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Present study focuses on the utilization of Earth observation satellite-04 (EOS-04) synthetic aperture radar (SAR) data for maintaining the continuity of the first Indian radar imaging satellite (RISAT)-1 SAR derived products along with exploring the potential of capability of the improved sensor over mountain and polar cryospheric region. Backscattering coefficient (σ0) of various snow and ice features over mountain and polar cryosphere have been analysed to understand the interaction mechanism using C-band SAR data. EOS-04 is able to pick up the spatio-temporal variability of SAR backscatters over accumulation and ablation zone of the glacier due to melt-freeze cycles, and observations were in accordance with variation in elevations over the glacier surface. When analysed for Drang-Drung glacier, wet snow zone was found to be prominently centered around 5500 m elevation zone, having sigmanaught backscatter lower than –10 dB in the ablation months, whereas percolation zone was observed at more than 6000 m elevation with higher sigma-naught backscatter of around –4 dB and above as winter started setting in. EOS-04 also showed the potential to classify various polar ice features based on backscattering signature using HH (H, horizontal) (σ0), HV (V, vertical) (σ0) and normalized difference polarization ratio index (NDPRI) respectively. EOS-04 data have been used to implement approaches to retrieve wet snow cover and set up of Weather Research and Forecasting Model Hydrological Modelling System (WRF hydro) model for snow melt runoff studies, interaction mechanism of snow and ice, snow/ice facies extraction, ice shelf monitoring, sea ice properties and sea ice advisory for Indian scientific expedition to Antarctica. Enrichment of EOS-04 data, suitable for cryosphere studies, will be employed to retrieve parameters such as snowpack properties, elevation, ice surface velocities over mountain and polar region, and to further improve comprehensive understanding on regional and global frozen ice dynamics. [ABSTRACT FROM AUTHOR]

Synthetic aperture radars (SARs) have enabled allweather sensing of land surfaces, which has significantly benefitted surface hydrology. In this article, we explore various hydrological applications enabled by Indian Space Research Organisation’s (ISRO’s) recently launched Earth observation satellite-04 (EOS-04) C-band SAR satellite. We present the preliminary results of EOS-04 driven flood inundation mapping, monitoring of water bodies and study of river dynamics. Novel application of EOS-04 SAR data in estimation of sedimentation rate is presented for Jayakwadi reservoir, Maharashtra, India. Additionally, this article explores the integrated use of SAR and altimeter data for estimation of lake and reservoir water level and volume. We have used multidate observations from EOS-04 SAR and Sentinel-3A/ 3B altimeters to derive river width and estimate area– water level hypsometric curves for reservoirs. Long-term and near real-time availability of EOS-04 data can provide an indispensable tool for monitoring water bodies and extreme events like floods, at regional scales. [ABSTRACT FROM AUTHOR]

The glacier database provides an opportunity to track its dynamics and address issues linked with water resources, hazards and sustainability. To better understand the dynamics of Eastern Dhauliganga basin, we mapped the clean and debris‐covered glaciers by using satellite images from Landsat‐series and Sentinel 2. The band‐ratio based methods—NDSI (Normalised Difference Snow Index) and NDVI (Normalised Difference Vegetation Index) were used to map the clean ice glaciers. The debris‐covered glaciers were delineated using topographic parameters and thermal band of Landsat TM. The glacier extent and length change were monitored for 25 glaciers in the basin, of which 13 are clean ice and 12 are debris‐covered glaciers. During the time period from 1994 to 2018, higher area loss was observed for clean ice glaciers (±20.6%) compared with debris‐covered glaciers (±10.9%). The clean‐ice glaciers retreated at a rate of 4.8–33.7 m/year, whereas debris‐covered glaciers retreated at a rate of 2.9–28.8 m/year during 1994–2018. [ABSTRACT FROM AUTHOR]

• Multi-wavelength signatures of volatiles have been detected in lunar south pole. • Low axial tilt allows permanently shaded cold traps like Shackleton Crater. • Shackleton Crater exhibits above average albedo vis-a-vis lunar south pole. • Certain regions in the lunar south pole exhibit albedo even higher than Shackleton. Shackleton Crater on the Moon is named in honor of a pivotal figure of the Heroic Age of Antarctic Exploration Sir Ernest Henry Shackleton. The Crater was formed about 3.6 billion years ago at the Lunar South Pole. Due to the low (1.5°) tilt of the lunar axis of rotation, the interiors of the crater receive almost no direct sunlight and observations by passive hyperspectral sensors are only possible due to reflected light. Active sensors are however able to illuminate the interior surface of the crater and make observations. Here we present the results of study of the crater using data from multiple sensors onboard two missions of Indian Space Research Organization (ISRO) and National Aeronautics and Space Administration (NASA). Hyperspectral observations from Moon Mineralogy Mapper (M3) on-board Chandrayaan-1, temperature from Diviner Lunar Radiometer Experiment (DLRE), albedo from Lunar Orbiter Laser Altimeter (LOLA) and Off/On band ratios from Lyman-Alpha Mapping Project (LAMP) on board Lunar Reconnaissance Orbiter (LRO) have been used. Permanently Shaded Regions (PSRs) are identified and Shackleton has been found, as reported, to be a PSR. Emphasis has been laid on LOLA albedo analysis of lunar south pole (80°-90° South). It is observed that the Shackleton Crater exhibits significantly higher albedo compared to its surrounding regions. Some regions exhibit albedo even higher than the Shackleton Crater in the lunar south pole region. The findings of high albedo, coupled with high Off/On band ratio of LAMP, extremely low DLRE temperatures in the permanently shaded regions and detection of hydration features in the M3 hyperspectral data suggests higher probability of hydration in the Shackleton Crater. [ABSTRACT FROM AUTHOR]

Recent studies have brought attention to the enormous megafloods and the considerable amount of water found on and beneath the surface of Mars. These ancient megafloods have not only carved out Martian surface, but also altered its climate. In the present study, ancient flooding of four Martian water channels (Mangala, Kasei, Ravi and Ma'adim) has been examined. The MCC dataset of MOM and MOLA-HRSC DEM were utilized to identify and estimate the hydraulic parameters of the channels. The estimated parameters were used in empirical equations to determine the flood velocity and discharge of Mangala (9.7 × 106 to 1 × 108 m³/sec), Ravi (6.5 × 107 to 9.6 × 108 m³/sec) and Ma'adim Valles (1.0 × 108 to 1.5 × 109 m³/sec). Estimated discharge magnitudes were in line with previous studies, except for Kasei Valles (2.6 × 108 to 5.3 × 109 m³/sec), where overestimation was observed. The two-dimensional simulations of full-bank floods were performed using the hydrodynamic model to generate scenarios of palaeomegafloods in the four valleys. [ABSTRACT FROM AUTHOR]

The needle‐based biopsy procedure is common in cancer detection and patient‐specific targeted therapy, wherein a tissue sample from the potential diseased site is acquired and frozen instantly with the help of a coolant medium. While liquid nitrogen (LN2) is the most widely used coolant for preserving the acquired sample and performing biopsy tests on the same at a later time, cold ischemia leads to inevitable cell degradation beyond a threshold time. In an effort to circumvent this challenge, here we aim to put forward the concept of an integrated biopsy sample acquisition and cryotherapy procedure, by incorporating an exclusively designed cooling circuit in a conventional biopsy‐needle for freezing the sample in vivo as soon as it is acquired, while causing cryoablation in the surrounding tissues simultaneously. An enthalpy‐based approach is employed to develop a bioheat transfer model for the cryotherapy design, with illustrative simulation data presented for breast cancer. Our model is demonstrated by considering a constant LN2 cooling temperature of 77.15 K, and cooling powers ranging from 2 to 10 W. The model results elucidate procedure‐specific insights such as the thermal penetration depth and the cooling time on being subjected to the cryoablation. The cooling rates thus obtained are further assessed from the simultaneous considerations of cryopreservation and cryosurgery, deriving critical insights on tissue survival and damage for acting as a precursor to patient‐specific treatment planning. [ABSTRACT FROM AUTHOR]

