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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.

Land use / land cover (LULC) has been considered as one of the important bio-physical parameters and have significant affect on local environmental change, particularly increasing anthropogenic temperature. Remote sensing images from Landsat series satellites are a major information source for LULC change analysis. In the present investigation, long term changes in LULC and its negative impact on land surface temperature (LST) were analyzed using multi-temporal Landsat satellite images between 2000 to 2016. firstly LULC of the study area has been classified and temporal changes in land use classes were quantify, and observed that in most of the land use classes such as vegetation (-1.28 %), water bodies (-1.65 %), agriculture (-3.52) and open land (-2.43 %) have shown negative change, however large scale positive changes in built-up area (+8.87 %) has been observed during the analysis, which is mainly due to continuous urbanization and growth of population in the area. The classified thermal images from the same period also show mean temperature of the area has increased by 1.60 °C since last 16 years. The observation from the present study reveals that due to the large-scale land use change practices in urban and peri-urban area witnessed for the rising temperature due to loss natural vegetation and other natural resources.

The immense dependence of the growing population on groundwater has resulted in depletion at a fast pace can be seen nowadays. Identifying a groundwater potential zone can be proved as an aid to provide insight to the decision-makers and local authorities for planning purposes. This study evaluated the delineation of groundwater potential zones using integrated remote sensing and GIS approach. Various thematic layers such as geology, geomorphology, lineament, slope, drainage, soil, land use/land cover, and rainfall were considered in this study as these have influence on the occurrence of groundwater and its cycle, and maps have been prepared in GIS domain. Afterward, appropriate weights were assigned to these layers based on multi-criteria decision analysis, i.e., Analytical Hierarchy Process (AHP). Groundwater potentiality has been delineated in different zones (low, moderate, high, and very high) in the study region based on weighted overlay analysis. The study reveals zones with different groundwater prospects viz. low (1.27%), moderate (15.65%), high (75.54%), and very high (7.29%). The ground survey data provided by CGWB (Central Ground Water Board) of nearly 100 wells/dug wells/borewells/piezometers have been used for validation purposes, showing comparable results with the groundwater prospects zones. It also confirms that the majority of these wells fall under very high or high groundwater potential zones. They were also found to be thereby indicating that there is the existence of a permeable reservoir with considerable water storage in the subsurface. One of the most important issues for users and governments is groundwater depletion. Planning for the available groundwater resource is made easier by identifying the potential for groundwater (low to high).

Waterlogging and raised soil salinity are leading to land degradation and desertification problems worldwide. It can significantly reduce the agricultural practices and crop yields of affected lands. The present study is attempted to map waterlogged and saline affected areas using LISS-III satellite imagery of pre-monsoon and post-monsoon season of the year 2012. It was observed that the total size of seasonal waterlogged (only Rabi or only Kharif) is 454.96 ha (2.37%) of the total area. The land covered with perennial waterlogged area was found to be 535.54 ha (2.79 %) of the entire command area. The waterlogged area concerning the depth of groundwater was further categorized into most critical, critical, less critical and non-critical. The identification and mapping of salt affected (saline) area was performed during Rabi and Kharif season. Only 0.46% of the command area identified as saline land either in both or single season patches, remaining 99.54% area comes under non saline category. Out of total command area 80.58 and 19.42% areas comes under non-saline and saline zones respectively. The saline area was further classified into medium, high and very high zones. The saline affected area covered with medium, high and very high salt categories is 2.25 ha (0.012%), 26.380 ha (0.137%), and 0.624 ha (0.003%), respectively. In-situ measurements such as pH, electrical conductivity (EC) and exchangeable sodium percentage (ESP) were also used to validate the results. The methodology proposed in this study can potentially be used for cost-effective mapping of soil salinity in other geographical regions.

