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Landslide poses severe threats to the natural landscape of the Lesser Himalayas and the lives and economy of the communities residing in that mountainous topography. This study aims to investigate whether the landscape change has any impact on landslide occurrences in the Kalsi-Chakrata road corridor by detailed investigation through correlation of the landslide susceptibility zones and the landscape change, and finally to demarcate the hotspot villages where influence of landscape on landslide occurrence may be more in future. The rational of this work is to delineate the areas with higher landslide susceptibility using the ensemble model of GIS-based multi-criteria decision making through fuzzy landslide numerical risk factor model along the Kalsi-Chakrata road corridor of Uttarakhand where no previous detailed investigation was carried out applying any contemporary statistical techniques. The approach includes the correlation of the landslide conditioning factors in the study area with the changes in land use and land cover (LULC) over the past decade to understand whether frequent landslides have any link with the physical and hydro-meteorological or, infrastructure, and socioeconomic activities. It was performed through LULC change detection and landslide susceptibility mapping (LSM), and spatial overlay analysis to establish statistical correlation between the said parameters. The LULC change detection was performed using the object-oriented classification of satellite images acquired in 2010 and 2019. The inventory of the past landslides was formed by visual interpretation of high-resolution satellite images supported by an intensive field survey of each landslide area. To assess the landslide susceptibility zones for 2010 and 2019 scenarios, the geo-environmental or conditioning factors such as slope, rainfall, lithology, normalized differential vegetation index (NDVI), proximity to road and land use and land cover (LULC) were considered, and the fuzzy LNRF technique was applied. The results indicated that the LULC in the study area was primarily transformed from forest cover and sparse vegetation to open areas and arable land, which is increased by 6.7% in a decade. The increase in built-up areas and agricultural land by 2.3% indicates increasing human interference that is continuously transforming the natural landscape. The landslide susceptibility map of 2019 shows that about 25% of the total area falls under high and very high susceptibility classes. The result shows that 80% of the high landslide susceptible class is contained by LULC classes of open areas, scrubland, and sparse vegetation, which point out the profound impact of landscape change that aggravate landslide occurrence in that area. The result acclaims that specific LULC classes, such as open areas, barren-rocky lands, are more prone to landslides in this Lesser Himalayan road corridor, and the LULC-LSM correlation can be instrumental for landslide probability assessment concerning the changing landscape. The fuzzy LNRF model applied has 89.6% prediction accuracy at 95% confidence level which is highly satisfactory. The present study of the connection of LULC change with the landslide probability and identification of the most fragile landscape at the village level has been instrumental in delineation of landslide susceptible areas, and such studies may help the decision-makers adopt appropriate mitigation measures in those villages where the landscape changes have mainly resulted in increased landslide occurrences and formulate strategic plans to promote ecologically sustainable development of the mountainous communities in India's Lesser Himalayas.

In this paper, a finite element analysis (FEA) has been used for the design of horn with different Bezier profiles for rotary ultrasonic machine (RUM). First, for validation, the results are compared with available literature. FEA-based MATLAB code is developed for finding the stress components, axial amplitude, and resonance frequency over the domain of horn with different Bezier profiles. In domain of horn with different Bezier profiles, the component of stresses is studied and found that the stress generated is within the endurance strength of the selected material. The amplification of the proposed horns is 24%, and 18% higher than the traditional linear Bezier horn with same length and diameters of surface end. For RUM, effect of inertia (self-weight or gravity of horn) on domain has been studied for horn with different Bezier profiles using FEA. The effect of tool shape and size on the stress distribution for horn have also been studied.

In this study, experiments were conducted to calculate the heat transfer rate and its augmentation with respect to a base fluid for the different parameters in an automobile radiator. The Magnesium Oxide nanoparticles were dispersed in the base fluid of the mixture containing distilled water and ethylene glycol. The fluid flow rate in the radiator was varied using a rotameter and the velocity of the incoming air on the radiator was kept constant. The inlet temperature to the radiator was also varied at different temperatures. From the experiments performed, it was concluded that the heat transfer rate increased proportionally for the nanofluid at different concentrations in comparison to the heat transfer by the base fluid. As the fluid flow rate increases, the heat transfer rate also increases at each concentration of nanofluid. Thus, it was concluded that the fluid flow rate and the addition of nanoparticles at different volume fraction in the base fluid are the main causes for the increase in heat transfer rate.