The present study has analyzed dynamics of Gangotri glacier using multiple remote sensing (RS) datasets and ground based observations. Interferometric Synthetic Aperture Radar (InSAR) data pairs from European Remote Sensing satellite (ERS 1/2) tandem pair for spring of 1996, Sentinel-1 SAR pairs and Japanese's Advance Land Observation System (ALOS) PALSAR-2 SAR data for Spring of 2015 were used to derive glacier-surface velocity at seasonal time scale using Differential InSAR (DInSAR) techniques. Bi-static TanDEM-X (Experimental) data was used for the 1st time to estimate glacier surface elevation changes for a period of 22, 44, 88 days during summer of 2012 using InSAR techniques in this study. Annual glacier velocity was also estimated using temporal panchromatic data of LANDSAT-5 (30 m), LANDSAT-7/8 (15 m), Sentinel-2 (10 m) and Indian Remote Sensing Satellite IRS-1C/1D panchromatic (5 m) data during 1998–2019 with feature tracking approach. This study has estimated glacier surface velocity and surface elevation changes for the major parts of Gangotri glacier and its tributary glaciers using medium to high resolution optical and SAR datasets, at annual and seasonal time scale, which is an improvement over earlier studies, wherein snout based glacier recession or only main glacier velocities were reported. The velocity and slope were used to assess glacier-ice thickness distribution using Glabtop-2, slope dependent and laminar flow based methods over the Gangotri group of glaciers. The estimated ice thickness was estimated in the range of 58–550 m for the complete glacier while few small areas in middle & upper regions carry higher thickness of about 607 m. The estimated glacier-ice thickness was found in the range of 58–67 m at the snout region. The estimation was validated using 2014 field measurements from Terrestrial Laser Scanner (TLS) for the first time and correlation was found to be 0.799 at snout of the glacier. [ABSTRACT FROM AUTHOR]

• Glacier radar zones identification and mapping of glacier facies using multi-temporal SAR images and polarimetric decompositions. • Interferometric glacial velocity using ERS 1/2 tandem pairs. • Long term and seasonal glacial flow using optical feature tracking. • Quantifying spatial–temporal ice velocity changes. Himalayan glaciers have shown more sensitivity and visible changes to the climate change and global warming in the last 150 years. The highly rugged topography and inaccessible remote areas makes satellite images as the most appropriate source of information retrieval. We performed remote sensing based glacier change study for Samudra Tapu glacier, located in the Chandra basin of North-West Himalaya. In the present study, the capabilities of both optical and microwave remote sensing data was analysed in glacier change study in terms of its coverage, shift in equilibrium line altitude (ELA) and surface velocity over a period from 2000 to 2021. Multi Sensor (RISAT-1, Sentinel-1) time series of C-band SAR data along with a object oriented classification technique were used to identify different glacier facies such as percolation facies, icefalls, bare ice facies, refreeze snow and supraglacial debris. These classified maps were also used to detect the snow line and firn line along with ELA, aided with elevation information from digital elevation model (DEM). It was identified that more than 50 % of the total glacier area still lies into accumulation region. Further, we estimated the glacier surface velocity using Differential Interferometric Synthetic Aperture Radar (DInSAR) technique using European Remote Sensing Satellite (ERS-1/2) tandem data of 1996. High value of coherence was observed from the SAR return signal for one-day temporal difference. A mean velocity of 17–24 cm/day was found for the months of March and May 1996, highest flow rates were seen in the high accumulation area located in the Eastern and Southern Aspect of glacier. Spatial analysis of velocity patterns with respect to slope and aspect show that high rates of flow was found in southern slopes and movement rates generally increase with increase in slope. Feature tracking approach was used to estimate the glacier flow for long term and seasonal basis using optical and SAR datasets (IRS-1C, 1D PAN, Landsat-7, 8 PAN, and TANDEM-x) during 1999–2020 period. The results suggest that glacier flow varies with season, i.e., high velocity during spring-summer season, as compared to late summer or winter and, the rate of ice flow changes over the years. The mean glacier velocity reduced to 49.5 m/year during 2013–2020 time, as compared to 67.67 m/year during 1999–2003 time. These results of reducing glacier velocity and changing snow line altitude indicates enhanced glacier's melt rate and overall negative mass balance for Smudra tapu glacier. [ABSTRACT FROM AUTHOR]

Hearing loss has long been associated with congenital hypothyroidism and, if not noticed and treated early, may result in delayed language acquisition and difficulties in comprehension. In light of the implications of congenital hypothyroidism and its associated hearing loss, we decided to conduct this study. The aim of this study was to identify the prevalence of hearing loss in congenital hypothyroidism and its relation to the severity of the disease and age of initiation of treatment. This study was conducted from July 2016 to June 2021 at a tertiary care hospital in Bhopal. The hearing status of congenital hypothyroid children and matched controls was assessed by pure tone audiometry or free field audiometry and, in selected cases, with brainstem evoked response audiometry. Eight children (25%) with congenital hypothyroidism had hearing loss, compared to one (3.12%) in the control group (p < 0.05). No statistically significant difference has been found in the gender, mean age of diagnosis, mean age of initiation of levothyroxine treatment, mean screening FT4 levels, and mean screening TSH levels between congenital hypothyroid children with and without hearing loss. Due to the high prevalence of hearing loss in congenital hypothyroidism and its impact on language and cognitive development, it is critical to create awareness among healthcare professionals that children diagnosed with congenital hypothyroidism must undergo audiological evaluation at the time of diagnosis and periodically thereafter. Alternatively, children with unexplained hearing loss must be screened for congenital hypothyroidism. [ABSTRACT FROM AUTHOR]

Soil quality is defined as the ability of soil to function as an essential living system within land-use boundaries. The quantification of soil quality under agricultural systems to estimate the impact of management intensity on soil productivity is crucial for the timely identification of adverse effects of management practices. Farmers' experience and indigenous knowledge provide a simple method of characterizing the status and detecting any variations in soil quality. The precise evaluation of soil quality requires the selection and interpretation of soil indicators associated with soil functions, which cannot be measured directly. A valid SQI assists in the interpretation of data from varied soil measurements and reveals whether management or land-use are having desired outcomes for productivity and environmental protection. The review will examine the concept of soil quality, associated computation, and assessments, and lastly the impact of management practices on the soil quality with an overall purpose of recognizing the practices that improve soil quality. [ABSTRACT FROM AUTHOR]

Code smell refers to substandard design patterns in software's source code that may lead to faults-prone implementation. Machine learning-based code smell prediction models suffer from data imbalance problems, i.e., one class contains significantly more instances than another. The existing oversampling approaches, such as SMOTE (Synthetic Minority Over-sampling Technique), have been used for balancing the code smell dataset by generating synthetic samples for the minority class. However, the distribution of classes of code smell datasets is overlapped; hence, randomly generated instances can damage the decision boundary between both classes. This paper addresses this issue and proposes a novel Cluster-Based Resampling Technique, CBReT , that generates synthetic instances by considering the distribution of the code smell data. The CBReT first formulates clusters (containing minority and majority instances) based on the data distribution using Gaussian Mixture Model (GMM). Next, each cluster is balanced separately by synthesizing minority instances. While balancing the clusters, the CBReT also checks the validity of the synthetic instances so that each synthetic instance holds similar properties as the other minority instances. To assess the performance of CBReT , extensive experiments have been conducted on the four publicly available benchmark code smell datasets. We have used various performance metrics to evaluate our model's performance. The experimental results show that the CBReT technique significantly increased the performance of the code smell prediction model by 0.18% (min) and 9.08% (max) compared to the state-of-the-art imbalance learning approaches. [ABSTRACT FROM AUTHOR]

