Weathering and mineralogical variation in gneissic rocks and their effect in Sangrumba Landslide,East Nepal

Sangrumba landslide is one of the largest and the most active landslides in Nepal Himalaya. Geologically the landslide belongs to the Higher Himalaya and consists of Pre-Cambrian biotite–garnet and sillimanite gneiss with some quartzite. The present paper aims at describing various degrees of rock weathering and their effect in Sangrumba landslide. Field study followed by mineralogical, geochemical and geotechnical analyses of the collected rock and soil samples from the landslide zone were used in characterizing weathering degree. The gneisses are intensely weathered while quartzite is unweathered. Petrographical and X-ray diffraction analyses showed that the rocks in the landslide zone had undergone weathering process with the formation of different types of clay minerals as kaolinite, vermiculite, smectite and chlorite. This was further confirmed by the Scan Electron Microscope and Energy Dispersive X-ray analyses. These clay minerals drastically reduced the rock strength facilitating the extensive failure of the Sangrumba landslide. The major and trace element composition of the rock and soil samples was calculated from the XRF analyses. The geochemical analyses and weathering indexes of rocks showed that they are significantly weathered and had a major influence in the formation of the Sangrumba landslide. In addition, mechanical strength measurement of rock/soil showed that the strength drastically decreases as the weathering intensity increases. Rainfall followed by the rock type are the most dominant parameters influencing the weathering process which leads to the formation of large landslide as the present one. These findings can be used in other areas with similar geological and topographical conditions.     

Sources and implications of particulate organic matter from a small tropical river—Zuari River,India

Transitional ecosystems,estuaries and the coastal seas,are distinctively affected by natural and anthropogenic factors.Organic matter(OM)originating from terrestrial sources is exported by rivers and forms a key component of the global biogeochemical cycles.Most previous studies focused on the bulk biochemical and anthropogenic aspects affecting these ecosystems.In the present study,we examined the sources and fate of OM entrained within suspended particulate matter(SPM)of the Zuari River and its estuary,west coast of India.Besides using amino acid(AA)enantiomers(L-and D-forms)as biomarkers,other bulk biochemical parameters viz.particulate organic carbon(POC),δ13C,particulate nitrogen(PN),δ15N and chlorophyll a were analyzed.Surprisingly no significant temporal variations were observed in the parameters analyzed;nonetheless,salinity,POC,δ13C,PN,δ15N,glutamic acid,serine,alanine,tyrosine,leucine and D-aspartic acid exhibited significant spatial variability suggesting source differentiation.The POC content displayed weak temporal variability with low values observed during the post-monsoon season attributed to inputs from mixed sources.Estuarine samples were less depleted than the riverine samples suggesting contributions from marine plankton in addition to contributions from river plankton and terrestrial C3 plants detritus.Labile OM was observed during the monsoon and post-monsoon seasons in the estuarine region.More degraded OM was noticed during the pre-monsoon season.Principal component analysis was used to ascertain the sources and factors influencing OM.Principally five factors were extracted explaining 84.52%of the total variance.The first component accounted for 27.10%of the variance suggesting the dominance of tidal influence whereas,the second component accounted for heterotrophic bacteria and their remnants associated with the particulate matter,contributing primarily to the AA pool.Based on this study we ascertained the role of the estuarine turbidity maximum(ETM)controlling the sources of POM and its implications to small tropical rivers.Thus,changes in temporal and regional settings are more likely to affect the natural biogeochemical cycles of small tropical rivers.     

Tilted bianchi type v bulk viscous cosmological models in general relativity

Conformally flat tilted Bianchi type V cosmological models in presence of a bulk viscous fluid and heat flow are investigated. The coefficient of bulk viscosity is assumed to be a power function of mass density. Some physical andgeometric aspects of the models are also discussed.     

Effect of Random Inclusion of Polypropylene Fibers on Strength Characteristics of Cohesive Soil

This paper presents the effect of random inclusion of polypropylene fibers on strength characteristics of soil. Locally available cohesive soil (CL) is used as medium and polypropylene fibers with three aspect ratios (l/d = 75, 100 and 125) are used as reinforcement. Soil is compacted with standard Proctor’s maximum density with low percentage of reinforcement (0–1% by weight of oven-dried soil). Direct shear tests, unconfined compression tests and CBR tests were conducted on un-reinforced as well as reinforced soil to investigate the strength characteristics of fiber-reinforced soil. The test results reveal that the inclusion of randomly distributed polypropylene fibers in soil increases peak and residual shear strength, unconfined compressive strength and CBR value of soil. It is noticed that the optimum fiber content for achieving maximum strength is 0.4–0.8% of the weight of oven-dried soil for fiber aspect ratio of 100.     

A novel hybrid integration model using support vector machines and random subspace for weather-triggered landslide susceptibility assessment in the Wuning area (China)

This study proposed a hybrid modeling approach using two methods, support vector machines and random subspace, to create a novel model named random subspace-based support vector machines (RSSVM) for assessing landslide susceptibility. The newly developed model was then tested in the Wuning area, China, to produce a landslide susceptibility map. With the purpose of achieving the objective of the study, a spatial dataset was initially constructed that includes a landslide inventory map consisting of 445 landslide regions. Then, various landslide-influencing factors were defined, including slope angle, aspect, altitude, topographic wetness index, stream power index, sediment transport index, soil, lithology, normalized difference vegetation index, land use, rainfall, distance to roads, distance to rivers, and distance to faults. Next, the result of the RSSVM model was validated using statistical index-based evaluations and the receiver operating characteristic curve approach. Then, to evaluate the performance of the suggested RSSVM model, a comparison analysis was performed to other existing approaches such as artificial neural network, Naïve Bayes (NB) and support vector machine (SVM). In general, the performance of the RSSVM model was better than the other models for spatial prediction of landslide susceptibility. The AUC results of the applied models are as follows: RSSVM (AUC = 0.857), followed by MLP (AUC = 0.823), SVM (AUC = 0.814) and NB (AUC = 0.783). The present study indicates that RSSVM can be used for landslide susceptibility evaluation, and the results are very useful for local governments and people living in the Wuning area.     

