Geostatistical and Geospatial Approaches for the Characterization of Natural Resources in the Environment

Singularity theory is an efficient way to quantify spatial variations of physical/chemical properties caused by geological processes. This study demonstrates several applications of singularity-based geo-information extraction. Choosing hydrothermal mineralization in Gejiu mineral district, China as an example, different singularity index estimation methods are employed to analyze controlling factors of the mineralization. At the end, this study introduces a fault-oriented singularity index estimation method. In comparison with the original singularity index, the new singularity index estimation method is able to describe anisotropy of geochemical/geophysical properties; meanwhile, controlling effects of fault activities on the hydrothermal mineralization can be quantified accordingly.

Contact analysis assesses the evolution of the average value along boreholes of a given variable at increasing distances from the contact between two facies or domains. The concept is long established in the geostatistical literature and software, albeit for studying the behavior of a single variable. This contribution explores practical ways for studying this transient behavior of a set of variables forming a composition, in such a way that spurious correlation effects are avoided. This is obtained with contact diagrams for each possible pairwise logratio of two components, as well as with a contact analysis of the centered-logratio transformed components. This approach is particularly promising when the set of components considered account for a considerable amount of the total mass, or dilution effects are suspected to have affected only a subset of the components. These concepts are illustrated with data from Murrin Murrin, WA, a Ni-Co laterite deposit where intensive remobilization of both value and deleterious components is known to have occurred.

Principal component analysis is a kind of effective method of extracting comprehensive geochemical data feature. By constructing a new comprehensive variable to instead of the original variables, the new can effectively reflect the compositive information of original variables; it also could indicate the pargenetic assemblage and genetic relationship of exploration geochemistry. But it is based on the hypothesis premise of the normal (liner) distribution of the sample data. However, the complexity of geological systems and multiple stage mineralization stage often lead to the nonlinear distribution of multivariate geochemical data. Therefore, compared with the traditional principal component analysis, the nonlinear principal component analysis is more suitable for extracting of the multivariate geochemical data. This paper introduces the principal component analysis basing on kernel function. With the help of a “nuclear techniques”, implicitly map the input space to a nonlinear characteristics space. In this space, we carry out principal component analysis of geochemical data. The algorithm is in line with the exploration geochemistry data features. Through the experimental analysis of Tibet Daewoo stream sediment data, the principal components analysis based on kernel function is compared with the conventional PCA can better complete the comprehensive exploration geochemistry data feature extraction.

Exploration geochemistry integrating anomaly characteristics is an important index of mineral prediction. Mineralizing process is complex. Because of the superposition of the primary environment and the evolution of the secondary environment, the dispersion of geochemical model presents complex features. Effective method of comprehensive abnormal extraction is especially important. In recent years, information fusion technology is a focal point of research. And it has achieved great success in signal and image processing. Information fusion technology offers a new way for comprehensive abnormal extraction. It is a processing method of multi-order, multi-aspects and multi-level for multi-sensor information, so as to get some new efficient information. Kalman filtering is one of the typical representatives. Kalman filtering is a kind of optimal estimation algorithm and it take for linear, unbiased and the minimum variance as the criterion, and the algorithm thought correspond to the comprehensive characteristics. The introduction of Kalman filter for exploration geochemistry integrating anomaly can provide a new method of exploration geochemical prospecting.

The local singularity model based on multifractal theory suggested by Cheng has gained significant attention in characterizing mineralization and predicting mineral deposits. Chen et al. developed an iterative approach of local singularity analysis to get the final singularity index. However the computational efficiency need to be improved, because the moving average with several scales are calculated for each cell of an raster dataset in the conventional algorithm. Summed area table (SAT), also called as integral image, was first prominently used within the Viola-Jones object detection framework in computer vision. We introduced SAT in local singularity mapping in this study. Once computed using SAT, any one of the rectangular sum can be computed at any scale or location in constant time. SAT is used in geochemical stream sediment survey data applications. A wide variety of scale changes for non-iterative or iterative approach are adopted to calculate the singularity index values efficiently, and then we compare the results and generate optimal singularity mapping.

A combination of logratio transformation (additive logratio) and linear discriminant analysis (LDA) is a powerful experimental data-handling coherent multi-dimensional probability-based statistical technique, which is superior to the use of conventional bi-variate or ternary diagrams. Application of this procedure is illustrated with three subsets of compositional data for 2270 igneous rock samples from the central part of the Mexican Volcanic Belt (MVB). A combination of isometric logratio transformation and LDA will be used in future to test these and other sub-compositions on an updated worldwide compilation of geochemical data, which will enable us to achieve newer sets of more versatile, efficient, and coherent diagrams and related probability estimates.

Conventional geostatistical simulation techniques require an upfront definition of the simulation locations – normally a regular grid. If simulation is performed with different simulation locations, previously simulated values may not be reproduced. A two-step grid-free simulation (GFS) approach is proposed to represent a realization as a function of the simulation location coordinates. Unconditional simulations are generated with turning bands, where 1D line simulations are presented as a function of the simulation location by Fourier series simulation (FSS) technique, and later conditioned to the data by dual kriging. The FSS is framed after the linear model of regionalization (LMR). The independent random factors of the LMR and their coefficients are derived by decomposing the covariance function of the line process into a sum of weighted covariances of random factors in cosine form, where weights are Fourier series coefficients of target 1D covariance function. Multivariate modeling is achieved with the linear model of coregionalization. The GFS implementation is demonstrated with a case study.

The paper presents a semianalytical method to solve the multispecies reactive solute-transport equation coupled with a sequential first-order reaction network under spatially or temporally varying flow velocities and dispersion coefficients. This method employs the generalized integral transform technique (GITT) and general linear transformation method by Clement [2001] to transform the set of coupled multispecies reactive transport equations into a set of independent uncoupled equations and to solve these independent equations for spatially or temporally varying flow velocities and dispersion coefficients, as well for temporally varying inlet concentration. The proposed semianalytical solution is compared against previously published analytical solutions of Srinivasan and Clement [2008] and van Genuchten [1985]. We show a practical implementation of the solution to an actual field, single-well push-pull test (PPT) example designed to obtain the concentration distribution of reactants consumed and products formed at the end of the injection phase.

Statistical evaluation of the results of inter-laboratory comparisons (1976-2012) suggests an overall measurement uncertainty of ±13% and serious problems in the measurements of total Si and HCO₃- in geothermal waters. The reasons for the dispersion among the results of participating laboratories are: inappropriate analytical procedure, limited number of digits in the calibration equation and errors in the calculation procedure of individual laboratory.

In this paper, we provide an approach based on mathematical morphological operators to quantify the complexity of thematic information (map) or binary image object as a quantitative index that is scale invariant, but shape-dependant. We demonstrate the applicability of this approach on a binary Koch quadric fractal. We define a shape-size based fragmentation technique for both foreground and background of the considered deterministic fractal. Further, we utilize this technique to: a) quantify the roughness of binary fractal, b) explore possible relations between the results generated via this fragmentation technique and fractal dimension. This exercise was further extended to draw the results for a binary random Koch quadric fractal.

We focus on the geostatistical characterization of the spatial distribution of soil particle-size curves (PSCs) within an alluvial aquifer. We consider as data object the entire PSC with a Compositional Data Analysis (CoDa) approach. Data are viewed as a point in the infinite-dimensional Hilbert space of functional compositions. The latter is endowed with the Aitchison geometry and enables us to derive a Functional Compositional Kriging (FCK) predictor. We demonstrate the methodology on a set of PSCs observed within an alluvial aquifer in the Neckar river valley in Germany.

New geochemical data for the Sierra de Las Cruces are combined with the published data from this volcanic range and the Sierra de Chichinautzin. Both Neogene-Quaternary ranges are located at the volcanic front of the central part of the Mexican Volcanic Belt (MVB). These geochemical data were statistically evaluated to establish central tendency and dispersion estimates for different magma types from basic to acid, which were compared with worldwide arcs and rifts. UDASYS software was used for this purpose. Similarly, multi-dimensional diagrams recently proposed (2006-2013) were also applied to decipher the tectonic setting. These statistical techniques provide further constraints on the origin of the MVB.

Empirical criteria (K1-K2> 0 and η-K3 >0) for predicting the presence of hollows in abandoned shallow underground workings in Donetsk city (Ukraine) located in the zone of intensive weathering are proposed. The hollows exist when both inequalities K1-K2>0 and η-K3 >0 are satisfied. The statistical analysis has established that the value of criterion K2 is inversely related to rock quality designation (RQD) and that a decrease in RQD leads to a decrease in K1-K2 and, hence, the probability of the hollow existence is decreased. It is also established that a statistical parameter in the left-hand part of inequality η-K3>0 decreases according to logarithmic law with increasing standard linear intensity of weathering-induced fractures (P10). When the fracture intensity (P10) increases, the probability of the presence of a hollow is decreased. The proposed criteria confirm that a thick immediate roof and sandstone layers contribute to the existence of hollows, whereas weak alluvium, argillites and sandy shale allow a collapse of the rock mass.

One of the key challenges in the geostatistical modeling of metallurgical variables is their nonlinearity; estimation techniques such as kriging require that the variable of interest average linearly. By quantifying and modeling the metallurgical properties of blends, these metallurgical variables can be spatially modeled and scaled. Atheoretical framework for the re-expression of these nonlinear metallurgical variables to linear variables using experimental data on the nature of blending is developed and demonstrated. The framework is developed using the power transformation family. Potential applications for this framework include mine plan optimization using high resolution spatial models and optimal decision making for processing multiple ore types.

During numeric modeling of clastic sedimentation, the modeler is faced with assigning values to several parameters that are difficult to estimate. However, proper handling of uncertainties translates to valuable uncertainty information in the output. To illustrate this process, we used a model called GPM (Geologic Process Modeler) to reproduce a deepwater turbidite system from the Campos Basin, offshore Brazil, for which good-quality 3D seismic was available. In the first stage we used a paleo-basin floor surface reconstructed from seismic and placed sediment sources at locations indicated by the inferred paleogeography. In the second stage, we varied several input parameters within a range of reasonable values while comparing results to observed data. The results of all plausible models, considered jointly, provide a picture of the uncertainty of the occurrence of observed features and sediment properties.

The paper focuses on chaotic time series analysis and its applications, consisting of three parts: reconstructed phase space; identification of the chaotic features of a time series, and time series prediction based on the phase space reconstructed. Based on the main shaft water inrush time series of the Wutongzhuang mine in China, a two-month of time delay for reconstruction of phase space could be obtained when calculating using autocorrelation function with an initial value of 1- 1/e. Mine water inrush time series model is established by Weighed first-order partial domain forecast method based on the reconstruction of phase space, and used for forecast of mine water inrushes. Results show the forecasting with a higher precision.

Computer codes, SteamTables and SteamTablesIF97 in VB.NET were written for the thermodynamic properties of pure water, using the formulations: IAPWS-95 for scientific use and IAPWS-IF97 for industrial use, respectively. The execution time for IAPWS-IF97 is in general 70 times less than that for IAPWS-95. The p and T accuracies for the both the formulations are within T = ±0.1 K and p = ±0.001 MPa. However, the steam tables contain thermodynamic inconsistencies, associated with the measurement errors of C_p near the liquid-vapor separation boundary. This causes limitation in the steam transport algorithm in a pipeline.

Surface-based geomodeling produces realistic and complex stratigraphy of hydrocarbon reservoirs by imitating the underlying physics with depositional rules. However, conventional rules utilized in surface-based models are designed based on qualitative understandings, which are normally implemented with a large number of tuning parameters. The increment of tuning parameters increases workloads in model conditioning and history matching. Moreover, there is no quantitative criterion to validate reproduction of the qualitative rules in model realizations. This work aims to introduce a set of simple random walk based depositional rules for lobate environments such that the number of empirical coefficients and parameters are minimized while the realism of the model is maintained. A quantitative characterization of the qualitative concept of lobe stacking pattern is also defined based on hierarchical clustering analysis. Demonstrations show that realizations of the new model were hierarchically similar to the input lobe sequence.

The main purpose of this study is to extend the analysis which has been made for the double layer theory (summarized by [1]) to situations where the distance between the solid walls is of the order of several molecular diameters. The intermolecular forces and their influence on fluid structure and dynamics can be taken into account by using the mesoscopic scale models based on the Boltzmann equation. Three types of fluid particles are considered, namely the anions, the cations and the solvent. They possess a finite diameter which should be at least a few lattice units. The collision frequency between particles is increased by the pair correlation function for hard spheres. The lattice Boltzmann model is built in three dimensions with 19 velocities; it involves two relaxation times. Some preliminary applications are illustrated.

Previous works demonstrated that dispersion increases with heterogeneities and travel distance in heterogeneous reservoirs. Therefore, scale-up of input dispersivity and reservoir attributes to the transport modeling scale should account for subscale heterogeneity and its variability. A quantitative procedure to scale-up both rock and flow-related properties is presented. First, to scale-up porosity and permeability, volume variance at the transport modeling scale is computed corresponding to a given spatial correlation model; numerous sets of “conditioning data” are sampled from probability distributions whose mean is the block average of the actual measure values and the variance is the variance of block mean. Stochastic simulations are subsequently performed to generate multiple realizations at the transport modeling scale. Next, a stochastic random walk particle tracking (RWPT) method, which is not prone to numerical dispersion, is applied. Multiple sub-grid realizations illustrating fine-scale heterogeneities and of the same sizes as the transport modelling mesh size are subjected to RWPT simulation. Effective longitudinal and transverse dispersivities are computed simultaneously by matching the corresponding breakthrough concentration history for each realization with an equivalent medium consisting of averaged homogeneous properties. Probability distributions of scaled-up dispersivities conditioned to average porosity and permeability values are established. Tracer injection responses obtained with the coarse-scale models and fine-scale models are compared. Anomalous behavior is observed, and the interplay between large-scale heterogeneity and sub-scale variability is studied. Scaled-up dispersivity is shown to increase with scale. This study demonstrates that (1) accounting for variability owing to scale-up could capture the actual fine-scale behavior; and (2) the ensuing uncertainty in transport response is underestimated when sub-scale variability is ignored. It underlines the significance of quantification and integration of uncertainty in subsurface “hard” data.

The present study explores for the first time, the possibility of modelling sediment concentration with Artificial Neural Networks at the source of Bhagirathi River in the Himalayas. Considering discharge, rainfall and temperature to be the main controlling factors of sediment concentration in the study area, seven ANN models using Feed Forward Back Propagation algorithm with different inputs have been created, trained and tested for prediction of sediment concentration. The inputs applied in the models are either the variables mentioned above as independent factors or a combination of them. Daily data of discharge, rainfall, temperature and sediment concentration for the melt period of May-October from the year 2000 to 2004, when maximum sediment movement takes place, has been used for modelling and a maximum Correlation Coefficient value of 0.89 has been obtained between observed and ANN predicted values of sediment concentration. The study has brought out that in the study area, where anthropogenic factors are minimal; discharge and rainfall taken together play a more significant role in affecting sediment concentration. Overall, ANNs perform better when multiple inputs are employed rather than single input.

Lacunarity (L) is a scale (r)-dependent parameter that was developed for quantifying clustering in fractals and has subsequently been employed to characterize various natural patterns. It has been further analytically proved that lacunarity analysis invoking the gliding-box algorithm can find the correlation dimension, D₂ of multifractals. The present research empirically tests this on a set of multifractal models generated with known D₂ values. The log-transformed lacunarityvalues of these models, log L were plotted as a function of the log-transformed box-size, log r. The slopes of these linear relations, estimated using regression analysis, were then used to calculate D₂ values that gave an approximately 1:1 relationship with the known values. Multifractal behavior can therefore, be checked without having to compute the whole spectrum of non-integer dimensions, D _q (-∞ < q < +∞) that typically characterize a multifractal. The technique thus developed was applied to fracture intensity maps generated from a set of nested fracture networks from the Devonian Sandstone, Hornelen Basin, Norway in order to test if such intensity maps display multifractal behavior.

