The Himalayan cryosphere: A critical assessment and evaluation of glacial melt fraction in the Bhagirathi basin

The cryosphere constitutes an important subset of the hydrosphere.The Himalayan cryosphere is a significant contributor to the hydrological budget of a large river system such as the Ganges.Basic data on the cryosphere in the Himalaya is inadequate and also has large uncertainties.The data on glacial melt component in the Himalayan rivers of India also shows high variability.The Gangotri glacier which constitutes nearly a fifth of the glacierized area of the Bhagirathi basin represents one of the fastest receding,large valley glaciers in the region which has been surveyed and monitored for over sixty years.The availability of measurement over a long period and relatively small glacier-fed basin for the Bhagirathi river provides suitable constraints for the measurement of the glacial melt fraction in a Himalayan river.Pre- and post-monsoon samples reveal a decreasing trend Of depletion of δ~(18)O in the river water from glacier snout(Gaumukh) to the confluence of the Bhagirathi river with the Alaknanda river near Devprayag.Calculations of existing glacial melt fraction(~ 30%at Rishikesh) are not consistent with the reported glacial thinning rates.It is contended that the choice of unsuitable end-members in the three component mixing model causes the overestimation of glacial melt component in the river discharge.Careful selection of end members provides results(~11%at Devprayag) that are consistent with the expected thinning rates.     

An expert system based on hybrid ICA-ANN technique to estimate macerals contents of Indian coals

Coal, as an initial source of energy, requires a detailed investigation in terms of ultimate analysis, proximate analysis, and its biological constituents (macerals). The rank and calorific value of each type of coal are managed by the mentioned properties. In contrast to ultimate and proximate analyses, determining the macerals in coal requires sophisticated microscopic instrumentation and expertise. This study emphasizes the estimation of the concentration of macerals of Indian coals based on a hybrid imperialism competitive algorithm (ICA)–artificial neural network (ANN). Here, ICA is utilized to adjust the weight and bias of ANNs for enhancing their performance capacity. For comparison purposes, a pre-developed ANN model is also proposed. Checking the performance prediction of the developed models is performed through several performance indices, i.e., coefficient of determination (R ²), root mean square error and variance account for. The obtained results revealed higher accuracy of the proposed hybrid ICA-ANN model in estimating macerals contents of Indian coals compared to the pre-developed ANN technique. Results of the developed ANN model based on R ² values of training datasets were obtained as 0.961, 0.955, and 0.961 for predicting vitrinite, liptinite, and inertinite, respectively, whereas these values were achieved as 0.948, 0.947, and 0.957, respectively, for testing datasets. Similarly, R ² values of 0.988, 0.983, and 0.991 for training datasets and 0.989, 0.982, and 0.985 for testing datasets were obtained from developed ICA-ANN model.     

Long‐term variability of proglacial groundwater‐fed hydrological systems in an area of glacier retreat,Skeiðarársandur,Iceland

Proglacial groundwater‐fed features, such as seeps, substantially impact proglacial geomorphology, hydrology, and ecology. However, there is a paucity of research on the impacts of climate change and glacier retreat on the extent of these important features. This paper aims to investigate the impact of glacier retreat on proglacial groundwater levels and on the extent of groundwater‐fed seeps. Research has taken place in western Skeiðarársandur, the large proglacial outwash plain of Skeiðarárjökull, a retreating temperate glacier in southeast Iceland. Changes in the extent of proglacial groundwater seeps were mapped using historical aerial photographs from 1986, 1997, and 2012. Proglacial groundwater levels were monitored in shallow boreholes between 2000 and 2012. The western margin of Skeiðarárjökull has retreated approximately 1 km beyond its position in 1986. However, this retreat was punctuated by short periods of readvance. The geomorphology and groundwater systems at the site were substantially impacted by the November 1996 jökulhlaup, whose deposits altered approximately 18% of the area of groundwater seeps. The surface areas of groundwater seeps and lakes in the study area have declined by ~97% between 1986 and 2012. Most of the decline took place after 1997, when the mean annual rate of retreat increased three‐fold. Groundwater levels also declined substantially between 2000 and 2012, although this trend varies spatially. The paper provides a conceptual model of the controls on proglacial shallow groundwater systems. Direct impacts of glacier retreat are suggested as the main cause for the declines in proglacial groundwater levels and in the extent of groundwater seeps. These declines are expected to adversely impact sandur ecology. Copyright © 2014 John Wiley & Sons, Ltd.     

