, within an area of 400,000 ha. It is a critical area constantly threatened by fires caused by invasions and deforestation owing to intense agribusiness advances and mining activities in its surroundings. This situation results in observations of many hotspots inside the study area for the same day and almost the same time period, in places of extreme opposites, demanding complex rapid analysis and hindering the decision of the displacement of fire-fighting teams. Further, a major mining company operates within the National Forest area, maintaining actions of protection as part of its environmental mining license. Results are presented under three aspects: (i) the credibility of the daily susceptibility map (algorithm), which showed strong correlation between areas of greatest risks and the confirmed forest fires; (ii) the reliability of hotspots (alert levels), confirming 71% of fires; (iii) accuracy in the decision of which hotspot to be checked, which revealed the same number of verifications at different alert levels, 82% confirmed alert 5 hotspots (maximum) and only 50% from alert 1 (minimum), resulting in faster fire-fighting actions, minimizing burned areas and, in some cases, allowing fire control before its spreading. Therefore, the methodology demonstrated that GIS routines are able to determine the relationship between a reality-based, interpreted susceptibility map of the area and satellite-generated hotspots, highlighting the ones of highest hazard level through the alert classification, becoming an important tool to help decisions from the fire-control center, especially for high-risk regions. The methodology may be extrapolated to other forested areas.     

Geophysical-Archaeological Survey in Lake Tequesquitengo,Morelos, Mexico

In August 2009, a marine geophysical survey was conducted in Lake Tequesquitengo (located in the state of Morelos, Mexico) to delineate the extent of the remains of a small town that has been submerged since the mid 19th century. The survey consists of the acquisition and mapping of magnetic, single beam bathymetric and side-scan sonar data. A dual receiver marine GPS navigation system was used to position the boat during the survey. Except for the larger structural remains that are visible on the side scan sonar images, the magnetic anomaly map proved to be most useful in delineating the extent of the town. These anomalies exhibit short wavelength components in the area surrounding a submerged church, with the shortest wavelength components being confined to the area immediately east of the church. These short wavelength components are only observed near the church; therefore, we propose that they delineate the buried remnants of the submerged town.     

Distinguishing the Regional Atmospheric Controls on Precipitation Isotopic Variability in the Central-Southeast Portion of Brazil

Precipitation isotope ratios (O and H) record the history of water phase transitions and fractionation processes during moisture transport and rainfall formation. Here, we evaluated the isotopic composition of precipitation over the central-southeastern region of Brazil at different timescales. Monthly isotopic compositions were associated with classical effects (rainfall amount, seasonality, and continentality), demonstrating the importance of vapor recirculation processes and different regional atmospheric systems (South American Convergence Zone-SACZ and Cold Fronts-CF). While moisture recycling and regional atmospheric processes may also be observed on a daily timescale, classical effects such as the amount effect were not strongly correlated (δ¹⁸O-precipitation rate r ≤ –0.37). Daily variability revealed specific climatic features, such as δ¹⁸O depleted values (~ –6‰ to –8‰) during the wet season were associated with strong convective activity and large moisture availability. Daily isotopic analysis revealed the role of different moisture sources and transport effects. Isotope ratios combined with d-excess explain how atmospheric recirculation processes interact with convective activity during rainfall formation processes. Our findings provide a new understanding of rainfall sampling timescales and highlight the importance of water isotopes to decipher key hydrometeorological processes in a complex spatial and temporal context in central-southeastern Brazil.