On the criteria to create a susceptibility map to debris flow at a regional scale using Flow-R

Studies on susceptibility to debris flows at regional scale(100-1000 km~2) are important for the protection and management of mountain areas. To reach this objective, routing models, mainly based on land topography, can be used to predict susceptible areas rapidly while necessitating few input data. In this research, Flow-R model is implemented to create the susceptibility map for the debris flow of the Vizze Valley(BZ, North-Eastern Italy; 134 km~2). The analysis considers the model application at local scale for three sub-catchments and then it explores the model upscaling at the regional scale by verifying two methods to generate the source areas of debris-flow initiation. Using data of an extreme event occurred in the Vizze Valley(4 August 2012) and historical information, the modeling verification highlights that the propagation parameters are relatively simple to set in order to obtain correct runout distances. A double DTM filtering-using a threshold for the upslope contributing area(0.1 km~2) and a threshold for the terrain-slope angle(15°)-provides a satisfactory prediction of source areas and susceptibility map within the geological conditions of the Vizze Valley.     

Trace elements in farmed and wild gilthead seabream, Sparus aurata

In the present study, we sought to determine the concentration of several trace elements (total and organic mercury, selenium, cadmium, lead, arsenic, copper, chromium, iron, manganese, molybdenum, vanadium and zinc) in muscle tissue of gilthead seabream (Sparus aurata), an edible finfish species that is widely cultured in the Mediterranean area. The phenomenon of bioaccumulation and bioamplification (especially of mercury) was investigated by comparing farmed fish with wild specimens of the same species. Farmed specimens showed mercury and arsenic concentrations significantly lower than wild specimens, and no relationship was found between mercury concentration and body size. The lower level of methylmercury in farmed fish has important implications for consumer health.     

Seismic fragility curves of as-built single-span masonry arch bridges

Masonry arch bridges are crucial elements in the railway transportation network throughout Europe. Although significant advances in seismic risk assessment of various bridge types have been made by developing fragility curves of generalized classes of structures, there are no comparable tools for masonry arch structures. In this context, this paper presents the construction of seismic fragility curves of single-span masonry bridges according to the limit analysis method. An iterative procedure is implemented to define the capacity curve of the equivalent single degree of freedom system through non-linear kinematic analysis. The process involves determination of the collapse mechanism, calculation of the limit load multiplier, and definition of the thrust line. The intrinsic variability of the seismic action is incorporated with the use of different sets of elastic spectra compatible with EC 8 Type-1 spectrum for various types of soil, with peak ground acceleration varying over the range 0.05–1.5 g. The fragility curves of the generalized classes of single-span masonry bridges are finally obtained from the effective ranges of the main geometric and material parameters affecting arch bridge capacity.     

Deterioration of Sediment Quality in Seagrass Meadows (<Emphasis Type="Italic">Posidonia oceanica</Emphasis>) Invaded by Macroalgae (<Emphasis Type="Italic">Caulerpa</Emphasis> sp.)

Species of the macroalgae Caulerpa sp. are increasingly being observed in meadows of the endemic Mediterranean seagrass Posidonia oceanica, and in particular Caulerpa taxifolia, has been considered as an invasive species leading to seagrass decline. Studies have so far failed to reveal the underlying mechanisms of the success of the macroalgae, and here, we examine how biogeochemical changes of the environment associated to indigenous (Caulerpa prolifera) and non-indigenous (Caulerpa racemosa and C. taxifolia) species affect the habitat of P. oceanica. Two of the species (C. prolifera and C. racemosa) affect the sediment biogeochemical conditions by increasing organic matter pools, microbial activity, and sulfide pools of the sediments, and limited effects were found for C. taxifolia. Biomass of the macroalgae contributed to the extent of impacts, and high sulfide invasion into the seagrasses and regression of the meadow were pronounced at the location with the highest Caulerpa biomass. This suggests that Caulerpa invasion contributes to seagrass decline probably because Caulerpa thrives better than the seagrasses in the modified environment.     

Water‐bottom multiple attenuation by Kirchhoff extrapolation

Despite being less general than 3D surface‐related multiple elimination (3D‐SRME), multiple prediction based on wavefield extrapolation can still be of interest, because it is less CPU and I/O demanding than 3D‐SRME and moreover it does not require any prior data regularization. Here we propose a fast implementation of water‐bottom multiple prediction that uses the Kirchhoff formulation of wavefield extrapolation. With wavefield extrapolation multiple prediction is usually obtained through the cascade of two extrapolation steps. Actually by applying the Fermat’s principle (i.e., minimum reflection traveltime) we show that the cascade of two operators can be replaced by a single approximated extrapolation step. The approximation holds as long as the water bottom is not too complex. Indeed the proposed approach has proved to work well on synthetic and field data when the water bottom is such that wavefront triplications are negligible, as happens in many practical situations.     

