Mineralogy and crystallization history of a highly differentiated REE-enriched hypabyssal rhyolite: Round Top laccolith,Trans-Pecos,Texas

Mineralogy and Petrology - The Round Top hypabyssal rhyolite laccolith is a highly evolved magmatic system, enriched in incompatible elements including REE [Rare Earth Element(s)], U, Be, and F....     

A new method for estimating high-frequency radar error using data from Central San Francisco Bay

This study offers a new method for estimating High-Frequency (HF) radar surface current velocity error in data comparisons with other types of instrumentation. A new method is needed in order to remove the zero-mean random spatial and temporal fluctuations present in surface-current measurements from all sensors. Conventional methods for calculating radar error when comparing with another instrument have included their root mean square differences and scatter plots that provide correlation coefficient and slope/intercept of the regression line. It seems that a meaningful estimate of radar error should attempt to remove both sensors’ zero mean random fluctuations, inasmuch as possible. We offer and compare a method that does this. The method was tested on data collected in the Central San Francisco Bay, where GPS surface-drifter deployments were conducted within the coverage of four 42 MHz radars over six days in October of 2008. Drifters were continuously deployed in these areas over the sampling days, providing 525 usable drifter measurements. Drifter and radar measurements were averaged into thirty-minute time bins. The three-day long-term averages from the sampling areas were then subtracted from the thirtyminute averages to remove biases associated with comparisons done with short, disjoint time-sample periods. These were then used to develop methods that give radar error or bias after the random fluctuations have been removed. Results for error estimates in this study are commensurate with others where random fluctuations have been filtered, suggesting they are valid. The estimated error for the radars in the SF Bay is low, ranging from ?7.57 cm/s to 0.59 cm/s.     

Geology of the Elephanta Island fault zone,western Indian rifted margin,and its significance for understanding the Panvel flexure

The Panvel flexure is a 150-km long tectonic structure, comprising prominently seaward-dipping Deccan flood basalts, on the western Indian rifted margin. Given the active tectonic faulting beneath the Panvel flexure zone inferred from microseismicity, better structural understanding of the region is needed. The geology of Elephanta Island in the Mumbai harbour, famous for the ca. mid-6th century A.D. Hindu rock-cut caves in Deccan basalt (a UNESCO World Heritage site) is poorly known. We describe a previously unreported but well-exposed fault zone on Elephanta Island, consisting of two large faults dipping steeply east–southeast and producing easterly downthrows. Well-developed slickensides and structural measurements indicate oblique slip on both faults. The Elephanta Island fault zone may be the northern extension of the Alibag–Uran fault zone previously described. This and two other known regional faults (Nhava–Sheva and Belpada faults) indicate a progressively eastward step-faulted structure of the Panvel flexure, with the important result that the individual movements were not simply downdip but also oblique-slip and locally even rotational (as at Uran). An interesting problem is the normal faulting, block tectonics and rifting of this region of the crust for which seismological data indicate a normal thickness (up to 41.3 km). A model of asymmetric rifting by simple shear may explain this observation and the consistently landward dips of the rifted margin faults.     

Timing of metamorphism and deformation in the Swat valley,northern Pakistan:Insight into garnet-monazite HREE partitioning

New metamorphic petrology and geochronology from the Loe Sar dome in the Swat region of northern Pakistan place refined constraints on the pressure, temperature and timing of metamorphism and deformation in that part of the Himalayan orogen. Thermodynamic modelling and monazite petrochronology indicate that metamorphism in the area followed a prograde evolution from ～525 ± 25 ℃and 6 士 0.5 kbar to ～610 ± 25 ℃ and 9 士 0.5 kbar, between ca. 39 Ma and 28 Ma. Partitioning of heavy rare earth elements between garnet rims and 30-28 Ma monazite are interpreted to indicate coeval crystallization at peak conditions. Microtextural relationships indicate that garnet rim growth post-dated the development of the main foliation in the area. The regional foliation is folded about large-scale N-S trending fold axes and overprinting E-W trending folds to form km-scale domal culminations. The textural relationships observed indicate that final dome development must be younger than the 30-28 Ma monazite that grew with garnet rims post-regional foliation development, but pre-doming-related deformation. This new timing constraint helps resolve discrepancy between previous interpretations,which have alternately suggested that N-S trending regional folds must be either pre-or post-early Oligocene. Finally, when combined with existing hornblende and white mica cooling ages, these new data indicate that the study area was exhumed rapidly following peak metamorphism.     

