巴基斯坦地方地震台网的监控能力与可靠性

使用Bungum和Huseby方法对地方地震台网的监控能力和可靠性进行了分析。用震源位置的标准计算机码重新定位地震事件。由频率震级分布导出50％，90％和100％的累积监控能力阀值，对这些阀值23年内记录资料的监控能力水平作了估测。分析表明，在台网内发生的地震事件的台网100％监控能力水平为ML=1.7，从台网内固定实时震源对台网震源解精度作了分析。地震事件在台网内发生时，震中误差低于4km。最后讨论了地方地震台网连续运行期间影响监控能力的因素。     

Seismic vulnerability assessment in the new urban area of Diriyah Governorate,Riyadh, Saudi Arabia

Nine seismic refraction profiles were conducted and processed to study the near-surface sediments in the new urban area of Diriyah. The 2D geoseismic models illustrate two layers: a surface layer of soft sediments and weathered to hard limestone bedrock. Moreover, microtremor measurements were performed at 38 sites for 40 min using three-component seismographs and processed to assess the peak spectral amplitude and the corresponding fundamental resonance frequency. The seismic vulnerability index at each measurement site was estimated. These results correlate well with the geotechnical borehole data. The north-western zone is highly vulnerable due to the great thickness of the soft sediments.     

Evaluation of nonlinear models for precipitation forecasting

Prediction of factors affecting water resources systems is important for their design and operation. In hydrology, wavelet analysis (WA) is known as a new method for time series analysis. In this study, WA was combined with an artificial neural network (ANN) for prediction of precipitation at Varayeneh station, western Iran. The results obtained were compared with the adaptive neural fuzzy inference system (ANFIS) and ANN. Moreover, data on relative humidity and temperature were employed in addition to rainfall data to examine their influence on precipitation forecasting. Overall, this study concluded that the hybrid WANN model outperformed the other models in the estimation of maxima and minima, and is the best at forecasting precipitation. Furthermore, training and transfer functions are recommended for similar studies of precipitation forecasting.     

Role of the Kazerun fault system in active deformation of the Zagros fold-and-thrust belt (Iran)

Field structural and SPOT image analyses document the kinematic framework enhancing transfer of strike-slip partitioned motion from along the backstop to the interior of the Zagros fold-and-thrust belt in a context of plate convergence slight obliquity. Transfer occurs by slip on the north-trending right-lateral Kazerun Fault System (KFS) that connects to the Main Recent Fault, a major northwest-trending dextral fault partitioning oblique convergence at the rear of the belt. The KFS formed by three fault zones ended by bent orogen-parallel thrusts allows slip from along the Main Recent Fault to become distributed by transfer to longitudinal thrusts and folds. To cite this article: C. Authemayou et al., C. R. Geoscience 337 (2005).     

Application of advanced technology to build a vibrant environment on planet mars

In order to make Mars a better planet, in this paper, photo-dissociation technology, mathematical modeling, and a series of chemical reaction methodology have been proposed to create a vibrant ecosystem and balance the atmosphere on Mars. Since CO₂ is a stable compound, breaking it down into C and O₂ always is challenging, but exciting thought. Interestingly, my recent research revealed that photo-dissociation by utilizing UVV (laser) could be an exciting technology to split CO₂ into C + O₂ since the theoretical reaction suggested that the production of C + O₂ channel from CO₂ photo-exciting technology releases the energetic level threshold of C(³P₂) + O₂(X³∑ _g ^? ) that can be detected by ultraviolet laser pump-probe spectroscopy. Subsequently, a mathematical model for creating of ocean on Mars by breaking its substantial polar ice has been performed considering algorithms for surface and coordinate between the barotropic momentum and continuity equations, and interestingly the calculation suggested that it is very much possible to flow ocean on Mars surface to meet its water demand. Subsequently, proposed series of chemical reaction technology suggested that implementation of carbonator looping and plasma reaction paths can convert photo-dissociated carbon (C) into N₂ and NH₃ to enrich Mars’ soil in order to grow vegetation as well as to create a balance ecosystem in Mars eventually. Finally, sustainable green technology has been proposed for the development of Mars to be a complete balanced planet to deliver all basic and modern needs to run daily life smoothly. Thus, implication of chemical reaction technologies along with sustainable development plans can indeed make the Mars a vibrant environment to live there in clean and green.     

Support vector machines and feed-forward neural networks for spatial modeling of groundwater qualitative parameters

The present study attempts to model the spatial variability of three groundwater qualitative parameters in Guilan Province, northern Iran, using artificial neural networks (ANNs) and support vector machines (SVMs). Data collected from 140 observation wells for the years 2002–2014 were used. Five variables, X and Y coordinates of the observation well, distance of the observation well from the shoreline, areal average 6-month rainfall depth, and groundwater level at the day of water quality sampling, were considered as primary input variables. In addition, nine qualitative variables were also considered as auxiliary input variables. Electrical conductivity (EC), sodium concentration (Na⁺), and sulfate concentration (SO₄ ^2?) of the groundwater in the region were estimated using ANNs and SVMs with different input combinations. The results showed that both ANNs and SVMs work well when the only primary input variable is the well location. The ANN yielded an RMSE of 1.03 mEq/l for SO₄ ^2?, 1.05 mEq/l for Na⁺, and 203.17 μS/cm for EC, using the X and Y coordinates of the observation wells in the study area. In the case of SVM, these values were, respectively, 0.87, 0.87, and 176.68. Considering the auxiliary input variables (pH, EC, and the concentrations of Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl^?, SO₄ ^2?, and HCO₃ ^?) resulted in a significant decrease in the RMSE of both ANNs (0.22, 0.30, and 33.04) and SVMs (0.26, 0.34, and 36.23). Comparing these RMSE values with those of cokriging interpolation technique (0.59, 0.98, and 177.59) indicated that ANNs and SVMs produced more accurate estimates of the three qualitative parameters. The relative importance of auxiliary input variables was also determined using Gamma test. The output uncertainty of ANNs and SVMs were determined using p-factor and d-factor. The results showed that SVMs have less uncertainty than ANNs.     

