Longshore drift estimation using fluorescent tracers: New insights from an experiment at Comporta Beach, Portugal

A fluorescent sand-tracer experiment was performed at Comporta Beach (Portugal) with the aim of acquiring longshore sediment transport data on a reflective beach, the optimization of field and laboratory tracer procedures and the improvement of the conceptual model used to support tracer data interpretation.

The field experiment was performed on a mesotidal reflective beach face in low energetic conditions (significant wave height between 0.4 and 0.5 m). Two different colour tracers (orange and blue) were injected at low tide and sampled in the two subsequent low tides using a high resolution 3D grid extending 450 m alongshore and 30 m cross-shore. Marked sand was detected using an automatic digital image processing system developed in the scope of the present experiment.

Results for the two colour tracers show a remarkable coherence, with high recovery rates attesting data validity. Sand tracer displayed a high advection velocity, but with distinct vertical distribution patterns in the two tides: in the first tide there was a clear decrease in tracer advection velocity with depth while in the second tide, the tracer exhibited an almost uniform vertical velocity distribution. This differing behaviour suggests that, in the first tide, the tracer had not reached equilibrium within the transport system, pointing to a considerable time lag between injection and complete mixing. This issue has important implications for the interpretation of tracer data, indicating that short term tracer experiments tend to overestimate transport rates. In this work, therefore, longshore estimates were based on tracer results obtained during the second tide.

The estimated total longshore transport rate at Comporta Beach was 2 × 10^− 3 m³/s, more than four times larger than predicted using standard empirical longshore formulas. This discrepancy, which results from the unusually large active moving layer observed during the experiment, confirms the idea that most common longshore transport equations under-estimate total sediment transport in plunging/surging waves.     

A six-step practical approach to semivariogram modeling

Geostatistical prediction and simulation are being increasingly used in the earth sciences and engineering to address the imperfect knowledge of attributes that fluctuate over large areas or volumes—pollutant concentration, electromagnetic fields, porosity, thickness of a geological formation. Central to the application of such techniques is the need to know the spatial continuity, knowledge that is commonly condensed in the form of covariance or semivariogram models. Their preparation is subdivided here into the following steps: (1) Data editing, (2) Exploratory data analysis, (3) Semivariogram estimation, (4) Directional investigation, (5) Simple modeling, (6) Nested modeling. I illustrate these stages practically with a real data set from a geophysical survey from Elk County, Kansas, USA. The applicability of the approach is not limited by the physical nature of the attribute of interest.     

Study of Metal Distribution in Raw and Screened Swine Manure

The growth of industrial swine production over the last few years has led to a growth in concern over effluents generated by the activity. Several elements, mainly toxic metals, can be present in swine wastewater and can have a serious environmental impact. It is important, therefore, to know the metal concentration before the discharge of wastewater. In this work the temporal metal distribution in swine manure and its potential reduction using coarse (2 mm) and fine (<0.45 μm) liquid‐solid separation techniques were investigated. In order to do this, different swine manure sample preparation methods for Al, Ba, Cd, Co, Cr, Cu, Fe, Mg, Mn, Ni, Pb, Sr and Zn determination by Inductively Coupled Plasma Optical Emission Spectrometry (ICP OES) were tested. The acid mixtures used to digest the manure sample significantly affected the metal recovery. Good analyte recoveries were observed with nitric acid/hydrogen peroxide mixtures or nitric acid/perchloric acid mixtures. Sulfuric acid/hydrogen peroxide mixtures produced inconsistent results and poor recoveries, mainly for Ba and Pb. It was observed that metal concentrations in swine manure varied greatly with time, up to one order of magnitude, due to changes in swine production such as feed and animal numbers. Metals concentrations observed in the raw wastewater exceeded Brazilian limits for discharge into water bodies and recommendations for agricultural use. Results obtained from the liquid‐solid separation study showed that metals in the raw swine manure were not removed with coarse screening. However, the major fraction of metals were removed by filtration (0.45 μm), with the exception of Na, K and Sr. Thus, the use of liquid‐solid separation techniques that capture the fine solid fractions (and associated metals) from raw manure can have a favorable impact on the environment and contribute to swine production wastewater treatment.     

Singularity and Nonnormality in the Classification of Compositional Data

Geologists may want to classify compositional data and express the classification as a map. Regionalized classification is a tool that can be used for this purpose, but it incorporates discriminant analysis, which requires the computation and inversion of a covariance matrix. Covariance matrices of compositional data always will be singular (noninvertible) because of the unit-sum constraint. Fortunately, discriminant analyses can be calculated using a pseudo-inverse of the singular covariance matrix; this is done automatically by some statistical packages such as SAS. Granulometric data from the Darss Sill region of the Baltic Sea is used to explore how the pseudo-inversion procedure influences discriminant analysis results, comparing the algorithm used by SAS to the more conventional Moore–Penrose algorithm. Logratio transforms have been recommended to overcome problems associated with analysis of compositional data, including singularity. A regionalized classification of the Darss Sill data after logratio transformation is different only slightly from one based on raw granulometric data, suggesting that closure problems do not influence severely regionalized classification of compositional data.     

Cotton Fiber/ZrO2, A New Material for Adsorption of Cr(VI) Ions in Water

The natural cotton fiber was used to synthesize an anion exchange, containing ZrO₂ film on its surface, NCFZC (natural cotton fiber/ZrO₂ composite). This anion exchanger was produced by the reaction of the zirconium oxychloride and hydroxyl groups on surface of the natural cotton fiber. The material was used for Cr(VI) ions adsorption studies. Adsorption equilibrium time and optimum pH for Cr(VI) adsorption were found to be 6 h and 4.0, respectively. The Langmuir and Temkin isotherms were used to models adsorption equilibrium data. The adsorption capacity of NCFZC was found to be 1.33 mmol/g. Kinetic studies showed that the rate of adsorption of Cr(VI) on NCFZC obeyed a pseudo‐second‐order kinetic model.     