Tetrahedral mesh has excellent properties such as being easy to be edited and suitable for simulating the complex geological body. However, classical algorithms for tetrahedral mesh generation such as Delaunay tetrahedral mesh algorithm, Advancing Front Technique (AFT) and Octree algorithm still have problem of low efficiency. Here three aspects Delaunay tetrahedral mesh algorithm are modified to improve its performance in geological applications. Optimization of efficiency is divided into two parts: macro-optimization and micro-optimization. The macro-optimization is to increase efficiency through the data pre-processing. For the micro-optimization, a practical topological structure is proposed to construct the topological relationships among the points, edges and triangles to achieve more efficient search speed. On the other hand, the sliver of tetrahedral mesh will affect its quality seriously. We classify the slivers into different types and eliminate these slivers by different methods. This improved approach is applied to gold mine reserve estimation of Zij in Mine, Fujian, China. The result shows the modified algorithm is robust and its performance is better than traditional method.

The lattice Boltzmann method is applied in the high performance computing of hydrothermal ore-forming systems. The scheme is highly amenable to parallelization and can deal with the multi-scalar fluid field without significant penalty. The method is implemented on a high performance computing platform with multi-processors and the paradigm of double-diffusive natural convection is used to verify the feasibility. The results are in agreement with those obtained by conventional methods. The parallelism is easily realized with the speedup ratio approaching the value of theoretical prediction. The present study provides a promising alternative to the simulation of hydrothermal ore-forming systems.

A methodology to accelerate GSLIB routines is presented, using the last updated Fortran codes as base. Minimal code modifications are added decreasing as much as possible the elapsed time of execution of the studied routines. If multi-core processing is available, the user can activate special instructions in the code to speed up the execution using all resources of the CPU. Two case studies are presented with the corresponding elapsed times and speedup results.

Mineral and chemical constituents are multiple in numbers (say, C-dimension with C > 3) and are estimated as positive random fractions in open interval (0,1) of total weight/volume of measurement. Such data suffer from several drawbacks as regards their statistical analysis and inference and subsequent geological/mining applications. These defects can be listed as: (i) data are closed with spurious negative correlations among the constituents(that is data are not FULLRANK lacking unique Inverse Matrix), (ii) data are Binomial/Poisson for major/trace components where means are highly correlated to corresponding variances and Not Independent as is required for Gaussian density that is needed for conventional LINEAR statistical estimations, tests of hypotheses etc. and mean values are highly positively skewed for constituent fractions less than 0.5 (1/C = 0.33), (iii) variances are Not Homoscedastic over mean values as is required for Gaussian density for regression(correlation) studies, and (iv) data belong only to the interior points of C-dimensional complex excluding apices, hyper-edges, hyper-planes etc. These drawbacks can be eliminated by suitable pre-analysis nonlinear transformation, such as log (c (i)/1- c(i)) where c(i) is the fractional value of the ith constituent in the rock/ore sample that was petrographically /chemically measured. The advantages of Gaussian density of constituents are LINEAR additions of random variables remain Gaussian (or, data are CLOSED or have CONSTANT SUM under summations) and hence, their second order statistics (mean, covatiance/correlation) are the only Two Non-ZERO Parameters needed for statistical characterization, as all the higher cumulants are zeros. Since rocks/ores are heterogeneous solids, a suitable volume/weight, representative elementary volume (REV), must be sampled and chemically analyses so that the resulting data are consistent, stable, unbiased and reliable. The author and his students have been using a log(c/1-c), or log (odds) having multiplicative errors(NOT additive errors as given in conventional probability theory), pre-transformation for Gaussianising the geochemical data and their subsequent statistical inference since 1980s and have obtained very good geological inferences for several ores including, Au, BIF, Pb-Zn-Cu-Ag, Cu-Ag, P and associated single and multi-element mineralisations. A measure-theorectic proof of the applicability of this logarithmic pre-transform, log (c/(1-c)), to obtaining Gaussian density is given. Applications of the pre-transform for Gaussianisation of fractional geochemical data for optimal grinding and beneficiation of ores, blending operations and processing to Marketable Grades, for exploration, anomaly detection, development & mine planning, and for obtaining Pathfinders of Single and Multiple-element ores are included here.

Reliable estimation of rainfall distribution in mountainous regions poses a great challenge not only due to complex relationships between irregular topography and precipitation, but also due to non-availability of abundant rainfall measurement points. This study presents a comparison of univariate and multivariate methods for spatial interpolation of rainfall in complex terrain of Indian Himalayas in Uttarakhand region. To understand the role of topography in explaining the spatial variability of rainfall, elevation and slope calculated from DEM are incorporated as covariables in multivariate interpolation methods. Further, the study area is divided into three different regions based on variation in the elevation of topography and the performance of different spatial interpolation methods is analyzed for subdivided regions. The normal annual rainfall data of 80 rain gauge stations spread over 53,484 km2 is used to generate rainfall map using different interpolation methods. Cross validation is used to compare the prediction performances of the three multivariate geostatistical interpolation algorithms: simple kriging with varying local means (SKlm), ordinary cokriging (OCK), regression kriging (RK) and two univariate techniques: inverse distance weighted (IDW) and ordinary kriging (OK). The inclusion of elevation or slope as auxiliary variables improves the prediction of rainfall in mountainous region. SKlm performs better than OCK in all the cases. Residual kriging outperforms SKlm in Shivalik and Lesser Himalayas region where the correlation between rainfall and elevation is high (r_shivalik = 0.79, r_{lesserhimalayas} = 0.5). Also, OCK proves to be a better choice than OK only when the correlation between the rainfall and secondary variable (elevation or slope in this case) is good. When the data of Shivalik region (r=0.79) is considered, the RMSE of OCK is 363 and that of OK is 368. The prediction using OK and OCK yields similar result when the correlation between rainfall and elevation is moderate (r < 0.4). For all the cases, residual kriging outperforms OCK.

Kerala, one of the smallest States of South India, is blessed with forty-four rivers. River Pampa is the third largest river in the State of Kerala, 176km long with a catchment area of 2235Sq.km. Recurring tropical monsoon floods during every season, causing substantial damages, is one of the perennial problems experienced in this river basin. Studying rainfall trend in the river basin and its underlying features are vital in understanding the flood phenomena and its socio-economic impacts. The present study evaluates the trend of rainfall in the Pampa river basin, utilizing the data from five gauging stations. The time series of monthly and annual rainfalls for the past twenty two years have been analyzed statistically. Significant changes have been observed in the basin rainfall features – both seasonal and annual rainfall.

The study aims to investigate rainfall trends in West Bengal, India. The paper deals with monthly, seasonal and annual general rainfall trends. The study is carried out to understanding the underlying feature for the purpose of forecasting and in identifying the changes and impact that are very crucial for an agro-based economy like the one of West Bengal, India. Here we studied using monthly data series of last 100 years (1901-2000). The methodology has been adapts various statistical approaches in order to detect the possible precipitation changes in annual, monthly and seasonal basis; including both the non-parametric tests for monotonies trend (Mann-Kendall test, Sequential version of Mann-Kendall test and Sen’s estimator of slope). Maximum of the districts showed an increasing trend in annual rainfall, but only one district (South 24 Pargana), this trend was statistically significant. In case of Monsoon months (June to September) maximum number of districts shows the increasing trend but it is not statistically significant. Only three districts (Midnapur west, North 24-Parganas and South 24-Parganas) of them are statistically significant. The majority of districts show very slight change in rainfall in non-monsoon months.

Punjab state in the northwestern part of India constitutes 1.57% of total area in the country and its economy is mainly controlled by agriculture by covering 85% of geographical area with cropping intensity reaching to 184% in the central parts of the state. During last 4 decades a shift from Sugarcane-Maize-Wheat cropping pattern to Wheat-Rice cropping pattern has lead to increase in the demand for irrigation water and further putting stress on the groundwater. Groundwater level monitoring has been carried out on 4 observation wells in 4 blocks namely Ajnala, Majitha, Rayya and Tarsika of Amritsar for 7 years during January 2006 to December 2013 for assessing the groundwater level. Groundwater occurs under phreatic condition and depth to groundwater varied from 6 to 11 m (bgl) in Ajnala, 5 to 11 m (bgl) in Majitha, 14 to 19 m (bgl) in Rayya and 9 to 14 m (bgl) in Tarsika. The increased depth of 6 m was observed in Majitha and 5 m was observed in other 3 blocks. Monthly groundwater level data have been analysed which indicates that the ground water is declining in all the four blocks with variable rate. The decline of groundwater level in each block during 7 years has become an area of concern for understanding the over exploitation of groundwater scenario in the region.

The hydrogeochemical parameters for forty five groundwater samples of the Dun valley aquifers of central Nepal were studied to appraise the major ion chemistry and suitability of groundwater quality for domestic and irrigation uses. Geologically, the area comprises Quaternary alluvium composed of boulder, cobble, pebble, gravel and sand with intercalation of clays. Geochemical classification of groundwater shows that the majority of groundwater samples belong to the calcium-bicarbonate type. TDS values of groundwater in the study area are <1000 mg/l, therefore all groundwater evaluated are suitable for drinking and irrigation uses. The high nitrate concentration (>50 mg/l) of about 53% of the groundwater samples may be due to the local domestic sewage, leakage of septic tanks, and improper management of sanitary landfills. In general, %Na and SAR values indicate good to permissible use of water for irrigation purposes.

The main objectives of this study are to identify spatial correlations between groundwater and hydro geological parameters using geostatistical and subjective probability methods, towards identifying the effect of surfacial oil pollution on groundwater. The data used included multi-element chemical data for the nine groundwater field and surface and subsurface geological data. A GIS database is constructed to map the spatial variations in the geochemical and geological parameters. Geostatistical analyses consisting of variogram and kriging analyses are conducted, and the results identified the geometries of spatial correlations between the geochemical variables in the nine groundwater fields. Weights Of Evidence (WOE) model, which is based on conditional probability analysis, is used to evaluate the spatial association between pollution related to hydrocarbon contamination and groundwater fields.

The present study attempts to understand the controls of geomorphological terrains on groundwater geochemistry and groundwater arsenic (As) distribution in the shallow aquifers of parts of the Brahmaputra floodplains of India. Three different geomorphologic units e.g. older alluvial (OA), younger alluvial (YA) and river channel deposits (RCD) were identified as predominant geomorphic terrains in the study area by coupled remote sensing and field observations. Groundwater compositions in the aquifers of these terrains were dominated by Ca–Na–HCO₃ and Na–Ca–HCO₃ hydrogeochemical facies. At least 60 % groundwater samples of study areahave As ≥ 0.01 mg/L. The reductive dissolution of (Fe-Mn)OOH is the dominant mechanism of As mobilization in different alluvial terrains and redox transitions play major role for As mobilization in groundwater.

This study presents an evaluation of ground water quality in a unique coastal ecosystem Kalpitiya, which is a low-lying peninsula in North-Western coast of Sri Lanka. In this study we assessed the physical quality of ground water in the peninsula and developed GIS maps. It was evident that pH, EC and salinity were unable to meet standards of water quality during the dry season. This condition warrants attention of the authorities since not only dry weather but also the climate change will aggravate the situation making water less available.

Significant amounts of fluoride are found in the abstracted groundwater of the southern part of the Upper Panda River basin, Sonbhadra district, Uttar Pradesh, India. Hence groundwater with high fluoride and water mixture patterns were studied in Panda River basin through hydrochemical interpretation from 65 groundwater chemical data information from different wells for both the seasons, premonsoon and postmonsoon. The chemical relationship and Gibbs diagram suggest that the groundwaters mainly belong to freshwater, alkali type and are controlled by rock dominance; due to influence of semi arid condition and water-rock interaction. Na-HCO₃ is dominated in most part (60 % of the total number of water samples for both the seasons) of the study area. The whole environment is favorable for the fluoride dissolution as the increasing Na concentrations are observed under alkaline conditions with a subsequent reduction in Ca concentration. Major rock types of the area are phyllites and granite gneissic rocks. Geochemical study reveals that Fluor-apatite and biotite mica in the granite gneissic rock is the main source of fluoride in the groundwater through water–rock interactions. Fluoride concentrations are in the range 0.4–5.6 mg/L in the pre-monsoon season and 0.1–6.7 mg/L in the post-monsoon season. Ion exchange, dissolution, semi-arid climate, alkaline conditions and weathering are responsible for fluoride enrichment in the groundwater of the study area.

Uranium is the heaviest naturally occurring element found at an average concentration of 0•0004 % in the earth’s crust and in low levels within all rock, soil and water. Natural uranium is a mixture of three isotopes, 238U, 235U and 234U and all three behave the same chemically, but they have different radioactive properties. The predominant forms of uranium are 234U and 238U which occurs naturally in groundwater and surface water. Its content in groundwater varies markedly depending upon geological terrain, climate, proximity of uranium deposits, as well as composition of the water. Uranium contamination of groundwater comes from the aquifer from which the water is pumped. The study area have a particular importance because of its elevated levels of uranium detected in the groundwater which may be attributed to the radioactive rich granitic rock formations of Tusham Hills (Bhiwani) of the neighboring state Haryana and from Shivalik Himalayas, parts of which are known for uranium mineralization and also through human activities like phosphate fertilizing. Being a radioactive mineral, high uranium concentration can cause impact on water, soil and health. The maximum contaminant level for uranium, recommended by the World Health Organization is 30 μg/L and this limit is found to be exceeded in the drinking water of various regions of Punjab. This work reviews and interprets the prevailing scenario in Punjab region, focusing on uranium as an important environment contaminant.

Water availability in Drâa basin (surface area ~ 115,000 km2) depends on rainfall, melting snow in the High Atlas mountains and groundwater. The region has strong evidence of groundwater flow presence whose functioning is required to be fully understood to achieve an adequate water management for an expected rainfall reduction. Previous objectives of carried out studies in the region included the aquifer unit theory and water-balance, lacking a 3D groundwater flow understanding. A regional approach allowing a clearer perspective of groundwater dynamics in its geological context was applied: the Groundwater Flow Systems Theory, which identifies local, intermediate and regional flows hierarchy. The conceptual 3D model included: hydraulic heads, hydraulic properties of rock units, soil type, vegetation, and geomorphology which are in agreement with the physical, chemical and isotopic properties of groundwater. This model was implemented, calibrated and validated using Visual Modflow. Obtained initial-heads were subjected to different recharge conditions; results show that change in recharge is more affecting local flows. However, in the Middle Drâa sub-basin where intermediate flows were identified, the simulated heads lack immediate response to the variation of recharge. Results suggest that local flows are more likely to be affected by climate conditions than those of intermediate and regional nature.

The over exploitation of groundwater in India is increasing day by day due to ever increasing population and industrialization, resulting in progressive lowering of static water level and reduction of well yields. The estimation of recharge to groundwater is crucial to better water resources management particularly in arid and semi-arid regions. The tritium tagging technique has been widely used for the estimation of groundwater recharge in different regions of India. This technique provides fairly accurate estimate of vertical downward flow component of soil moisture through unsaturated zone. In the present paper, the groundwater recharge due to monsoon rains in Ozar watershed located in Nashik district (Maharashtra) in Godavari basin has been assessed using tritium tagging technique. The experiments have been carried out in cultivated agricultural fields. Artificial radioisotope (Tritium) was injected at four cultivated sites before the onset of monsoon and soil samples were collected from the injection points soon after the withdrawal of monsoon. In the study area, mainly three types of soils were found, namely clay, loam and sand in which sand predominants. The percentage of groundwater recharge varies from 9.77 % to 23.19 % in the study area depending on the type of soil and other geo-hydrological conditions of the study area.

Groundwater pollution can be illustrated as degrading of water quality for any usage. The Eleven hydrochemical parameters of groundwater samples from different formation were used in this study to understand groundwater chemistry in this complex multilayer aquifer system. The statistical analysis of the results shows that dominant process of weathering of feldspar, pyroxene and ion exchange. The water flows along the formation dissolving these ions along its flow path through the process of leaching of the secondary salts inherited in the formation obtained by the mixing of several geochemical processes. The anthropogenic impacts in the groundwater are noted in the younger formation than that of Cretaceous and Lower Cuddalore.