Seismic stratigraphic framework and depositional sequences in the Santos Basin,Brazil

The Santos Basin, situated offshore southern Brazil, is one of nine marginal rift basins in the equatorial South Atlantic. It formed by the collapse of a thermal dome in the late Jurassic and by subsequent rifting and opening of the South Atlantic in the early Cretaceous. Rifting was accompanied by immense volcanic outpouring seen at the surface today throughout the onshore Paraná Basin and thought to underlie the entire Santos Basin, and the adjacent São Paulo Plateau. Vulcanism was followed by subsidence of up to 10 km from Aptian to Recent time, and a coastal hingeline coincides with the Serra do Mar uplift. The basin depocentre, which is 700 km long, is bounded to the north and south by basement and volcanic highs, respectively. A restricted water circulation in the ocean basin, which prevailed up to the Santonian stage, has important repercussions for the hydrocarbon potential of the area. The nine genetically related basins have collective reserves of ≈ 5 billion barrels of oil and associated gas. A stratigraphic framework, based largely on seismic data, has been erected for the Santos Basin. Seven regional unconformities, or ‘R’ reflections, can be traced throughout the basin and form the boundaries for seismic sequences. Isopaching the seismic sequences defines the principal depositional units in the basin and also shows how the basin depocentre shifted with time. Limited well control has enabled the seismic sequences to be correlated with litho-environmental sequences which more fully reflect the geological evolution and provide a working exploration model. Finally, an attempt has been made to recognize and map seismic facies within the seismic sequences and to predict the lithofacies in areas away from well control     

A nonlinear stability problem in the three dimensional restricted three body problem

The question of whether or not there is a transfer of energy between the in-plane motion and out-of-plane motion in the neighborhood ofL ₄ in the restricted problem of three bodies is investigated in this paper. The in-plane motion is assumed to be finite and the out-of-plane motion to be infinitesimal. The equation governing the out-of-plane motion becomes one with time varying coefficients. The stability of this equation is then investigated using Lie Series.Presented as a paper AAS No. 70-313, at the AAS/AIAA Astrodynamics Specialists Conference 1971 at Fort Lauderdale Fla., U.S.A.     

A spatially-explicit approach for estimating carrying capacity: An application for the Atlantic menhaden (Brevoortia tyrannus) in Chesapeake Bay

A spatially-explicit methodology was developed for estimating system carrying capacities of fish stocks, and used to estimate the seasonal and spatial patterns of carrying capacity of Chesapeake Bay for Atlantic menhaden (Brevoortia tyrannus). We used a spatially-explicit three-dimensional (3-D) model that divided the heterogeneous habitat of Chesapeake Bay into over 4,000 cubes. Each cube represented a volume of water that was characterized by a specific set of environmental variables (phytoplankton biomass, temperature, and dissolved oxygen) driven by the 3-D water quality model. Foraging and bioenergetics models transformed the environmental variables into measures of potential growth rates of menhaden. Potential carrying capacity of menhaden was estimated as a function of phytoplankton production, menhaden consumption rate, and potential growth rate, combining phytoplankton production, thermal habitat, and menhaden physiology into one ecological value that is a measure of habitat quality from the perspective of the fish. Seasonal analysis of the Chesapeake Bay carrying capacity for Atlantic menhaden suggested two bottleneck periods: one in early June and a second during the fall. The bottleneck in carrying capacity was at about 10 billion age-0 fish. Annual recruitment of age-0 menhaden for the entire Atlantic coast of the U.S. ranged from 1.2–18.6 billion fish between 1955 and 1986. It appears that carrying capacity of, Chesapeake Bay does not limit the coastwide production of young menhaden. Any conditions such as nutrient reduction strategies, further eutrophication, or global climatic warming, that may influence the carrying capacity during the fall or early June periods, may ultimately alter coastwide abundance of menhaden through changes in Chesapeake Bay carrying capacity.     