Most of the part of India is already under water-stressed condition. In this regard, the continuous monitoring of the water levels (WL) and storage capacity of reservoirs, lakes, and rivers is very important for the estimation and utilization of water resources effectively. The long term ground observed WL of many of the water bodies is not easily available, which may be very critical for proper water resources management. Satellite radar altimetry is the remote sensing technique, which is being used to study sea surface height for the last three decades. The advancement in radar technology with time has provided the opportunity to exploit the technique to retrieve the WL of inland water bodies. In the current study, an attempt has been made to generate long term time series on WL of around 29 geometrically complicated inland water bodies in India. These water bodies are mainly large reservoirs namely Ban Sagar, Balimela, Bargi, Bhakra, Gandhi Sagar, Hasdeo, Indravati, Jalaput, Kadana, Kolab, Mahi Bajaj, Maithon, Massanjore, Pong, Ramganga, Ranapratap Sagar, Rihand, Sardar Sarovar, Shivaji Sagar, Tilaiya, Ujjani, and Ukai. The WL of these water bodies was retrieved for around two decades using the European Remote-Sensing Satellite – 2 (ERS-2), ENVISAT Radar Altimeter – 2 (ENVISAT RA-2), and Saral-AltiKa altimeters data through Ice-1 retracking algorithm. Further, an attempt has also been made to estimate the WL of gauged/ungauged lakes namely Mansarovar, Pangong, Chilika, Bhopal, and Rann of Kutch over which Saral-AltiKa pass was there. As after July 2016, the SARAL-AltiKa is operating in the drifting orbit, systematic repeated observation of WL data of all reservoirs was not possible. The data of drifted tracks of Saral-AltiKa were tested for WL estimation of Ban Sagar reservoir. As the ERS-2, ENVISAT RA-2 and Saral-AltiKa all were having almost the same passing tracks, a long term WL series of these lakes could be generated from 1997 to 2016. However, at present only Sentinel – 3 is in orbit, the continuous altimeter based WL monitoring of some of these reservoirs (Gandhi Sagar, Nathsagar, Ranapratap, Ujjani, and Ukai) was attempted through Sentinel-3A satellite data from 2016 to 2018. The accuracy of the retrieved WL was than validated against the observed WL. In most of the reservoirs, a systematic bias was found due to the different characteristics and geoid height of each reservoir. The coefficient of determination, R2, value for a majority of reservoirs was as good as 0.9. In the case of ERS-2, the values of R2 varied for 0.44–0.97 with root mean square error (RMSE) in the range of 0.63–2.72 m. These statistics improved with the ENVISAT RA-2 data analysis, the R2 value reached more than 0.90 for around 11 reservoirs. The highest, 0.99, for Hasdeo and Shivaji Sagar Reservoirs with RMSE of 0.44 and 0.56, respectively. Further, the accuracy improved with the analysis of Saral-AltiKa data. The R2 was always more than 0.9 for each reservoir and the lowest RMSE reduced to 0.03. Therefore, it can be said that the accuracy and consistency of WL retrieval through satellite altimetry has improved with time. Furthermore, the altimeter based retrieved WL may be used in hydrological studies and can contribute to better water resources management. [ABSTRACT FROM AUTHOR]

Hydrodynamic (HD) modelling in data sparse region represents a challenge due to poor hydrological and topographic data availability. Recently, remote sensing techniques offer additional data that may help to improve the reliability and accuracy of such analysis. In this study, an attempt has been made to investigate the potential and added value of altimeter measurements for multi-site validation of the HD model and constructed rating curves (RCs) in a sparsely gauged Brahmaputra River, India. The HD model (MIKE 11) was developed for a Brahmaputra River stretch of 135 km, between Tezpur and Guwahati, where 4 ground-tracks of the SARAL/AltiKa (the first Ka band altimeter mission) cross the river. The Nash Sutcliffe efficiency (NSE) between HD model based water level and in-situ water level during calibration (January-October 2013) and validation (January-March 2014) was found to be 0.93 and 0.79 respectively. Calibrated and validated HD model was used to simulate water level and build rating curves at virtual stations. The bias correction (7.2 cm to 9.5 cm) was applied to the altimetry measurements before comparison with the modelled water levels. The root mean square error (RMSE) ranging between 15 cm and 42 cm was observed between the modelled and altimetry-derived water level at all the virtual stations, indicating the potential of satellite altimetry for multi-site validation of the HD model (inline with previous studies) and validation of the constructed RCs. The availability of RCs at virtual stations allows the expansion of the gauging network along the Brahmaputra River, thus enabling the estimation of the discharge at additional locations and the potential evaluation of the contributions of lateral tributaries could be evaluated in future work. [ABSTRACT FROM AUTHOR]

Groundwater is an important resource for a multitude of purposes, and change in groundwater levels is an important factor in determining the increase and decrease of groundwater quantity in aquifers. This study has been carried out for Gomti River basin, where groundwater is the major drinking water source for the entire region. This paper evaluates the behavior of the groundwater levels using Visual MODFLOW under RCP 4.5 and RCP 8.5 scenarios. For modeling of groundwater flow, the entire study area was discretized into 108480 (X-direction) and 207090 (Y-direction) gridal network with each cell size of 1000 m × 1000 m. The model was calibrated for the period 2002 to 2008 and validated for the period 2009 to 2013 using data of 24 observation wells. During the calibration period of Visual MODFLOW, residual mean ranged between 0.658 and 0.268 m, and absolute residual mean ranged between 2.035 and 2.174 m. The calibrated Visual MODFLOW model was employed to evaluate the influence of climate change on future groundwater levels. Future groundwater recharge (2020–2030), obtained after the application of four (MIROC-ESM, MIROC-ESM-CHEM, MIROC MIROC5, and MOHC-HADGEM2-ES) global climate model (GCM) data into prior SWAT model, was applied to Visual MODFLOW. After applying, the projected future (2020–2030) trend in the groundwater levels was found continuously decreasing due to low groundwater recharge and excessive groundwater withdrawal in the basin in future. [ABSTRACT FROM AUTHOR]

Objectives Emergency Tracheostomy is a life saving surgical procedure. With the advent of newer instruments and equipments in the critical care units, there is marked improvement in the quality of care of the critically ill patients and such patients are able to survive for a longer period. Elective tracheostomy is being done in those patients who needs positive pressure ventilation, for a longer duration. Objectives of our study are to compare conventional tracheostomy (CT) to percutaneous tracheostomy (PcT) and to identify the strategy with the lowest frequency of potentially life threatening events. Study Design Retrospective comparative study. Patients Included 30 patients who met inclusion criteria. Study Settings Tertiary care centre (medical college). Results 15 patients underwent CT and 15 underwent PcT. Blood loss, mean operation time and complications were compared. Blood loss and operation time was lesser in CT compared to PcT. There were no reported complications in both the techniques. Conclusion In our study CT took lesser time with lesser blood loss and without any complications. But statistically, this difference was not significant. Thus person with refined skill in the technique is of utmost importance in deciding the choice of a technique. [ABSTRACT FROM AUTHOR]

In the present study, behavior of the SARAL/AltiKa (Satellite with ARgos and ALtiKa) waveforms over Maithon Reservoir (∼65 km2of surface area), Jharkhand, India, has been studied. The estimated water level has been compared with thein situmeasurements at hydro-gauging station at the dam site. The problem of minimization of errors in the water level retrieval from AltiKa measurements has been resolved by improvement of the retracking method. A real retracking gate detection algorithm based on statistical analysis harnessing various physical parameters of the waveform has been developed, which has been applied to SARAL/AltiKa waveforms over the Maithon reservoir. Comparing thein-situmeasurements with altimetry data (from cycle 1, 19 March 2013 to cycle 12, 8 April 2014) showed that it is crucial to improve the retracking method. Results showed accuracy of water level monitoring increased by nearly 76% by the newly developed waveform retracking algorithm over non-retracked water level. We also compared this new method with the existing ice-1 algorithm and found that with the new method there is improvement of ∼27% over ice-1 retracked water level. The correlation coefficient values and root mean square values without retracking, with ice-1 algorithm and with newly developed retracking algorithm were 0.87, 0.91, and 0.95, and 8.12 cm, 2.08 cm, and 1.42 cm, respectively. This shows the proposed retracker performed better than ice-1. The retracking procedure helped in outliers' identification and substitution and with waveform fitting and waveform parameter extraction. This algorithm should have good performance capability for retrieving water level over inland water bodies like Maithon reservoir. [ABSTRACT FROM PUBLISHER]