Radon-222 is a daughter element of radium-226 and are member of the uranium decay series. Radon-222 concentrations in groundwater of Bangalore city in different geological units were measured in 42 tube wells. The study area is underlain by Granite, Migmatite, Granodiorite and Gneiss rock and many dolerite dykes. The radon-222 concentration in groundwater is widely varying and ranging from 14 to 1000 Bq/L with an average value of 172.4 Bq/L. Significant differences in the radon-222 concentrations in groundwater among geological units were observed. The radon-222 distribution in groundwater is related to the presence of uranium in aquifer materials of the various rock types. Uranium concentration in groundwater is ranging from 0.2 to 523 μg/L. Transport of radon-222 through bedrock by water depends mainly on the percolation of water through the pore and along fractured planes of the rocks. Rn-222 cannot travel farther than several hundred meters away from their origin because of its short half-life of 3.8 days. It may travel the farthest within fractured or fissured geological formation where groundwater movement is fastest. The study shows that radon concentration in groundwater is controlled by geohydrological and hydrochemical characteristics of the study area.

Groundwater arsenic (As) survey in tubewell was done from Bengal Delta (West Bengal), Middle Ganga Plain (Uttar Pradesh-Bihar), Ghaghara Valley (Uttar Pradesh), Imphal Valley (Manipur) and Barak Valley (Assam). About 51% of tubewells have As > 10 μg/l (WHO guideline) and 30% of tubewells have As > 50 μg/l (max. As 500 μg/l) in the Bengal Delta (West Bengal). In the Middle Ganga Plain (Uttar Pradesh-Bihar), about 73% of tubewells have As > 10 μg/l and 41% of tubewells have As > 50 μg/l (max. As 1300 μg/l). About 49% of tubewells have As > 10 μg/l and 29% of tubewells have As > 50 μg/l (max. As 510 μg/l) in the Ghaghara Valley (Uttar Pradesh). In the Manipur Valley, about 63% of tubewells have As >10 μg/l and 40% of tubewells have As > 50 μg/l (max. As 502 μg/l). In the Barak Valley (Assam), about 66% of tubewells have As > 10 μg/l and 26% of tubewells have As > 50 μg/l (max. As 350 μg/l). Most of the As-contaminated (As > 10 μg/l) tubewells are located within the depth of 15 to 50 m in the Holocene Newer Alluvium aquifers. Arsenic affected villages are preferentially located close to abandoned or present meander channels and floodplains of the Ganga, Ghaghara, Bhagirathi, Barak and Imphal rivers.

In recent times, there has been a tremendous increase in demand for fresh water and water shortage in arid and semi-arid regions due to population increase, industrialization and agricultural activities in parts of world. Comparative studies of ground water resources in Varanasi district have been carried out with the objective to identify reasons why groundwater resources is increasingly being exploited, and to explore ways through which the exploitation could be done sustainably. In study area, erratic rainfall, diminish of ponds and reduction of surface water create tremendous pressure on groundwater to fulfill increasing demands. The heavy withdrawal of ground water for sustainable development of agricultural practices, fast urbanization and industrialization led to problems of overdraft, falling water levels and failure/dried up of shallow tubewells/dugwells, degradation of ground water quality and shift of blocks from safe to critical and semi-critical.

A three years lasting isotope hydrological study has been performed in the 14,000 km2 catchment of river Gunt in the western Pamir in Tajikistan to resolve the contributions of different components to the total run-off out of the catchment. River samples have been taken from about 30 locations and precipitation from five stations in this high-alpine and partly glaciated region both in a monthly interval. Precipitation as important initial parameter was shown to originate from different wind systems tracing regionally the isotopic composition in time. Within the catchment, the subcatchments group with respect to deuterium excess of their waters. This strengthens the assumption of the varying influence of different wind systems. Along with the isotopic composition, hydrochemistry of the river waters varies in an annual cycle as result of a varying contribution of groundwater and/or melt water. Similarly, with these tracers the low-energy flow of the eastern part of the valley can be clearly separated from the dominating fraction from the high-energy flow in the western part.

Madurai is a water scarce, semiarid region in southern part of Peninsular India. Currently, tank-fed agriculture development programme is being implemented in this region by utilizing the large number of traditionally existing minor irrigation tanks. Hence, an isotope hydrological investigation has been conducted in the Thirumal village, Madurai district to demarcate the zone of influence (i.e., the command area) of the cascade of tanks (4 tanks) and to quantify the groundwater recharge to the downstream wells. Pre (October 2011) and post (February 2012) monsoon samples were collected from the irrigation tanks, open wells upstream and downstream of the tanks etc. and analysed for δ2H, δ18O and hydrochemistry. The downstream well samples lie in a mixing line between the tank water and the rainwater in the δ18O - δ2H plot, indicating groundwater recharge from the irrigation tanks and the area of influence of these tanks were demarcated. The tanks contribution to the downstream wells varies from 97% at 20 m to 41% upto 880m for the first tank, 93% at 60m to 26% at 880m for the second tank, 95% at 30m to 18% at 940m for the fourth tank and varies from 25% at 20 m to 9% at 550m for the third tank.

We use quantitative provenance analysis (geochemical analysis; high-resolution bulk-petrography and heavy-mineral analysis, exploratory compositional data analysis and Aitchison distance) on present-day river sediments of the Changjiang (Yangtze) River toquantify the contributions of each tributary to the Changjiang River Delta, and thus to evaluate sediment provenance in the distinct parts of the drainage basin.

Textural (grain size) analysis is one of the parameter that helps in determining sedimentary environment. In the present investigation, texture was analysed from sixteen stations in the Khurar River, Madhya Pradesh. Grain size analysis was carried out employing mechanical sieving method using a sonic shaker. Frequency and cumulative frequency curves were prepared from the grain size data on centimetre and arithmetic probability papers, respectively. The phi values were determined and used to calculate the statistical parameters such as mean, standard deviation, skewness and kurtosis. It is found that the mean value varies from -0.63 to 0.80 with a graphic mean distribution ranging from -0.27 to 0.40 φ, indicating that the size of the river sand is very coarse- to coarse-grained. The standard deviation (sorting) shows a range of 0.69 to 1.65 φ, while the skewness values of the sediment samples range from 0.19 to 0.29 φ, thus indicating the presence of fine fraction to near-symmetrical fraction in the population. The kurtosis varies between 1.03 and 1.09 φ, indicating that 25% of the samples are leptokurtic, 6.25% are very leptokurtic, 50% are mesokurtic and 12.5% are platykurtic. The platykurtic nature in few cases suggests mixing of the sediments from two sources. Bivariate plots prepared combing different textural parameters were used to interpret their behaviour in the river sediments. C-M plot was also prepared to understand the dominant mode of transportation in the Khurar River sediments. In this river all the sediments are dominantly characterized by the rolling process of deposition. This study reveals that sorting varies from poorly sorted to moderately well sorted from upstream to downstream part of the river may be because of dominance of winnowing and selective sorting in the lower reaches of the river.

Rivers constitute the lifeline for any country. Both natural and anthropogenic processes influence the river processes. Recently, erosion processes and fluvial transport of materials have become a focus of reviving attention owing to their significance in land use and environmental aspects. To understand the erosion process and sediment geochemistry, more than 25 samples were collected from river Ramganga. Ramganga River originates from a Namik glacier in Gairsain village of Chamoli district in Uttarakhand lying at an elevation of 2926metres. Ramganga River flows in the Kumaon Himalayas and is the first major tributary of river Ganga in the Indo-Gangetic plains. The study area includes the entire catchment of river Ramganga covering a stretch of approx. 350 km from the Chamoli district in Uttarakhand to Farrukhabad district in Uttar Pradesh before joining with the Ganga River on its left bank at an elevation of 124 meters. The river bank sediments were evaluated for their size determination by using the particle size analyzer. All the sediments were treated with H₂O₂ to remove organic matter; the computed results were interpreted using the statistical approach mentioned by [2]. Most of the sediment were found to be of sand grade and are well sorted to poorly sorted in nature. Population of sediments varies from being coarse skewed to fine skewed. An attempt has been made to find out the factors controlling the sediment size. Multivariate analysis was performed to find out the relation of sediment size with discharge and climatic conditions such as rainfall. The results point out the role of topographical, lithological, and climatic factors in determining the grain size of sediments.

Recent studies have probed grain size analysis to understand the transport energy, deposition, source of the sediments in rivers. Sediment size also relates to the geochemical composition of the sediment and for predicting the response of climate and anthropogenic activities on watersheds. Following the approach of Folk and Ward, 1957 grain size characteristics were evaluated for the channel sediment sampled from river Alaknanda during different time periods. River Alaknanda is one of the major tributary of River Ganga flowing in Garhwal Himalayas. The erosion rate in the Alaknanda basin is very high, almost double the world’s average; a large number of landslides occur in the entire watershed which are caused naturally due to steep slopes and lithology and nowadays promoted by increased anthropogenic disturbances and thus in this case grain size becomes the fundamental character to understand the river processes. Grain size was evaluated by using a particle size analyzer. The different time period data highlights the spatial and temporal variation in the statistical parameters of grain sizes. The values of mean size, sorting, skewness and kurtosis varies considerably. It was found that sand dominates in most of the samples. Well sorted to poorly sorted nature of the sediment was observed. The skewness and kurtosis values show the heterogeneous nature of grain sizes. An approach has also been followed to discriminate the grain size distribution of two different intervals by using the ANOVA test. A one way ANOVA test was performed to estimate the remarkable difference in the mean values of grain size parameters of two samples. ANOVA results confirm that significant differences exist between the samples. The outcome of the study demonstrates the influence of discharge, river energy, erosion rate and seasonal variability in determining the sediment size.

This paper adds to the understanding of monsoon precipitation in Southern Africa as a contribution to isotope hydrological studies in that region. Central Mozambique’s climate has a wet and a dry season, both controlled by the migration of the Inter-Tropical Convergence Zone (ITCZ). Two rain collectors were installed at an altitude of 34 m and 346 m about 60 km and 120 km west of the Indian Ocean. Both were operational from 02/2007 to 09/2010. Reference is made to the IAEA/GNIP stations Harare and Antananarivo. The local meteoric water line is δD = 8.7 δ18O + 15.5‰ (R2 = 0.97). The mean annual rainfall in 2007-2010 is lower than for the period 1956-1984 and is most pronounced for the dry season. The observed high deuterium-excess values suggest contributions from different water vapour sources that evaporated under varying conditions over the trail of ITCZ. δ2H and δ18O ratios in dry season precipitation are more depleted in 18O due to atmospheric recycling of evaporated and equilibrated water vapour in convective systems.

Climate change could be blamed on observed water quality decline. This is an undesirable response in any supply project based on groundwater that could produce negative effects as health hazards for the population, undesirable impacts to infrastructure, and increases of maintenance costs for economic activities. Climate change has created recent concern, also the increase in groundwater extraction resulting in enhancement of salinity and/or toxic element content. Results are significant in regions where aquifer thickness is ~1,000 m or more. The objective of this work is to propose the control of groundwater quality in extraction boreholes when the dynamics of the governing flow systems is defined by establishing their hierarchy as proposed by the Groundwater Flow Systems (GFS). Understanding GFS and their role in extracted groundwater provides adequatestrategies for efficient water use and its corresponding planning and management. Usually boreholes response to groundwater extraction is a mixture of flows of different hierarchy. Vertical inflows increase their importance as drawdown progresses with extraction time. Results suggest climatic conditions may affect local flows. A joint groundwater monitoring for adequate managing is highly satisfactory ie. hydraulic data (water-level), physical (temperature) and chemical (specific element) data may be used to monitor expected response due to extraction.

The western part of India is hot desert, which is known as Thar Desert. The largest extent of this desert is spread over Rajasthan state. In order to increase agriculture potential of desertic soil Indira Gandhi Canal Project (IGCP) was introduced. The development of IGCP project has bought changes in the land use pattern in terms of increase in area under the agriculture. The increase in area under agriculture and under irrigation network has brought fluctuations in the groundwater level. This fluctuation in groundwater level is result of the seepage of water through the excessive irrigation and the seepage from the canal network. Thus the human impact in form of land-use pattern of a land is an important determinant of rise and fall in groundwater level. The spatial and temporal variation in groundwater level has been analysed Inverse Distance Weightage technique across different pentards for 128 observation wells of the Anupgarh, Vijayanagar and Suratgarh tehsil of Sriganganagar district of Rajasthan, which lies in the northwestern part of IGCP Stage I.

Rajasthan is one of the water scarce states of India where the annual average rainfall varies from less than 100 to 1000 mm. Kolayat area of district Bikaner located in western part of the state, receives average annual rainfall of 275 mm. Owing to the less rainfall of this low magnitude, the water availability problem in the Kolayat area is critical in comparison to many other parts of the state. The water requirement, of the area, is mainly met by Indira Gandhi Nahar Project (IGNP) canal. The groundwater quality of the area through which IGNP canal passes has been studied to understand the effect of canal recharge on groundwater and subsurface movement of recharge pathways. The canal trends in NE-SW direction and flows towards SW. The study has been carried out across the canal 40 km in the eastern and 20 km in the western direction. The depth to water varies between 10 and 55 m bgl. The water levels are shallow in western direction and upto Bajju in eastern direction from the canal. The water levels become deeper as one moves towards eastern direction. This suggests that the groundwater regime receives recharge from the canal towards western direction and upto Bajju in eastern direction. The groundwater flow directions obtained from water table contours also reveal the presence of groundwater mound in the vicinity of the canal. The EC of the canal water is 302 μS/cm where as the EC of groundwater varies from 563 μS/cm to 23600 μS/cm. The EC of groundwater along the canal varies from 563 μS/cm (Bajju) to 1916 μS/cm except Modayat where as EC is high away from the canal. Water quality analysis confirms the same result as interpreted from groundwater contours. The groundwater of the area has high calcium, magnesium, sodium, potassium, chloride, sulphate, they range upto 634, 787, 5890, 1015, 7908, 2650 mg/L respectively. Further, fluoride in the areas around Chak 4 GMR (3.8 mg/L), Bajju (1.93 mg/L), Godu Krishi farm (4.12 mg/L), Godu village (1.93 mg/L) exceeds the permissible limit for drinking purpose. The study also reveals that recharge from IGNP canal has a long term influence in the study area where groundwater is withdrawn for various activities.

Fresh water resources in most areas of world are shrinking at an alarming rate and may not meet the ever increasing demands for domestic, agriculture and industry in future. Moreover, estimates reveal an annual production of ~30 MT of wastewater in the World. In India, estimated sewage water generation from Class I and Class II cities is 38,255 MLD, out of which only 11,787 MLD is being treated. The untreated wastewater enters in groundwater, rivers, and other water bodies thereby making it unfit for human consumption. The projected wastewater generation in India will be 122,000 MLD by 2050, which necessitates strengthening of existing treatment plants and investment in new treatment plants for safeguarding fresh water resources and human health. Pre-treatment is an integral part of any wastewater treatment scheme and results in appreciable reduction in capital as well as operating cost associated with downstream units due to reduction in organic load. A tannin based natural flocculent (Tanfloc) along with ferric chloride was used for pre-treatment of domestic wastewater using jar-test. It was able to achieve reduction in turbidity, COD, and BOD up to 95%, 69%, and 60% respectively. The optimum dosage for treatment of municipal wastewater under investigation was 10 ppm ferric chloride with 15 ppm Tanfloc.

The persistence of Organochlorine pesticides (OCPs) and Black Carbon (BC) was studied in sediment samples from river Yamuna, a major tributary of the Ganges (one of the largest, most populated and intensively used rivers in Asia). High levels (21.41 to 139.95 ng g-1) of sum of 20 OCPs (∑₂₀OCPs) have been detected with β-HCH as the predominant component. ∑HCH and ∑DDT constituted ~86% of ∑₂₀OCPs. Lindane, DDT and technical grade HCH were recently used. Toxicological studies with reference to fresh water sediment quality guidelines showed alarming levels of γ-HCH and DDT. DDD, DDE, β-HCH, α-HCH, Endrin, Heptachlor epoxide and Chlordane exceeded some of the guideline levels. High levels of BC (0.46 ± 0.23 mg g-1) constituted 1.25 to 10.56% of TOC. BC was correlated with isomers of HCH, p,p’-DDT and Methoxychlor; while TOC with ∑₂₀OCPs, γ-HCH, Endosulfan Sulfate and Methoxychlor. PCA enabled better understanding of the relationship between various OCPs, BC and TOC. The association of BC with various OCPs indicated its importance in retention of some OCPs into fluvial sediments; exhibiting the potential to reduce their bioavailability. The study is unique to report the role of BC in persistence of OCPs in fluvial sediments.