A neuro fuzzy approach to recognize rock magnetic and lithological patterns in a stratigraphic well from the Llanos Foreland Basin (Colombia)

The Neuro Fuzzy System (NFS) is a hybrid algorithm that combines fuzzy logic with neural networks. Since it can be used as a pattern recognition technique, we explore its potential to characterize the major lithological units encompassed by the first 512 m of the Colombian stratigraphic well Saltarin 1A (Guayabo and León Formations). Thus, we employ the NFS to infer the magnetic remanence S-ratio using bulk magnetic susceptibility (κ), κ-normalized saturation isothermal magnetization (SIRM κ) and/or volume of shale (V_sh) obtained from a gamma-ray log. The best results in terms of their corresponding Root Mean-Square Error (RMSE) values, throughout most of the upper Guayabo Formation, where magnetite seems to be an important magnetic phase, are attained with logκ and SIRM κ as input variables. Beyond 350 m downcore, the quality of the inference decreases over the León Formation, characterized by a significant presence of pyrrhotite. However, the extra input variable V_sh adjusts the inferred S-ratio to their experimental counterparts throughout this formation suggesting that the early diagenesis process that led to the formation of dispersed clay in these samples was also responsible for the formation of pyrrhotite. Hence the inclusion of manifold input data increases the ability of the net to predict S-ratio in complex geological settings with a sequence of changing lithologies, varying amounts and types of magnetic minerals, and different distributions of mineral grain sizes. In case these variables do not properly infer the actual S-ratio data, the extent of the different lithostratigraphic units would be still identifiable in some cases by the uneven quality of the correlation observed between inferred and experimental values.     

Numerical relationships between magnetic parameters measured in Quaternary sediments and global paleoclimatic proxies

The complexity of most geological and geophysical problems prompts sometimes the use of non linear mathematical methods to handle them. An adaptive neuro fuzzy inference system (ANFIS) that combines fuzzy logic with neural networks, is applied here to study a paleoclimate section from the Quaternary sedimentary fill of the Lake Mucubají (western Venezuela). The purpose of this work is to find a set of numerical relationships that could predict the possible connections between oxygen isotope (δ¹⁸O) values from two different locations in the northern hemisphere (Ammersee in southern Germany and an ice core from the Greenland Ice Core Project — GRIP) and rock-magnetic parameters measured in Mucubají samples (i.e. mass-specific magnetic susceptibility — χ, magnetic remanence S-ratio, mass-specific saturation isothermal remanent magnetization — SIRM and anhysteretic remanent magnetization — ARM). The best inferences in terms of coefficient of determionation R² and the Root Mean-Square Error (RMSE) are obtained using those magnetic data as input that include information about magnetite grain size distributions, e.g., SIRM and ARM in FIS structures [1χ, 4ARM] and [4ARM, 1SIRM]. A comparison between Ammersee and GRIP actual data, as well as their corresponding inferences for the FIS structure [4ARM, 1SIRM], reveals a reasonable good inference of global trends for both records, overlooking the regional and/or local paleoclimate forcings that might have affected Ammersee. A better correlation between global isotope paleoclimate records and magnetic proxies, is perhaps prevented by the role played by local and regional paleoclimate and tectonism in Mucubají. We also argue that the ratio of ARM over SIRM appears to be related in a complex way to the onset and to the end of the Younger Dryas. Our novel approach to the assessment of a specific paleoclimate case study shows the potential of the ANFIS technique in solving problems where traditional univariate and multivariate linear regression methods could prove inadequate.     

An advanced process for evaluating a linear dielectric constant–bulk electrical conductivity model using a capacitance sensor in field conditions

Abstract

The Hilhorst model was used to convert bulk electrical conductivity (σ_b) to pore water electrical conductivity (σ_p) under laboratory conditions by using the linear relationship between the soil dielectric constant (ε_b) and σ_b. In the present study, applying the linear relationship ε_b–σ_b to data obtained from field capacitance sensors resulted in strong positive autocorrelations between the residuals of that regression. We were able to derive an accurate offset of the relationship ε_b–σ_b and to estimate the evolution of σ_p over time by including a stochastic component to the linear model, rearranging it to a time-varying dynamic linear model (DLM), and using Kalman filtering and smoothing. The offset proved to vary for each depth in the same soil profile. A reason for this might be the changes in soil temperature along the soil profile.

Editor D. Koutsoyiannis; Associate editor M.D. Fidelibus     

Magma plumbing beneath Anak Krakatau volcano, Indonesia: evidence for multiple magma storage regions

Understanding magma plumbing is essential for predicting the behaviour of explosive volcanoes. We investigate magma plumbing at the highly active Anak Krakatau volcano (Indonesia), situated on the rim of the 1883 Krakatau caldera by employing a suite of thermobarometric models. These include clinopyroxene-melt thermobarometry, plagioclase-melt thermobarometry, clinopyroxene composition barometry and olivine-melt thermometry. Petrological studies have previously identified shallow magma storage in the region of 2–8 km beneath Krakatau, while existing seismic evidence points towards mid- to deep-crustal storage zone(s), at 9 and 22 km, respectively. Our results show that clinopyroxene in Anak Krakatau lavas crystallized at a depth of 7–12 km, while plagioclase records both shallow crustal (3–7 km) and sub-Moho (23–28 km) levels of crystallization. These magma storage regions coincide with well-constrained major lithological boundaries in the crust, implying that magma ascent and storage at Anak Krakatau is strongly controlled by crustal properties. A tandem seismic tomography survey independently identified a separate upper crustal (<7 km) and a lower to mid-crustal magma storage region (>7 km). Both petrological and seismic methods are sensitive in detecting magma bodies in the crust, but suffer from various limitations. Combined geophysical and petrological surveys, in turn, offer increased potential for a comprehensive characterization of magma plumbing at active volcanic complexes.