Multiparametric Traveltime Inversion

In conventional seismic processing, the classical algorithm of Hubral and Krey is routinely applied to extract an initial macrovelocity model that consists of a stack of homogeneous layers bounded by curved interfaces. Input for the algorithm are identified primary reflections together with normal moveout (NMO) velocities, as derived from a previous velocity analysis conducted on common midpoint (CMP) data. This work presents a modified version of the Hubral and Krey algorithm that is designed to extend the original version in two ways, namely (a) it makes an advantageous use of previously obtained common-reflection-surface (CRS) attributes as its input and (b) it also allows for gradient layer velocities in depth. A new strategy to recover interfaces as optimized cubic splines is also proposed. Some synthetic examples are provided to illustrate and explain the implementation of the method.     

Consequences of winter upwelling events on biogeochemical and phytoplankton patterns in a western Galician ria (NW Iberian peninsula)

The consequences of two upwelling events in mid- (MW) and late (LW) winter on biogeochemical and phytoplankton patterns were studied in the Pontevedra Ria and compared with the patterns measured under typical winter conditions and under a summer upwelling event. Thermohaline patterns measured during the mid-winter upwelling event (MW-up) revealed the intrusion of saltier seawater (35.9) into the ria associated with the Iberian Poleward Current (IPC). During the late-winter upwelling event (LW-up), the seawater which had welled up into the ria showed characteristics of the Eastern North Atlantic Central Water mass (ENACW). In both cases the measured water residence time (4 days during MW-up and 10 days during LW-up) was related to both meteorological and fluvial forcing. This residence time contrasts with that of summer upwelling (7 days) and with that estimated under unfavorable upwelling atmospheric conditions (2–4 weeks). During MW-up, the ria became poor in nutrients due to continental freshwater dilution, associated with the shorter residence time of the water, and the intrusion of IPC, which is a water body poor in nutrient salts: 2.9 μM of nitrate, 0.1 μM of phosphate and 1.5 μM of silicate. During this event, the ria exported 3.4 mol_DIN s⁻¹, compared with 6.9 mol_DIN s⁻¹ in non-upwelling conditions. Phytoplankton showed a uniform distribution throughout the ria, as during unfavorable upwelling conditions, and was characterized by the dominance of diatoms, mainly Nitzschia longissima and Skeletonema costatum. During LW-up, a nutrient depletion in the photic layer also occurred, but as a result of a phytoplankton spring bloom developing at this time. The ria was a nutrient trap where 4.1 mol_DIN s⁻¹ were processed by photosynthesis. This budget is three times higher than the one under non-upwelling conditions. In contrast with the MW-up, which had no effect on primary production, during LW-up the ria became more productive, although not as productive as during a summer upwelling event (9.9 mol_DIN s⁻¹). The taxonomic composition of the phytoplankton community did not change noticeably during LW-up and the summer upwelling, with the same species present and changing only in relative proportions. Diatoms were always the dominant microphytoplankton community, with Pseudonitzschia pungens, Thalassionema nitzschioides and several species of Chaetoceros as characteristic taxons.     

Comparison of llama fiber obtained from two production regions of Argentina

The Puna is an arid region running along the Andes mountains, more than 3600 m above sea level. Overgrazing has severely degraded much of this ecosystem, and this has dramatically reduced agricultural production and resulted in poverty for human inhabitants. Llamas are native to the Puna and are well suited to live there. Their grazing habits and digestive system make efficient use of native forages, and their padded feet keep soil disturbance to a minimum, thereby reducing erosion. Uncontrolled llama breeding over the last 500 years has degraded the quality of the fiber they produce, so today it is generally of low quality. Analysis of llama fibers obtained from two production regions of Argentina showed that some llamas possess sufficiently fine mean fiber diameters (less than 23 μm if guard hairs are excluded) to allow their fleeces to be sold at a premium. A higher price would make llamas more attractive to raise than the goats and sheep commonly found in the Puna today. Switching to llama production would increase grower income and sustainability of agriculture in the region.     

Numerical homogenization-based seismic assessment of an English-bond masonry prototype: Structural level application

A multiscale strategy is evaluated at a structural level for the analysis of unreinforced masonry structures. The mechanical characterization of the masonry is deduced from homogenization-based micro-scale finite element (FE) models. The derived data are here employed at a structural level via a discrete FE model. The discrete FE model is composed of quadrilateral rigid plates interconnected through vertical and horizontal interfaces. On the interfaces, between adjoining discrete elements, a model that accounts for the in- and out-of-plane behavior of masonry, with damage and plasticity, is adopted. Such interfaces represent the material pre- and post-peak regimes, its orthotropy, and, depending on the micro-model assumed, account by three-dimensional shear effects that are especially important for multi-leaf walls and complex regular textures. The discrete model has been implemented in an advanced structural analysis software where powerful built-in features as the arc-length method, line-search algorithm, and implicit or explicit solver schemes are available. The multi-scale model is applied for the dynamic study of a small English-bond masonry house prototype subjected to a series of consecutive earthquake records. Detailed comparisons between the experimental and numerical data are presented, including the results obtained through a continuous total strain rotating crack model. Quasi-static and dynamic analyses are conducted. Results demonstrate that when enough experimental information is available on the masonry components under tension, shear, and compression regimes, the approach predicts well the seismic structural response in terms of time-history displacements, seismic capacity, and damage patterns. The required computational cost (CPU time) is very attractive.