As landfills are used to dispose Municipal Solid waste (MSW) but due to lack of proper engineering facilities, these landfills have always been the source of pollution in the soil and water environment. The leachate samples were collected from Bhalaswa landfill site in Delhi in winter season. Leachates were characterized by measuring physicochemical parameters like pH, EC, TDS, concentrations of metals like Pb, Cu, Fe, Ni, Cr, Ca, K, Na, Mg. Toxicity tests such as germination inhibition and growth were tested and cell apoptosis was assesed by Flow cytometry. The toxicity tests were conducted by diluting the crude leachate with distilled water and toxicity was recorded against Triticum aestivum (Wheat). The results indicate that lower concentration stimulated germination as well as growth while higher concentrations inhibited the process in a time and dose dependent manner. This implies that leachate from the landfill is toxic to plants and exposure to the leachate in aquatic environment may pose a potential risk to the organisms. The results show that Triticum aestivum treated with different concentrations of leachate induces toxicity in Triticum aestivum in a time and dose dependent manner. The results further indicate the relationship between physicochemical parameters and toxicity.

Soil physico-chemical properties and concentrations of heavy metals in the soils around Jharia coalfield in Jharkhand state of India were determined to quantify the levels of contamination in the area. The extensive coal mining in the area altered physico-chemical properties of the soil. Sites near coal mining areas were heavily contaminated with all the measured heavy metals. The average concentrations of Fe, Mn, Zn, Pb, Cu, Ni, Cd and Cr were higher compared to the critical soil concentrations. At the sites near coal mining areas, Mn, Cu and Ni were near the toxic limits of the respective metals. Soil pollution assessment was carried out using enrichment factor, geo-accumulation index and pollution load index. Higher enrichment factor for Mn, Zn, Pb, Cu, Ni and Cd indicated significant inputs from mining activities in the soil. The geo-accumulation index values revealed that Cu, Pb and Ni are significantly accumulated in the study area. The pollution load index derived from contamination factor indicated that the sites near coal mining areas are most polluted. Multivariate statistical analyses, principal component and cluster analyses suggested that Ni, Cu and Pb were derived from anthropogenic sources, particularly coal mining activities and vehicular transport.

Coal has been the leading fuel in the energy industry. Its usage has shown far reaching consequences to health and environment. Occurrence of PAH in coal is well known fact but its effect to the human health is least addressed. It is one of the dangerous carcinogens with its ubiquitous presence in the environment. The present investigation on few coal samples reveals presence of substantial amount of PAH in the Mahanadi basin coalfields. Proper mitigation of this substance is required to ensure proper health of the miners and personnel in coal industry. Among the PAH reported are Anthracene, Benzo(a)pyrene, Phenanthrene and Pyrene etc. According to International Agency for Research on Cancer (IARC) a study in 1936 by investigators in Japan and England showed lung cancer mortality among workers in coal carbonization and gasification processes. Later on studies in US was carried on coke oven workers which confirmed the lung cancer mortality, with the suggestion of excessive genitourinary system cancer mortality. Given these implications this investigation attempts to address PAH in the coals of Mahanadi basin.

Soil organic matter and soil aggregate stability are good indicators of soil quality and both can be positively affected by reduced tillage and residue management practices. A field study was conducted to find the impacts of tillage and residue management practices on soil carbon stock and distribution of SOC within different soil physical fractions. The study site was a 30-year experiment divided to six treatment classes, conventional tillage (CT) and reduced tillage (RT) with straw incorporated (S), straw removed (SR) and straw burned (SB). The soil was segregated into four different classes: large and small macroaggregates, microaggregates and silt and clay which were analyzed for total carbon. Reduced tillage or residue incorporation did not result in higher C sequestration but there were more water stable aggregates in the reduced tillage treatment.

Physical alteration of soil characteristics of especially the plough layer (0-20 cm) is brought about through land culture. The type of land cover, in fact, is an important factor controlling the soil texture, soil organic carbon (SOC) and soil erosion. The objectives of this paper areto analyze soil particle size distribution in the plough layer and quantify the SOC storage in the finer soil separate under native vegetation cover, cultivated land, eucalyptus plantations and barren land. A digital land cover map of the study area has been generated using Resourcesat-2 image. Soil samples from plots under different land cover types have been collected from depths of 0-10 cm and 10-20 cm. Particle size analysis has been done by dry sieving. SOC content of each soil separate – sand, very fine sand, silt + clay, under different land cover, has been done with the help of Walkley and Black method. Analysis of particle size distribution showed that proportion of sand particle is high. However silt+clay proportions have been found to vary with land cover types. SOC was high in silt+clay particles in general; but tended to increase in the sand fractions when particulate organic matter is incorporated. SOC decreased with soil depth under all land cover conditions but showed a reverse trend in some plots of cultivation.

Salt-affected soil (SAS) is a permanent problem inherited in landscape of arid and semi-arid region due to climatic conditions. Sodic soils are an important category of SAS which are characterized by excess levels of sodium ions (Na+) in the soil solution phase as well as on the cation exchange complex. Soil sodicity is one of the major problems that deteriorates the quality and quantity of produce and limits the choice of cultivable crops. The objective of the study was to assess the sodicity status in the salt-affected area of Israna. Soil chemical properties related with sodicity viz., electrical conductivity (EC), exchangeable sodium (Na+) concentration, exchangeable sodium percentage (ESP), sodium adsorption ratio (SAR) and soil pH were analyzed using standard methods. Results showed significantly (P≤ 0.05) higher values of pH, exchangeable Na+ concentration, ESP and SAR in all the affected sites relative to the control sites. This study reveals that the salt- affected soils are sodic in nature which affects the growth and yield of crops.

This paper analyses the dynamics of AOD over north-western part of northern Indian plain during the harvesting season its effect on surface reaching solar radiation from 2001 to 2009 using MODIS level 2 atmospheric data set. The analysis carried out for post monsoon season during rice harvesting period and is based on 8 days composite AOD, Ozone, Water vapour, and surface pressure data. Spatial variability of AOD has been shown in 0.47 μm and 0.66 μm in order to grasp the idea of relative difference in occurrence of fine and coarse mode aerosol. Analysis of the particles under SEM-EDX collected through air sampling in the agricultural field in Punjab and Haryana during rice harvesting season shows released particles from the residue burning have 72% of O, 8% of C, 7% of Si, 2% Al, and 7% F in significant amount and barely less that equal to 1% of other elements such as Na, K, Ba, Mg, Fe, Ca, Ti, Zn, P, and Cl. NOAA-HYSPLIT back trajectory analysis shows these emitted smoke and aerosol plumes which transport a long distance through active wind system affect insolation amount at the surface. AOD levels between 2003 and 2007 were moderate to high in the western part of North Indian plain, with an average of 0.8–1.8 at 0.47 μm and 0.6–1.4 at 0.66 μm. Radiative forcing in this region during the study period vary pronouncedly amounting to -20 Wm-2 to 11 Wm-2.

Environmental pollution is one of the major health problems in both industrialized and developing countries including Sri Lanka. The main categories are water pollution, air pollution, land pollution and noise pollution etc. Out of this, air pollution is one of the severe and growing problem in worldwide and highly affects to the human health specially those who live in urban centers. It is a dangerous and silent hazard in comparison to other hazards since it is invisible. There are two types of air pollution respectively indoor air pollution and outdoor air pollution. Mainly indoor pollution is increasing with human domestic activities and outdoor air pollution is increasing with urbanization, industrialization and transport activities. The usage of motor vehicles in the Colombo City has been increased by over 300% in the last 20 years. The majority of these are motor cycles and three wheels and also other vehicles such as public transports. In that case resent results show that the city of Colombo is heavily polluted and the level of air pollution has been reached to its dangerous levels. During peak traffic hours (between 6 am to 8.30 am and 4 pm to 6 pm), Colombo area face to severe air pollution. Air pollution level was increase with rainfall variation of the area. Contamination of air pollutant was travel to another area using wind and Sea breeze. Main air pollutant emitter was Traffic and vehicles. It was clearly shows with monthly variation of pollutant distribution. Air pollution was increased with festival seasons and school holding time period.

Pt, Pd and Rh emitted into the air through the exhausts of cars and trucks collected from Bangalore, Hyderabad and Visakhapatnam cities of south India were assessed in the context of their accumulation and resultant risks on human health and ecology. Apart from road dusts, respirable suspended particulate matter (RSPM) samples from these three cities were collected and studied. Road dust and top soil samples from road junctions and traffic signals with heavy and erratic traffic flow showed higher PGE levels than those from roads with low and free flow traffic suggesting that traffic flow conditions greatly influenced emissions of PGE from the auto-catalysts. Further studies on the exposure levels from Hyderabad, showed higher amounts of Pt, Pd and Rh in the blood samples of older people (for example, traffic police) who are exposed to extreme traffic conditions. Owing to the adverse health and ecological risk potential of PGE on humans, monitoring their levels, understanding the transformation paths and to find out mitigation methods are necessary.

During the last decades, snow-dominated Northern American (NA) ecosystems have experienced prolonged spring warming and earlier spring onsets. Recent studies showed that these changes have adverse effects on plant productivity due to water stress. In this study, we analyze relationships between longer non-frozen period, peak summer vegetation greenness index and a drought index by using the three decades of optical satellite data, microwave Freeze-Thaw record and climatic data. Results show that longer non-frozen period caused decline in summer soil moisture availability. This suggests a mechanism of ‘longer non-frozen period-summer drought’ which has led to widespread decline in peak summer vegetation greenness across large portions of NA’s mid- and high-latitude ecosystems. This mechanism may be exacerbated in the future under accelerated spring warming and associated longer growing season, and depending on the future precipitation pattern generally larger degrees of dryness during the peak of the northern growing seasons can be expected.

To assess the status of diversity and regeneration of Sabaiya collaborative forest phytosociological study of the forest was carried out and Species Diversity, Importance value index, basal area, density and regeneration status were accessed. Edaphic characteristics were also studied. A total of 51 species were recorded in the study, of which 15 were represented in tree group, 20 in the shrub group and 9 in the herb group. Both seedling and sapling were represented by 11 species each. The forest was dominated by Shorea robusta (68.8 %) and Mallotus phillipensis (6.8 %). Occasionally Terminaliatomentosa (4 %) and Syzygiumcumini (4.8 %) were present in the canopy. The sub-canopy was dominated by Lagerstroemia parviflora and Semecarpusanacardium. The understory was quite sparse and dominated by Shorearobusta and Daubangagrandifloraseedlings; and shrubs such as Clerodendroninfortunatum and Eupatorium oderatum. Among herbs Cyperusiria and Cynadondactylon were dominant. Despite having satisfactory regeneration of seedlings of Sal (16960 stem/ha), very few (120 stem/ha) saplings were recorded. Similar was the case with other tree species. The soil was sandy loam to loamy sand, slightly acidic to near neutral (pH 5.34–6.88), soil Nitrogen moderate (0.12–0.25 %) and Organic carbon moderate (1.5–3.0 %).

Duckweeds are small; floating aquatic plants belongs to Lemnaceae, capable to degrade phenol in wastewater. Synthetic wastewater, similar to the characteristics of coke-plant effluents, was prepared in the laboratory, and tested the degradation efficiency in terms of reduction of COD and phenol under different organic loading rate (OLR) at 4 d and 8 d of hydraulic detention time (HRT). Artificial duckweeds ponds were kept in outdoor conditions and meteorological parameters were monitored and used for the estimation of evapo-transpiration rate and degradation of phenol. From the present experiment, it can be concluded that, for phenol concentration of 250 mg/L, 4 d detention is sufficient for the removal of 91% phenol. At higher phenol concentration of 600 mg/L, a detention time of 8 d is essential. If phenol concentration in the effluent exceeds greater than 800 mg/L pre-treatments wastewater is required. A design example for the treatment of low temperature coal carbonization wastewater by duckweeds pond system also given.

This paper describes the harmonic motion of the Earth and its calculation method. It based stress analysis of motion of Earth and generalized Hooke ‘s law, derived equations of motion of the crust, calculate the crustal movement of the major weft, and use the results to reproduce the original ancient land of before 250 Ma. By comparing the calculated results with measured values of the ITRF 2000, it proof: 1. Due to the mechanical properties of Earth’s interior rock, tidal forces suffered there are differences, with the solid tidal advance from east to west, arise relative movement between the circle layer. This is the harmonic motion of the Earth. 2. Harmonic movement of the earth is the basic driving force to promote the evolution of the Earth. Its energy from the Earth’s rotation. 3. Before 250 Ma, the Earth is only a piece of the original ancient land, it radius 7550 km, the north is slightly missing. 4. Earlier 250 Ma, continent began to split.

Fifteen multi-dimensional diagrams [1–3] for basic and ultrabasic rocks, based on log-ratio transformations, were used to decipher tectonic setting for two case studies of Borborema province, NE Brazil. The applications of these diagrams indicated the following results: (1) a mid–ocean ridge setting for ForquilhaEclogite Zone during the Mesoproterozoic; (2) a transitional island arc to mid–ocean ridge setting for Algodões during the Paleoproterozoic. Our interpretations of main result for basic-ultrabasic magmas, along with the original authors’ findings, were generally consistent.

The origin of magmas in the western part of the Mexican Volcanic Belt (W-MVB) was constrained from tectonomagmatic discrimination diagrams under the assumption that the magmas originated from different tectonic settings are distinguishable from differences in their chemical compositions. For the W-MVB, the diagrams for basic rocks generally indicate a continental rift setting whereas those for intermediate and acid rocks show either an arc or a transitional arc to rift setting but with relatively low total percent probability values. Besides these diagrams, the conventional significance tests (Fisher F, Student t, and ANOVA) were also applied to understand the complex petrogenetic and tectonic processes in the W-MVB.

The sub-crustal stress has been traditionally computed using the Runcorn’s formulae. This method allows computing the stress field only with a very limited spectral resolution. To overcome this problem, we apply a new method of computing the sub-crustal stress components based on utilizing the stress function with a subsequent numerical differentiation. This method increases the (degree-dependent) convergence domain of the asymptotically-convergent series and consequently allows evaluating the stress components to a higher spectral resolution compatible with currently available global crustal models. This method also facilitates the variable Moho geometry, instead of assuming only a constant Moho depth in the Runcorn’s formulae. The crustal thickness and the sub-crustal stress are then determined directly from gravity and (seismic) crustal structure models. The numerical result reveals that the largest intensity of the sub-crustal stress occurs mainly along seismically active convergent tectonic plate boundaries, particularly along oceanic subduction zones and continent-to-continent collision zones.

Inspired by the principle of wavelet analysis and blind signal separation in denoising, this paper presents a one-dimensional blind-wavelet algorithm. Some corresponding parameters of the blind-wavelet algorithm are discussed. In this paper, the blind-wavelet algorithm contains the following three main steps. Firstly, the multi-channel seismic signals are decomposed into multi-level wavelet, the scale coefficients and the multi-level wavelet coefficients can be obtained, then, the multi-level wavelet coefficients are processed by soft threshold method. Secondly, all the scale coefficients and the same depth wavelet coefficients of the signals are decomposed by the blind source separation, and the sequences of the decomposed signals can be correctly reflected through an appropriate method. Finally, the source signals are estimated via signal reconstruction. The results show that the organic combination of blind source separation and wavelet analysis (the blind-wavelet algorithm) can effectively eliminate the noise of the deep metal ores seismic data, it meets the requirements of the high resolution and fidelity after the denoising in the deep metal ores seismic exploration. The results of this research demonstrate that the blind-wavelet algorithm is quite fit for two adjacent channel signals processing of metal ore deposits seismic data denoising. It is shown that application of the blind-wavelet algorithm to seismic data processing is effective.

The definition and arithmetic (including add-subtract, bracket multiplication and Hadamard products) of N-dimensional matrices are studied and proved. The cubic matrices are a special case of N-dimensional matrices. The multi-dimensional data are expressed more brief and facility in theoretical analysis by the method of N-dimensional matrices. A geological example is given to illustrate the method and procedure of N-dimensional matrices in geological application. The method of N-dimensional matrices are considered a good tool in exploration and forecast.