Estimating growing-season root zone soil moisture from vegetation index-based evapotranspiration fraction and soil properties in the Northwest Mountain region,USA

A soil moisture retrieval method is proposed, in the absence of ground-based auxiliary measurements, by deriving the soil moisture content relationship from the satellite vegetation index-based evapotranspiration fraction and soil moisture physical properties of a soil type. A temperature–vegetation dryness index threshold value is also proposed to identify water bodies and underlying saturated areas. Verification of the retrieved growing season soil moisture was performed by comparative analysis of soil moisture obtained by observed conventional in situ point measurements at the 239-km² Reynolds Creek Experimental Watershed, Idaho, USA (2006–2009), and at the US Climate Reference Network (USCRN) soil moisture measurement sites in Sundance, Wyoming (2012–2015), and Lewistown, Montana (2014–2015). The proposed method best represented the effective root zone soil moisture condition, at a depth between 50 and 100 cm, with an overall average R² value of 0.72 and average root mean square error (RMSE) of 0.042.     

Assessment of fractal dimension and geometrical characteristics of the landslides identified in North of Tehran,Iran

The aim of the presented study is to assess the fractal dimension (D) and the geometrical characteristics (length and width) of the landslides identified in North of Tehran, Iran. At first, the landslide locations (528 landslides) were identified by interpretation of aerial photographs, satellite images and field surveys, and then to calculate the fractal dimension (D), we used the computer programming named as FRACEK. In the next step, geometrical characteristics of each landslide such as length (L) and width (W) were calculated by ArcGIS software. The landslide polygons were digitized from the mentioned landslide inventory map and rotated based on movement direction. The fractal dimension for all landslides varied between 1.665 and 1.968. Subsequently, the relationship between the length/width ratios and theirs fractal D values for 528 landslides was calculated. The results showed that correlation coefficients (R), which are different regression models such as exponential, linear, logarithmic, polynomial, and power, between D and L/W ratio are relatively high, respectively (0.75, 0.75, 0.76, 0.78, and 0.75). It can be concluded that the fractal dimension values and geometry characteristics of landslides would be useful indices for the management of hazardous areas, susceptible slopes, land use planning, and landslide hazard mitigation.     

Spatio-temporal Assessment of Urban Heat Island Effects in Kuala Lumpur Metropolitan City Using Landsat Images

Alteration in climatic pattern has resulted to a steady decline in quality of life and the environment, especially in and around urbanized areas. These areas are faced with increasing surface temperature arising mostly from human activities and other natural sources; hence land surface temperature has become an important variable in global climate change studies. In this paper, Landsat TM/ETM imagery acquired between 1997 and 2013 were used to extract ground brightness temperature and land use/land cover change in Kuala Lumpur metropolis. The main objective of this paper is to examine the effectiveness of quantifying UHI effects, in space and time, using remote sensing data and, also, to find the relationship between UHI and land use change. Four land use types (forest, farmland, built-up area and water) were classified from the Landsat images using maximum likelihood classification technique. The result reveals that Greater KL experienced an increase in average temperature from 312.641°K to 321.112°K which was quite eminent with an average gain in surface temperature of 8.4717°K. During the period of investigation (1997–2013), generally high temperature is been experienced mostly in concentrated built-up areas, the less concentrated have a moderate to intermediate temperature. Again, the study also shows that low and intermediate temperature classes loss more spatial extent from 2,246.89 Km² to 1,164.53 Km² and 6,102.42 Km² to 3,013.63 Km² and a gain of 4,165.963 Km² and 307.098 Km² in moderate and high temperature respectively from 1997 to 2013. The results of this study may assist planners, scientists, engineers, demographers and other social scientists concerned about urban heat island to make decisions that will enhance sustainable environmental practices.     

Universe with Time Dependent Deceleration Parameter and Λ Term in General Relativity

A new class of exact solutions of Einstein's field equations with perfect fluid for an LRS Bianchi type-I spacetime is obtained by using a time dependent deceleration parameter. We have obtained a general solution of the field equations from which three models of the universe are derived: exponential, polynomial and sinusoidal form respectively. The behaviour of these models of the universe are also discussed in the frame of reference of recent supernovae Ia observations.     

iGeoTrans – a novel iOS application for GPS positioning in geosciences

The iGeoTrans is an iOS application designed for navigation purposes for iPhone, iPad and iPod Touch. This application uses Global Positioning System (GPS), Assisted GPS system, GLONASS, Wi-Fi and Cellular Network for positioning. The iGeoTrans has included datum transformations and map projections that enable users to convert the collected data between different coordinate systems for almost all areas in the world. In addition, other features are also included such as distance, area measurements, and GPS results could be exported to the AutoCad dxf format for GIS softwares. The average horizontal and vertical root mean square errors (RMSEs) for the static test are around 4.11 and 3.51?m, respectively. The horizontal RMSE for the dynamic outdoor test is around 2.72?m. The iGeoTrans application can be used to support surveying, mapping and geosciences fieldworks for any area in the world.