Estimation and validation of atmospheric water vapor content using a MODIS NIR band ratio technique based on AIRS water vapor products

Atmospheric water vapor validation needs simultaneous, well-defined, and independent information which are not easily available causing limitations in the development of remote sensing water vapor retrieval algorithms. This study is concerned with the retrieval of total atmospheric water vapor content and its validation. A band ratio method has been used to estimate the water vapor content based on Moderate Resolution Imaging Spectroradiometer (MODIS) Near InfraRed (NIR) data. The method uses MODIS bands 17, 18, and 19 as NIR bands and band 2 to remove the land cover reflectance. Furthermore, the Atmospheric Infrared Sounder (AIRS) has been used for both algorithm development and analysis of the results. The method has been modified to take into account the dry condition of the central parts of Iran. Using some various datasets, the method is implemented and evaluated quantitatively. The validation of the water vapor estimates has been undertaken by an analysis of AIRS data. The validation results shows error as low as 9 % for the estimated water vapor using the MODIS NIR band ratio method.     

Investigation of Arsenotrophic Microbiome in Arsenic‐Affected Bangladesh Groundwater

Arsenotrophic bacteria contribute to the nutrient cycling in arsenic (As) affected groundwater. This study employed a culture‐independent and ‐dependent investigation of arsenotrophic microbiomes in As affected groundwater samples collected from Madhabpur, Sonatengra, and Union Porishod in Singair Upazila, Manikganj, Bangladesh. Total As contents, detected by Atomic Absorption Spectrophotometry (AAS) of the samples, were 47 µg/L (Madhabpur, SNGW‐1), 53 µg/L (Sonatengra, SNGW‐2), and 12 µg/L (Union porishod, SNGW‐3), whereas the control well (SNGW‐4; depths >150 m) showed As content of 6 µg/L. Denaturing Gradient Gel Electrophoresis (DGGE) analysis of the amplified 16S rRNA gene from As‐affected groundwater samples revealed the dominance of aerobic bacteria Pseudomonas within heterogeneous bacterial populations. DGGE of heterotrophic enrichments supplemented with arsenite [As (III)] for 4 weeks showed the dominance of Chryseobacterium, Flavobacterium, and Aquabacterium, whereas the dominant genera in that of autotrophic enrichments were Aeromonas, Acinetobacter, and Pseudomonas. Cultured bacteria retrieved from both autotrophic and heterotrophic enrichments were distinguished into nine genotypes belonging to Chryseobacterium, Acinetobacter, Escherichia, Pseudomonas, Stenotrophomonas, Janibacter, Staphylococcus, and Bacillus. They exhibited varying range of As(III) tolerance from 4 to 27 mM. As(III) transformation potential was confirmed within the isolates with oxidation rate as high as 0.143 mM/h for Pseudomonas sp. Sn 28. The arsenotrophic microbiome specifies their potential role in groundwater As‐cycling and their genetic information provide the scientific basis for As‐bioremediation.     

Factor and cluster analysis of water quality data of the groundwater wells of Kushtia, Bangladesh: Implication for arsenic enrichment and mobilization

The study area is located in the southwestern part of Bangladesh. Twenty-six groundwater samples were collected from both shallow and deep tube wells ranging in depth from 20 to 60 m. Multivariate statistical analyses including factor analysis, cluster analysis and multidimensional scaling were applied to the hydrogeochemical data. The results show that a few factors adequately represent the traits that define water chemistry. The first factor of Fe and HCO₃ is strongly influenced by bacterial Fe (III) reduction which would raise both Fe and HCO₃ concentrations in water. Na, Cl, Ca, Mg and PO₄ are grouped under the second factor representing the salinity sources of waters. The third factor, represented by As, Mn, SO₄ and K is related to As mobilization processes. Cluster analysis has been applied for the interpretation of the groundwater quality data. Initially Piper methods have been employed to obtain a first idea on the water types in the study area. Hierarchical cluster analysis was carried out for further classification of water types in the study area. Twelve components, namely, pH, Fe, Mn, As, Ca, Mg, Na, K, HCO₃, Cl, SO₄ and NO₃ have been used for this purpose. With hierarchical clustering analysis the water samples have been classified into 3 clusters. They are very high, high and moderately As-enriched groundwater as well as groundwater with elevated SO₄.     

Automatic detection of residential buildings using LIDAR data and multispectral imagery

This paper presents an automatic building detection technique using LIDAR data and multispectral imagery. Two masks are obtained from the LIDAR data: a ‘primary building mask’ and a ‘secondary building mask’. The primary building mask indicates the void areas where the laser does not reach below a certain height threshold. The secondary building mask indicates the filled areas, from where the laser reflects, above the same threshold. Line segments are extracted from around the void areas in the primary building mask. Line segments around trees are removed using the normalized difference vegetation index derived from the orthorectified multispectral images. The initial building positions are obtained based on the remaining line segments. The complete buildings are detected from their initial positions using the two masks and multispectral images in the YIQ colour system. It is experimentally shown that the proposed technique can successfully detect urban residential buildings, when assessed in terms of 15 indices including completeness, correctness and quality.