Shock-fragmentation of the Ries impact crater forms characteristic and complex fracture patterns from micro- to kilometre-scale. Outside the crater rim, prominent fractures are mainly vertical to sub-vertical, either in radial or tangential orientation to the crater. The traces of radial fractures from various outcrops around the Ries consistently point towards impact centre and, consequently, represent an excellent tool for locating the crater centre. The presence of prominent fractures in numerous outcrops outside the Ries crater indicates that impact-induced brittle deformation reaches as far as 70 km away from the crater centre. Time series analyses of fracture frequency reveals regularly spaced, ca. 3-4 m interval elongate vertical to sub-vertical zones of high deformation. This periodicity of increased fragmentation appears typical of impact fragmentation. The cyclic repetition of intensely fractured zones and their variations with distance are most likely the results of the interaction of rapidly evolving impact-induced shock waves.

This research aims at studying the vertical distribution modes of geochemical elements in the covering layer above a deposit. Seventy-eight samples were sequentially collected from a vertical loess drill core above Diyanqinamo Mo-deposit, which were equally separated in 1m’s intervals. Each of the samples was screened into grains of grade 20, 40, 80, 120, 160, 200 and 200+ meshes to get 78×7 graded samples. The contents of 32 elements in each graded sample were measured by a handheld X-ray fluorescence analyzer to form a 78×7×32 dataset. Firstly, since the grain grades as attributes in a panel dataset are in orders, we regarded this dataset as a new type one and named it as Ordered-Attributes Panel Data (OAPD). Secondly, the non-parametric Friedman test was used to explore the correlation of the contents of the elements with both the distancefrom the ore and the grain grade separately. It turned out that among the 32 elements Mo, Zr, Sr, Rb, Th, Pb, Zn, Ni, Co, Fe, Mn, V, Ti, Sc, Ca, K, Ba, Cs, Te, Sb, Sn and Cd are correlated with both the distance and the grade. Then, varying coefficient-models were applied to the 22 elements to get the variation modes of the regression coefficients, reflecting the change rates of the contents with respect to the grain grades. At last, the variation modes were sketched and classified.

The Sewell consists of NE-SW to nearly E-W trending flat topped mounts with intervening valleys with a more steeper SE slope than the NW due to the presence of boundary faults as indicated by the profiles studies. The subvolcanic textured rock is rhyolitic in composition with additional mineral phases of calcite, calcite veins, Fe-oxide veins, albite (An0-10), apatite and titanite which are identified as part of hydrothermal veins. Furthermore, this subvolcanic texture indicate these hydrothermal veins were emplaced at subcrustal level for sometime followed by migration to the surface along the crustal scale faults associated with the Sewell Rise. Fe-Mnmicronodules, Fe (19.81 to 30.82 wt%)-Mn (17.72 to 29.93 wt%) encrustations with Fe-Mn coronas having more or less the same mineral chemistry and close proximity of the Andaman Back Arc Spreading Centre (ABSC) suggests a large scale hydrothermal activity and consequent deposition of initial phase of development of ABSC related sea floor massive sulphide deposits formed at ~4 m.a at different pulses for a prolonged period on the Sewell Rise.

The studies on the basis of the seismic records of seismic events in Uttaranchal a review of the events have been done and a probability of the earthquake has been workout in the part of Garhwal-Kumaun-Himalaya in Uttaranchal. In the southern part of outer Himalaya thrust zones are expected to produce a long term probabilities of large earthquakes of magnitude more than 6, on Richter scale which have on and average 5 to 20 mm reactivation and neotectonic upliftments along the shear zones. These zones have estimated to have future probabilities of earthquakes on these areas which are based on the historical seismic records, the long term slip rate and the displacement caused by the previous seismic events. The historical records of seismic events in these part of the Himalaya have the earthquake intensities varying from 4 to 6.0 on Richter scale in the geological past. The Kangra earthquake (1905) was recorded more than 7.0 Richter scale, Garhwal Earthquake (1883), (6.0), ‘Uttarkashi earthquake’ (1920), 1991 (5.6, 6.8) respectively, Chamoli earthquake (1999), 6.5 and the Dehradun earthquake of (1970). The approach followed for calculations of probabilities employ the estimated recurrence times with a model that assumes probability increases with elapsed time from the large earthquake on the fault/thrust zone areas. Through the calculated probabilities the estimated natural disaster/hazards in the newly born state of Uttaranchal in Himalayan belt can be reduced.

Dams are the hydraulic structures built with impervious material across river which provides water impounding for various purposes. These structures are constructed on rock formation so proper stress deformation analysis should be done. So it is important to analyze different stress concentration which results into undesirable deformation in dam foundation system. The paper presents analysis of dam foundation system under the shear seam using explicit finite difference method. Seams not only change the physical properties of the rock in and near the discontinuous zones, but they substantially affect the distribution of stresses and the overall stability of dam foundation. With different inclination of seam, stress deformation is concluded in the dam foundation system. These seams originate from the heel and software used for the analyses is FLAC 3D (Fast Lagrangian Analysis of Continua in 3 Dimensions). From the study it was concluded that the most critical case is the dam-foundation system with 120° inclined shear seam.

Along the Darjeeling–Mangpu region, polyphase deformation and barrovian metamorphism has been delineated in relation to the Main Central Thrust (MCT). The different parageneses of pelitic rocks containing chlorite, muscovite, biotite, garnet, staurolite, kyanite, sillimanite, k-feldspar and plagioclase show various texture resulting by the continuous and discontinuous reactions in the different zones. From the Microprobe data of the coexisting minerals show that X_Mg varies in order garnet<staurolite<biotite<chlorite. White mica which is the solid solution between muscovite and phengite is the commonest mineral within the lower grade; garnet is almandine rich showing normal zoning in the lower part of the MCT and in the upper parts shows reverse zoning. In the lower grade rocks the oriented chlorite, mica grains and rolled garnet formed syntectonically and after succeeded by cross cutting mica, chlorite and idioblastic garnet. P-T condition estimated by different models of geothermobarometry, the temperature value range from 570°C for garnet zone and 780°C for sillimanite zone and the pressure range from 5 kbar to 7.5 kbar. Different models have been proposed to explain inverted metamorphism but recently the channel flow model which defines a flow of a weak crustal layer in between relatively rigid yet deformable crustal slab is most appropriate. If the channel flow is operating at the same time of focused denudation, this can result in exhumation of channel material within a narrow, nearly symmetric zone.

The investigated area around Diguva Sonaba represents a part of granulite facies terrain of Eastern Ghats Mobile Belt (India). The Precambrian metamorphic rocks of the area consist of mafic granulite (± garnet), khondalite, leptynite (± garnet, biotite), charnockite, enderbite, calc-granulite, migmatic gneiss and sapphirine-spinel-bearing granulite, which comprise the major rock types of the area. Sapphirine-spinel-bearing granulite occurs as lenticular bodies in khondalites, leptynites and calc-granulites. Textural relations such as presence of corroded blebs of biotite within garnet and orthopyroxene, resorbed hornblende within pyroxenes, and coarse prisms of sillimanite presumably pseudomorphs after kyanite, provide evidence of either, an earlier episode of upper amphibolites facies metamorphism or represent relict of a single prograde event leading to granulites facies metamorphism. In the sapphirine-spinel granulite, osumilite and sapphirine + spinel + quartz were stable during the thermal peak of granulite facies metamorphism (early stage) but were later replaced by the (Crd-Opx-Qtz-Kfs) - symplectites and variety of reaction coronas respectively during the retrograde episode (middle stage). Variable amounts of retrograde biotite or biotite + quartz symplectite replace orthopyroxene, cordierite, (Opx-Crd-Kfs-Qtz)-symplectite (late stage). The prograde path was followed by peak metamorphism at a temperature of c. 1000 °C and a pressure of c. 12 kbar as computed by isopleths of X_Mg garnet and X_Alorthopyroxene. The sequence of reactions as deduced from the corona and symplectites assemblages, together with petrogenetic grid and pseudosection considerations, records a clockwise P-T evolution.

The spatial distribution of seismic site coefficients at Guwahati is presented in this article. Estimated site coefficients consider different site types in the city and several level of ground shaking consider average of probable seismic event. The evaluation of site coefficients is based on the standard penetration test data at 105 boreholes distributed over the city. Equivalent linear one dimensional site response analyses are performed to predict the site amplification and to determine the spectral acceleration response. Due to the unavailability of recorded ground motion data for the region, synthetic ground motions simulated at the bedrock level for the city corresponding to several combinations of magnitude (M _w ) and source-to-site distance (R) are used as input excitation. Simulated synthetic ground motion data with varying levels of excitation have been used to take care of the uncertainties in the input ground motions. The analyses depict the modification of the seismic ground motion due to the presence of soil overlying the bedrock.

In western region of Zhejiang province, structure and magma activity occur frequently; Proterozoic eon and Paleozoic era of copper mineralization favorable layers are distributed in those regions; the NE orientation deep fractures develop and move; the Shengong period and early Yanshanian of magma activity closely relate to mineralization. There are well metallogenic conditions of Au, Ag and Cu minerals in the regions according to the long-term and complex geological evolution, tectonism and magmatic activity. Based on analysis of tectonism, stratum, rock, fractures and minerogenetic map in the region, the geological variables are obtained by the multi-source information of geological abnormity, minerogenetic abnormity using MAPGIS and MORPAS software. The study regions are divided into 1755 grid cells with 5km×5km. The five minerogenetic prospect regions of Cu deposits are obtained by weightsof evidence modeling, which show that weight of evidence method is a good tool for minerogenic prediction.

The present study emphasizes the application of fuzzy operators in landslide susceptibility mapping along Yercaud ghat road section in the state of Tamil Nadu, India. Yercaud is one of the important hill stations and tourist spot in Tamil Nadu. In recent times, it faces frequent landslide occurrences. There is a urgent need for detail study of landslides along the ghat road to prevent further slope failure. The study has been conducted through integrated remote sensing, GIS and field investigations. The existing landslide locations were collected from previous study and verified in the field. The slope gradient, slope aspect, relief, lithology, land cover, geomorphology, proximity to road, proximity to drainage and proximity to lineament were analyzed with the help of Survey of India topo map, published geology map and satellite data. The relationship between various causative factors with past landslide locations were compared using frequency ratio method. These frequency ratio values were normalized to get fuzzy membership values between 0 to 1. The parameter maps with membership values were integrated using fuzzy algebraic product, fuzzy algebraic sum and fuzzy gamma operators to get final landslide susceptibility map. The produced map was verified by comparing with existing landslide locations for calculating prediction accuracy. The fuzzy gamma operator (γ=0.975) showed the highest accuracy of 0.7895.

A benchmark synthetic fractured reservoir dataset is built as an initial step towards evaluating methodologies for using deterministic Discrete Fracture Network (DFN) models from an explored area in predicting performance in relatively underexplored adjacent zones. In this exercise we create a robust synthetic dataset comprising about seven million grid cells with details on geology, geomechanical and geophysical properties. It starts with a simple three-layered subsurface geology reflecting aeolian, fluvial and coastal environments and four major sealing faults that dissect the domain into a “core”, “graben” and a “horst” area. The entire reservoir is populated with relevant facies properties, porosity and permeability. Fracture intensity and orientation distributions are computed from geomechanical constraints. A subset of this data within the middle-layer of the core region is considered to be the “area of interest”. This region is populated with fractures invoking a DFN model by talking into account fracture intensity and orientations from geomechanical constraints. The influence of these fractures on seismic responses is evaluated based on computation of the effective elastic stiffness tensor. The seismic response can then be used as templates to interpret the characteristics of the fractured reservoir in the unexplored areas. Finally, the feasibility of production within the “area of interest” is evaluated by adding a set of injector and producer wells and simulating flow over a 10-year time period.

Based on the geological background of Tonglushan region, and combining with the metallogenic theory, this paper reorganizes and analyzes the regional metallogenic model systematically, then determines the ore-prospecting criteria respectively from the strata, magmatic rocks, structure and wall rock alteration. Then guided by prospecting model, the paper selects favorable ore-forming strata, fault buffer, center symmetrical, fault density, tectonic intersection, the geochemical information etc. as evidence factors. Using the MICROMINE software as a platform and combining with the concealed geological body to build the digital geological model of surrounding areas, which is realize the 3D visualization, and viewers can watch the predictive result from different angles and positions. Through materialization of ore block model, then the materialization of each cell line interpolation and assignment, the final weight is obtained by 3D evidence model. By the primary halo zoning features of ore deposits, indicator of the geochemical exploration, forecasts the deep concealed ore, and realizes the geological and geochemical comprehensive prediction; Finally Marks out three of metallogenic prospect. The prospective areas show that the study area has a good potential for prospecting minerals and the method of ore prediction is very effective. The application of the analysis method which is quantitative information of structures as new prospecting variables achieve a new breakthrough in 3D prospecting minerals.

The problems correlation of data of the Kola Superdeep Borehole was hampered by an imbalance between extremely detailed borehole studies and more piecemeal observations on the day surface in the Pechenga ore district. The rock density and anisotropy in Vp, geological, gravity, and geochronological data were employed for the formalization and correlation of the borehole section and the reference profile on the day surface using computer-based technologies. The integrated deep geodynamic model accounts for the modern structure of the Pechenga ore districts to a depth of 15 km and entails a new interpretation of its geological boundaries, development stages, and metallogeny. Ore-forming systems of the Pechenga ore district ae known for large deposits of Cu-Ni ores deposits and occurrences of Pt, U, Au, Pb, and Zn.

Considering the multivariable deposits that consist of various attributes that are frequently spatially correlated, the uncertainty associated with the grade-tonnage curves is assessed through the joint conditional simulation techniques. This paper presents the joint simulation of five attributes using the Minimum/Maximum Autocorrelation Factors (MAF). The methodology for joint simulation is three-fold: (1) MAF is used to transform the attributes to non-correlated factors; (2) the variograms for each MAF are computed and modelled; (3) the independent MAFs are individually simulated and back-transformed to the original data space. The methodology is demonstrated in an iron ore deposit in Western Australia, where the attributes of an iron ore deposit are successfully decorrelated and simulated independently. The grade-tonnage curves for each realisation are plotted and compared with the generated one by the kriging estimate. The MAF approach proves itself to be an efficient method for joint simulation of multivariable deposits.

For comprehensive study of heavy mineral placers the modern methods areneeded for integrated analysis. The generalization of methodological approaches and techniques has done for two kinds of modeling, widely used in the study of placers. The digital structural-lithological (DSL) modeling [1] is based on the principles of authoring partition for geological objects using a wide range of lithological, geochemical, metallogenic properties and other features. DSL-model is built as the result of computer processing of the target database, prepared on the basis of these principles. Methodology of geological-dynamic modeling of heavy mineral placers [2] is based on the study of the dynamic mechanisms of the main stages of placer formation processes - from the mobilization in the load sources of placer-forming material to deposition in the terminal sedimentary basin. Technology of hybrid expert systems [3] is the best for development of expert systems based on digital models for target prediction and evaluation of placer objects, because it permits the using of different knowledge about the object of study in various forms, allowing their automatically applying during expert system operation. The experimental sample model shave shown a high level oftargetfunction.

For the demands of geometallurgy a vast amount of data in multifaceted shape is needed. There are high resolution images from the MLA, data tables with information on the chemistry of some mineral phases, statistics on the distribution of the grain size, and so on. This data needs to be stored in a database, which reflects the often hierarchical structure of it and is flexible enough to be extended with almost any potential occurring information. We provide a MySQL template for such a database. Finding the desired data there can be a tough task, since queries might be highly complex and confusing. Therefore, we developed an easy accessible R interface for accessing this database.

