Olive tree phenology and climate variations in the Mediterranean area over the last two decades

The flowering characteristics of plant species of economic interest and the influence of climate on them are of great importance considering the implications for fruit setting and the final harvest: Olive is one of the typical species of the Mediterranean habitat. We have investigated the timing of olive full flowering during the anthesis period and flowering intensity over a period of 20 years (1990–2009), in three major cultivation areas of the Mediterranean basin: Italy, Spain and Tunisia. The importance of these characteristics from a bioclimatic point of view is considered. The biological behaviour was studied to determine its main relationships with temperature and water availability, considering also the different sub-periods and the bio-climatic variations during the study period. The flowering dates and pollen emissions show different behaviours for the Spanish monitoring area in comparison with the other two olive cultivation areas. In the Italian and Tunisian areas, the flowering period over the last decade has become earlier by about 5 and 7 days, respectively, in comparison to the previous decade. Moreover, pollen emissions have decreased in Perugia (Italy) and Zarzis (Tunisia) over the period of 2000–2009, while in Cordoba (Spain), they showed their highest values from 2005 to 2009. The climate analysis has shown an increase in temperature, which results in an increase in the growing degree days for the growth of the olive flower structures, particularly in the more northern areas monitored. Although the olive tree is a parsimonious water consumer that is well adapted to xeric conditions, the increase in the potential evapotranspiration index over the last decade in the Italian and Tunisian olive areas might create problems for olive groves without irrigation, with a negative influence on the flowering intensity. Overall, in all of these Mediterranean monitoring areas, the summer water deficit is an increasingly more important parameter in comparison to the winter parameters, which confirms that the winter period is not as limiting as the summer period for olive tree cultivation in these Mediterranean areas.     

Mapping fractional landscape soils and vegetation components from Hyperion satellite imagery using an unsupervised machine-learning workflow

An unsupervised machine-learning workflow is proposed for estimating fractional landscape soils and vegetation components from remotely sensed hyperspectral imagery. The workflow is applied to EO-1 Hyperion satellite imagery collected near Ibirací, Minas Gerais, Brazil. The proposed workflow includes subset feature selection, learning, and estimation algorithms. Network training with landscape feature class realizations provide a hypersurface from which to estimate mixtures of soil (e.g. 0.5 exceedance for pixels: 75% clay-rich Nitisols, 15% iron-rich Latosols, and 1% quartz-rich Arenosols) and vegetation (e.g. 0.5 exceedance for pixels: 4% Aspen-like trees, 7% Blackberry-like trees, 0% live grass, and 2% dead grass). The process correctly maps forests and iron-rich Latosols as being coincident with existing drainages, and correctly classifies the clay-rich Nitisols and grasses on the intervening hills. These classifications are independently corroborated visually (Google Earth) and quantitatively (random soil samples and crossplots of field spectra). Some mapping challenges are the underestimation of forest fractions and overestimation of soil fractions where steep valley shadows exist, and the under representation of classified grass in some dry areas of the Hyperion image. These preliminary results provide impetus for future hyperspectral studies involving airborne and satellite sensors with higher signal-to-noise and smaller footprints.     

Measured performance of the application of EGNOS in the road traffic sector

European Geostationary Navigation Overlay Service (EGNOS) is a satellite-based system developed to improve the performance of GPS in the European region. It not only enhances the estimated positioning accuracy but also provides an integrity solution. We assess the EGNOS performance through analysis of real measurements, performed in different road user environments. We investigate the use of the integrity concept in future Global Navigation Satellite System (GNSS)-based applications in the road environment, considering both suburban and dense urban areas. The analysis is motivated by the fact that there is an increasing number of road applications, such as billing system, transportation of dangerous goods, remote tracking of trucks and snow plows, fleet management and “pay as you go” car insurances, where the system liability has to be guaranteed. The scope of the analysis is to investigate to which extent the use of the integrity concept can be used for such purpose; the assessment is based on real measurement campaigns in representative environments, providing statistical results in terms of accuracy and integrity, and in a wider sense of the feasibility of the use of EGNOS for augmenting the reliability of GNSS positioning for road applications.     

Conceptually-based shot noise modeling of streamflows at short time interval

A conceptual-stochastic approach to short time runoff data modelling is proposed, according to the aim of reproducing the hydrological aspects of the streamflow process and of preserving as much as possible the dynamics of the process itself. This latter task implies preservation of streamflow characteristics at higher scales of aggregation and, within a conceptual framework, involves compatibility with models proposed for the runoff process at those scales. At a daily time scale the watershed response to the effective rainfall is considered as deriving from the response of three linear reservoirs, respectively representing contributions to streamflows of large deep aquifers, with over-year response lag, of aquifers which run dry by the end of the dry season and of subsurface runoff. The surface runoff component is regarded as an uncorrelated point process. Considering the occurrences of effective rainfall events as generated by an independent Poisson process, the output of the linear system represents a conceptually-based multiple shot noise process. Model identification and parameter estimation are supported by information related to the aggregated runoff process, in agreement to the conceptual framework proposed, and this allows parameter parsimony, efficient estimation and effectiveness of the streamflow reproduction. Good performances emerged from the model application and testing made with reference to some daily runoff series from Italian basins.     

