Recharge mechanism and processes controlling groundwater chemistry in a Precambrian sedimentary terrain: a case study from Central India

Unplanned and unsustainable extraction has created stress on groundwater resources in many parts of India. The stress symptoms are more pronounced in hard rock areas, where the aquifer potentials are comparatively low. Present research targeted an area of 3000 km² in the interstream region between the Kharun and Seonath rivers, which is one such region in Central India. In spite of being a water-stressed area, so far, little is understood about processes of recharge, amount of recharge and processes controlling chemical quality, which are key inputs for groundwater management in the area. This study presents an appraisal of recharge mechanism, recharge rate and prevailing water–rock interactions in the study area. Stable isotope composition of groundwater when compared to that of rainfall indicates monsoon rainfall as the primary source of groundwater recharge. Winter rains, which are characteristically enriched in heavier isotopes, do not contribute notably to groundwater recharge. Recharge is rapid with minor or no evaporative enrichment before recharge. Further, analysis of stable isotopes show that ‘macropore recharge’ is dominant in limestone or calcareous shale, covering more than 70% of the study area. Also apparent is the vertical connectivity amongst the aquifers. However, active intermixing of surface water and groundwater is not a predominant process. Annual groundwater recharge from rainfall, as derived from chloride mass balance, is 105.26 million cubic metre. Groundwater is predominantly of bicarbonate type, irrespective of its hydrostratigraphic (lithology) setting. Dissolution of carbonates and gypsum (occurring as veins), weathering of feldspar and ion exchange of clay minerals are amongst the most likely processes controlling the regional groundwater chemistry.     

Groundwater vulnerability mapping assessment of central West Bank catchments using PI method

A groundwater vulnerability assessment was carried out in order to understand and control the pollution sources affecting vulnerable regions in two adjacent catchments (Sarida and Natuf), located in the western middle part of the West Bank. The catchments were subjected to groundwater vulnerability mapping and assessment using the modified German State Geological Surveys (GLA method) method called Protective Cover and Infiltration Conditions method (PI method) via ArcGis 2014.2 software package in February of 2016. The results showed that the study area has high effectiveness of protective cover (P-factor), which was obtained by overlying top soil, bedrock, subsoil, and recharge layers. On the other hand, the dominant flow types, land usage, slopes, and topographical classification layers were overlaid to get the infiltration conditions (I-factor). The interaction between the two main factors was carried out in order to obtain the final spatially distributed π-factor values (vulnerability map), which was classified into four vulnerability classes. Statistically, about 4% of the overall area was of extreme vulnerability and concentrated along the sinking streams, while 22% was of low vulnerability and existed outside the main watersheds, followed by high vulnerability with 26%. The largest proportion with 48% of the overall area was of moderate vulnerability to groundwater contamination.     

Identification of the Major Allergen in Greasy-Back Shrimp （Metapenaeus ensis） by MALDI-TOF-MS

In order to better understand shrimp allergen,some basic characters of the major allergen of greasy-back shrimp (Metapenaeus ensis)were investigated.The major allergen was extracted and separated,and its peptide mass fingerprint(PMF) was analyzed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry(MALDI-TOF-MS).After screening in the NCBI database with Mascot searching engine,the results indicated that the major allergen of greasy-back shirmp was muscle tropomyosin.Database matching search showed that the top protein matched,i.e.the tropomyosin from giant tiger prawn(Penaeus monodon),had a Mowse value of 268.In addition,there were 27 queries matched with the allergen in greasy-back shirmp with an amino acid sequence coverage value of 65%.The matching scores and the sequence coverage values were also high with tropomyosins of other invertebrates,including Tyrophagus putrescentiae and Lepisma saccharina.These results indicated that the allergen of Metapenaeus ensis had high homology with other crustacean allergens,and provided molecular explanations for the high cross-reactivity of the major allergens between crustaceans and some other invertebrates.     

GIS-based high-resolution spatial interpolation of precipitation in mountain–plain areas of Upper Pakistan for regional climate change impact studies

In this study, the baseline period (1960–1990) precipitation simulation of regional climate model PRECIS is evaluated and downscaled on a monthly basis for northwestern Himalayan mountains and upper Indus plains of Pakistan. Different interpolation models in GIS environment are used to generate fine scale (250?×?250 m²) precipitation surfaces from PRECIS precipitation data. Results show that the multivariate extension model of ordinary kriging that uses elevation as secondary data is the best model especially for monsoon months. Model results are further compared with observations from 25 meteorological stations in the study area. Modeled data show overall good correlation with observations confirming the ability of PRECIS to capture major precipitation features in the region. Results for low and erratic precipitation months, September and October, are however showing poor correlation with observations. During monsoon months (June, July, August) precipitation pattern is different from the rest of the months. It increases from south to north, but during monsoon maximum precipitation is in the southern regions of the Himalayas, and extreme northern areas receive very less precipitation. Modeled precipitation toward the end of the twenty-first century under A2 and B2 scenarios show overall decrease during winter and increase in spring and monsoon in the study area. Spatially, both scenarios show similar pattern but with varying magnitude. In monsoon, the Himalayan southern regions will have more precipitation, whereas northern areas and southern plains will face decrease in precipitation. Western and south western areas will suffer from less precipitation throughout the year except peak monsoon months. T test results also show that changes in monthly precipitation over the study area are significant except for July, August, and December. Result of this study provide reliable basis for further climate change impact studies on various resources.     

