Structure Function Analysis of Two-Scale Scalar Ramps. Part II: Ramp Characteristics and Surface Renewal Flux Estimation

Ramp features in the turbulent scalar field are associated with turbulent coherent structures, which dominate energy and mass fluxes in the atmospheric surface layer. Although finer scale ramp-like shapes embedded within larger scale ramp-like shapes can readily be perceived in turbulent scalar traces, their presence has largely been overlooked in the literature. We demonstrate the signature of more than one ramp scale in structure functions of the turbulent scalar field measured from above bare ground and two types of short plant canopies, using structure-function time lags ranging in scale from isotropic to larger than the characteristic coherent structures. Spectral analysis of structure functions was used to characterize different scales of turbulent structures. By expanding structure function analysis to include two ramp scales, we characterized the intermittency, duration, and surface renewal flux contribution of the smallest (i.e., Scale One) and the dominant (i.e., Scale Two) coherent structure scales. The frequencies of the coherent structure scales increase with mean wind shear, implying that both Scale One and Scale Two are shear-driven. The embedded Scale One turbulent structure scale is ineffectual in the surface-layer energy and mass transport process. The new method reported here for obtaining surface renewal-based scalar exchange works well over bare ground and short canopies under unstable conditions, effectively eliminating the α calibration for these conditions and forming the foundation for analysis over taller and more complex surfaces.     

Groundwater-level prediction using multiple linear regression and artificial neural network techniques: a comparative assessment

The potential of multiple linear regression (MLR) and artificial neural network (ANN) techniques in predicting transient water levels over a groundwater basin were compared. MLR and ANN modeling was carried out at 17 sites in Japan, considering all significant inputs: rainfall, ambient temperature, river stage, 11 seasonal dummy variables, and influential lags of rainfall, ambient temperature, river stage and groundwater level. Seventeen site-specific ANN models were developed, using multi-layer feed-forward neural networks trained with Levenberg-Marquardt backpropagation algorithms. The performance of the models was evaluated using statistical and graphical indicators. Comparison of the goodness-of-fit statistics of the MLR models with those of the ANN models indicated that there is better agreement between the ANN-predicted groundwater levels and the observed groundwater levels at all the sites, compared to the MLR. This finding was supported by the graphical indicators and the residual analysis. Thus, it is concluded that the ANN technique is superior to the MLR technique in predicting spatio-temporal distribution of groundwater levels in a basin. However, considering the practical advantages of the MLR technique, it is recommended as an alternative and cost-effective groundwater modeling tool.     

Non-point source pollution in Indian agriculture: Estimation of nitrogen losses from rice crop using remote sensing and GIS

The paper presents a detailed understanding of nitrogenous fertilizer use in Indian agriculture and estimation of seasonal nitrogen loosses from rice crop in Indo-Gangetic plain region, the ‘food bowl’ of the Indian sub-continent. An integrated methodology was developed for quantification of different forms of nitrogen losses from rice crop using remote sensing derived inputs, field data of fertilizer application, collateral data of soil and rainfall and nitrogen loss coefficients derived from published nitrogen dynamics studies. The spatial patterns of nitrogen losses in autumn or ‘kharif’ and spring or ‘rabi’ season rice at 1 × 1 km grid were generated using image processing and GIS. The nitrogen losses through leaching in form of urea-N, ammonium-N (NH₄-N) and nitrate-N (NO₃-N) are dominant over ammonia volatilization loss. The study results indicate that nitrogen loss through leaching in kharif and rabi rice is of the order of 34.9% and 39.8% of the applied nitrogenous fertilizer in the Indo-Gangetic plain region. This study provides a significant insight to the role of nitrogenous fertilizer as a major non-point source pollutant from agriculture.     

Stellar contents of two young open clusters: NGC 663 and 654

UBVRI CCD photometry in a wide field around two young open clusters, NGC 663 and 654, has been carried out. Hα and polarimetric observations for the cluster NGC 654 have also been obtained. We use the photometric data to construct colour–colour and colour–magnitude diagrams, from which we can investigate the reddening, age, mass and evolutionary states of the stellar contents of the these clusters. The reddening across the cluster regions is found to be variable. There is evidence for anomalous reddening law in both clusters; however, more infrared and polarimetric data are needed to conclude about the reddening law. Both clusters are situated at about a distance of 2.4 kpc. Star formation in both clusters is found to be a continuous process. In the case of NGC 663, star formation seems to have taken place sequentially, in the sense that formation of low-mass stars precedes the formation of most massive stars. Whereas, in the case of NGC 654, formation of low-mass stars did not cease after the formation of most massive stars in the cluster.     

