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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.

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.

Prioritization of river basin in semi-arid to sub-humid tropical region is important in the context of natural resources conservation and management. In this paper, the Gomti River basin was prioritized for soil–water resource conservation based on analysis of morphometric parameters and land use–land cover with RS and GIS techniques. Gomti River is a monsoon and groundwater-fed river; it is a tributary of Ganga River. The basin has been divided into seventeen sub-basins. ASTER (30 m) Digital Elevation Model data and LANDSAT—8 (30 m) satellite imagery were used to analyze the morphometric parameters and to generate land-use–land-cover data for the basin through supervised image classification technique. The linear, areal, and relief aspects of each sub-basins were determined. Morphometric analysis revealed that the basin is a fifth-order drainage system with a dendritic to sub-dendritic drainage pattern. Drainage patterns indicate that sub-surface materials are homogeneous and lack structural control over topography. The circulatory ratio value indicates the basin is an elongated shape. Low values of morphometric parameters indicate good permeability, infiltration, and coarse drainage texture, low relief, and elongated shape indicated good groundwater potential in the basin. The final prioritization result shows that the sub-basin 12 is at the highest priority with the greatest shortage of groundwater potential, so immediate water conservation measures are needed. Contrary, sub-basin 3 is at low priority that indicates the highest groundwater potential. This study suggests the primary priority to improve the water resource management in semi-arid regions at the basin level.

The spatiotemporal study of the glaciers under the changing environment is critical from the freshwater availability, especially in the perennial rivers flowing out of them during the lean season. The Mrigthuni Glacier, one of the major glaciers in the Pindar River basin in Uttarakhand, has been selected as a study glacier for the present analysis. The long-term (1951–2018) meteorological data analysis indicated that the temperature increased in both the maximum ablation and accumulation period; however, the precipitation decreased during the primary accumulation period. The change detected in climate patterns provided an impetus to study its impact on the glacier using geospatial techniques. It was found that the glacier front retreated by 831.4 ± 42 m at the rate of 32.94 m yr−1 from 1990 to 2015. Further, the glacier accumulation area ratio has reduced from 55.63 to 53.22%, with a 66 m upward shift in equilibrium line altitude (ELA). The glacier's mass balance has reduced from 0.23 to 0.28 ± 0.035 m w.e. during the analysis period, based on a general equation developed for northwestern Himalaya using the optical remote sensing data. Due to the limitations of optical data, Synthetic Aperture Radar (SAR) data was used to map glacier radar zones. The distinct percolation/refreeze, transient firn, and ablation zones were identified on the SAR data composite of the different seasons. Considering SAR-based ELA as the most accurate, the analysis confirmed the negative mass balance with a value of 0.62 ± 0.036 m w.e. Therefore, it was concluded that SAR-based analysis might be vital for accurate glacier dynamics studies especially the mass balance.

The catchments of Rishiganga and then Dhauliganga valleys in the Chamoli district of Uttarakhand were impacted by a catastrophic flood triggered due to a massive rockslide, caused by wedge failure on 7th February, 2021. It is estimated that the massive rockslide of ~ 23 million cubic meter volume containing base rock, deposited ice, and snow got detached from the northern slopes of the Trishul mountain range near Ronti Glacier and created a vertical fall of almost 1700 m before severely impacting the Ronti Gad valley located at 1.5 km downstream of Ronti Glacier snout. The huge detached mass of rock and ice (GLIMS ID: G079733E30381N) swiftly moved downstream through the glaciated valley entraining snow, debris, mud on its way, caused rapid fluidization, created massive water/slush waves, and washed away partially or completely the hydel power projects and bridges in its route. It is estimated that ~ 0.93 Peta Joules of potential energy led to the generation of a significant amount of kinetic and thermal energy, good enough to trigger above-mentioned processes. Post-event analysis of high-resolution satellite data shows flood water marks in the valley and on the rock outcrops reaching up to ~ 80–150 m height on the way to Raini Village. The mud and the slush produced through this process led to the formation of a dammed lake and temporarily blocked one of the tributaries of the Rishiganga joining from the northeast. This study provides an insight into the sequence of events as they unfolded, through multi-temporal satellite image analysis, aerial survey, seismological data in conjunction with various other geo-spatial and geo-visualization tools for unraveling the flood event that has happened on February 7, 2021. We also discuss the potential cause of rockslide and the process mechanism of this unique event, causing loss of lives and property besides widespread devastation.