Traditional mineral resources prospecting and information extraction method cannot satisfy the complexity of geological and multi-stages of ore-forming processes. In this paper, empirical model decomposition (EMD) and independent component analysis (ICA) are applied to separate and reconstruct magnetic data so as to extract the signals from different sources. Firstly, original magnetic data is sifted to get intrinsic mode functions (IMFs) from high to low frequency. Secondly, ICA is utilized to reconstruct the former IMFs which obtained by removing background and get independent components (ICs). Finally, nine IMFs and three ICs are obtained by the combining method that is used to process magnetic data of Gobi desert coverage in Eastern Tianshan. IC1 discriminates igneous rocks, and may be related to magmatic intrusion, IC2 tracks the distribution of plates and may be related to plate subduction, IC3 indicates the basite-ultrabasic rocks which are distributed in the middle of area and may be related to crustal thickening.

In order to evaluate the quantity and quality of city’s underground space resources effectively, this paper puts forward a new three dimensional modeling for the city geology body of the Knowledge Driven Analysis (KDA) method. Based on the professional knowledge analysis of city engineering geology, hydrogeology, it selects geology, road, explored underground resources and so on, as the affecting factors to evaluate the urban geological body. By using a 3D software platform, this paper discusses the comprehensive modeling details for these factors even from non-spatial entities. The case of Beijing City shows this method can effectively describe the spatial and non-spatial properties for the city geological body.

A constant value of the Moho density contrast is often assumed in methods for a gravimetric determination of the Moho geometry. This assumption might be sufficient in some regional studies. In global studies, however, this assumption is not reasonable due to the fact that the Moho density contrast vary significantly. Large errors then can be expected in the Moho geometry determined globally from gravity data. In this study we utilize a generalized compensation scheme based on variable depth and density of compensation. The Moho depths are determined based on assuming the variable Moho density contrast. We demonstrate that this assumption (instead of a uniform model) significantly improves the agreement between the global gravimetric and seismic Moho models; the RMS fit of the gravimetric result with the CRUST1.0 seismic Moho model is 4.5 km (for a uniform model) and 3.0 km (for a variable model).

Transport of colloids in fractured media has gained a considerable importance in recent years, mainly in the field of chemical pollutant transport and in nuclear waste management in groundwater system. The major reason being, colloids assist in migration of radionuclides through fractured rocks. Field studies and experiments have shown that natural fractures have apertures which are complex in geometry and vary spatially. An attempt has been made to numerical model the colloidal transport in a single fracture-matrix system to investigate the mobility of colloids in the presence of variable fracture apertures. To capture the effect of variation of fracture aperture, two different geometrical distributions logarithmic and sinusoidal, have been developed to generate the variations of fracture aperture. Analysis for both linear and nonlinear sorption isotherm cases has been carried out. The nonlinear sorption isotherm has been carried out given by Langmuir and Freundlich of isotherms. Cauchy type of boundary condition is applied at the fracture inlet to better represent the field scenario. The results indicate that colloidal migration in fracture and rock matrix is sensitive to fracture aperture variation and the parallel plate model exaggerates the colloid concentration in fracture. Further the results also suggest that the type of colloid source condition has a profound effect on the migration of the colloids in fracture and rock matrix.

The knowledge of the global solar surface irradiance (SSI) incident on the earth’s surface and its spatiotemporal distribution is important to numerous solar-based applications. However, spatiotemporal modelling of SSI (a non-linear process) from Earth observation data is unfortunately not straightforward. From a signal processing perspective, it is a non-stationary, non-linear/non-Gaussian dynamical inverse problem. In this paper, we propose an MCMC particle filter approach that combines satellite images and in situ data for space-time-referenced SSI modelling. We propose original observation and transition functions taking advantage of the characteristics of the involved types of data. A simulation study of solar irradiance is conducted in parallel with this method and a map of SSI potential in French Guiana for the year 2012 is provided.

Basin and petroleum system modeling allows geoscientists to examine the dynamics of sedimentary basins and their associated fluids to determine if past conditions were suitable for hydrocarbons to fill potential reservoirs and be preserved there. Commonly geological models are created using simple assumptions about the superposition of sedimentary layers during deposition. However, for prograding sequences foreland basin and passive margin settings in particular, this results in simplistic models with limited geological validation of thicknesses or facies distribution. Stratigraphic forward modeling is a quantitative approach to create a geological model by simulating dynamic sedimentary processes, such as erosion, sediment transport, and deposition, while maintaining mass balance. By suitably varying parameters that represent paleogeographic conditions (such as sea level, sediment input, and major tectonic events) stratigraphic forward modeling can generate a realistic three-dimensional model and predict the distribution of sediments and their properties.

The distribution of seismic activity in the area of Pacific volcanic ring. The mathematical model of its seismic activity cost based Burridge Knopoff (Burridge-Knopoff). Discuss the results of numerical experiments.

We evaluated the performance of thirteen single extreme outlier statistical discordancy tests (Grubbs-type N1, N2, N4; Dixon-type N7, N8, N9, N10; and high-order moment statistics skewness N14 and kurtosis N15) using highly precise and accurate Monte Carlo simulations for 20,000,000 replications and 102 independent simulation experiments. Our simulation errors and total uncertainties were extremely low for normal samples of sizes 5 to 20 involving a simple statistical contamination of one datum resulting from a parameter called δ from ±0.1 up to ±20 for modeling the slippage of central tendency or another parameterε from ±1.1 up to ±200 for the slippage of dispersion. Both criteria − Power of Test proposed by Hayes and Kinsella [1] and Test Performance Criterion of Barnett and Lewis [2] were used. Our results indicate that the Dixon tests perform less well than the Grubbs-type, skewness, and kurtosis tests.

Maximum of the utilization of sustainable and recyclable energy sources could be an effective way for the reduction of carbon dioxide emission, which is mainly caused by energy consumption. In this study, the characterization of the heat stored underground and the analysis of the deep geothermal potential was performed for different geothermal systems based on various geology structures, fault zones and volcanic zones, including Hokkaido, Northeast of Honshu, Center of Honshu, Southwest of Honshu, Shikoku, and Kyushu geothermal systems. Geothermal energy potential maps were firstly produced at different depth intervals using two dimension kriging interpolations. The temperature distribution was then modeled in the three dimension to a depth of 1 km from the surface underground. In addition, the dataset from multi-sourced well loggings was used to improve the accuracy of 3D model and furthermore, predict the geothermal properties. Finally, based on the analysis of the deep geothermal potentials, location of high potential areas where further exploration and future exploitation of the geothermal resources is feasible in Japan were detected.

The standard geostatistical models, both linear and nonlinear, require the data to be stationary, which is very rare in reality. The changing of means and variances, and spatial covariance structure are evident in the real life data. The so called global non-stationarity over a spatial field is captured by a model which is considered to be locally stationary but globally non-stationary. The proposed model is simultaneously defined everywhere in the concerned domain not only in the defined areas, but again the model behaves like a local stationary process in small areas. For this purpose, the smoothly varying local multivariate spatial distribution function has been derived by weighting all the data values in the spatial field using kernel function and consequently represented by Hermite polynomial expansions. The locally varying spatial covariance structure is modeled by a local covariance function defined by semi-variance parameters estimated experimentally by the local samples present in the local stationary region. The local recoverable reserve is estimated by calculating conditional cumulative distribution function using nonlinear geostatistical techniques such as disjunctive kriging and multi Gaussian kriging. The proposed method has been applied in an Indian beach sand deposit for local recoverable reserve estimation. An appropriate support effect model has been incorporated for designing this estimation algorithm. The impacts of support effect and nonstationarity in terms of local recoverable reserve are analyzed for the deposit.

The UK’s North Wyke Farm Platform (NWFP) for sustainable grassland farming is set up as a large agriculture modelling system of 15 hydrologically-isolated catchments, where in each catchment, water chemistry, precipitation and soil moisture data are continuously monitored. This spatio-temporal data are then interrogated with respect to climatic timings and changes in crop, livestock and farm management, across the NWFP. Complementary data sets are also found via spatial field surveys, remote sensing and greenhouse gas studies. This study focuses on one such field survey, consisting of soils data at 495 sites. We spatially explore this data using a geographically weighted principal components analysis, where we provide a novel adaptation of the technique to deal with the distinctly partitioned nature of the data, which is collected across 20 fields, spread over the 15 catchments.

The climate impact studies in hydrology often rely on climate change information at fine spatial resolution. Downscaling is a practice for obtaining local-scale hydrological variables from regional-scale atmospheric data that are provided by General Circulation Models. Among two downscaling methods, Statistical Downscaling is taken into account, as it offers less computational work as compared to Dynamic Downscaling and also provides us with a platform to use ensemble GCM outputs. In the present study, a Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and Hybrid of Support Vector Machine (SVM) with K-Nearest Neighbor (KNN) approaches are proposed for Statistical Downscaling of precipitation at monthly time scale. To reduce the dimensionality of the dataset, the Principal Component Analysis (PCA) is also performed. The CanCM4 simulations are run through the calibrated and validated SVM, KNN and hybrid of SVM with KNN downscaling models to obtain future projections of precipitation values. A comparison is made between the models in this study.

Flood forecasting is considered as an important component of non structural measures for flood management planning. Hence it is of immense importance to accurately estimate the flood hydrographs resulting from storm events for all the tributaries of a river system which causes flood. In the present study simulation of precipitation-runoff process for the Tel Sub basin of Mahanadi Basin is carried out and various important parameters of the model are calibrated. It is pertinent to mention that Tel (catchment area 22800 km2) is an important tributary of Mahanadi system and contributes significantly to the flood peak at the delta head of Mahanadi at Munduli. Historical flood records show that the River Tel alone contributed 74.85% and 71.1% of the total flood peak at the delta head of Mahanadi during the floods of 2008 and 2009 respectively. For precipitation-Runoff simulation study of Tel Sub basin of Mahanadi Basin the HEC-HMS model, developed by Hydrologic Engineering Center of US Army Corps of Engineers is used. Using the model and available data some important model parameters which significantly affect precipitation-runoff process are calibrated considering the storm event of 29 August 2006 to 4 September 2006. Further, using the calibrated model parameters, the model is run to estimate the flood peak and time to peak for the storm event of Sept 2008 flood (14 Sep 2008 to 25 Sep 2008) and July 2009 flood (14 July 2009 to 25 July 2009). The observed and computed values of flood peaks and time to peaks are compared and it is seen that there is a close agreement between the observed and computed values. The result shows that there is an error of 4.8% and 0.82% between the observed and computed flood peaks respectively for the storm events of 2008 and 2009.

A simulation study using SWAT hydrological model has been carried out to evaluate the impacts of changing cropping pattern and agricultural expansions on overland flow in Penganga Sub watershed, Maharashtra. Remote sensing data combined with ground-truthing and extrapolation of pixel signatures were done for generation of spatial crop inventory for the years 2011, 1999, 1990 and 1976. The crop inventory analysis showed a significant change in the cropping pattern over the decades. Less water intensive crops like Jowar, Tuarand Gram were heavily replaced by water intensive crops like Cotton and Wheat. Over 30% of the open scrubs were also converted for cultivation. These four different scenarios were modeled without hydrological structuresunder constant climatic conditions of 1975-76. The resultant simulated runoff showed higher peak discharges (~2000 cumecs in July, ~1500 cumecs in September) under the cover conditions of 1975. Under similar climatic conditions the consecutive scenarios showed gradual decline in runoff. The flow generatedunder the cover conditions of 2011 showed lowest and delayed peak discharges (~1000 cumecs in July and ~700 cumecs in September). The study showed that the shift in cropping pattern to water intensive crops reduced surface flow. This calls for appropriate crop combination for better utilization of available water.

The near surface or depth to the first occurrence of groundwater is vital in evaluating liquefaction initiation and therefore a liquefaction loss model. If groundwater is below a susceptible layer, that layer is unlikely to liquefy. This study will discuss the challenges in modeling near surface groundwater depths over a large region, using the Canterbury region of New Zealand as an example, and its importance to loss estimation relative to liquefaction hazard. Estimating the depth to near surface groundwater is an emerging discipline that benefits from geostatistics and hydrology. While accounting for spatial randomness in the groundwater depth, we develop a site-specific mean trend model assimilating secondary datasets correlated with the primary variable and process it through the Kriging system. Secondary datasets considered are a continuous map of distance to a water body (DWB) and ground surface elevation through a digital elevation model (DEM). Resulting estimation improves upon a Kriging method not incorporating the secondary information (Mean Square Error reduction ranges from 47.5 to 73.8 %). The estimation of the groundwater depth at unsampled locations leads to enhanced understanding of liquefaction over a region and thus of spatial distribution in the loss uncertainty. The findings of this study would be of great help to investigate the importance of the location of groundwater monitoring networks near concentrations of building exposures.

Essential to developing a robust risk-management model is to clarify first “where are the exposed properties”. Geocoding is a process that binds property exposure in a built-in environment to spatiotemporal dynamics of natural catastrophes. While addresses geocoded to the finest possible spatial resolution lead to relatively precise estimation of losses from surrounding perils, incomplete/invalid input addresses must fall back to coarser spatial scales (postal code, city, and county etc.), resulting in less precise loss estimation. This work aims at providing the foundation to place the low-resolution geocoding outcomes into gridded locations at a targeted finer resolution. We take advantage of auxiliary information such as land use/cover to infer the likelihood of an exposure placement at the gridded locations. This development is showcased with a postcode in Florida to understand loss changes from low-resolution geocoding uncertainty perspectives.

The deployment of Wireless Sensor Networks at ocean provides on-site, distributed sensing of some specific events. To the existing satellite and airborne radar scrutinizing, providing incessant and real-time data feed. Due to the unforeseen conditions, it is not possible to imagine the location, size or weather circumstances affecting the region. We present a novel framework for a large-scale sensor network deployment at ocean. Our main objective is to develop communication algorithm to localize maritime monitoring using realistic channel and weather models. The design choices are based on the present application situations, through a bottom-up approach. Wireless channel and physical layer are fundamental for dependability of results, thus particular focus is given to their model assortment. The network architecture is based on a cluster model protocol with an application-specific decision. The aim is to provide the best compromise between, message delivery, energy consumption and network connectivity under dynamic change in environments.

Using SASI aerial hyperspectral image data combining with the field measured spectral information and spectroscopic data in the USGS standard mineral spectral library, this paper studied the information extracting method for the clay alteration minerals which is related to the oil gas in the Jimusaer Area, Xinjiang Province, P.R. China. To begin with, based on the data calibration and spectral reconstruction of the SASI hyper-spectral images, the image dimension judgement and noise separation were made by minimum noise fraction (MNF). And then with the pixel purity index (PPI), the automatic matching recognition and information extraction of the images was performed, straight after which, two common clay alteration minerals—Kaolinite and Illite. At last, the mineral alteration mapping for the two clay alteration minerals was carried out by mixing tuning matched filtering (MTMF) technology. This exploring and method proposed in this paper point out an effective approach for oil and gas exploration by hyperspectral remote sensing technology.

Rainfall estimates from low earth orbiting satellites like Tropical Rainfall Measuring Mission (TRMM) will be subjected to sampling errors of non negligible proportions owing to the satellite swath coupled with a lack of continuous coverage due to infrequent satellite visits. In the present work, the authors investigate relative sampling errors of space-time averaged rainfall in the active and passive sensors of TRMM namely, Precipitation Radar (PR) and TRMM Microwave Imager (TMI) using the data products of PR 2A25, TMI 2A12 and PR 2B31. A statistical bootstrap technique was found to provide good estimates of relative sampling errors for PR 2A25 data products [Indu and Kumar, 2014]. This study investigates the effect of different sampling techniques in estimating relative sampling errors using the monsoonal rainfall of 6 years [2002-2007] over the basin of Mahanadi, India. Results verify that the spatial distributions of relative sampling errors were affected by sampling technique employed. These findings clearly document that proper characterization of error structure from TMI and PR has wider implications for decision making prior to incorporating the resulting orbital products for basin scale hydrologic modeling.

Because clarifying a regional groundwater system is required for development and management of groundwater resources, it is important to evaluate the hydraulic property of a fracture system and alteration zones which act as the pass of groundwater flow in a rock body. For a case study of such hydraulic characterization, we selected an area in which the basement rock is composed of Cretaceous granite. We first constructed a 3D fracture model by a geostatistical method to simulate the regional fracture distribution by incorporating the orientation of the sampled fracture data obtained from the borehole investigations, and this model revealed the features of this fracture system in that area. We then incorporated a dataset of hydraulic conductivity obtained from single borehole hydraulic tests and rock-core tests using a N₂ gas permeameter and found a positive correlation with the size of simulated fractures. Finally, a numerical simulation using MODFLOW was applied to this hydraulic conductivity model for estimating the regional groundwater flow system. Anisotropic behavior of flows near the fault was revealed by this simulation.