Green and Eco‐Friendly Removal of Mycotoxins with Organo‐Bentonites; Isothermal,Kinetic, and Thermodynamic Studies

In the current study the application of organo‐modified bentonite for the adsorption of mycotoxins (aflatoxin B1, citrinin, patulin, and zearalenone) is presented. The modification of clays is carried out using benzyl‐tri‐n‐butyl ammonium bromide (BTB), benzethonium chloride (BTC), and dioctyl sodium sulfosuccinate (DSS). Various experimental parameters such as pH, time, adsorbent dose, and mycotoxins concentration are thoroughly studied. The modified clays (B‐BTB, B‐BTC and B‐DSS) are characterized by X‐ray fluorescence, X‐ray diffraction, and Fourier transform infrared spectroscopy. The results depicted the high detoxification efficiency (≈99%) of modified clays for the removal of mycotoxins under optimized conditions (pH 5, time: 30 min, adsorbent amount: 50 mg). The adsorption capacities of modified clays are found in the order of: B‐BTC (AFB1: 18.02, CIT: 18.35, PAT: 18.21, ZEA: 18.09 mg g^?1) > B‐BTB (AFB1: 17.7, CIT: 18.11, PAT: 17.95, ZEA: 17.90 mg g^?1) > B‐DSS (AFB1: 17.5, CIT: 18.02, PAT: 17.86, ZEA: 17.80 mg g^?1). The obtained results fitted well with thermodynamic, isothermal (Langmuir) and pseudo‐second order kinetics. Low cost organo‐modified bentonite shows the promise in mitigating mycotoxin contamination, which could improve food safety and reduce environmental contamination.     

<Emphasis Type="Italic">Integrated Remote Sensing and</Emphasis> Structural Analysis Studies of Tayyib Al-Ism Area,Northwestern Arabian Shield,Saudi Arabia

Geological and structural mappings of Tayyib Al-Ism area were carried out using the rocks finite strain data, the Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data and the field based observations. To analyze the finite strain in the studied rocks, the R_f /? and Fry methods are applied to feldspar porphyroclasts and mafic grains from nine metavolcano-sedimentary samples (Hegaf Formation), four diorite-gabbros suite samples (Sawawin Complex), two meta-granite samples (Ifal suite) and five Zuhd alkali granite samples. The obtained data indicate traces of high to moderate level of deformation in the meta-granite and metavolcano-sedimentary rocks. The axial ratios along the XZ section range from 1.70 to 4.80 for the R_f/? method and from 1.50 to 4.50 for the Fry method. A sub-vertical trend of short axes in association with sub-horizontal foliation is also observed. These informations allow us to conclude that a finite strain in the deformed granitic rocks is of the same order of magnitude as in the metavolcano-sedimentary rocks. The contacts between the metavolcano-sedimentary and granitic rocks in Tayyib al Ism area were formed during the granitic intrusions along some of the faults under brittle to semi-ductile deformation conditions. These faults have significantly influenced the geometry and style of rifting in the Red Sea during the Neogene. The finite strain was accumulated in the area during the process of deformation, which superimpose the already existed nappe structure. It indicates that the nappe contacts formed during the accumulation of finite strain. In addition to finite strain analysis, band ratio images (3/1, 5/3, 7/5) and Principal Component Analysis (PCA) technique have been used, which proved effective in mapping geological and structural features of various rock bodies exposed in the study area.     

Group velocity dispersion analysis in northern Peninsular Malaysia

The crustal structure beneath three seismic stations over Malaysia has been investigated with the application of the group velocity dispersion analysis of the northern Sumatra earthquake data which occurred on 06 April 2010. Eighteen crustal layer models are constructed to assess the structure. Group velocity dispersions have been computed for the recorded earthquake data using a graphical method and modified Haskell matrix method for the models. Both dispersions have been presented for the interpretation of crustal layers. Findings have shown four major crustal layers having thicknesses of 2.5–4.0, 2.0–5.5, 5.0–8.0, and 8.5–9.0 km, while in Terengganu, it has shown three layers. Density, shear, and compressional wave velocities used in models have suggested that the crustal structure of the northern part of Peninsular Malaysia is crystalline. Major crustal minerals are of quartz, plagioclase, and mica. Most layers seem to have upward directions toward Perak from Kedah and Terengganu.     

A study of soft computing models for prediction of longitudinal wave velocity

Genetic algorithm (GA) and support vector machine (SVM) optimization techniques are applied widely in the area of geophysics, civil, biology, mining, and geo-mechanics. Due to its versatility, it is being applied widely in almost every field of engineering. In this paper, the important features of GA and SVM are discussed as well as prediction of longitudinal wave velocity and its advantages over other conventional prediction methods. Longitudinal wave measurement is an indicator of peak particle velocity (PPV) during blasting and is an important parameter to be determined to minimize the damage caused by ground vibrations. The dynamic wave velocity and physico-mechanical properties of rock significantly affect the fracture propagation in rock. GA and SVM models are designed to predict the longitudinal wave velocity induced by ground vibrations. Chaos optimization algorithm has been used in SVM to find the optimal parameters of the model to increase the learning and prediction efficiency. GA model also has been developed and has used an objective function to be minimized. A parametric study for selecting the optimized parameters of GA model was done to select the best value. The mean absolute percentage error for the predicted wave velocity (V) value has been found to be the least (0.258 %) for GA as compared to values obtained by multivariate regression analysis (MVRA), artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and SVM.