The glaciated areas of the Himalaya often experience mass movement, glacial lake outburst flood and other associated hazards, posing threat to the communities and infrastructure in the downstream areas. A large debris flow occurred during July 16–19, 2017 near the present snout of the Gangotri Glacier in the Garhwal Himalaya, India resulting in significant geomorphological changes in the vicinity. The present study assesses the applicability of multi-source remote sensing data from satellites, unmanned aerial vehicle (UAV) and terrestrial laser scanner (TLS) along with process-based modelling to understand and quantify glacier snout dynamics and morphological changes around Gangotri Glacier in the Garhwal Himalaya of India. We show that retreat rates of Gangotri Glacier snout along the lateral flowlines are (left flowline 29.6 m year−1; right flowline 60.5 m year−1) are significantly higher compared to the central flowline (18.2 m year−1) during 2010–2020 leading to total loss in glacial ice area of 0.11 ± 0.015 km2. The snout dynamics and evolution of the new channel from the terminus of the adjoining Meru Glacier, connecting the moraine-dammed glacial lake and the Bhagirathi River, suggest that retreat of the Gangotri Glacier, intense precipitation and excessive seepage from the glacial lake were the important drivers of the debris flow in July 2017. The accumulated debris occupied an area of ~0.25 km2 near the snout of the Gangotri Glacier and shifted Bhagirathi River by 36–200 ± 9.35 m towards northeast. The synergistic analysis of pre- and post-event satellite, UAV and TLS-based digital elevation models (DEMs) and satellite images indicate that about −8 ± 0.066 × 106 m3 of sediments were generated by the debris flow. The results from remote sensing data suggest that a significant portion (~60%) of the deposited debris has been transported to the downstream areas between July 16–19, 2017 and October 2, 2017. Regular monitoring of the area is recommended, especially in light of climate change using earth observation data and ground measurements. The multi-source integrated framework implemented in this study is generic and can be applied for any debris flow or landslide studies in glaciated terrain. • UAV and DGNSS data improved absolute geo-positioning of a satellite-based DEM. • High-resolution satellite and TLS data used for glacier retreat and snout ice loss. • Deposited debris quantified using temporal DEMs and debris-flow modelling. • Lower ablation zone of Gangotri glacier is highly vulnerable for ice loss. [ABSTRACT FROM AUTHOR]

The effect of in- and anti-phase mode decoupling on the frequency response of coupled in-plane resonators was examined, experimentally, to suppress the acceleration sensitivity (acceleration output) in tuning fork gyroscopes (TFGs). Finite element simulations, conducted in our recent works, show that the origin of acceleration sensitivity for the sensing resonators in TFGs lies in the transduction of linear (in-phase) acceleration to anti-phase resonant vibration of the sensing resonators in TFGs. We further revealed that the frequency decoupling of the in- and anti-phase vibration modes is effective in suppressing the transduction. To experimentally validate this, two types of coupled resonators (one coupled with a frame and the other with a spring) to represent the sensing resonators of TFGs were fabricated on silicon-on-insulator wafer. Different resonant frequencies were used to evaluate the frequency decoupling effect on the coupled resonators, i.e., the coupling from in-phase mode oscillation to the anti-phase mode vibration. The vibration amplitude of the anti-phase mode increased in the coupled resonators with small frequency decoupling (decoupling ratio, DR) value. Additionally, the two types of coupled resonators exhibit similar output after considering the effect of decoupling ratio, anti-phase frequency and different stiffness unbalances. Our results reveal that TFG can be designed with lower acceleration sensitivity by utilizing sense resonators with large decoupling ratio, higher anti-phase frequency, and possessing structures which are insensitive to fabrication imperfections. [ABSTRACT FROM AUTHOR]

The snow and glacier melt run-off is one of the most important sources of freshwater for the perennial Himalayan rivers. The water from these rivers sustains billions of people in South Asia, especially during lean season. The study has been done to integrate temporal snow cover area (SCA) and digital elevation model (DEM) derived from satellite remote sensing data with Geographic Information System (GIS) and finally into temperature index-based snowmelt run-off estimation model. The study area for snowmelt run-off estimation is part of head reach sub-basins of Ganga river, i.e. Alakhnanda and Bhagirathi river basins up to Joshimath and Uttarkashi respectively. The temporal SCA (2002–07 for Bhagirathi river and 2000, 2008 for Alakhnanda river) was derived from remote sensing data and DEM was used to find elevation zones and aspect maps. Snowmelt run-off model (SRM) is a temperature index-based snowmelt run-off simulation model, which has been used in this study for simulating snowmelt run-off. The daily hydro meteorological data from India Meteorological Department and Central Water Commission were used for estimating snowmelt. Overall accuracy of SRM for Alakhnanda river in terms of coefficient of correlation (R2) is 0.84–0.90 for years 2000 and 2008, and 0.74–0.84 in Bhagirathi river for 2002–2007. [ABSTRACT FROM AUTHOR]

This study has been done using Polarimetric Synthetic Aperture Radar (SAR) data to estimate the snow physical properties (snow wetness and snow density), inManali sub-basin of Himachal Pradesh, India. The SAR data used are of Radarsat-2 (RS2) and Environmental Satellite, Advanced Synthetic Aperture Radar (ASAR). SAR-based inversion models were implemented in Mathematica and MATLAB, and have been used for finding out wet and dry snow dielectric constant, snow wetness and snow density. The SAR-based inversion models were implemented separately for fully polarimetric RS2 and dual polarimetric ASAR Alternate Polarization System datasets. Masks for forest, built area, layover and shadow were considered in estimating snow parameters. The overall accuracy in terms of R 2 value comes out to be 0.86 for snow wetness and 0.84–0.72 for snow density based on the ground truth data for subset area of Manali sub-basin of Beas river up to Manali. [ABSTRACT FROM PUBLISHER]

Rapid urban growth processes give rise to impervious surfaces and are regarded as the primary cause of urban flooding or waterlogging in urban areas. The high rate of urbanization has caused waterlogging and urban flooding in many parts of Dhaka city. Therefore, the study is undertaken to quantify the changes in land use/land cover (LULC) and urban runoff extent based on the Natural Resources Conservation Service (NRCS) Curve Number (CN) during 1978–2018. The five-decadal LULC has been analyzed using three-generation Landsat time-series data considering six different classes, namely agriculture, built-up, wetland, open land, green spaces, and water bodies for the years 1978, 1988, 1998, 2007, and 2018. Significant changes in LULC for the study area from 1978–2018 are observed as 13.1%, 4.8%, and 7.8% reduction in agricultural land, green spaces, and water bodies, respectively, and a 22.1% increase in the built-up area is estimated. Within Dhaka city, 14.6%, 16.0%, and 12.3% reduction in agricultural land, green spaces, and water bodies, respectively, and a radical increase of 41.9% in built-up area are reckoned. The decadal runoff assessment has been carried out using the NRCS-CN method, considering an extreme rainfall event of 341 mm/day (13 September 2004). The catchment area under very high runoff category is observed as 159.5 km2 (1978) and 318.3 km2 (2018), whereas, for Dhaka city, the setting is dynamic as the area under the very high runoff category has increased from 74.24 km2 (24.44%) to 174.23 km2 (57.36%) in years 1978 and 2018, respectively, and, mostly, the very high runoff potential areas correspond to the dense built-up surfaces. [ABSTRACT FROM AUTHOR]