Deep learning-based water quality estimation and anomaly detection using Landsat-8/Sentinel-2 virtual constellation and cloud computing

ABSTRACT

Monitoring of inland water quality is of significant importance due to the increase in water quality related issues, especially within the Midwestern United States. Traditional monitoring techniques, although highly accurate, are vastly insufficient in terms of spatial and temporal coverage. Using a virtual constellation by harmonizing Landsat-8 and Sentinel-2 data a high temporal frequency dataset can be created at a relatively fine spatial scale. In this study, we apply a novel deep learning method for the estimation of blue-green algae (BGA), chlorophyll-α (Chl), fluorescent dissolved organic matter (fDOM), dissolved oxygen (DO), specific conductance (SC), and turbidity. The developed model is evaluated against previously studied machine learning methods and found to outperform multiple linear regression (MLR), support vector machine regression (SVR), and extreme learning machine regression (ELR) generating R² of 0.91 for BGA, 0.88, 0.89, 0.93, 0.87, and 0.84 for Chl, DO, SC, and turbidity respectfully. This model is then applied to all available data ranging from 2013–2018 and time series for each variable were generated for four selected waterbodies. We then use the Empirical Data Analytics (EDA) anomaly detection method on the time series to identify abnormal data points. Upon further analysis, the EDA method successfully identifies abnormal events in water quality. Our results also demonstrate strong correlation between non-optically active variables such as SC with Chl and fDOM. The framework developed in this study represents an efficient and accurate empirical method for inland water quality monitoring at the regional scale.     

Simulating sensitivity of soil moisture and evapotranspiration under heterogeneous soils and land uses

Soil moisture (SM) plays an important role in land surface and atmospheric interactions. It modifies energy balance at the surface and the rate of water cycling between the land and atmosphere. In this paper we provide a sensitivity assessment of SM and ET for heterogeneous soil physical properties and for three land uses including irrigated maize, rainfed maize, and grass at a climatological time-scale by using a water balance model. Not surprisingly, the study finds increased soil water content in the root zone throughout the year under irrigated farming. Soil water depletes to its lowest level under rainfed maize cultivation. We find a ‘land use’ effect as high as 36 percent of annual total evapotranspiration, under irrigated maize compared to rainfed maize and grass, respectively. Sensitivity analyses consisting of comparative simulations using the model show that soil characteristics, like water holding capacity, influence SM in the root zone and affect seasonal total ET estimates at the climatological time-scale. This ‘soils’ effect is smaller than the ‘land use’ effect associated with irrigation but, it is a source of consistent bias for both SM and ET estimates. The ‘climate’ effect basically masks the ‘soils’ effect under wet conditions. These results lead us to conclude that appropriate representation of land use, soils, and climate are necessary to accurately represent the water and energy balance in real landscapes.     

Using parallel projection mathematics to orient an object relative to a single image

The paper presents a straightforward method of calculating approximate orientation parameters (six degrees of freedom) of a known targeted object relative to a single calibrated camera. These can then initialise an optimised non-linear calculation of the same parameter values. The method uses the mathematics of a scaled parallel projection and is particularly suited to narrow angle images obtained using a telescope, telephoto or zoom lens. However, the method can also be used with cameras having wider fields of view provided the target group occupies a moderately small part of the image.