In view of an exponential increase in the negative impacts of flash-floods globally, the present work aims at the identification of flash-floods-prone river reaches in the Beas river basin, Himachal Pradesh, India using a multi-criteria indexing technique. The flood hazard index (FHI) was computed by implementing analytical hierarchy process (AHP) model on 6 hydrologic parameters influencing flood hazard, namely rainfall intensity, curve number (CN) grid, time of travel, slope, Manning's roughness coefficient and drainage density. The CN grid (empirical parameter to estimate direct surface runoff) was used as one of the parameters which depend upon the land use, hydrologic soil group and hydrologic conditions. It is imperative to mention that remote sensing and geographical information system (GIS) techniques played a crucial role in the preparation of these 6 parameter layers. The AHP model calculates the normalized weights for each parameter using pair-wise comparison matrices. The rainfall intensity and curve number were the factors having the highest normalized weight of 34.52 each. Subsequently, the estimated weights of the parameters and hazard level-wise rating scores were used in a GIS environment to generate FHI. The generated FHI raster was masked using floodplain layer within geomorphology map and river buffer to identify flash-floods-affected river reaches. The generated flash-floods map was validated by historical flash-floods ground points, field observations and remote sensing data. The results depicted that the river reaches in the north and east of the Beas basin are susceptible to flash-floods which are mainly governed by heavy rainfall intensity and high runoff characteristics. The river stretches namely Bahang–Manali (Beas), Kullu–Bhuntar (Beas) and Manikaran–Kheer-Ganga (Parvati) have been categorized into very high and high flash-floods zones. Decreasing trend of normalized differential vegetation index (NDVI) was observed for river reaches falling within the very high and high zones indicating the vegetation loss post successive flash-floods events. The river order 2 lies in the very high and high flash-floods zones, indicating the fact that the contribution of tributaries is significant to flood events. Flash-floods map will serve as catastrophic product, which will help policymakers to take suitable measures to reduce the risk of flash-floods.

Many methods and techniques utilize a combination of different bandwidths in the visible, NIR (Near Infrared), and SWIR (Shortwave Infrared) regions for glacier ice mapping. In this study, we investigated and compared various techniques to map the clean ice area of the glaciers using Landsat 8 and Sentinel 2 images. The effectiveness of different techniques and effects of different sensors on the mapping accuracy was also assessed in the Dhauliganga basin of Pithoragarh district, Uttarakhand state of India. Also, the time series composite of Sentinel-1 SAR (Synthetic Aperture Radar) data was used as reference data for estimating the bare or clean glacier ice area. It was reported from the study that clean ice/snow areas mapped using band ratios Red/SWIR and NIR/SWIR from Landsat 8 were overestimated by 4.41% and 4.94% respectively which were larger as compared to Sentinel 2. The most rigorous and well-known technique for glacier mapping, NDSI (Normalized Difference Snow Index) was also checked for both sensors. Clean ice/snow areas mapped from NDSI were found to be 1.35% less as compared to Red/SWIR and 2.62% greater as compared to NIR/SWIR bands of the Landsat 8. However using the same bands from the Sentinel 2, NDSI overestimated 0.67% and 5.27% respectively over both the ratios.

In the present study, Artificial Neural Networks (ANNs) and Genetic Programming (GP) soft-computing models were established to estimate streamflow in Tel River Basin, Odisha, India. In most of the ...

An integrated approach using remote sensing (RS) and geographical information system (GIS) and groundwater modelling (GM) has been used for waterlogged areas identification in the Rohtak district of Haryana State, India. Surface waterlogged areas were delineated using optical remote sensing satellite data-based normalized difference water index (NDWI) technique. Sentinel 2 MSS (optical data) images pertaining to pre-monsoon and post-monsoon seasons were acquired and processed to extract water pixels. To overcome the limitation of false positives and cloud penetration associated with optical images, water pixels were also extracted using synthetic aperture radar (SAR) images of Sentinel 1A. Thresholding of NDWI for optical images and sigma naught for SAR images was done using the respective histograms to distinguish water and terrestrial features. Surface waterlogged areas were delineated from the generated combined water body raster based on the visual interpretation technique in a GIS environment. Sub-surface waterlogging conditions were simulated for the same year using process-based groundwater model MODFLOW. A conceptual model was created to simulate groundwater system based on flow processes, hydrogeological characteristics, aquifer hydraulic properties, source and sinks and boundary conditions. Sub-surface waterlogged areas were delineated based on depth to water table classification criteria. It was found that surface waterlogged area varies from 0.55 to 1.0% of the district area from pre-monsoon to post-monsoon season, while the percentage of sub-surface waterlogged areas was higher, varying from 9.1 to 21.6%, respectively. Statistics also shows that most of the surface waterlogged areas do not fall under the areas plagued by sub-surface waterlogging.

