Geological and hydrogeological reconstruction of the main aquifers of the Maltese islands

Hydrogeology Journal - Geological and hydrogeological conceptualizations of the five main aquifers of Malta were performed by means of characterization of the groundwater bodies’ geometries...     

Recent innovations in hazard and risk analysis

Air pollution has been a major transboundary problem and a matter of global concern for decades. Climate change and air pollution are closely coupled. Just as air pollution can have adverse effects on human health and ecosystems, it can also impact the earth’s climate. As we enter an era of rapid climate change, the implications for air quality need to be better understood, both for the purpose of air quality management and as one of the societal consequences of climate change. In this study, an attempt has been made to estimate the current air quality to forecast the air quality index of an urban station Kolkata (22.65°N, 88.45°E), India for the next 5 years with neural network models. The annual and seasonal variability in the air quality indicates that the winter season is mostly affected by the pollutants. Air quality index (AQI) is estimated as a geometric mean of the pollutants considered. Different neural network models are attempted to select the best model to forecast the AQI of Kolkata. The meteorological parameters and AQI of the previous day are utilized to train the models to forecast the AQI of the next day during the period from 2003 to 2012. The selection of the best model is made after validation with observation from 2013 to 2015. The radial basis functional (RBF) model is found to be the best network model for the purpose. The RBF model with various architectures is tried to obtain precise forecast with minimum error. RBF of 5:5-91-1:1 structure is found to be the best fit for forecasting the AQI of Kolkata.     

New discoveries of vertebrate remains from the Triassic of Riba de Santiuste,Guadalajara (Spain)

The palaeontological sites of Riba de Santiuste and Sienes (Riba de Santiuste area) are located in the province of Guadalajara, Spain. They include a stratigraphic interval in Muschelkalk facies belonging to the “Cuesta del Castillo Sandstones” Formation and “Royuela Dolostones, Marls and Mudstones” Formation. These sites include numerous fossil plants, direct vertebrate remains, and vertebrate swim traces. The vertebrate remains correspond to a multitude of anatomical elements of Sauropterygia (Nothosauroidea, Placodontia) and possible Archosauria (Rauisuchia) remains. The fossil material attributed to nothosaurs includes teeth, coracoids, a thoracic vertebra, some isolated vertebral centra, humerus, rib fragments, and some dorsal and caudal vertebrae. The remains attributed to placodonts correspond to fragments of skull, quadrate, teeth and osteoderms. Other undetermined sauropterygian remains, such as ulnas, fragments of long bones, fragments of ribs, and articular facets of ribs have been also recovered. Additionally, a fragment of mandible and an intervertebral disk of indeterminate reptiles whose size could be compatible with archosaurs are also described. These bones are exceptionally well-preserved because the fossilization processes have preserved the microstructure of the tissues. The sites also show vertebrate traces, with parallel scratch impressions interpreted as swim traces. The relative stratigraphic position and the palaeontological content of these sites suggest a Ladinian age (Middle Triassic). The interpretation of the sedimentary facies here described also suggests that the sites could correspond to detrital-carbonate mixed deposits of coastal intertidal to supratidal environments.     

Machine learning for graph-based representations of three-dimensional discrete fracture networks

Structural and topological information play a key role in modeling flow and transport through fractured rock in the subsurface. Discrete fracture network (DFN) computational suites such as dfnWorks (Hyman et al. Comput. Geosci. 84, 10–19 2015) are designed to simulate flow and transport in such porous media. Flow and transport calculations reveal that a small backbone of fractures exists, where most flow and transport occurs. Restricting the flowing fracture network to this backbone provides a significant reduction in the network’s effective size. However, the particle-tracking simulations needed to determine this reduction are computationally intensive. Such methods may be impractical for large systems or for robust uncertainty quantification of fracture networks, where thousands of forward simulations are needed to bound system behavior. In this paper, we develop an alternative network reduction approach to characterizing transport in DFNs, by combining graph theoretical and machine learning methods. We consider a graph representation where nodes signify fractures and edges denote their intersections. Using random forest and support vector machines, we rapidly identify a subnetwork that captures the flow patterns of the full DFN, based primarily on node centrality features in the graph. Our supervised learning techniques train on particle-tracking backbone paths found by dfnWorks, but run in negligible time compared to those simulations. We find that our predictions can reduce the network to approximately 20% of its original size, while still generating breakthrough curves consistent with those of the original network.     

Robust iterative schemes for non-linear poromechanics

We consider a non-linear extension of Biot’s model for poromechanics, wherein both the fluid flow and mechanical deformation are allowed to be non-linear. Specifically, we study the case when the volumetric stress and the fluid density are non-linear functions satisfying certain assumptions. We perform an implicit discretization in time (backward Euler) and propose two iterative schemes for solving the non-linear problems appearing within each time step: a splitting algorithm extending the undrained split and fixed stress methods to non-linear problems, and a monolithic L-scheme. The convergence of both schemes are shown rigorously. Illustrative numerical examples are presented to confirm the applicability of the schemes and validate the theoretical results.     