This paper introduces a new dictionary learning approach for hyperspectral images classification with structured sparse representation based on Compressed Sensing (CS), An important contribution of our paper is partition the pixels of a hyperspectral image into a number of spatial neighborhoods called pixel groups and the pixel group can be modeled of different size. The idea is to use of hyperspectral remote sensing image spatial correlation between pixels and the aim is to obtain a dictionary of each pixel. The dictionary is a linear combination of a few dictionary elements learned from the hyperspectral data and can accurately represent hyperspectral remote sensing images with less coefficients. The pixels are induced a common sparsity pattern and have a implicitly spectral correlation between pixels which are in a identical pixel group. The sparse coefficients are then used for classification hyperspectral images by a linear Support Vector Machine. The experiments show that the proposed method can get a better representation of hyperspectral images and has a higher overall accuracy and Kappa coefficients.

The study of the Land Surface Temperature (LST) is very important for its applications in many fields of natural sciences and is oftenused as input data in climate, agro-meteorological or hydrological models for forecasting ecosystem responses. Due to sparse and irregular distribution of meteorological station over Kashmir Himalayas, climate forecasting using interpolation of metrological air temperature data (T_air) is not scientifically robust option. Remotely-sensed LST is, therefore, a good option to supplement the scanty network of the ground-based temperature observations for understanding and modelling a variety of environmental and ecological processes and phenomena. In the present study, an attempt was made to estimate LST and its lapse rate over Kashmir Himalayas using MODIS data and relate it with air temperature (T_air) from Indian Metrological Department. Comparison between LST and T_air shows a very close agreement with MAE of ±20C. The calculated correlation coefficient between T_air and LST is above 0.9. Using ASTER DEM, LST was used to estimate the Lapse rate along various transects across the Kashmir Himalaya, which showed variations in space and time (from 0.30C to 1.20C per 100m change in the altitude). The information and knowledge generated from this research are going to improve the understanding and quantifications of various processes related to climate, hydrology and ecosystem where the use of temperature and lapse rate is an important and critical driving force.

The tectonic stress field is crucialto the study of tectonics, engineering geology, seismology and mineral exploration. In this paper, the author proposed a new theory and method for calculating the structural stress field using the composite quantitative data of remote sensing information on circular structures and related linear structures to approximate the iso-elevation line map of local structures bearing oil or gason the basis of the phase-separation analysis of remote sensing information field and the theory of elastic mechanics.

This paper reports a deposit-scale GIS-based 3D mineral potential assessment for Jiama copper-Polymetallic deposit area in Tibet, China. The assessment is achieved through the combined use of a metallogenic model, and 3D geological, geochemical modelling and Prospectivity modelling. In this contribution, a metallogenic model for the Jiama deposit and a 3D modelling flow chart are used to construct multiple 3D layers of volumetric and triangular mesh models to represent geology, geochemistry and ore-controlling features in the study area. GIS-based 3D weights-of-evidence analysis is used to quantify and target the subsurface Prospectivity for Cu(-Mo) ore-bodies in the area, which defined three prospective deep-seated exploration targets. This contribution ends with a discussion on the potential fluid flow pathways based on the 3D zonation of major geochemical elements and their ratios, such as Zn / Pb ratios. The discussion confirms the GIS-based 3D quantitative assessment of the Prospectivity of the Jiama copper-Polymetallic deposit.

This research has integrated the use of the Linear Imaging Self Scanner (LISS-III) satellite data and Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model (DEM) for assessing the surface hydrological behavior of Lidder and Rembiara watersheds of the Jhelum Basin. The results reveal that the Lidder watershed exhibits lesser basin lag time compared to Rembiara watershed for a same magnitude storm event. Moreover higher population density in the downstream regions of Lidder makes it more vulnerable to flooding than Rembiara. The methodology and results of this study intends to help in formulating better flood mitigation strategies in this part of the Himalayan region where the observation network of hydro-meteorological and estimation of other land surface parameters is either missing or very scanty.

Jodhpur city has been experiencing rising ground water levels. The water levels in many parts of the city especially in the old city area, Tripoliya market, Gantaghar, Nai Sarak, Chandpole, Sajoti Gate, Shivanchi Gate and housing busy markets have touched to even 1-2 mbgl., causing seepage in underground basement of shops and houses in these areas and weakening the foundations and reducing the lives of the buildings due to dampness of the walls. Traditional field survey methods for detection of seepage channel are costly and time consuming. In this study, a rapid, cost-effective remote sensing technique was used for finding out the seepage channel in these parts of Jodhpur city and adjoining areas. In the present study Landsat-7 ETM, multi-date image and survey of India toposheets were used for generation of different thematic maps of the study area. A three- step process, image acquisition, processing and analysis have been applied for identification of seepage channel through visual interpretation of the satellite imagery. Finally based on the prepared thematic maps, analysis of remote sensing imagery and delineation of major structural control over ground water seepage flow channel was done along the lineaments. These lineaments are providing easy conduit for movement of ground water and seepage path of flow of ground water towards the city area.

In the present study, Advanced Wide Field Sensor (AWiFS) of Indian remote sensing satellite data is used to monitor seasonal snow cover measurement in Bhaga basin of Western Himalaya, Himachal Pradesh, India. The AWiFS images are being corrected topographically using ASTER Digital Elevation model. An attempt has been made towards estimation of snow cover using algorithms based on Normalized Difference Snow Index (NDSI), Normalized Difference of Cloud Index (NDCI) and Snow Under Vegetation (S3). Algorithm S3 is used for estimation of snow pixels in vegetation area without reference data. Algorithms NDSI and NDCI are involving NIR band of reflectance for snow pixel area. Comparison of the estimated snow cover using all the three algorithms is carried out which represent that the results estimated using S3 algorithm are more accurate than NDSI and NDCI algorithms.

In the present study, Artificial Neural Network (ANN) based semi-automatic multisource classification approach has been applied for the glacier terrain mapping in the Kashmir Himalayas (Kolahoi glacier) using integrated dataset comprising of multispectral Landsat TM data and several ancillary data layers (topographic attributes and transformed spectral bands). Terra ASTER data has been used for accuracy assessment. The study aims at selecting the best multisource dataset for classification and to investigate the impact of various neural network parameters on classification accuracy. The present study clearly demonstrates that selection of appropriate multisource dataset; network model and parameter values have a major influence on the performance of the ANN classification process.

This study investigates the spatial variations of SL using visual basic computer program called R. Profiler. The graphical interface of R. Profiler allows the user to calculate the SL easily and draw the river long profiles. In order to check the efficiency and accuracy, R. Profiler is validated by using the drainage networks data of Kali River basin of southern India. The digitized data were converted into .txt format and imported into R. Profiler. Using query option, streams of third order and above have been selected and calculated the SL automatically. The calculated SL values of each portion of the river were converted into point shapefile and prepared the spatial map by using Inverse Distance Weighted (IDW) interpolation method available in ArcGIS 9.3. The results show that, R.Profiler is effective in calculating SL using the text data of ESRI line shapefile as an input.

Mineral prospectivity mapping (MPM) is one of the most crucial steps in mineral resources exploration and assessment, which aims to delineate prospective areas within the region of interest through integrating and analyzing diverse geoscience datasets including geological data, geophysical data, geochemical data and remote sensing data. With the help of geographic information system (GIS), we have realized many MPM methods in 2D in the past few decades. Now, with the development of 3D geological modeling and the requirement of deep prospecting, mineral resources potential evaluation also extends to 3D space. In this paper, we establish relevant solid models of study area and rasterize them into block models with Micromine, then, we use a single standalone mineral resources prediction and evaluation application GeoCube to integrate the anomaly information exported from Micromine and evaluate the mineralization potential of study area.

Open cast mining process destroys landscapes, forests and wildlife habitats due to clearance of trees, plants, and topsoil. This results in ecological degradation such as soil erosion, destruction of agricultural land, water pollution, etc. Therefore mapping and monitoring of landscapes for temporal detection is extremely essential. A study of application of data fusion techniques for mapping of land use cover has been carried out for a mining coalfield in order to ascertain potential impact of mining activities on flora and fauna. The study has incorporated pixel level Image fusion process as well as decision level fusion procedures. High Pass Filter (HPF) method based on pixel level fusion is applied to fuse the multispectral (MS) and panchromatic (PAN) image of Landsat ETM+ data. The fused MS image is classified into seven land use categories viz. agricultural land or open shrub, water bodies, dense vegetation, built-up land, barren land, mining area and overburden dump area using different classifiers. The selected classifiers are maximum likelihood, mahalanobis distance and support vector machine. The Naive Bayes classifier fusion rule on abstract level is applied to integrate the decisions from each classifier. The result of accuracy assessment shows an little increment of 0.41% and 0.73% in both classification accuracy as well as kappa coefficient in comparison to single classifier with the highest accuracy.

The basin characteristics of Pampa River – the third largest river of the State of Kerala, flowing through the heart of central region of the State – has undergone tremendous variations in the recent past. Alternating cycles of recurring flood and drought has become a predominant feature of this river, which, once used to be a rich and sustainable source of water throughout the seasons and lifeline for a population. The rapid pace of urbanization, massive encroachment of river banks, deforestation, transition in the agricultural pattern etc transformed the land use pattern of this river basin. A large number of villages and densely populated regions on the bank of this river face the ravage of flood every year. In this context, this study attempts to evaluate the land use and land cover (LULC) changes occurred in Pampa river basin during the last decade i.e., 2001-2010, identify the human intervention factors as well as the possible impacts of these factors on the floods occurring in this river basin.

Chandigarh is among the most important city of the northern India in terms of socio-economic growth due to upcoming major projects, modernization of industrial activities and development of Information Technology sector so many people immigrated to the city and this resulted in greater load on the city population, thus, was selected for this study. Landsat TM and ETM+ images were used to characterize the land cover type and land cover changes in Union Territory of Chandigarh. The analysis revealed that the urban development of the city has been very rapid during the last decade and more recently, vegetation has greatly declined. The results demonstrated that the pressure of increased commercialization has driven change in land use pattern over a period of time and has resulted in widespread environmental degradation.

Trees Resources Outside Forests (TROF) is an important natural resource and comprises tree formations in agro-forestry systems. However, determining suitable remote sensing technique to represent TROF for semi-urban to rural environment in India is a challenge. A research is undertaken to develop this technique for a study area existing at the outskirts of Rae Bareli, UP. A classification based approach is tried to be evaluated. The study tried to understand importance of resolution and date of data captured for effective classification of TROF. As classification algorithms can significantly alter accuracy of classification, different classification techniques are analyzed as well. Results are compared statistically with ground truth data for accuracy assessment. The images are geocoded using GPS coordinates of control points. The result of accuracy assessment is summarized using Kappa coefficient. Explanatory statistics is used to compare classified data correspond to classification done with different algorithms over images of various resolution and to comment on efficacy of combinations of resolution of satellite image and classification technique.

With the growth of human population and their demands, constructed environment has replaced the natural environment in a significant way. Urban forestry, Urban Green Spaces (UGS) and natural parks are very important which urban planners and designers are interested in. This study is focused on the sustainable development of green spaces. Therefore Identification and analyzing of existing urban green areas was done through supervised image classification method by using high resolution satellite images. Central place theory and spatial analytical techniques were combined to understand the existing patterns of the green spaces. The green areas were analyzed with the other critical natural and human factors and weighted under existing urban regulations and standards in Sri Lanka and developed a multi criteria model for analyzing the suitability and probability of expansion of existing urban green spaces for sustainable green space planning activities. The results were presented in cartographical maps as well as web based maps which encourage the citizen engagement activities for nature conservation.

GIS technology is a computer-based data collection, storage, and analysis tool that combines previously unrelated information into easily understood maps. GIS can perform complicated analytical functions and then present the results visually as maps, tables or graphs. This allows decision-makers to virtually see the issues before them and then select the best course of action. The database prepared from existing field survey can be compiled using digital map for monitoring the availability of the species in the unknown locations through Ecocrop model of DIVA GIS. The spatial analysis thus helps in choosing the best location for the crop depending on the environmental parameters. The plotting of Piper species and Garcinia species collected from Western Ghats gave information of the species richness sites as well as the diversity of the species. Based on these results the prediction of the distribution of piper species and Garcinia species in North Eastern India was done and confirmed the availability with survey. The climatic parameters, important for crop suitability, The studies indicated that area under the natural habitat or the cultivation of the crop has a positive relation with the environmental suitability.

The river Ganges has its practical origin from the confluence point of its two tributaries the Alaknanda and Bhagirathi at a place known as Devprayag. These two rivers have their own very large catchments or drainage basin. Both of them have their own drainage characteristics in terms of physical area and ecological habitats. The variability of discharge from both the catchments determines the flow regime in the river Ganga. The international nature of river Ganga and its huge basin makes its study complicated and its hydrological data difficult to obtain. For the sake of studying the flood behavior downstream in period of emergency like that in 2013 Uttarakhand tragedy, an indirect approach is to obtain the flow regime through morphometry. The various novel and traditional approaches gives us a unique opportunity to predict the flow regime in 30 year to more than 100 year return period flood conditions. In this study the DEM of ASTER and SRTM have been utilized to analyze morphometry using D-8 method. The drainage basin shape, area, perimeter, density, river network, river length, vertical distances, slope, hypsometric curves and longitudinal profiles are calculated for both the basins using both ASTER DEM of 30 m and SRTM DEM of 90 m resolution. Further using empirical equations an attempt is made to calculate discharge at outlet point for both the basins. This is correlated statistically with different morphometric parameters to know which factors are best representing the basin flow regime of the basins.

Remote Sensing techniques play a pioneer role in this field, where space images have special characteristics and properties which are not found in the traditional methods, since wide and valuable information can be acquired about the geoenvironmental systems which adequately reflect the recent situation of the natural environment, and the impact of human activity effect. In comparison between old and recent remote sensing data, it is possible to study and determine the direction and intensity of the negative and positive processes which are related to both natural or human made factors and their impact on the environment, as well as the characteristics and extent of environment damage and pollution. We have carried out by these techniques. Geoenvironmental survey of the southern area of Syria on 1/100000 scale, with 10000squere km2 Preparing geoenvironmental maps that reflect the natural components of ecosystems and the impact of human activity, in addition to the effect of the geological factors and those of geochemical pollutants. Also it was preparing maps of geoenvironmental assessment of the study area. We had digital processing for Russian and land sat TM images which we used, by using IRDAS software, especially those related to natural anomalies determination. The work is completed through field actions, which are represented by the checking the result of space images interpretation, collecting more than 4000 samples of soil, plants, ground and surface water, bottom sediments, rocks, for analysis. The results reflected in geochemical pollution maps.

Commercially available software for energy monitoring provide the output in terms of graphs and tables, however, they are limited in visualization of spatial distribution of energy consumption. In this study we have used Samsung Galaxy S4 as the relatively cheaper platform to collect data for temperature and humidity inside an academic block of Shiv Nadar University and visualized it in 3D with other datasets. This study has been treated as an exploration of cellphone based sensors to collect data and integrate it into GIS domain for effective visualization. It was found that the smartphone based data collection is easy, has a potential of crowd sourcing for data collection and can be integrated with GIS with certain additional steps. This study is a part of a grant received by Shiv Nadar University from Dept. of Electronics and IT, Govt. of India.

The purpose of the portal (http://geotime.tw.rpi.edu/) described in this paper is to provide formal background information of Golden Spikes. Golden Spike is the nickname for Global Boundary Stratotype Section and Point, or GSSP, which a stratigraphic section is serving as the reference unit for a particular boundary on the geologic time scale. In this work we deployed a number of state-of-the-art information technologies, such as semantic modeling and encoding, data visualization, SPARQL query, and online map layers from Web Map Services. The portal received positive feedbacks from researchers in the domain of stratigraphy and we are assembling further information and updating the portal to make it more useful.