Under a warming climate scenario, precipitation extremes are projected to increase as indicated by both observations and climate model simulations in the previous studies. In this study, we have considered five regional climate simulations under Coordinated Regional Climate Downscaling Experiment-South Asia domain (CORDEX-SA) to study changes in precipitation extremes over India in the near (2020–2049) and far (2070–2099) future under changing climate scenario with respect to different representative concentration pathways (RCPs)—4.5 and 8.5. Extremes in precipitation are studied and described here using a set of climate indices as defined by the joint CCL/CLIVAR/JCOMM Expert Team (ET) on Climate Change Detection and Indices (ETCCDI). The study reveals that CORDEX-SA simulations under scenarios of increasing greenhouse gas concentration indicate a marked increase in the frequency of wet precipitation extremes over central India in both the near and far future (2070–99) as well as a consistent increase throughout the twenty-first century as indicated by trend values. Simultaneously, dry precipitation extremes show a decreasing trend in most of the simulations. However, the distribution of changes varies widely in its magnitude and sign across the Indian region along with a wide intermodel uncertainty. In the far future and under the intensified scenario RCP8.5, the changes seem to be much more pronounced than those in the near future and less intensified scenario RCP4.5.

In ultrasonic machining (USM), higher amplitude is required for higher material removal rate (MRR). The objective of this research is to develop a new horn design for high displacement amplitude for getting maximum MRR within a working condition. The profile of the horn has been optimized and designed. In this analysis, optimization procedure and finite-element method have been used for the design of horn of USM. In this, the variation of stress components along the length of the horn has been studied. In the middle, maximum stress is found due to a change in cross-section but it is within the endurance limit of the horn material. The cubic Bezier horn as compared with traditional horn is up to 19% more amplified. Finally, an optimized cubic Bezier profile for the horn has been designed, which has maximum displacement amplitude for higher MRR and safe working stresses for the horn material.

Land use/land cover changes (LULCC) are one of the foremost aspects of environmental changes caused by human-induced activities mainly in rapidly developing areas. This study endeavors to evaluate and compare three hybrid models: stochastic Markov chain (ST-MC), cellular automata-Markov chain (CA-MC), and multi-layer perceptron-Markov chain (MLP-MC) to predict future land use/land cover (LULC) scenario in Varanasi district. LULC information extracted for years 1988 and 2001 was first employed to predict LULC scenario for 2015 using three hybrid models. The predicted results were compared with the observed LULC information for the year 2015 to appraise the validity of models through kappa index statistics. The MLP-MC model yielded reliable and best results. Finally, based on this consequence, the prediction of future LULC scenarios for years 2030 and 2050 was performed. The findings of this study exhibited the constant but overall increase of built up area and a considerable reduction in agricultural land. The results also demonstrate the potentiality of MLP-MC hybrid model for better understanding of spatio-temporal dynamics and predicting future landsacpe scenario in Varanasi district of Uttar Pradesh, India.

Digital change detection is the process that helps in shaping the changes associated with land use land cover (LULC) properties with reference to geo-registered multi-temporal remote sensing data. In this study different methods of analyzing satellite images are presented, with the aim to identify changes in land cover in a certain period of time (1980-2016). The methods represented in this study are vegetation indices, image differencing and supervised classification. These methods gave different results in terms of land cover area. Urban expansion has brought serious losses of agriculture land, vegetation and water bodies. The present study demonstrates changes in land trajectories of Varanasi district, India using Landsat MSS (1980), TM (1990 and 2010), ETM+ (2000) and Landsat-8 OLI data (2016). The LULC classes in the study area are divided into eight categories using supervised classification method. Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) are also calculated to estimate the changes in LULC classes during these time periods. Major changes are seen from 2000 to 2016 for the built-up, agriculture land, water bodies and wasteland.

Geoinformatics-based morphological studies play a significant role in planning, designing, and development of river engineering structures. Quantitative morphometric parameters affect catchment streamflow pattern through their influence on concentration time, and geomorphic characteristics of a drainage basins play a vital role in controlling the basin’s hydrology. In the present paper, an effort has been made to assess the inferences of various linear, areal, drainage, and relief aspects of quantitative morphometric characteristics of the Narmada basin and its down (13) and upper watersheds (17) using ASTER DEM data in GIS platform. Total basin area of the Narmada is about 98,796 km2, and it is identified that the study area is an eighth order drainage basin. A total 31,211 stream segments including the Narmada river are identified, and it is clear that the cumulative stream length is higher in first-order streams and decreases as the stream order increases. The bifurcation ratio (Rb) of the Narmada basin is varied from 2 to 9, and it designates that the drainage pattern of the basin has been affected by the structural disturbances. The lowest value of elongation ratio in the basin indicates high relief and steep slope, while highest value specifies relatively plain land with low relief and low slope than other down watersheds. Sinuosity index of Narmada basin is 1.58, which shows that the Narmada river is meandering in nature.