Geophysical surveys to investigate the relation between the Quaternary Nile channels and the Messinian Nile canyon at East Nile Delta, Egypt

This paper compares the pattern of historical Eastern Nile Delta branches, delineated by geoelectric resistivity investigation, with the path of the Nile canyon of Messinian time revealed in seismic reflection. A close correlation is evident between the Late Quaternary Nile River channels and the Messinian canyons (wadies) in the eastern Nile Delta. This indicates that the Messinian canyons were a persistent topographic (or geomorphic) feature until historical branches. The results may also have implications for long-term patterns of subsidence in the delta area.     

The role of visual saliency in the automation of seismic interpretation

In this paper, we propose a workflow based on SalSi for the detection and delineation of geological structures such as salt domes. SalSi is a seismic attribute designed based on the modelling of human visual system that detects the salient features and captures the spatial correlation within seismic volumes for delineating seismic structures. Using this attribute we cannot only highlight the neighbouring regions of salt domes to assist a seismic interpreter but also delineate such structures using a region growing method and post‐processing. The proposed delineation workflow detects the salt‐dome boundary with very good precision and accuracy. Experimental results show the effectiveness of the proposed workflow on a real seismic dataset acquired from the North Sea, F3 block. For the subjective evaluation of the results of different salt‐dome delineation algorithms, we have used a reference salt‐dome boundary interpreted by a geophysicist. For the objective evaluation of results, we have used five different metrics based on pixels, shape, and curvedness to establish the effectiveness of the proposed workflow. The proposed workflow is not only fast but also yields better results as compared with other salt‐dome delineation algorithms and shows a promising potential in seismic interpretation.     

Application of artificial neural networks in optimal tuning of tuned mass dampers implemented in high-rise buildings subjected to wind load

High-rise buildings are usually considered as flexible structures with low inherent damping. Therefore, these kinds of buildings are susceptible to wind-induced vibration. Tuned Mass Damper (TMD) can be used as an effective device to mitigate excessive vibrations. In this study, Artificial Neural Networks is used to find optimal mechanical properties of TMD for high-rise buildings subjected to wind load. The patterns obtained from structural analysis of different multi degree of freedom (MDF) systems are used for training neural networks. In order to obtain these patterns, structural models of some systems with 10 to 80 degrees-of-freedoms are built in MATLAB/SIMULINK program. Finally, the optimal properties of TMD are determined based on the objective of maximum displacement response reduction. The Auto-Regressive model is used to simulate the wind load. In this way, the uncertainties related to wind loading can be taken into account in neural network’s outputs. After training the neural network, it becomes possible to set the frequency and TMD mass ratio as inputs and get the optimal TMD frequency and damping ratio as outputs. As a case study, a benchmark 76-story office building is considered and the presented procedure is used to obtain optimal characteristics of the TMD for the building.     

Mapping dune dynamics by InSAR coherence

It is generally held that subtle changes in sandy environments are very difficult to detect in imagery. Nonetheless, this study demonstrates how synthetic aperture radar (SAR) interferometric decorrelation can be used to identify changes in individual sand dunes. The use of coherence maps over time facilitates the analysis of dune dynamics, both temporally and spatially. The Ashdod‐Nizzanim coastal dunes, along the southern coastal plain of Israel, were chosen as an illustrative example of the analysis of dune dynamics. High‐resolution TerraSAR‐X (TSX) radar images covering the entire research area were acquired for the period February to July 2012, together with meteorology data (wind and rain) for the area. The coherence results enabled the stability of individual dunes to be described as a function of time. It was found that the dune crests were more stable than the windward slopes and that the degree of stability was dependent on the distance of the dune from the sea. The results of this study show the potential of using interferometric synthetic aperture radar (InSAR) decorrelation for aeolian studies, even in areas characterized by low coherence. Copyright © 2017 John Wiley & Sons, Ltd.     

Smoothed response spectra including soil-structure interaction effects

Elastic response spectra that take into account the effects of soil-structure interaction on soft soils are developed. The response spectra are calculated utilizing a 3 DOF system including deformations of the superstructure and foundation. The equations of motion of the system are solved using direct integration under normalized earthquake records. Statistical processing of the results is implemented resulting in response spectra for "short and dense buildings with low interaction", "short and dense buildings with high interaction", "tall and light buildings with low interaction" and "tall and light buildings with high interaction". The resulting response spectra are smoothed and discussed.     

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.