Comparison of cell- and vertex-centered discretization methods for flow in a two-dimensional discrete-fracture–matrix system

Simulations of flow for a discrete-fracture model in fractured porous rocks have gradually become more practical, as a consequence of increased computer power and improved simulation and characterization techniques. Discrete-fracture models can be formulated in a lower-dimensional framework, where the fractures are modeled in a lower dimension than the matrix, or in an equi-dimensional form, where the fractures and the matrix have the same dimension.     

Use of remote sensing in lineament analysis for tectonic evolution and resource study of a part of Vindhyan Basin,Jhalawar area,India

Synoptivity and the exemplified fracture systems exhibited by the space borne imagery data has helped in solving many of the geological enigma in various parts of the world. The study conducted, using such remotly sensed data, in Jhalawar anticline, part of Proterozoic Cratonic Vindhyan Basin, Rajasthan, India, led to infer the history of tectonic evolution of peribasinal deformation which has been a matter of controversy for a century and more. In Landsat MSS data the Jhalawar region displays a panorama of lineaments and their analysis through azimuthal frequency diagrams, isofracture, lineament incidence and lineament intersection incidence density maps shows that the mean orientation of the lineaments fall in NW-SE and NE-SW and the shape of the various lineament density contours also show NE-SW and NW-SE orientations. In aerial photographs the area exhibits four sets of lineaments in NE-SW, NW-SE, N-S and E-W directions. Amongst these the former two sets are expressed as wide open master fracture systems with prolific vegetation fills along them and the latter two sets are characteristically observed as thin vegetation linears with frequent strike slip faulting along them. The further analysis of these fracture/lineament systems derived from multi-level remote sensing data shows that the Jhalawar anticline, which followed the pattern of flexural slip fold mechanism, was evolved by horizontally disposed σ1 (greatest principal stress) and 3σ (least principal stress) with the former oriented in NE-SW and the latter aligned in NW-SE directions with vertically disposed 2σ. The inference of such palaeostress environment of the Jhalawar region lead in the identification of a buried rigid basement high southwest of Jhalawar anticline, beneath the Deccan pile and loci of ground water, silica sand and probable igneous plug.     

Unusual spatial-temporal dynamics of geomagnetic disturbances during the main phase of the extremely strong magnetic storm of November 7–8, 2004

The spatial dynamics of geomagnetic variations and pulsations, auroras, and riometer absorption during the development of the main phase of the extremely strong magnetic storm of November 7–8, 2004, has been studied. It has been indicated that intense disturbances were observed in the early morning sector of auroral latitudes rather than in the nighttime sector, as usually takes place during magnetic storms. The unusual spatial dynamics was revealed at the beginning of the storm main phase. A rapid poleward expansion of disturbances from geomagnetic latitudes of 65°–66° to 74°–75° and the development of the so-called polar cap substorm with a negative bay amplitude of up to 2500 nT, accompanied by precipitation of energetic electrons (riometer absorption) and generation of Pi2–Pi3 pulsations, were observed when IMF B _z was about ?45 nT. The geomagnetic activity maximum subsequently sharply shifted equatorward to 60°–61°. The spatial dynamics of the westward electrojet, Pi2–Pi3 geomagnetic pulsations, and riometer absorption was similar, which can indicate that the source of these phenomena is common.     

Bayesian improver of a distribution

 An estimate of a distribution obtained from a sample by any method of classical statistics may be erroneous when the sample is not representative of the population. A subjective distribution elicited from an expert may be miscalibrated when information is scanty and experience limited. The Bayesian Improver of a Distribution (BID) exploits a coherence principle and improves, in the ex ante sense, an initial estimate of a continuous distribution by using (i) the known distribution of a related variate and (ii) information about the dependence structure between the two variates. The theory of BID is developed into an applied (ABID) procedure. The ABID estimator is applicable to any continuous, monotone likelihood ratio dependent variates with arbitrary, strictly increasing marginal distributions, parametric or nonparametric; it is analytic in form and easy to implement via statistical or judgmental methods; it converges to the true distribution, provided the initial estimator does, as the sample size n→∞; it outperforms the initial estimator in the expected Kolmogorov–Smirnov distance for all n; and it offers the greatest gains when n is small – precisely when improved estimates are needed most.