The basin was calibrated through monthly discharge for the period (2002–2008) including 2 years as warm-up (2000–2001), after that model was validated on 5 years of hydrometeorological datasets (2009–2013) at two gauge sites located at Neemsar (upstream gauge) and Lucknow (downstream gauge). It is found that the most sensitive parameter for moisture condition II (CN2) was initial curve number. The p-factor and r-factor were obtained in calibration period at Neemsar 0.73 and 0.58 while at Lucknow values are 0.79 and 0.51, whereas in validation period values are 0.61, 0.45 and 1.22, 0.75, respectively. Three statistical parameters have been used to evaluate the SWAT model performance such as Coefficient of Determination (R 2), Nash–Sutcliff efficiency (NSE), percent bias (PBIAS). The NSE and R 2 values were observed as 0.85, 0.84 and 0.87, 0.86, respectively, in the time of calibration period and values is 0.76, 0.76 and 0.79, 0.83, respectively, in the time of validation period at two above said gauging stations. The PBIAS values during calibration and validation period are − 13.3, − 14.7 and − 4.0, − 15.7, respectively, at the same gauge site which indicates good model performance result.

The LULC change vis-à-vis climate change inherently encompassing human dimensions consequently impact hydrological processes. A slight change in it may affect the water yield, as both are explicitly linked through various hydrological processes. The future availability of water resources largely depends upon planning and management of land use in this changing environment. However, the continuous human interactions keep on modifying the land use land cover (LULC) to fulfil the enhanced demand especially due to significant increase in population and development towards better facilities. These changes consequently impact each and every hydrological process vis-à-vis water availability. It has now become a major concern for water resources planners and managers. Moreover, these changes in LULC pattern along with changing climate put forth a huge challenge in front of them. The present study investigates the capabilities of Variable Infiltration Capacity (VIC) model, which has been developed as soil-vegetation-atmosphere transfer schemes, to assess the runoff potential. Initially, the required model inputs were derived and simulated at the national scale. It was found that the model has assessed the runoff potential of major river basins with high accuracy. The successful implication of the model at the national scale offered an opportunity to carry out a detailed hydrological simulation to study the impact of LULC change on hydrological regime of a basin. For the analysis, the Pennar River Basin, located in Southern part of India, was selected. The LULC change detection analysis showed that there is human induced alteration to LULC pattern, as the area under urban landscape is increasing (0.14%) and natural forest is declining (0.7%). These changes resulted in increase of runoff potential by around 45%. The study on Indian River basin clearly indicates that the LULC change influence and alter the hydrological regime of the river basin. Keywords: Land use land cover change, Runoff potential, Hydrological modeling, Variable infiltration capacity model, Impact assessment

Satellite data are making revolutionary changes in the field of archaeology, and nowadays they have been widely used by the scientific community for regular mapping and monitoring of cultural heritage sites. The development of synthetic aperture radar (SAR) sensors helps in monitoring the heritage site with higher accuracy. This study uses the Persistent Scatter Interferometric SAR (PSInSAR), which is an advanced technique of differential SAR interferometry to find the surface deformation of the Angkor Wat temple and its premises. Seven interferometric data from the Phased Array type L-band Synthetic Aperture Radar (PALSAR) of Advanced Land Observing Satellite-1 (ALOS-1) for the period 2006–2009 and ten interferometric data from the ALOS-2 PALSAR-2 for the period 2014–2018 have been used in this study to identify the deformation pattern. It is found from this study that the Angkor Wat temple and its outer walls are stable.

Climate change can adversely affect the elements of water balance in river basins. This paper studies the effects of climate change on hydro-climatological components of the Gomti River basin using SWAT hydrological model. Model performance has been evaluated through sensitivity analysis, calibration, and validation. During calibration and validation time period, the Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2) values were obtained as 0.86, 0.87, and 0.79, 0.83, respectively. From the sensitivity analysis, it was found that SCS runoff curve number for antecedent moisture condition II (CN2) is the most sensitive parameter, followed by saturated hydraulic conductivity (SOL_K) and then available water capacity of the soil layer (SOL_AWC) etc. To assess the future climate change effects on hydrological variables, MIROC-ESM, MIROC-ESM-CHEM, MIROC_MIROC5, and MOHC_HADGEM2_ES Global Climate Models (GCMs) under RCP 4.5 and RCP 8.5 were applied in the calibrated SWAT model. The following trends were observed after applying the scenarios—the temperature is rising under RCP 4.5 (8.5) scenarios, near-century by + 0.24% (+ 0.65), mid-century by + 2.8% (+ 4.62), and end-century by + 5.25% (+ 10.98), respectively. Precipitation is declining under RCP 4.5 (8.5) by − 29.17% (− 29.65%), − 28.69% (− 28.88%), and − 23.82% (− 20.11%), respectively. Evapotranspiration under RCP 4.5 (RCP 8.5) is increasing by + 3.62% (+ 3.95%), + 4.30% (+ 5.38%), and + 5.49% (+ 6.03%), respectively. Consequently, streamflow under RCP 4.5 (RCP 8.5) is declining by − 31.27% (− 23.99%), − 27.45% (− 28.96%), and − 24.30% (− 18.03%), respectively in near, mid, and end century. The findings will be beneficial for managing future water resources in the Gomti River basin.

