Geochemical characteristics of Holocene sediments from Chuadanga district,Bangladesh: Implications for weathering,climate, redox conditions,provenance and tectonic setting

The present research deals with the geochemical characteristics of the Holocene sediments from Alamdanga area, Chuadanga district, Bangladesh. Main goals of the study are to delineate source rock characteristics, degree of chemical weathering and sorting processes and behavior of redox conditions during deposition of the sediments. Geochemical characteristics of the sediments show comparatively a wide variation in accordance with stratigraphy in their major element contents （e.g. SiO2 69.46-82.13, A1203 2.28-8.88 in wt%）, reflecting the distinctive provenance and in part an unstable period in terms of tectonic activity. Geochemical classification of the sediments shows mostly sub-arkose with few sub-litharenites. Some major and trace elements display comprehensible correlation with A1203 confirming their possible hydraulic fraetionation. The chemical index of alteration （CIA＊）, W＊ index, index of compositional variability （ICV）, plagioclase index of alteration （PIA＊） values and the ratio of SIO2/Al2O3, suggest low degrees of chemical weathering in the source areas as well as immature to moderately mature the sediments. The sediments suggest semi-arid climatic trends within oxic deltaic depositional conditions during the Holocene, at 3-12 ka. Whole rock geochemistry and discrimination diagrams demonstrate the continental signature derivatives, which might have been derived from the felsic to intermediate igneous rocks （granitic plutonic rocks） as well as from quartzose sedimentary/metamorphic provenance. These typical sources are present in a vast region of the Himalayan belt and catchment areas of Ganges. The tectonic setting of the sediments demarcates typically passive margin with slightly continental arc system.     

A Neuro-Fuzzy modeling for prediction of solar cycles 24 and 25

The paper presents a Neuro-Fuzzy model to predict the features of the forthcoming sunspot cycles 24 and 25. The sunspot time series were analyzed with the proposed model. It is optimized based on Backpropagation scheme and applied to the yearly smoothed sunspot numbers. The appropriate number of network inputs for the sunspots data series is obtained based on sequential forward search for the Neuro-Fuzzy model. According to the model prediction the maximum amplitudes of the cycles 24 and 25 will occur in the year 2013 and year 2022 with peaks of 101±8 and 90.7±8, respectively. The correlation and error analysis are discussed to ensure the performance of the proposed Neuro-Fuzzy approach as a predictor for sunspot time series. The correlation coefficient between Neuro-Fuzzy model forecasted sunspot number values with the actual ones is 0.96.     

Mixing efficiency from microstructure measurements in the Sicily Channel

Ocean Dynamics - The dissipation flux coefficient, a measure of the mixing efficiency of a turbulent flow, was computed from microstructure measurements collected with a vertical microstructure...     

Geochemistry of subsurface Late Quaternary ironstones in Rajshahi and Bogra Districts,Bangladesh: implications for genetic and depositional conditions

The present study deals with the geochemistry of Late Quaternary ironstones in the subsurface in Rajshahi and Bogra districts, Bangladesh with the lithological study of the boreholes sediments. Major lithofacies of the studied boreholes are clay, silty clay, sandy clay, fine to coarse grained sand, gravels and sands with(fragmentary) ironstones. The ironstones contain major oxides, Fe_2 O_3*(*total Fe)(avg. 66.6 wt%), SiO_2(avg. 15.3 wt%), Al_2 O_3(avg. 4.0 wt%), MnO(avg. 7.7 wt%), and CaO(avg. 3.4 wt%). These geochemical data imply that the higher percentage of Fe_2 O_3* along with Al_2 O_3 and MnO indicate the ironstone as goethite and siderite, which is also validated by XRD data. A comparatively higher percentage of SiO_2 indicates the presence of relative amounts of clastic quartz and manganese-rich silicate or clay in these rocks. These ironstones also have significant amounts of MnO(avg. 7.7 wt%) suggesting their depositional environments under oxygenated condition. Chemical data of these ironstones suggest that the source rock suffered deep chemical weathering and iron was mostly carried in association with the clay fraction and organic matter. Iron concretion was mostly formed by bacterial build up in swamps and marshes, and was subsequently embedded in clayey mud.Within the coastal environments, the water table fluctuates and goethite and siderite with mud and quartz became dry and compacted to form ironstone.     

Mapping groundwater recharge potential zones in arid region using GIS and Landsat approaches,southeast Tunisia

The rapid growth of population and agricultural and industrial activities has caused an increase in demand on the Jeffara aquifers of Gabes (southeast Tunisia). In fact, the over-pumping of this aquifer system has resulted in water-level declines ranging from 0.25 to 1 m/year during the past three decades. The aim of this study is to identify favourable artificial recharge sites of this aquifer system based on the combined use of remotely sensed data, a geographic information system (GIS), the Shuttle Radar Topography Mission (SRTM) product and a multiple criteria decision making (MCDM) technique. The delineation of artificial recharge zones shows high to moderate potential for groundwater recharge (40%) in the Gabes region, with high precision of good potential proposed sites. Recharge processes need to account for natural conditions and ecosystems.     

Modeling the Potential Distribution of Pine Forests Susceptible to Sirex Noctilio Infestations in Mpumalanga,South Africa

Reducing the impact of the siricid wasp, Sirex noctilio is crucial for the future productivity and sustainability of commercial pine resources in South Africa. In this study we present a machine learning model that serves as a spatial guide and allows forest managers to focus their existing detection and monitoring efforts on key areas and proactively adopt the most appropriate course of intervention. We implemented the random forest model within a spatial framework to determine which pine forests in Mpumalanga are highly susceptible to S. noctilio infestations. Results indicate that a majority (63%) of pine forest plantations located in Mpumalanga have a high susceptibility (>70%) to S. noctilio infestation. A KHAT value of 0.84 and F measures above 0.87 indicate that the random forest model is a robust classifier that produces accurate results. Additionally, the use of the backward variable selection method enabled us to simplify the random forest modeling process and identify the minimum number of explanatory variables that offer the best discriminatory power and help in the empirical interpretation of the final random forest model. Overall, the results show that pine forests that experience stress caused by evapotranspiration and evaporation followed by rainfalls, especially during the summer months are more susceptible to S. noctilio infestations.     

Assessing the oscillation of channel geometry and meander migration cardinality of Bhagirathi River,West Bengal,India

Journal of Geographical Sciences - Lateral migration of the Bhagirathi River temporally creates unavoidable geomorphic hazards in West Bengal, India. The Bhagirathi River flows SW for ~67.30 km...     

Laboratory study of shear strength response of Chlef natural sand: Effect of saturation

Abstract

The study of the unsaturated soils is a very complex field to which several researches in laboratory and on site are directed these last years. An experimental study aims to quantify the influence of the Skempton coefficient B characterizing the degree of saturation on the behavior of the granular sand to the liquefaction resistance of sand. The study is based on undrained triaxial tests performed on natural Chlef sand carried out at an initial relative density Dr = 50% under a confining pressure of 50, 100 and 200?kPa for Skempton coefficient B?=?10 to 92%. The results of the tests show that an increase of confining pressure leads to an increase of the shear stress of the samples. For the lower value of the degree of saturation results of our findings indicate an increase of the resistance to liquefaction; our results are in good agreement with others observed in several research projects conducted with other sands. The increase of Skempton coefficient B induces an increase of pore water pressure and a decrease of the shear strength. The pore pressure (u) increases with an exponential manner with the increase of the degree of saturation; while the residual shear strength (Rs) decreases with logarithmic manner with the increase of degree of saturation (B).