The change in the phase, from quiescence to surge, may perturb the glacier's dynamical behavior. To understand these changes through geospatial technique, the fastest moving tidewater Monacobreen Glacier, Svalbard, was studied for the year 2016–2019. It was elucidated that the surge had initiated during 2017–2018 before it the glacier was in quiescence since 2001. Initially, the glacier radar zones, namely percolation refreeze, lower percolation, and clean ice, were identified using the multi-temporal SAR data. These zones were utilized to delineate the equilibrium line altitude, and it was found that it is continuously moving down during surging, unlike the quiescence phase. The accumulation area ratio was always more than 0.67 throughout the analysis. The seasonal change in glacier surface velocity for both the phases was estimated, adapting the most appropriate Offset Tracking approach using the SAR data. The mean velocity over the main trunk was found to vary from 0.5 to 4 m/day. Thereafter, Glen's flow law equation was used to estimate the ice-thickness and found that the glacier has an average thickness range of 216–326 m in quiescence and 136–244 m during the surging. The analysis depicted that the basal shear stresses are increasing with surging, and the viscosity is decreasing. It can be said that the transition of the glacier from quiescent to surging phase has entirely changed its dynamic behavior and characteristics. Further, in the absence of field observations, the geospatial technique may provide reasonable estimates of the glacier's physical and dynamical parameters. [ABSTRACT FROM AUTHOR]

Glaciers are a critical source of freshwater, especially during the lean season. Globally, the glaciers are losing their mass balance rapidly under the influence of climate change. In view of this, the regular study of these glaciers is very vital. However, field-based studies of most of the glaciers is a daunting task. On the contrary, emerging geospatial technology may play an important role in the studies of glaciers. The equilibrium line altitude (ELA) of the glaciers has been considered an essential indicator of climate change. There are numerous methods to delineate the equilibrium line of a glacier; however, each has its own merits and demerits. In the present study, the synthetic aperture radar (SAR) remote sensing-based approach has been used for identifying the ELA of glaciers in the Ala-Archa River catchment of Kyrgyzstan from 2015 - 2019. Initially, the glacier radar zonesweremapped using the Sentinel-1 SAR datasets of each year under consideration. It was found that mainly the middle percolation, lower percolation, and bare-ice zones along with debris cover-ice are present in the glaciers. It was observed that the percolation refreeze zone covers approximately 40%, and the Bare-Ice zone covers 48% of the total area. Considering the boundary of lower percolation and bare-ice zone as ELA, the ELA of each glacier in each year was estimated. The lowest ELA of 3462 m was observed in 2018, whereas the highest (4309 m) was recorded in 2019. It was noticed that the trend of ELA is consistently increased from 3839.25 m in 2015 up to in 3868.29 m 2019. The temporal analysis of glacier radar zone estimation and ELA may help in studying the impact of climate change on glacier retreat and mass balance change. It can be concluded that geospatial techniques can make the glacier change studies possible without field survey. However, to validate the results of the study, field observations are a must. [ABSTRACT FROM AUTHOR]

Tea is being grown on the gentle slopes of Himachal Pradesh located in the north-western region of mighty Himalaya, since 1850s. However, degrading soil health due to rampant usage of agrochemicals, and long-run tea cultivation adversely affects the productivity potential of the region. Analyzing soil-nutrient status is of great value to meet the crop nutrient demand. The research aimed to identify the vulnerable soil properties and their assessment for soil restoration under major tea estates of the North-western Himalaya. The study examined the physico-chemical and biological properties of soils of 37 tea estates. The large variation among different sites for physical parameters signifies the textural difference between the sites under study. Meanwhile, the soil pH of tea estates varied from extremely acidic to slightly acidic reaction, with an overall pH (H2O) of 5.33 in the top soils and 5.47 in the subsoils. High OC (13.35 g kg−1) under overall soil depth of tea estates presumably correlated with higher concentration of available nutrients, i.e. N (r = 0.641), K (r = 0.492), and S (r = 0.623) alongside exchangeable Ca (r = 0.724) and Mg (r = 0.718). The substrate carbon availability due to higher amount of organic matter in the top soils (16.1 g kg−1) leads to increased biological activity (MBC and DHA) in the surface soils as compared to subsoils. The unscientific approach of fertilizer application led to huge variability in green leaf yield across different tea estates. Thus, to achieve higher yield, it should be necessary to adopt nutrient application in a judicial manner in the tea plantations. [ABSTRACT FROM AUTHOR]

Remote sensing has already proven its capability in water quality studies. The technology enables the mapping of water quality parameters that affect its optical properties. Generally, multi-spectral remote sensing data has been utilized for such analysis. Mostly, the band rationing or simple regression approaches have been adapted to map the water quality, however, they result in qualitative estimates rather than quantitative. On the other hand, sensor technology has made steep advancements from multi-spectral to hyperspectral. The hyperspectral data provides contiguous spectral information over several hundred narrow spectral bands. This emerging technique provides a more in-depth means of investigating spatial, spectral, and temporal variations, leading to more quantifiable/accurate estimates of the process under consideration. At present, very few satellite-based hyperspectral data are available. Recently, the Indian Space Research Organisation has initiated an airborne hyperspectral remote sensing campaign to cover the important earth features in India using Airborne Visible/Infrared Imaging Spectrometer – Next Generation (AVIRIS-NG) sensor in collaboration with the National Aeronautics and Space Administration (NASA). As the AVIRIS-NG hyperspectral data measures the spectral response in the wavelength range from 380 to 2510 nm at very narrow spectral bandwidth of 5 nm. These advanagtes of AVIRIS-NG datasets enable researchers to analyse the spectra of each and every pixel of the image spatially to match its spectral characteristics with the spectra collected in the field. In the present study, this spectral similarity approach has been expoilted within the context of turbidity, the optical property of water for Chilika Lake, Odisha, India; using the AVIRIS-NG data and field reference spectra. The lake was surveyed synchronous to AVIRIS-NG flights over it during the month of December 2015. A field-based spectral library with respect to various concentrations of turbidity in the lake has been generated using sophisticated instruments like field spectro-radiometer, handheld Global Navigation Satellite System (GNSS) receiver, and turbidimeter. The spectral angle mapper (SAM) spatial-spectral contextual image analysis has been carried out to map the turbidity of the lake. It was observed that almost at each and every pixel the image spectra were matching with the field-collected spectra. Further, the match between two spectra (field and image) measured in terms of SAM score was as high as 0.9 for most of the instances. Moreover, the estimated turbidity was in the agreement (R2 = 0.96) with the turbidity measured on the field. It was realized that the spectral similarity approach using hyperspectral remote sensing data provides more quantitative estimates as compared to multi-spectral data analysis. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar (SAR) remote sensing is a state-of-the-art tool for snow monitoring and snow parameters estimation. SAR remote sensing-based techniques, such as interferometric SAR (InSAR) and Polarimetric SAR (PolSAR) have already proven useful in the estimation of geophysical parameters of snow. InSAR-based techniques utilize interferometric phase information from repeat-pass datasets for snow parameters retrieval. During the monitoring of snow, the large temporal gap between the repeat passes results in the temporal decorrelation in the snowpack, which leads to the loss of interferometric coherence. Hence, there is a need for a technique for snow parameters estimation, which can work with zero temporal baseline datasets. This study works on the development of a Polarimetric SAR Interferometry (PolInSAR) based modelling approach for snow-depth estimation using TerraSAR-X/TanDEM-X datasets acquired in the pursuit monostatic mode (temporal baseline = 10 seconds). The study area of this work is the Manali region of Himachal Pradesh situated in the Beas basin. Multi-temporal analysis of the snow-depth variation is executed utilizing the two pursuit-monostatic TanDEM-X interferometric quad-pol dataset pairs of the dates 21 January 2015 and 22 January 2015. In this study, the PolInSAR-based Coherence Amplitude Inversion modelling approach is used for the snow-depth retrieval. The magnitude of the complex interferometric coherence is used during the modelling implementation. The snow extinction coefficient is estimated and used as an input during PolInSAR modelling. Further, a comparison of the calculated volume coherence magnitude and the observed volume coherence magnitude is done during model implementation for the snow-depth estimation. The snow depth is estimated at a resolution of 15 m × 15 m in range and azimuth directions respectively. The estimated snow depth for both the dates shows a precise correlation with the ground datasets. The rise in model retrieved snow-depth value from 0.84 m to 1.24 m is observed during the period. The retrieved results were validated using the ground data of snow depth from the Automatic weather station (AWS) of Snow and Avalanche Study Establishment (SASE), Defence Research and Development Organization (DRDO), and Indian Institute of Remote Sensing (IIRS) installed in the Dhundi region of the study area for same dates. [ABSTRACT FROM AUTHOR]

The article focuses on space-based observations on annular solar eclipse of June 2020. Topics include the traditional methods of observing the solar eclipse through telescopes using solar filters or using solar projectors, this phenomenon can also be captured using satellite data, and the shadow cast by the moon on the surface of the Earth leads to a drop in the solar flux over the Earth's surface, which can be recorded by space based sensors in the visible near-infrared spectral range.