Assessing the performance of land change simulation models is a critical step when predicting the future landscape scenario. The study was conducted in the district of Varanasi, Uttar Pradesh, India because the city being “the oldest living city in the world” attracts a vast population to reside here for short and long-term, leaving the city’s ecosystem more exposed to fragility and less resilient. In this work, an approach based on landscape metrics is introduced for comparing the performance of the ensemble models designed to simulate the landscape changes. A set of landscape metrics were applied in this study that offered comprehensive information on the performance of scenario-based simulation models from the viewpoint of the spatial ordering of simulated results against the related reference maps. A supervised support vector machine classification technique was applied to derive the LULC maps using Landsat satellite images of the year 1988, 2001, and 2015. The LULC maps of 1988 and 2001 were used to simulate the LULC scenario for 2015 using three Markov chain-based simulation models namely, multi-layer perceptron-Markov chain (MLP_Markov), cellular automata-Markov chain (CA_Markov), and stochastic-Markov chain (ST_Markov) respectively. The mean relative error (MRE), as a measure of the success of simulation models, was calculated for metrics. The MRE values at both the class and landscape levels were accounted for 21.63 and 11.45% respectively using MLP_Markov simulation model. The MRE values at both the class and landscape levels were accounted for 39.61 and 28.31% respectively using CA_Markov simulation model. The MRE values at both the class and landscape levels were accounted for 55.36 and 45.75% respectively using ST_Markov simulation model. The MRE values considered at class and landscape levels are further evaluated qualitatively for comparing the performance of simulation models. The results indicate that the MLP_Markov performed excellently, followed by CA_Markov and ST_Markov simulation models. This work showed an ordered and multi-level spatial evaluation of the models’ performance into the decision-making process of selecting the optimum approach among them. Landscape metrics as a vital characteristic of the utilized method, employ the maximum potential of the reference and simulated layers for a performance evaluation process. It extends the insight into the main strengths and drawbacks of a specific model when simulating the spatio-temporal pattern. The quantified information of transition among landscape categories also provides land policy managers a better perception to build a sustainable city master plan.

The ability of Regional Climate Model (RCM: RegCM4) forced with two different Global Climate Model (GCM: CCSM4 and MIROC5) and three land-surface parameterization (LSP) (i.e., BATS, CLM4.5 and Subgrid-BATS) in simulating the Indian summer monsoon (ISM) is tested for the present climate (1975–2005). Thus six simulation combinations are assessed for seasonal mean temperature, precipitation, and low-level wind for ISM season (June, July, August, September: JJAS) over the COordinated Regional climate Downscaling EXperiment-South Asia (CORDEX-SA) domain. The simulations are evaluated in terms of Taylor’s metric (for precipitation, temperature, zonal wind, meridional wind and total cloud fraction), mean annual cycle, index of agreement, normalized root mean squared deviation and probability distribution function. The experiments simulated moderate events more accurately than high-intensity precipitation events compared to the corresponding observations. The inherent biases in the model simulations are attributed to the weaker meridional wind along with restrained vertical motion during ISM, especially with CCSM4 forcing. A careful analysis of tropospheric temperature gradient (TTG) suggests a weaker north–south (N–S) gradient due to the warmer atmospheric column in these experiments. On the contrary, the MIROC5_CLM4.5 experiment captures the magnitude and the temporal evolution of TTG better during ISM. It also represents the mean features of ISM better than other experiments. Also, the CLM4.5 LSP shows promising performance in ISM simulation when forced with MIROC5. It also provides further avenues for testing of the same combination under different frameworks, including the intended future climate study. This study emphasizes the importance of using appropriate GCM and LSP forcings to the RCM for simulating a coupled complex systems such as ISM.

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.