In the present study, 16 selected glaciers including Gangotri and surrounding covering an area of 2982.14 sq km, Garhwal Himalaya (Uttrakhand) India were mapped and their boundaries were delineated using the Landsat MSS (3rd November, 1976), TM (16th October, 1990), ETM+(18th October, 1999 and) and OLI-TIRS (29th Oct., 2013) ) and ASTER images. In this study a total of 101 glacial lakes are identified in 2013 while the number of identified glacial lakes was 69 and 128 in 1990 and 1999. The valley of Gangotri glacier and Satopanth glacier show huge increase in number and area of glacial lakes especially supraglacial lakes. Several morphometric parameters like length, width, total area, perimeter, accumulation area, ablation area, area accumulation ratio (AAR), thickness etc. were estimated for detailed morphometric analysis among the mapped glaciers. The mapping of selected 16 glaciers during the period 1972–2013 reveals that the glacier covered area reduced from 409.08 to 377.83 sq km observing approx. 7.63% deglaciation in the Gangotri and surrounding area. Gangotri glacier shown a net loss of 4.68% area during 1972–2013 while it shows a net gain of 1.32% area during 1999–2013. Advancement in the total glacier area was also recorded during 1979–1999. A higher rate of retreat of the some of the glaciers was observed during 1989–2006 as compared to the retreat during 1972–1989. The average elevation of the ablation zone of Gangotri glacier showed an upward shift from 3944 m (1972) to 4033 m (2013) which may be a consequence of a shift in Equilibrium Line Altitude (ELA) reflecting imbalance. In this study it is estimated that the Gangotri glacier was retreated 1.60 km between 1972–2013. During the period of 1972–2013, it was observed that maximum retreat among selected 16 glacier were mainly Arwa, Raktavaran, Panpatia, Chaturangi, Satopant glaciers (9.47 km, 6.43 km, 3.87 and 3.04 km respectively).

Glaciers influence a variety of natural systems in the environment and act as a key source of freshwater worldwide. Remote sensing satellite data has proved to be important tool for defining the glacier inventory and retreating pattern of a glacial region. An attempt has been made to investigate changes in glacial area of five selected glaciers i.e. Bara shigri, Chota shigri, Hamtah, G4 and Parvati glacier in Himanchal Pradesh from 1976 to 2013 through the LANDSAT data of MSS (1976), TM (1989 and 2009), ETM+ (2001) and OLI-TIRS (2013) whereas ASTER-DEM data was used for relief information. Glacier snout positions were demarcated by identifying glacier features such as the origin of the stream from the terminus, supraglacial lakes, and disposition of end moraines. The uncertainty (U) was calculated for multi-temporal measures of the glacier front position using these images. Amongst the selected five glaciers in which snout could be demarcated accurately for all the datasets, three glaciers experienced very nominal retreat of their terminus; the maximum retreat (6.63 m) was calculated in the case of G4 glacier while Humtah glacier exhibited advancement in 37 years. However, Bara shigri glacier experienced a retreat of 1.50 m. The study shows that the glacial covered area reduced from 154.58 to 123.39 km2 indicating 20.17% deglaciation during the period from 1976 to 2013. The outcome of this study may obligatory to monitor spatio-temporal changes in glaciers and their conservation towards the sustainable management of water resources in Himalayan river watersheds.

Land use and land cover (LULC) changes are recognized as one of the most significant driver of environmental changes, mainly due to rapid urbanization. In this paper, an attempt has been made to appraise the ability of multi-layer perceptron-Markov chain analysis (MLP-MCA) integrated method to monitor and predict the future LULC change scenarios in Patna district, Bihar using remote sensing images. A supervised maximum likelihood classification method was applied to derive LULC maps from 1988, 2001, and 2013 Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+)/Operational Land Imager (OLI) images, respectively. The LULC maps of 1988 and 2001 were employed to predict the LULC scenario for 2013 using MLP-MCA method. The predicted result was compared with the observed LULC map of 2013 to validate the method using kappa index statistics. Finally, based on the results, the future LULC change prediction for 2038 and 2050 was performed. The outcomes of this study reveal the rapid growth in ​built up area results in continuous decrease in agricultural lands.

Updated and accurate information of rice-growing areas is vital for food security and investigating the environmental impact of rice ecosystems. The intent of this work is to explore the feasibility of dual-polarimetric C-band Radar Imaging Satellite-1 (RISAT-1) data in delineating rice crop fields from other land cover features. A two polarization combination of RISAT-1 backscatter, namely ratio (HH/HV) and difference (HH−HV), significantly enhanced the backscatter difference between rice and nonrice categories. With these inputs, a QUEST decision tree (DT) classifier is successfully employed to extract the spatial distribution of rice crop areas. The results showed the optimal polarization combination to be HH along with HH/HV and HH−HV for rice crop mapping with an accuracy of 88.57%. Results were further compared with a Landsat-8 operational land imager (OLI) optical sensor-derived rice crop map. Spatial agreement of almost 90% was achieved between outputs produced from Landsat-8 OLI and RISAT-1 data. The simplicity of the approach used in this work may serve as an effective tool for rice crop mapping.