• This study proposes a novel methodology for the estimation of snow wetness utilizing the C-band hybrid polarimetric RISAT-1 SAR dataset. • The Estimation of Surface and Volume Dielectric Constant of Snowpack is done for the retrieval of Snowpack Wetness utilizing surface and volume scattering characteristics. • The modeled generalized surface and volume scattering parameter (α), and (γ), based on the X-Bragg's reflection coefficients and Fresnel transmission coefficients, are used for the inversion of surface and volume snow permittivity respectively. • The proposed method using RISAT-1 dataset outperformed the estimates based on fully polarimetric RADARSAT-2 dataset utilizing the conventional Shi and Dozier method. • The developed methodology for snow wetness estimation will be applicable for the Hybrid Polarimetric mode datasets from upcoming missions like NISAR, ALOS-3, and Radar Constellation Mission (RCM). Snow wetness estimates are critical inputs in the understanding of snow hydrological processes. With early warming in winters in the Himalayas, snowpack shows early signs of melting in February with increased snow wetness. Typically, in February, the snowpack comprises a mix of dry and wet snow layers. In the literature, methods for quantitative analysis of snow wetness are mostly based on fully polarimetric synthetic aperture radar (SAR) data. Methods based on the hybrid polarimetric SAR (PolSAR) data for snow monitoring are virtually inexistent. This study proposes a novel methodology for the estimation of snow wetness utilizing the C-band hybrid polarimetric RISAT-1 SAR dataset. Using radar remote sensing to analyze the behavior of such a snowpack requires information on the surface and volume scattering characteristics. The modeled generalized surface and volume scattering parameters (α), and (γ), based on the X-Bragg's reflection coefficients and Fresnel transmission coefficients, are used for the inversion of surface and volume snow permittivities, respectively. The investigations are carried out for February 2014 for a study area in the Manali region in Himachal Pradesh, India. The retrieved snow estimates showed a coefficient of determination of 0.86 and a root mean square error of 0.667 with respect to in-situ measurements. Further, it was observed that the snow wetness estimates derived from the proposed method using RISAT-1 dataset outperformed the estimates based on fully polarimetric RADARSAT-2 dataset using the conventional Shi and Dozier method. [ABSTRACT FROM AUTHOR]

• This study proposes a novel methodology for the estimation of snow wetness utilizing the C-band hybrid polarimetric RISAT-1 SAR dataset. • The Estimation of Surface and Volume Dielectric Constant of Snowpack is done for the retrieval of Snowpack Wetness utilizing surface and volume scattering characteristics. • The modeled generalized surface and volume scattering parameter (α), and (γ), based on the X-Bragg's reflection coefficients and Fresnel transmission coefficients, are used for the inversion of surface and volume snow permittivity respectively. • The proposed method using RISAT-1 dataset outperformed the estimates based on fully polarimetric RADARSAT-2 dataset utilizing the conventional Shi and Dozier method. • The developed methodology for snow wetness estimation will be applicable for the Hybrid Polarimetric mode datasets from upcoming missions like NISAR, ALOS-3, and Radar Constellation Mission (RCM). Snow wetness estimates are critical inputs in the understanding of snow hydrological processes. With early warming in winters in the Himalayas, snowpack shows early signs of melting in February with increased snow wetness. Typically, in February, the snowpack comprises a mix of dry and wet snow layers. In the literature, methods for quantitative analysis of snow wetness are mostly based on fully polarimetric synthetic aperture radar (SAR) data. Methods based on the hybrid polarimetric SAR (PolSAR) data for snow monitoring are virtually inexistent. This study proposes a novel methodology for the estimation of snow wetness utilizing the C-band hybrid polarimetric RISAT-1 SAR dataset. Using radar remote sensing to analyze the behavior of such a snowpack requires information on the surface and volume scattering characteristics. The modeled generalized surface and volume scattering parameters (α), and (γ), based on the X-Bragg's reflection coefficients and Fresnel transmission coefficients, are used for the inversion of surface and volume snow permittivities, respectively. The investigations are carried out for February 2014 for a study area in the Manali region in Himachal Pradesh, India. The retrieved snow estimates showed a coefficient of determination of 0.86 and a root mean square error of 0.667 with respect to in-situ measurements. Further, it was observed that the snow wetness estimates derived from the proposed method using RISAT-1 dataset outperformed the estimates based on fully polarimetric RADARSAT-2 dataset using the conventional Shi and Dozier method. [ABSTRACT FROM AUTHOR]

The study provides estimates of summertime evaporation over a glacial lake located in the Schirmacher oasis, Dronning Maud Land, East Antarctica. Lake Zub (alternately named Lake Priyadarshini and referred to throughout as Lake Zub/Priyadarshini) is the second-largest lake in the oasis, and its maximum depth is 6 m. The lake is also among the warmest glacial lakes in the oasis, and it is free of ice during almost 2 summer months. The summertime evaporation over the ice-free lake was measured using the eddy covariance method and estimated on the basis of five indirect methods (bulk-aerodynamic method and four combination equations). We used meteorological and hydrological measurements collected during a field experiment carried out in 2018. The eddy covariance method was considered the most accurate, and the evaporation was estimated to be 114 mm for the period from 1 January to 7 February 2018 (38 d) on the basis of this method. The average daily evaporation was 3.0 mm d -1 in January 2018. During the experiment period, the largest changes in daily evaporation were driven by synoptic-scale atmospheric processes rather than local katabatic winds. The bulk-aerodynamic method suggests the average daily evaporation is 2.0 mm d -1 , which is 32 % less than the results based on the eddy covariance method. The bulk-aerodynamic method is much better in producing the day-to-day variations in evaporation compared to the combination equations. All selected combination equations underestimated the evaporation over the lake by 40 %–72 %. The scope of the uncertainties inherent in the indirect methods does not allow us to apply them to estimate the daily evaporation over Lake Zub/Priyadarshini. We suggested a new combination equation to evaluate the summertime evaporation over the lake's surface using meteorological observations from the nearest site. The performance of the new equation is better than the performance of the indirect methods considered. With this equation, the evaporation over the period of the experiment was 124 mm, which is only 9 % larger than the result according to the eddy covariance method. [ABSTRACT FROM AUTHOR]