Present study attempts to project extreme precipitation indices over 34 different meteorological subdivisions and six homogeneous regions such as Northwest, Central Northeast, Northeast, West Central, Peninsular India and Hilly Region during summer monsoon season in the twenty-first century. For this purpose, the Regional Climate Model version4 (RegCM4) had been run at 50 km horizontal resolution forced with the global model GFDL-ESM2 M, during reference period 1976–2005 for the model validation, and the mid- (2031–2060) and far-future (2070–2099) for projections under RCP8.5 scenario over the South Asia CORDEX domain. In this paper, model simulated precipitation has been validated against IMD, APHRODITE and NCEP/NCAR data sets. The results indicate that RegCM4 captures the important features of seasonal precipitation and various extreme indices over the study area. The RegCM4 has projected an increase in the mean seasonal precipitation by 0.56 mm/day whereas in case of GFDL model the rate is 0.39 mm/day during the far-future relative to the reference period. The heavy precipitation indices are projected to increase more frequently (0.264/decade) than the mean precipitation rate (0.01/decade) over India. The correlations between the extreme precipitation indices and the seasonal mean precipitation are found to be strong. In addition, the consecutive dry days are projected to occur more frequently (3–5 days) over West Central (Telangana, Vidarbha and Marathwada) and west Rajasthan while consecutive wet days are projected to decrease over larger parts of India during far-future. Similarly, 1 day maximum precipitation and the simple daily intensity index are projected to increase consistently from mid- to far- futures over some sub-divisions of West coast, Hilly and Northeast regions. From a spatial probability perspective, model projection indicates more frequent severe drought and flood conditions over India.

An assessment of Varuna river basin of India was performed to study the various drainage parameters in GIS platform. The delineation of drainage network is possible either physically from topographic sheets or with the help data of Digital Elevation Model (DEM) by methods for calculation techniques. Extraction of the basin and sub-basins, stream network has been produced to evaluate the drainage characteristics in the study zone. The entire Varuna river basin has been subdivided into 3 sub-watersheds and 41 morphometric parameters have been computed under four broad categories i.e. drainage network, basin geometry, drainage texture, and relief characteristics. The morphometric analysis has been performed and different parameters have been correlated with each other to understand their underlying connection and their role over the basin hydro geomorphology. The study discloses different types of morphometric analysis and how they influence the soil and topography of the basin. The investigation and estimation of basin morphometry and relief parameters in GIS will be of massive utility in catchment area advancement, understanding the watershed for natural resource evaluation, planning and administration at any scale. The outcomes thus generated equip us with significant knowledge and may also provide an input that are essential in decision making for watershed planning and drainage development of the watershed.

The detailed study of glacier surges in St. Elias Mountains is very scarce.Robust and repeat observation of surface displacement, elevation changes and surge reoccurrence intervalsare limited to few surge-type glaciers (e.g., Variegated, Bearing, Lowell and Donjek). Therefore, this study presents the first detailed surge dynamics of Klutlan (1990-2019) and Fisher (1984-2019) glaciers in the St. Elias Mountains, North America. Surface displacement estimation using optical imagery (Landsat TM, ETM+, OLI and Sentinel 2) and surface elevation changes derived from ASTER DEMs were used to understand the surge dynamics. Klutlan Glacier lackspre-surge acceleration and had six years longactive phase (2013-2019). The surge of Klutlan Glacier showed two surface flow maxima(6.2 ± 0.2 m d-1and ~5 ± 0.2 m d-1),in summer of 2016 and2018 respectively.During 2019-2020, in the reservoir zone, maximum surface lowering of -65± 33m was observed whereas, in the receiving zone, maximum ice thickness increased by +31 ± 40 m. The dynamic balance line (DBL)on Klutlan Glaciermoved ~16 km down-glacier during 2019 (788masl.) in comparison with 2004 (1998 masl.). The Fisher Glacier exhibitssix years (2007-2013) long pre-surge acceleration, three years (2013-2016) long active phase and surge terminated gradually. The peak surge displacement ~7 ± 0.4 m d-1was observed in summer of 2015. The reservoir zone experienced a maximum lowering of -60 ± 22 mfrom 2019 to 2003 while lower receiving zone maximum thickened by +80± 22 m. The DBL shifted ~3 km down-glacier during 2019 (959 masl.) as compared to 2016 (1006 masl.). This study assumes that the surge of Fisher Glacier is partially matched with a thermally controlled surge. However, the surge characteristics of Klutlan Glacier doesnot corroborate with globally recognised hydrological or thermally controlled surge mechanism.

