Thresholds of intrabed flow and other interactions of turbidity currents with soft muddy substrates

Controlled laboratory experiments reveal that the lower part of turbidity currents has the ability to enter fluid mud substrates, if the bed shear stress is higher than the yield stress of the fluid mud and the density of the turbidity current is higher than the density of the substrate. Upon entering the substrate, the turbidity current either induces mixing between flow‐derived sediment and substrate sediment, or it forms a stable horizontal flow front inside the fluid mud. Such ‘intrabed’ flow is surrounded by plastically deformed mud; otherwise it resembles the front of a ‘bottom‐hugging’ turbidity current. The ‘suprabed’ portion of the turbidity current, i.e. the upper part of the flow that does not enter the substrate, is typically separated from the intrabed flow by a long horizontal layer of mud which originates from the mud that is swept over the top of the intrabed flow and then incorporated into the flow. The intrabed flow and the mixing mechanism are specific types of interaction between turbidity currents and muddy substrates that are part of a larger group of interactions, which also include bypass, deposition, erosion and soft sediment deformation. A classification scheme for these types of interactions is proposed, based on an excess bed shear stress parameter, which includes the difference in the bed shear stress imposed by the flow and the yield stress of the substrate and an excess density parameter, which relies on the density difference between the flow and the substrate. Based on this classification scheme, as well as on the sedimentological properties of the laboratory deposits, an existing facies model for intrabed turbidites is extended to the other types of interaction involving soft muddy substrates. The physical threshold of flow‐substrate mixing versus stable intrabed flow is defined using the gradient Richardson number, and this method is validated successfully with the laboratory data. The gradient Richardson number is also used to verify that stable intrabed flow is possible in natural turbidity currents, and to determine under which conditions intrabed flow is likely to be unstable. It appears that intrabed flow is likely only in natural turbidity currents with flow velocities well below ca 3·5 m s^?1, although a wider range of flows is capable of entering fluid muds. Below this threshold velocity, intrabed flow is stable only at high‐density gradients and low‐velocity gradients across the upper boundary of the turbidity current. Finally, the gradient Richardson number is used as a scaling parameter to set the flow velocity limits of a natural turbidity current that formed an inferred intrabed turbidite in the deep‐marine Aberystwyth Grits Group, West Wales, United Kingdom.     

Toxic metals in a highly urbanized industry-impacted estuary (Bahia Blanca Estuary,Argentina): spatio-temporal analysis based on GIS

Cadmium, chromium, nickel, and lead were evaluated in the particulate fraction at one of the most industrialized estuaries at the Southwestern Atlantic Ocean, through Geographic Information System (GIS). Concentrations were analyzed at 21 stations during 2008–2010. The highest metal concentrations (Cd: 8,9; Cr: 256,49; Ni: 27,02; Pb: 78,43 µg g^??1 d. w.) were recorded at the stations located near industrial and urban discharges situated along the estuary. In addition, Pb presented a different seasonal and spatial behavior in comparison with Cd, Cr and Ni. Winter and spring presented the higher concentrations of Pb, and the inner stations presented the higher values. The estuary is considered a moderate to strongly polluted and significantly polluted according to the Index of geoaccumulation (I_geo) and the Enrichment Factor of Cd, respectively. The Multidimensional Scaling plot showed three groups of stations: the inner, associated to low levels of metals (G1), middle stations (G2) with intermediate levels and the outer (G3) with the highest ones. In addition, this work reveals the usefulness of the GIS-mapping techniques in the distribution of pollutants along an estuarine environment and the environmental quality assessment of estuarine systems.     

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.     

The Effect of Key Parameters on the Strength of a Dispersive Soil Stabilized with Sustainable Binders

Geotechnical and Geological Engineering - Dispersive soils are susceptible to phenomena of internal and external erosion when in contact with relatively pure water due to its particle’s...     

Modelling size effect on rock aggregates strength using a DEM bonded-cell model

Empirical evidence has shown that particle breakage affects the mechanical behaviour of granular materials. The source of this mechanism takes place at the particle scale, and the main consequence on the macromechanical behaviour is increasing compressibility. Due to the inverse correlation between particle size and particle crushing strength, coarse rockfill materials are particularly vulnerable to mechanical degradation due to particle breakage. However, such coarse materials do not fit in standard laboratory devices, and the alternative of large sample testing is usually unavailable or too expensive. Alternatively, recent works have proposed multi-scale approaches using the discrete element method (DEM) to carry out numerical testing of coarse crushable materials, although few studies have focused on size effects. This article presents the application of a DEM bonded-cell model to study particle size-strength correlation on angular rock aggregates. Each particle is modelled by a cluster of perfectly rigid polyhedral cells with Mohr–Coulomb contact law. Constant cell density within particles implies that the presence of potential fragmentation planes increases with size. Therefore, particle strength decreases with size. A comprehensive sensitivity analysis was carried out through 1477 particle crushing simulations in a given particle size. Based on published experimental data on calcareous rock aggregates, part of the simulations were used for calibration, and 97 additional simulations of a coarser size fraction were performed for validation. The results show a good agreement with the empirical data in terms of size effect and data scatter through Weibull statistics.

     

Area usage estimation and spatiotemporal variability in distribution patterns of southern right whales,Eubalaena australis,of southern Brazil

Southern right whales—Eubalaena australis (Desmoulins, 1822)—migrate seasonally from high‐latitude feeding grounds to coastal breeding and calving grounds at lower latitudes such as the southern coast of Brazil. Understanding how these whales are distributed along the coast is important for monitoring their postwhaling recovery and defining management strategies. In this study, we applied Kernel density estimators to aerial survey data to determine main occurrence and concentration areas of right whales in southern Brazil and investigate inter‐ and intra‐annual distribution patterns between 2003 and 2012. Our results show considerable variation in area usage within and among years, and changes in the general distribution pattern of right whales in the last years of the study. Intra‐annually, higher concentration area tended to expand from July to September and decrease in November. Some areas stood out as high‐density areas for right whales: Ribanceira/Ibiraquera, Itapirubá Sul/Sol, and from Arroio to Gaivota. Some evidences also suggest preferential areas for mother–calf pairs. The higher concentration area of right whales in southern Brazil was estimated at 52,541 km² and the occurrence area was 682.69 km², which is the whole study area. As right whale distribution in the region is likely expanding due to this population's current recovery, our study provides essential information for management plan of the Right Whale Environmental Protection Area.     

Hurricanes and labor market outcomes: Evidence for Mexico

Hurricanes are becoming frequent events that affect more people every time, and in this context the identification of the effects on the labor market may be important for the policy design of mechanisms to cope more effectively with these shocks. Using hurricanes as exogenous shocks and with microdata from 32 metropolitan areas in Mexico from 2000 to 2011, we analyze the effect on the returns for skill levels, hours worked and jobs with access to social security. Results show that the impact seems to be mostly positive on wages and formal jobs for low educated workers. There is no specific pattern of results for intensity of the hurricanes.