Extensive global dependency on rice and wheat crops has necessitated the adoption of intensive cultivation practices, thereby compelling to closely monitor the potential yield-limiting factors, among which, boron (B) deficiency stands out to be a prime concern. The present study explores the effects of B fertilization strategies within the Rice-Wheat Cropping System (RWCS) in the Tarai region of North-West India. A comprehensive six-year field experiment was conducted (2013–2019) at G.B. Pant University of Agriculture and Technology, Uttarakhand, India. The experiment tested graded B doses (0.5, 1.0, 1.5, and 2.0 kg ha−1) at varied frequencies (single, alternate, and annual) in a factorial design. The study revealed significant impacts of alternate B application at 1.5 kg ha−1 on crop yields and the Sustainable Yield Index (SYI). The System Rice Equivalent Yield (SREY) exhibited an increase of 6.7% with B supplementation over B-deprived plots, highlighting the pivotal role of B fertilizer in enhancing productivity within the RWCS. The economic optimum B dose was found to be 1.422 kg ha−1 using a linear plus plateau model, resulting in a calculated annual SREY of 9.73 t ha−1 when applied alternately to the cropping system. Continuous application and higher B rates demonstrated substantial increases in various B fractions, while the mobility factor remained within 10%, depicting safe ecological limits. The distribution of fractions in B-treated plots on average followed the order: residual B > organically-bound B > oxide bound B > specifically adsorbed B > readily soluble B. Similarities in the distribution patterns of B fractions between B-treated plots and the control indicated potential influence of biotic or abiotic processes on B fraction dynamics, even in the absence of external B application. To sum up, B application in alternate years at 1.5 kg ha−1 was most sustainable in enhancing the SREY, SYI, available soil B, and B fractions and lowering the environmental hazards. [Display omitted] • Boron (B) deficiency emerging as a major threat in RWCS under the Tarai region of North-West India. • Alternate B application enhanced rice and wheat yield. • Figured out the economic optimum B dose as 1.422 kg ha−1. • Continuous B application at higher rates had positive and significant impact only on boron fractions. [ABSTRACT FROM AUTHOR]

Indo Gangetic flood plains are subjected to recurring floods due to large low-lying land areas adjacent to major Himalayan Rivers. Recent floods in the Ganga River during the late withdrawal phase of Indian summer monsoon rains in 2019 had reportedly caused death of ∼200–500 people and damaged major infrastructures in different parts of Bihar state, India. This paper presents a detailed analysis of the spatial extent and temporal pattern of flood inundation areas in Patna district of Bihar using Sentinel-1 Synthetic Aperture Radar (SAR) data. The results obtained using K-means classification show that about 1268 km2 (20% of the studied portion) of the land area were inundated during the peak flooding conditions on 9th October 2019. The peak flooding lasts for more than 20 days, with a maximum water depth of 18 m in the main river. Owing to the continually changing nature of river morphology by recurring floods, we also analyzed the channel morphology and bar characteristics before, during, and after the floods. Geomorphic change assessment indicates that the total bar occupied area was decreased from 661 km2 for pre-flood time to 446 km2 in peak flood time, whereas it retains its original shape in post-flood images. [ABSTRACT FROM AUTHOR]

Antarctica is the focus of scientific studies considering the largest reservoir of terrestrial water in the form of ice and doubling of ice area during winter due to sea-ice growth. The third pole -- Himalaya is equally important due to the large extent of snow and ice cover outside the polar region, which is a major source of water for the Asian countries. At present, the Ku-band scatterometer observing global cryosphere is the SCATSAT-1 launched by India. This article describes the study carried out on different cryospheric parameters using high-resolution (~2.2 km) scatterometer data in the Antarctica and Himalaya. Impact of seasonal variations in snow/ice and ice calving on the backscatter over Antarctica is discussed in detail. A procedure developed for the estimation of sea-ice extent, which yielded overall accuracy of 89%, has been presented and successfully applied for daily monitoring of the Antarctic ice extent for 2017. Surface melting using backscatter and brightness temperature data has been discussed and the contrast between large-sized and small-sized Antarctic ice shelves during the austral summer period of summer 2017-18 is highlighted. The higher average surface melt observed around majority of east Antarctic ice shelves, particularly near the Indian station 'Maitri', is of particular interest. Typical surface melting patterns observed over the third largest Antarctic ice shelf, Amery, are discussed in detail. Over northwest Himalaya, derived changes in snow water equivalent (ΔSWE) shows a good correlation between observed and calculated SWE variations. The present study demonstrates that simultaneous availability of high-resolution brightness temperature and backscatter data from SCATSAT-1 provides a unique opportunity to study the polar and mountain cryosphere. [ABSTRACT FROM AUTHOR]

Snow and urban land cover are important due to their role in hydrological management and utility, climate response, social aspects and economic viability, along with influencing the Earth's environment at local, regional and global scale. Hyperspectral data enable identification, characterization and retrieval of these land-cover features based on physical and chemical properties of compositional materials. AVIRISNG hyperspectral airborne data, with synchronous ground observations using field spectroradiometer and collateral instruments, were collected over two widely varied land-cover types, viz. a relatively homogenous area covered by snow in the extreme cold environment of the Himalaya (Bhaga sub-basin, Himachal Pradesh), and a completely heterogeneous urban area of a metropolitan city (Ahmedabad, Gujarat). AVIRIS-NG airborne data were analysed to understand the effect of terrain parameters such as slope and aspect on snow reflectance. Snow grain index using visible and near-infrared (VNIR) bands and absorption peak in the near-infrared (NIR) were used to retrieve grain size in parts of the Himalayan region. A radiative transfer model was used to understand the grain size variability and its effect on absorption peak in NIR. Continuum removal was performed for snow spectral observations obtained from airborne, modelled and field platforms to estimate band depth at 1030 nm. Grain size was observed to vary with altitude from 100 to 500 µm using AVIRIS-NG image. In the urban area, the data also separated pervious and impervious surface cover using spectral unmixing technique, identified several urban features over multispectral data such as buildings with red tiled roofs, metallic surfaces and tarpaulin sheets using the material spectral profiles. Two single-frame superresolution methods namely sparse regression and natural prior (SRP), and gradient profile prior (GPP) were applied on AVIRIS-NG data for the mixed environment around Kankaria Lake in the city of Ahmedabad, which revealed that SRP method was better than GPP, and affirmed by eight indices. Preliminary analysis of AVIRIS-NG imaging over snow-covered areas and densely populated cities indicated utility of future spaceborne hyperspectral missions, particularly for hydrological and climatological applications in such diverse environments. [ABSTRACT FROM AUTHOR]

• The evaluation of HAND, TWI, and SP in a data-scarce Himalayan basin. • The reference floodplain map was simulated by MIKE11 hydrodynamic model. • HAND and TWI showed better efficacy than SP in floodplain mapping. • HAND showed greater consistency while TWI showed an underestimation tendency. • Integrating extensive field observations minimized the effect of DEM uncertainty. Despite a proven record of accurate floodplain mapping, complex hydrodynamic models lack efficiency due to their data-intensive approach and high computation time. As fast-computing low-complexity alternatives, topography-based hydrogeomorphic approaches are being increasingly used in recent times. Yet, there is little evidence to suggest whether and to what extent such topography-based approaches, simply relying on Digital Elevation Models (DEMs), can effectively delineate floodplains/flood hazard zones in data-scarce, highly complex mountainous terrains. We fill this knowledge-gap by conducting a floodplain mapping comparative assessment with three topography-based approaches along a 56-km river reach in the North West Himalayas (Beas River, India). Specifically, we generated floodplain extent using Height Above the Nearest Drainage (HAND), Topographic Wetness Index (TWI), and Slope Position (SP), and estimated their relative differences compared to a reference inundation extent simulated by MIKE11 hydrodynamic model. The unique feature of our study was an extensive field survey to collect longitudinal and cross-sectional elevation data across 223 locations, which allowed us to verify vertical accuracy across multiple alternative DEMs and subsequently improve the selected DEM via bathymetry integration. Statistical measures estimating the degree of consistency across three topography-based approaches suggested that HAND and TWI produce more reasonable floodplain maps than SP. HAND-based floodplain demonstrated greater agreement with the model-simulated reference map. TWI showed moderate predictability with a tendency of underestimating floodplains. SP was largely inconsistent, demarcating floodplains in areas where the hydrodynamic model found uplands and vice versa. Our study can offer critical insights to support floodplain hydrological, biological, and habitat studies across the world's developing countries where locally relevant delineation of floodplains remains challenging due to data scarcity. [ABSTRACT FROM AUTHOR]