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.

The major rainfall period over the southern peninsular part of the Indian Subcontinent generally occurs during the months of October-December (OND) through the northeast (NE) monsoon (also called winter monsoon or post-monsoon season). The present study focuses on the ability of regional climate model RegCM4 forced with MIROC5 Global Climate Model and three different land-surface parameterization schemes: Biosphere-Atmosphere Transfer Scheme (BATS, herewith referred as CONTROL), Community Land Model (CLM4.5), and Sub-grid BATS in capturing the mean features of NE monsoon for the present climate (1975-2005) over India region. Based on their ability to simulate the inter-annual and intra-seasonal variability, and seasonal mean during monsoon, the current GCM is selected for downscaling from the available literature. The model performance is evaluated against the gridded temperature and precipitation datasets from the Climate Research Unit (CRU) and India Meteorological Department (IMD) respectively. We have found that the MIROC5_CLM4.5 is simulating the precipitation and surface temperature better than other experiments with relatively less bias over the study. MIROC5_CLM4.5 experiment again performs well in capturing the precipitation and surface temperature during wet and dry years’ composite. Overall, our results show a better representation of NE Monsoon mean features by MIROC5_CLM4.5 compared to other sets. The RegCM4-CLM4.5 coupled simulation has shown promising performance in representing NE monsoon. Further, it is envisaged to test and customize this framework in order to generate reliable future projections in subsequent studies.Keywords: RegCM4, CLM4.5, NE Monsoon, Downscaling.

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.

In the present study, a quantitative morphotectonic analysis of Sheer Khadd River basin has been carried out based on geomorphic and morphometric indices such as hypsometric integral, drainage basin asymmetry, mountain front sinuosity, basin elongation ratio, valley floor width to valley height ratio, river sinuosity and stream length gradient index using ASTER digital elevation model (DEM) and Google Earth images to understand the morphotectonics of the basin. The results indicate that Sheer Khadd River basin is tilting towards east and is elongated in shape due to active faulting and folding activity in the terrain. A moderate hypsometric integral value indicates that the basin is still under mature stage of erosion and reflecting a complexity in topography. Fluctuations in stream length gradient index over fault zones indicate irregularities in the drainage course due to the presence of fluvial knick points. The results of morphotectonic and morphometric analysis using DEM data is useful tool for morphotectonic evaluation of any complex terrain.

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.

River is important for every human being as well as flora and fauna. Over the last century, riverine ecosystems have suffered from intense human intervention resulting in habitat loss and degradation and as a consequence, many biotic species have become highly endangered, particular in rivers where heavy demand is placed on freshwaters. This study was aimed to estimate the pollution status and their variation across the stretch of river Gomti flowing through the city of Jaunpur. The sampling is concerned from upstream to downstream regions of the river through the city. Four sampling sites namely, Gokul Ghat (upstream), Gular Ghat, Shastri Bridge and Gomti Barrage (downstream) were selected for sampling. The water samples were collected and analyzed for a period of one year during March 2016 to February 2017. For the study total 6 parameters such as Temperature, pH, Dissolved Oxygen (DO), Biological Oxygen Demand (BOD), Nitrate (NO3-) and Phosphate (PO43-) were detected with reference to the monsoonal variation (summer, monsoon and winter). The results indicate that Gomti River water was in polluted condition due to the city drainage systems, unplanned municipal wastes and industrial waste. Religious idol immersions are also found on the bank and in river water. On the other hand river was polluted mainly by local waste like daily garbage, faecal flow and plastic bags. It indicates that the unplanned urbanization is responsible for the deterioration of river water. To keep the river clean for the future, it is strongly recommended that urban effluents should not be over-looked before their discharge into the river and it is very necessary to assess the river water quality and subsequently, prepare the mitigation measures to reduced pollution level in Gomti River