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.     

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.     

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.     

Isotopic insights into smoothening of abandoned fan surfaces, Southern California

Cosmogenic nuclide concentrations measured on abandoned fan surfaces along the Mojave section of the San Andreas Fault suggest that sediment is generated, transported, and removed from the fans on the order of 30-40 kyr. We measured in situ produced cosmogenic ¹⁰Be, and in some cases ²⁶Al, in boulders (n = 15), surface sediment (n = 15), and one depth profile (n = 9). Nuclide concentrations in surface sediments and boulders underestimate fan ages, suggesting that ¹⁰Be accumulation is largely controlled by the geomorphic processes that operate on the surfaces of the fans and not by their ages.Field observations, grain-size distribution, and cosmogenic nuclide data suggest that over time, boulders weather into grus and the bar sediments diffuse into the adjacent swales. As fans grow older the relief between bars and swales decreases, the sediment transport rate from bars to swales decreases, and the surface processes that erode the fan become uniform over the entire fan surface. The nuclide data therefore suggest that, over time, the difference in ¹⁰Be concentration between bars and swales increases to a maximum until the topographic relief between bars and swales is minimized, resulting in a common surface lowering rate and common ¹⁰Be concentrations across the fan. During this phase, the entire fan is lowered homogeneously at a rate of 10-15 mm kyr⁻¹.     

Development of a numerical groundwater flow model using SRTM elevations

Remotely-sensed elevation data are potentially useful for constructing regional scale groundwater models, particularly in regions where ground-based data are poor or sparse. Surface-water elevations measured by the Shuttle Radar Topography Mission (SRTM) were used to develop a regional-groundwater flow model by assuming that frozen surface waters reflect local hydraulic head (or groundwater potential). Drainage lakes (fed primarily by surface water) are designated as boundary conditions and seepage lakes and isolated wetlands (fed primarily by groundwater) are used as observation points to calibrate a numerical flow model of the 900 km² study area in the Northern Highland Lakes Region of Wisconsin, USA. Elevation data were utilized in a geographic information system (GIS) based groundwater-modeling package that employs the analytic element method (AEM). Calibration statistics indicate that lakes and wetlands had similar influence on the parameter estimation, suggesting that wetlands might be used as observations where open water elevations are unreliable or not available. Open water elevations are often difficult to resolve in radar interferometry because unfrozen water does not return off-nadir radar signals.     

Timing of surficial process changes down a Mojave Desert piedmont

We measured ¹⁰Be and ²⁶Al in 29 sediment samples to infer the history and millennial-scale rates of change down a low-gradient piedmont, a common but enigmatic landform that dominates the Mojave Desert. Nuclide data suggest that a large volume of sediment was deposited on the proximal East Range Road piedmont in Fort Irwin, California, ∼ 75,500 yr ago. Since then, this material has been stable or eroding slowly. In contrast, on the distal piedmont (3.5 km from the upland source basins) soil stratigraphy suggests that there have been alternating periods of surface stability, erosion, and deposition over the last 70,000 yr. Nuclide data from samples amalgamated along cross-piedmont transects suggest that long-term average down-gradient sediment speeds range from 9 cm yr^− 1 near the uplands to 22 cm yr^− 1 6 km down-piedmont. These speeds are similar to ¹⁰Be-estimated sediment speeds down three other piedmonts in the Mojave Desert, suggesting that piedmont surface morphologies dominated by shallow migrating channels have similar sediment transport rates. The timing of surface process change down the East Range Road piedmont is determined by a combination of sediment available in the source basins, sediment transport rates, and the size of the piedmont.     

Surrogate-based parameter inference in debris flow model

This work tackles the problem of calibrating the unknown parameters of a debris flow model with the drawback that the information regarding the experimental data treatment and processing is not available. In particular, we focus on the evolution over time of the flow thickness of the debris with dam-break initial conditions. The proposed methodology consists of establishing an approximation of the numerical model using a polynomial chaos expansion that is used in place of the original model, saving computational burden. The values of the parameters are then inferred through a Bayesian approach with a particular focus on inference discrepancies that some of the important features predicted by the model exhibit. We build the model approximation using a preconditioned non-intrusive method and show that a suitable prior parameter distribution is critical to the construction of an accurate surrogate model. The results of the Bayesian inference suggest that utilizing directly the available experimental data could lead to incorrect conclusions, including the over-determination of parameters. To avoid such drawbacks, we propose to base the inference on few significant features extracted from the original data. Our experiments confirm the validity of this approach, and show that it does not lead to significant loss of information. It is further computationally more efficient than the direct approach, and can avoid the construction of an elaborate error model.