Deep-seated gravitational slope deformations triggered by extreme rainfall and agricultural practices (eastern Michoacan,Mexico)

The study of deep-seated gravitational slope deformations (DSGSD) in Mexico is scarce; therefore, their localization and causes are highly overlooked. The present paper examines the characterization of the DSGSD of Jungapeo and Las Pilas in eastern Michoacan state, currently active and endangering their inhabitants. An integrated study, including detailed lithology, morpho-structural inventories, analysis of land use, and pluviometric regime, was performed and complemented with differential global positioning system monitoring networks. Both landslides developed over highly weathered volcano-sedimentary rocks. On the one hand, the Jungapeo landslide has an estimated volume of 990,455 m³ with steady decreasing velocity rates from 41 to 15 cm/month in the first monitoring period to 13–3 cm/month in the last one. On the other hand, the Las Pilas landslide estimated volume is about 1,082,467 m³ with a stable velocity rate of 1.3 to 0.1 cm/month. Despite the multi-storeyed style of activity, two behaviors of instability were distinguished: slow deformation and secondary landslide stages. The conditioning factors for slow deformation in both DSGSD are the combination of weathered lithology with clay- and sand-rich content, and the shift toward intensive monoculture. The triggering factor is related to excess water produced by an inefficient flood-irrigation system that also generates an atypical acceleration behavior in both landslides during the dry season. The DSGSD activity thus predisposes the generation of tension cracks and secondary scarps from which the collateral landslides are triggered by atypical rainfall, such as that of 2010.     

Full waveform inversion in the time lapse mode applied to CO2 storage at Sleipner

Carbon capture and storage is a viable greenhouse gas mitigation technology and the Sleipner CO₂ sequestration site in the North Sea is an excellent example. Storage of CO₂ at the Sleipner site requires monitoring over large areas, which can successfully be accomplished with time lapse seismic imaging. One of the main goals of CO₂ storage monitoring is to be able to estimate the volume of the stored CO₂ in the reservoir. This requires a parametrization of the subsurface as exact as possible. Here we use elastic 2D time‐domain full waveform inversion in a time lapse manner to obtain a P‐wave velocity constrain directly in the depth domain for a base line survey in 1994 and two post‐injection surveys in 1999 and 2006. By relating velocity change to free CO₂ saturation, using a rock physics model, we find that at the considered location the aquifer may have been fully saturated in some places in 1999 and 2006.     

Rock-magnetic and paleomagnetic results from the Tepic-Zacoalco rift region (western Mexico)

A rock-magnetic and paleomagnetic investigation was carried out on eleven Pleistocene and Pliocene ⁴⁰Ar/³⁹Ar dated lava flows from the Tepic-Zacoalco rift region in the western sector of the Trans-Mexican Volcanic Belt (TMVB) with the aim of obtaining new paleomagnetic data from the study region and information about the Earth’s magnetic field recorded in these rocks. Rock-magnetic experiments including measurement of thermomagnetic curves, hysteresis parameters and isothermal remanence acquisition curves were carried out to find out the carriers of remanent magnetisation and to determine their domain structure. Although some samples were characterised by the presence of a single ferromagnetic phase (magnetite), in most cases more phases were observed. Analysis of hysteresis parameters showed a mixture of single domain and multidomain particles, the fraction of the latter varying between 40% and 80%. Paleomagnetic results were obtained in all sites, although in 7 sites characteristic remanence directions and remagnetisation circles had to be combined in order to calculate site means. The six Pliocene sites not showing intermediate polarity yielded a paleomagnetic pole (latitude ? = 81.1°, longitude λ = 94.3°) which roughly agrees with the expected one. Paleomagnetic directions do not indicate significant vertical-axis block rotations in the western TMVB area. Reversed polarities observed can be correlated to the Gilbert chron, normal polarities to the Gauss chron or the Brunhes chron and intermediate polarities to the Cochiti-Gilbert or the Gilbert-Gauss transition. The reversed or intermediate polarity magnetisation recorded in one of the sites (542 ± 24 ka) corresponds either to the West Eifel 4 or the West Eifel 5 excursion, while the reversed polarity observed in the other site (220 ± 36 ka) very likely provides new evidence for the Pringle Falls excursion or the event recorded in the Mamaku ignimbrite.     

Effect of extraction-method,period of incubation and tidal emersion on the viability of haemocytes from oysters

The impacts of pollution on marine organisms are often investigated using the viability of their haemocytes. Although this assay is routinely used in monitoring, field and laboratory experimentation, there has been less effort in further optimizing procedures to reduce artefacts and facilitate sampling over large geographic areas.     

Assessment of terrestrial laser scanning technology for obtaining high‐resolution DEMs of soils

Terrestrial Laser Scanners (TLS) provide a non‐contact method to measure soil microtopography of relatively large surface areas. The appropriateness of the technology in relatation to the derived Digital Elevation Models (DEM) however has not been reported. The suitability of TLS for soil microtopography measurements was tested on‐field for three large soil surface areas in agricultural fields. The acquired point clouds were filtered with a custom cloud import algorithm, and converted into digital elevation models (DEM) of different resolutions. To assess DEM quality, point clouds measured from different viewpoints were statistically compared. The statistical fit between point clouds from different viewpoints depends on spatial resolution of the DEM. The best results were obtained at the higher resolutions (0.02 to 0.04 cm), where less than 5 % of the grid cells showed significant differences between one viewpoint and the next (p < 0.01). Copyright © 2012 John Wiley & Sons, Ltd.