Converted-wave imaging in anisotropic media: theory and case studies

Common‐conversion‐point binning associated with converted‐wave (C‐wave) processing complicates the task of parameter estimation, especially in anisotropic media. To overcome this problem, we derive new expressions for converted‐wave prestack time migration (PSTM) in anisotropic media and illustrate their applications using both 2D and 3D data examples. The converted‐wave kinematic response in inhomogeneous media with vertical transverse isotropy is separated into two parts: the response in horizontally layered vertical transverse isotrophy media and the response from a point‐scatterer. The former controls the stacking process and the latter controls the process of PSTM. The C‐wave traveltime in horizontally layered vertical transverse isotrophy media is determined by four parameters: the C‐wave stacking velocity V_C2, the vertical and effective velocity ratios γ₀ and γ_eff, and the C‐wave anisotropic parameter χ_eff. These four parameters are referred to as the C‐wave stacking velocity model. In contrast, the C‐wave diffraction time from a point‐scatterer is determined by five parameters: γ₀, V_P2, V_S2, η_eff and ζ_eff, where η_eff and ζ_eff are, respectively, the P‐ and S‐wave anisotropic parameters, and V_P2 and V_S2 are the corresponding stacking velocities. V_P2, V_S2, η_eff and ζ_eff are referred to as the C‐wave PSTM velocity model. There is a one‐to‐one analytical link between the stacking velocity model and the PSTM velocity model. There is also a simple analytical link between the C‐wave stacking velocities V_C2 and the migration velocity V_Cmig, which is in turn linked to V_P2 and V_S2. Based on the above, we have developed an interactive processing scheme to build the stacking and PSTM velocity models and to perform 2D and 3D C‐wave anisotropic PSTM. Real data applications show that the PSTM scheme substantially improves the quality of C‐wave imaging compared with the dip‐moveout scheme, and these improvements have been confirmed by drilling.     

Performance of a base isolator with shape memory alloy bars

A new and innovative base isolation device is introduced in this paper based on extensive research carried out by the authors and their co-workers. A prototype of the device was built and experimentally tested on the shaking table. The new base isolation device consists of two disks, one vertical cylinder with an upper enlargement sustained by three horizontal cantilevers, and at least three inclined shape memory alloy (SMA) bars. The role of the SMA bars is to limit the relative motion between the base and the superstructure, to dissipate energy by their super-elastic constitutive law and to guarantee the re-centring of the device. To verify the expected performance, a prototype was built and tested under sinusoidal waves of displacement of increasing frequency with different amplitudes. It is shown that the main feature of the proposed base isolation device is that for cyclic loading, the super-elastic behavior of the alloy results in wide load-displacement loops, where a large amount of energy is dissipated.     

Spectroscopic Characterization of Organic Structures and Organic‐Inorganic Interactions in Paper Mill Sludge

The organic composition and organic‐inorganic interaction in paper mill sludge (PS) solvent extracts (hexane, ethyl acetate, acetone and ethanol) and humic fractions, humic acid (HA) and humin (HU) were studied by electron paramagnetic resonance spectroscopy (EPR), proton and carbon‐13 nuclear magnetic resonance spectroscopy (¹H NMR; ¹³C NMR), Fourier‐transformed infrared spectroscopy (FTIR), and ultraviolet‐visible spectroscopy (UV‐vis). The strategy of fractionating the PS, sequentially, with organic solvents of increasing polarity is a reliable analytical procedure for humic substance sample separation because it results in more purified fractions. FTIR, ¹H NMR and ¹³C NMR results showed that hexane extract consisted mainly of aliphatic hydrocarbon structures. Their contents in the extracts decreased as the polarity of the extracting solvent increased and the content of oxygen functional groups increased. Carboxylic and carboxylate functional groups were found in the acetone extract, and ester and ether functions were predominantly found in the ethanol extract. EPR spectra revealed some Fe³⁺ complexes with rhombic structure (g₁ = 4.3; g₂ = 9.0) in the humic fractions and in all solvent extracts, except hexane. Quasi‐octahedral Fe³⁺ complexes (g = 2.3; ΔH_pp ≤ 400 G) were found in the HU fraction and in the acetone extract. The organic free radical content in the HA fraction was higher than the non‐fractionated PS sample and HU fraction.     

Three-dimensional tomographic inversion of the seismic velocity structure of the crust and upper mantle of northwestern Nicaragua

Journal of Seismology - A three-dimensional tomographic image of the seismic velocity structure in the crust and upper mantle of northwestern Nicaragua was performed using the back-projection...     

Understanding the statistical properties of the percent model affinity index can improve biomonitoring related decision making

The percent model affinity (PMA) index is used to measure the similarity of two probability profiles representing, for example, an ideal profile (i.e. reference condition) and a monitored profile (i.e. possibly impacted condition). The goal of this work is to study the effects of sample size, evenness, true value of the index and number of classes on the statistical properties of the estimator of the PMA index. We derive and extend previous formulas of the expectation and variance of the estimator for estimated monitored profile and fixed reference profile. Using the obtained extension, we find that the estimator is asymptotically unbiased, converging faster when the profiles differ. When both profiles are estimated, we calculate the expectation using transformation rules for expectation and in addition derive the formula for the estimator’s variance. Since the computation of the probabilities in the variance formula is slow, we study the behavior of the variance with simulation experiments and assess whether it could be approximated with the variance for the fixed reference profile. Finally, we provide a set of recommendations for the users of the PMA index to avoid the most common caveats of the index.