Organizations use facility management as an important management tool and also as strategy for resource and facility management. But, question arises in defining facility management and how GIS can help improvising FM? Such systems require three dimensional data alongside time. GIS can provide a solution to the lacuna. In organizations, the demand for additional space and resources increases through time. Indian Institute of Space Science and Technology plans to use GIS for FM of the campus. A methodology has been developed for FM utilizing GIS platform. This paper proposes the methodology utilizing ArcGIS, proprietary software for data preparation and open source software’s such as Geoserver, Unity 3D Game Engine, C++, JavaScript, CSS and XML for developing various components of the Web based facility management.

The main goal of this paper is to examine a possibility of application of Monin-Obukhov similarity theory for the wind speed estimation at 2 m above the ground using the routine weather elements. Consequently, for this purpose the meteorological data for the year 2005 at the Zagreb-Maksimir Observatory, located in a suburban setting was used. The similarity theory is adopted for the purposes of estimation of the wind speed at 2 m above the ground, that is, for calculation of turbulence parameters. One of the most important results is the classification of effective roughness length according to wind direction. The comparison between measured and estimated wind speed at 2 m above the ground ignoring and taking into account the dependence of effective roughness length on wind direction was performed. The verification parameters for estimation of wind speed at 2 m are bias, mean absolute error and root mean squared error between measured and estimated values of wind speed. Taking into account the dependence of effective roughness length on wind directions, all three parameters decreased, especially the bias.

Indian northeast monsoon season (October to December) is the major period of rainfall activity over south peninsula. The season is also referred to as “Post-Monsoon Season” or “Retreating Indian Summer Monsoon (ISM) Season”. This study examines the role of Arabian Sea surface pressure on the inter-annual variability (IAV) of Indian northeast monsoon rainfall (INEMR). For establishing the teleconnections, sea surface temperature (SST), rainfall, mean sea level pressure (MSLP), and lower troposphere zonal and meridional wind data have been analyzed. The study reveals that during excess INEMR years, similar to ISM semi-permanent low and monsoon trough, the anomalous semi-permanent surface low pressure and trough are observed over Arabian Sea and peninsular India, respectively. These anomalous low and trough intensifies the tropical storms, depressions and cyclones over Bay-of-Bengal, which hits peninsular India and gives widespread rainfall, affecting the IAV of INEMR.

The atmospheric dust plays a major role in deciding the radiation balance over the earth. This property of the dust has a long term effect on the Indian summer monsoon and its spatial distribution. Two sets of simulations (control and dust chemistry simulation) are made to analyze the effect of dust on the Indian summer monsoon. The analysis of the pre-monsoon and May temperature climatology reflects that the heating of the land mass is more in the dust chemistry simulation as compared to the control simulation, which is providing the strength to the monsoon flow during JJAS.

The ionosphere represents one of the most important error sources that affecting GPS positioning. It is strongly related to solar activity and geomagnetic field. The GPS satellites and dual frequency receivers can be used to measure the Total Electron Content (TEC) of the Earth’s ionosphere. In this paper, the total electron content (TEC) profile features, have been utilized for extraction of parameters like profile factor, P and anomaly factor, PEA separately for three seasons (summer, winter and equinox) and the parameters are used for assertion of a certain day as quiet (Q) or disturbed (D). The ionospheric Total electron content (TEC) is used to examine the influence of solar activity by taking advantage of the dispersive nature of the ionospheric medium. The definitions of Q and D days are made through profile features and the threshold values of ∑Kp for each season are evaluated. The relations between Disturbed storm time (Dst) and P factor, ∑Kp and P factor are established after corrections for solar activity condition. The prediction and assertion of Q/D days are then made by examining IEC profiles for the cases where IEC data were not used for the parameter extraction. A few case studies using these methods are also presented in these papers. Work is based on TEC/IEC data collected from VHF Radio Beacon (RB) technique from geostationary satellite and GPS receiver at Guwahati (26.20N, 91.750E), an equatorial anomaly crest station.

This study describes unusual winter hailstorm occurring over New Delhi, India. Cold and dry conditions during winter are not conducive for generating a hailstorm, thus making them a rare meteorological occurrence. This study uses numerical simulation to understand the dynamics of a winter-time hailstorm occurrence. The cause of a hailstorm during winter is attributed to low level convective available potential energy and moisture incursion that causes rising of air till the mid-tropospheric level and then further rising takes place due to the western disturbance in the mid-troposphere causing baroclinic instability.

This paper deals with the spatial and temporal pattern in monthly rainfall and temperature (maximum and minimum) distribution over the Northeast India. Five meteorological stations have been chosen for this study. The stations considered for analysis of temperature are Dibrugarh (1952–2000), Guwahati (1951–2000), Cherrapunji (1952–2000), Imphal (1954–2000), and Darjeeling (1952–2000). The rainfall analysis has been done for all the above stations for the period 1951–2010. The Mann-Kendall trend test was carried out to assess the trend in rainfall and temperature for different seasons during study period. The analysis has shown that these stations of Northeast India have not experienced any specific trend in rainfall in winter and monsoon seasons. The pre-monsoon season has an increasing trend in rainfall while during post-monsoon season a declining trend in rainfall was observed in two stations. All the stations experienced insignificant rise in maximum temperature during the post monsoon period while rest of the seasons have not shown any persistent trend over the region. An increasing trend in minimum temperature was observed in these stations during post-monsoon season, except Imphal and Cherrapunji. Dibrugarh is the only station which observed an increasing trend in minimum temperature in all of the seasons except winter. In winter minimum temperature increased insignificantly in Guwahati and Darjeeling stations. Even though insignificant, the later indicated a warming tendency for the region.

The energy balance at the glacier-atmosphere interface is the key control of the interaction between glaciers and climate. Melting at the glacier surface is controlled by the surface energy balance. Here we report, the energy and mass balance study carried out on Chorabari Glacier, Mandakini basin, Central Himalaya for the period of one year (Nov 2011-Oct 2012). The meteorological data collected from an Automatic Weather Station (AWS) were used to compute the annual cycle of local surface energy balance in the ablation zone. The average energy flux is calculated 28.5 Wm-2 for surface melting. In addition, the net radiation component is the largest contributor (52%) to the total surface energy heat flux followed by turbulent sensible (26%) and latent (9%) fluxes and the remaining 13% is only from subsurface heat. The study shows that the modelled ablation is well matched with ground measurement by 2% relative error.

The temporal monitoring of any glacier is important for observing the effects of changing climate. This study reports the decadal changes in Siachen glacier. Analysis was carried out on decadal basis by processing and analyzing Landsat images from 1978 to 2013. Images were co-registered within Root Mean Square Error (RMSE) limit of 0.5 pixel. An object based classification approach was adopted to perform temporal semi-automated areal change detection. The glacier inventory of 1978 showed around 74976 ha of glacier area which further decreased by around 1302 ha in 2013 with a shift of 1.5 km in the snout position.

Alteration in glacial parameters are pertinent indicators of glacier health and their response to climate change. In the present study, five glaciers of Zanskar basin including Pensli-lungpa, Durung Drung, Kangi, Hogshu and one unnamed glacier have been studied for temporal changes in glacial extent, glacial mass balance via accumulation area ratio (AAR) and ELA. For this purpose various multi-temporal satellite datasets of the study area and ASTER DEM have been used. ELA has been derived by using normalized difference glacier index (NDGI) technique and DEM together. Glacier boundaries have been derived by manual digitization. The mapping of glaciers during the period 1980–2000 & 2000 to 2011 reveals that the glacier cover reduced from 291.98 km2 to 259.11 km2, and 259.11 km2 to 250.96 km2 witnessing deglaciation of 11.25% and 3.14% respectively. Moreover, that there has been an increase in SLA of the sub basin from 5126 m a.s.l to 5297 m a.s.l from 1977 to 2000 and 5297 m a.s.l to 5361 m a.s.l from 2000 to 2011. Besides, the minimum and maximum AAR derived mass balance for the study area during the period of study has been 42.61 cm and -13.17 cm, respectively. An increase in the mean ELA in the area is followed by pronounced glacier recession and deglaciation.

This study is an attempt to look at intra seasonal and inter annual variations in temperature and in snow covers area (SCA) of the Upper Beas river basin (up to Pandoh dam) of the Western Himalaya. The SCA was assessed based on Normalized Differential Snow Index (NDSI) using representative images of MODIS Snow Cover Daily L3 Global) data for the period 2000–2010. Air temperature data from adjacent India Meteorological Department stations were used to examine the relationship between the snow cover and air temperature. It has been observed that the SCA showed large scale fluctuations both in time and space.

Trend analysis for 8 stations of Lidder watershed was performed using 3 Non-parametric and 2 parametric tests. It was found that upstream and downstream stations didn’t showed much variation except one downstream station i.e Ader station which showed significant decreasing trend for spring, winter and Autumn season. It was observed during last 40 years, the glacier area in the basin has decreased from 45.82 km2 in 1969 to 38.98 km2 in 2010. Differential response has been observed between the upstream downstream region streamflow of the River. The insignificant decreasing trends in the downstream of the Lidder and the increasing observed trends of discharge at Ader discharge stations downstream could be primarily attributed to the Karst topography of the region.

High mountain basins provide high specific discharges to headwaters of major continental rivers. Glacierised catchments show a discharge regime that is strongly influenced by snow and glacier melt waters. Many of the major rivers in India originate from the Himalayas. These rivers have significant contribution from snow and ice which makes these rivers perennial. Himalayan region has high concentrations of mountain glaciers. Large extent of this region is covered by seasonal snow during winter. Runoff generates from melting of these snow and glaciers is one of the important sources of water for the Himalayan rivers. Glaciers and snowfields are distributed throughout the Himalayas and form a source of numerous streams. Considering this aspects, in this study a snowmelt runoff simulation model SNOWMOD suitable for Himalayan basins developed earlier has been modified and applied for simulation of flows from the Gangotri Glacier, the headwaters of River Bhagirathi in the Uttarakhand Himalayas. The flow data for the year 2010 has been considered for calibrating the model whereas the year 2011 and 2012 have been considered for validating the model for simulating the daily flows. The efficiency of the model has been computed based on the daily simulated and observed flow values for three years. The values of the model efficiencies are 86%, 87% and 90% respectively for the years 2010, 2011 and 2012.

The ODP Site 738B Leg 119 is located on the base of southern slope of Kerguelen Plateau. Twenty nine samples from two sections viz., 1H1-1H2 were used to carry out the present study. The polycystine radiolaria Cycladophora davisiana Ehrenberg first appears in upper Pliocene sediments in North Pacific at approximately 2.7 Ma. Peaks and curves of C. davisiana abundance are used as stratigraphic and Paleoceanographic markers indicating glacial period during the Quaternary and over the last 425 Kyrs. The two zones were established viz. Omega and Psi and which are equivalent to NR1 and NR2 of upper Quaternary. On the basis of abundances, C. davisiana having one peak in omega while eight in the Psi zone. Further, it is interpreted that in the Psi zone more cooling or glacial periods were present compared to Omega.

A field experiment was carried out in rainfed semi-arid tropics of India to develop sustainable conservation agriculture (CA) practices as an alternative to conventional agriculture practices to increase yields, soil fertility in pigeon pea –castor cropping system. But this may offset the benefits by increasing greenhouse gas (GHG) emissions; hence the GHG emissions were monitored. A replicated trial was laid out in split plot design with three tillage practices viz., conventional tillage (CT), reduced tillage (RT) and zero tillage (ZT) and three anchored residue height (0 cm, 10 cm and 30 cm). The pooled analysis of data showed that seed yield and biological yield are influenced by tillage practices and anchored residue height. ZT recorded significantly lower yields (seed and biological yield) in both crop (pigeonpea and castor) compared to conventional and reduced tillage. In general, with increase in anchored residue height seed yield increased. CT recorded the higher harvest index as compared to the ZT. A higher CO2 emission was recorded in ZT whereas the N2O emission was lower and no significant difference was observed in methane oxidation between tillage practices.

Considering importance of weather conditions for development of agricultural grades influence of the Nurek reservoir on formation of a microclimate of the Dangara district with the developed agricultural branch investigated. It has observed that the natural trend of temperature in summer and the winter periods before construction of a reservoir transformed to the return, i.e. temperature increases in the winter and decreases in the summer. Analysis of annual precipitation shows the cyclical their fluctuations by interval of 3-5 years. Humidity reduction for the considered periods that is connected with increase of temperature at almost invariable trend of the precipitation change in Dangara was observed.

The study indicates that abnormal weather phenomena in the form of less rainfall with no snowfall and reduction in number of rainy days, short span heavy rainfall, hydrogeologic and geomorphologic conditions of the aquifer system and availability of surface water resource are the major limitations for groundwater recharge in the study area. A detailed study of the seven micro-watersheds of Western Ramganga River in the Kumaun Lesser Himalayan terrain has been carried out to identify and propose area specific artificial groundwater recharge structures (AGRS) using remote sensing, geographical information system, field survey and multi criteria decision making techniques (MCDM). The small-scale AGRS structures can be built across lower order streams in order to enhance infiltration into the subsurface formations. The results of the present study can serve as guidelines for planning future artificial recharge projects in the area in order to ensure dependable water supply and sustainable groundwater utilization on a long-term basis.

Global threats including climate change, land degradation, environmental contamination, and water shortages lead to economic, social and environmental damage. These need to be addressed to overcome the major disaster occurring now and in near future. Sustainable Biochar (BC) from biomass and wastes can be an environmentally-friendly option for carbon sequestration, soil fertility improvement, pollution remediation and agricultural by-product/waste recycling. Pyrolysis of lignocellulosic biomass to bio fuels and other value-added products including biochar has attracted considerable attention since the mid-1970s due to petroleum price spikes, climate change and increasing energy demand [1]. Fast and slow pyrolyses are promising routes to renewable liquid fuels, biochars and chemicals. Fast pyrolysis is a promising route to recover renewable liquid fuels. Fast pyrolysis employs short residence time (<3 s) at 400-5000C in absence of oxygen to generate bio-oil or pyrolytic oil, bio-char and gas [1, 2].

In front of the modern changing climate, an integrated coastal zone management requires future scenarios of coastal evolution that can be projected by multi-scale Long Term Morphodynamic Models (LTMMs). A realistic initial Digital Elevation Model (DEM) assigned to the historical starting time is essential for calibrating and validating these models. By using the information of historical coastline changes, relative sea level record and modern DEM, the inverse modelling method (i.e. Dynamic Equilibrium Shore Model, DES Model) has been developed and validated for approximately estimating historical morphology at the Pomeranian Bay, southern Baltic Sea. This model bears also the potential for future projection of coastal morphogenesis based on sea level rise scenarios. The Pomeranian Bay is a wave-dominated sandy coast where sand remains within the coastal area and fine-grained suspended matter discharged by rivers is transported cross-shore basinward. A Long-shore Sediment Transport Capacity Model (LSTC) has proven the area to be semi-enclosed – one of the main preconditions for applying the inverse model to coastal environments. For comparison the Laizhou Bay (Bohai Sea) has been selected as a research area. Here, joint factors such as river discharge, tides, waves, and sea level variations shape the nearshore bottom morphology. In addition to the wind-wave driven Long-shore Sediment Transport Capacity, tidal residual currents are also important for estimating long-shore sediment flux to determine the boundary of the semi-enclosed area. At the Laizhou Bay, the muddy sediments at the sea bottom descend from numerous rivers’ discharges. So, the riverine sediment source has to be taken into account here when balancing the sediment mass as distinguished from the Pomeranian Bay. In terms of modelling coastal morphogenesis, the comparative study carried out here helps to understand different formation mechanisms of wave-dominated sandy coast and tide-influenced muddy coast.

A non-linear first-order differential equation is proposed to describe the decay function of probability density around the mean values. Assume the decay rate of probability density function is negatively proportional to the density itself, with a functional coefficient dependent on the value of the random variable. Applying Taylor series expansion to the coefficient function, the differential equation can be approximated by multiple simple dynamic systems, each with explicit solutions. These functions can be utilized either as separate and combined solutions to generate various commonly used probability distributions including but not limited to Gaussian, power-law, gamma, inverse gamma, Pareto, Weibull, Rayleigh, and Maxwell-Boltzmann distributions.