In order to assess the available sulphur and micronutrients (Fe, Mn, Zn and Cu) status in soils of Banaskantha district of Gujarat, five hundred and fifty six representative surface (0-15cm) soil samples were collected from farmer's field of each taluka of Banaskantha district. All the collected soil samples were analyzed for available sulphur and DTPA-extractable cationic micronutrients (Fe, Mn, Zn and Cu) as per standard procedures. The available S content in soils of Banaskantha district varied from 4.98 to 66.89 mg kg-1 with a mean value of 15.49 mg kg-1. The DTPA- extractable Fe, Mn, Zn and Cu were in the range of 2.74 to 21.98; 4.22 to 25.02; 0.20 to 2.76 and 0.12 to 3.16 mg kg-1 with a mean value of 6.72, 10.15, 0.60 and 0.60, respectively. The overall nutrient index values were marginal for available S (1.82) and DTPA-extractable Fe (1.84) and Zn (1.74); high for DTPA-extractable Mn (2.40) and very high for Cu (2.75). [ABSTRACT FROM AUTHOR]

Snow cover is one of the most important land surface parameters in global water and energy cycle. Large area of North West Himalaya (NWH) receives precipitation mostly in the form of snow. The major share of discharge in rivers of NWH comes from snow and glacier melt. The hydrological models, used to quantify this runoff contribution, use snow-covered area (SCA) along with hydro-meteorological data as essential inputs. In this context, information about SCA is essential for water resource management in NWH region. Regular mapping and monitoring of snow cover by traditional means is difficult due to scarce snow gauges and inaccessible terrain. Remote sensing has proven its capability of mapping and monitoring snow cover and glacier extents in these area, with high spatial and temporal resolution. In this study, 8-day snow cover products from MODIS, and 15-daily snow cover fraction product from AWiFS were used to generate long-term SCA maps (2000–2017) for entire NWH region. Further, the long term variability of 8-daily SCA and its current status has been analysed. The SCA mapped has been validated using AWiFS derived SCA. The analysis of current status (2016–17) of SCA has indicated that the maximum extent of snow cover in NWH region in last 17 years. In 2nd week of February 2017, around 67% of NWH region was snow covered. The comparison of SCA during the 1st week of March and April in 2016–17 against 2015–16 indicates 7.3% and 6.5%, increased SCA in current year. The difference in SCA during 1st week of March 2017 and 1st week of April 2017 was observed to be 14%, which indicates that the 14% SCA has contributed to the snow melt during this period. The change in snow water equivalent retrieved using SCATSAT-1 data also validates this change in snow volume. [ABSTRACT FROM AUTHOR]

Turbidity is an important quality parameter of water from its optical property point of view. It varies spatio-temporally over large waterbodies and its well distributed measurement on field is tedious and time consuming. Generally, normalized difference turbidity index (NDTI), or band ratio, or regression analysis between turbidity concentration and band reflectance, approaches have been adapted to retrieve turbidity using multispectral remote sensing data. These techniques usually provide qualitative rather than quantitative estimates of turbidity. However, in the present study, spectral similarity analysis, between the spectral characteristics of spaceborne hyperspectral remote sensing data and spectral library generated on field, was carried out to quantify turbidity in the part of Chilika Lake, Odisha, India. Spatial spectral contextual image analysis, spectral angle mapper (SAM) technique was evaluated for the same. The SAM spectral matching technique has been widely used in geological application (mineral mapping), however, the application of this kind of techniques is limited in water quality studies due to non-availability of reference spectral libraries. A spectral library was generated on field for the different concentrations of turbidity using well calibrated instruments like field spectro-radiometer, turbidity meter and hand held global positioning system. The field spectra were classified into 7 classes of turbidity concentration as <5, 5–10, 10–15, 15–25, 25–45, 45–100 and >100 NTU for analysis. Analysis reveal that at each location in the lake under consideration, the field spectra matched with the image spectra with SAM score of 0.8 and more. The observed turbidity at each location was also very much falling in the estimated turbidity class range. It was observed that the spectral similarity approach provides more quantitative estimate of turbidity as compared to NDTI. [ABSTRACT FROM AUTHOR]

The evolution of land-atmosphere-ocean models has resulted in the need for hydrologic models applicable to large areas and river basins. Such developments offer new challenges and opportunities for hydrologists to understand the hydrologic response of areas as large as continents. In the present study, the ability of variable infiltration capacity (VIC) hydrological model has been studied to assess run-off potential and other hydrological components for entire India. VIC is a semi-distributed macroscale hydrological model designed to represent surface energy, hydrological fluxes and states at scales from large river basins to the entire globe. It is grid-based model which quantifies the dominant hydro-meteorological process taking place at the land surface-atmospheric interface. In the present study, the model was forced with 15 years daily precipitation, maximum and minimum air temperature at daily time-step on 25 × 25 km grid. The water balance of entire India has been studied and the model results on daily, monthly and annual timescales are discussed. It was found that the VIC model results in idealistic hydrology as it takes into account a large number of parameters influencing the process. It was realized that to study such a complex hydrological interaction between land surface and atmosphere over a large region, requires enormous data; in this regard remote sensing data may play an important role. The model can easily be adopted to get primarily information on water balance at any scale. [ABSTRACT FROM AUTHOR]

Spaceborne and airborne polarimetric synthetic-aperture radar interferometry (PolInSAR) data have been extensively used for forest parameter retrieval. The PolInSAR models have proven their potential in the accurate measurement of forest vegetation height. Spaceborne monostatic multifrequency data of different SAR missions and the Global Ecosystem Dynamics Investigation (GEDI)-derived forest canopy height map were used in this study for vegetation height retrieval. This study tested the performance of PolInSAR complex coherence-based inversion models for estimating the vegetation height of the forest ranges of Doon Valley, Uttarakhand, India. The inversion-based forest height obtained from the three-stage inversion (TSI) model had higher accuracy than the coherence amplitude inversion (CAI) model-based estimates. The vegetation height values of GEDI-derived canopy height map did not show good relation with field-measured forest height values. It was found that, at several locations, GEDI-derived forest height values underestimated the vegetation height. The statistical analysis of the GEDI-derived estimates with field-measured height showed a high root mean square error (RMSE; 5.82 m) and standard error (SE; 5.33 m) with a very low coefficient of determination (R2; 0.0022). An analysis of the spaceborne-mission-based forest height values suggested that the L-band SAR has great potential in forest height retrieval. TSI-model-based forest height values showed lower p-values, which indicates the significant relation between modelled and field-measured forest height values. A comparison of the results obtained from different SAR systems is discussed, and it is observed that the L-band-based PolInSAR inversion gives the most reliable result with low RMSE (2.87 m) and relatively higher R2 (0.53) for the linear regression analysis between the modelled tree height and the field data. These results indicate that higher wavelength PolInSAR datasets are more suitable for tree canopy height estimation using the PolInSAR inversion technique. [ABSTRACT FROM AUTHOR]

As a catchment phenomenon, land use and land cover change (LULCC) has a great role in influencing the hydrological cycle. In this study, decadal LULC maps of 1985, 1995, 2005 and predicted-2025 of the Subarnarekha, Brahmani, Baitarani, Mahanadi and Nagavali River basins of eastern India were analyzed in the framework of the variable infiltration capacity (VIC) macro scale hydrologic model to estimate their relative consequences. The model simulation showed a decrease in ET with 0.0276% during 1985-1995, but a slight increase with 0.0097% during 1995-2005. Conversely, runoff and base flow showed an overall increasing trend with 0.0319 and 0.0041% respectively during 1985-1995. In response to the predicted LULC in 2025, the VIC model simulation estimated reduction of ET with 0.0851% with an increase of runoff by 0.051%. Among the vegetation parameters, leaf area index (LAI) emerged as the most sensitive one to alter the simulated water balance. LULC alterations via deforestation, urbanization, cropland expansions led to reduced canopy cover for interception and transpiration that in turn contributed to overall decrease in ET and increase in runoff and base flow. This study reiterates changes in the hydrology due to LULCC, thereby providing useful inputs for integrated water resources management in the principle of sustained ecology. [ABSTRACT FROM AUTHOR]