Glacier velocity is one of the significant parameter for the assessment of the glacier dynamics, which directly signifies the response of the glacier health with the respect to climate change. The present work focuses on analysing the spatio-temporal characteristics of the surface velocity in the Dhauliganga basin for seven glaciers. The cross-correlation method was applied on the panchromatic scenes of Landsat-7 Enhanced Thematic Mapper Plus (ETM +), Landsat-8 Operational Land Imager (OLI) and Sentinel-2A Multispectral Instrument (MSI) sensors to estimate the velocity. The mean velocity of the seven glaciers along the central flow line ranges from 59.57 to 5.34 m/year while the average of mean velocity ranges from 30.82 to 11.04 m/year during 1993–2018. Whereas, across the flow line, mean velocity ranges from 63.58 to 4.74 m/year. The lowest velocity was observed in the T1–T2 locations near the snout, where the velocity highly dominated by mass loss and debris cover; the error in velocity estimation ranges from ± 3.67 to ± 4.57 m/year. Decreasing trend of surface velocity was observed for all the glaciers. The present work demonstrates the application of cross-correlation technique to monitor the dynamics of a group of glaciers on a basin scale having similar climatic setting. The velocity profiles of various glaciers can be used as input to methods estimating ice thickness and volume and to prioritize the glaciers in view of glacier-dynamics linked events such as surges and retreat induced to rise to pro-glacial lakes and glacier melt contribution to the river flows.

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.

Nowadays, remote sensing (RS) technology under the space programs of the world’s leading agencies provides multispectral optical and microwave data for natural resource mapping of the Earth’s surface. Snow and glacier mapping are critical for the accurate assessment of water resource availability on the Earth’s cryosphere and to quantify the impact of climate change on these cryosphere components. At present, the availability of multispectral remote sensing data is a major source for studying the snow and glaciers from space. The RS approach provides data visualization, interpretation, and assessment of the time series scenario of both snow cover change and glacier dynamics. The mapping of snow is comparatively easier than glacier mapping. Most commonly, the normalized difference snow index (NDSI) band ratio technique has been adopted for snow cover mapping and monitoring. There are various remote sensing-derived snow cover area products available. To overcome the limitations of optical data in terms of cloud presence, the microwave RS data is highly useful for snow cover mapping and snow physical parameters retrieval. However, for snow physical parameters such as snow water equivalent, the scatterometer data incorporating the synthetic aperture radar (SAR) data was used. Recently, semi-automated algorithms are used for glacier mapping separating clean ice and debris cover area. For the Indian Himalayan region, glacier mapping was primarily based on Survey of India (SoI) and Geological Survey of India (GSI) topographic maps ranged on the scale 1:250,000 to 1: 50,000. The innovation of novel geospatial approaches for glacier mapping like manual delineation, band ratios, image segmentation, and classification is based on the multispectral/panchromatic data. However, mapping clean-ice and debris cover of the glacier still has some limitations for automated methods. Automated approaches for glacier mapping dealt with the comparison of different datasets, measurement of glacier change in length, volume, and snout positions by multi-temporal satellite imagery, and digital elevation model. Further, the high-resolution RS data has been extensively used for glacier lake mapping and monitoring. The regular study of glacier lakes is critical for any possible glacier lake outburst flood. In this way, the critical glacier lakes may be identified. It is concluded that geospatial technology plays a significant role in cryosphere studies and analysis from a climate change perspective.

Present study is based on the change in surface area of the glaciers in downstream area of Dhauliganga basin, Pithoragarh district, Uttarakhand. For this study, Survey of India toposheets (surveyed in 1963) have been used for preparation of initial boundary of glaciers. Total 11 glaciers have been selected for the study in downstream valley. RGI (Randolph Glacier Inventory) data version 60. (15_RGI 60.SouthAsiaEast) from GLIMS, released July 28 2017, used for measuring temporal change in surface area. Landsat 8 OLI/TIRS image of 06 November 2016 has used to measure present area of glaciers. ASTER GDEM was used for automatic extraction of basin boundary by hydro-processing methods. Glacier boundaries were manually digitised from the Landsat image for better accuracy. The total glacier area was 69.35 km2 (1963), 48.10 km2 (2001) and 34.35 (2016) as determined from SOI toposheet, GLIMS and the Landsat image of 2016 respectively. Total vacated area by the retreat and melting of glaciers from 1963 to 2016 is 35 km2, which accounts to a total loss of 50 % from the total glaciated area. Google Earth imagery was also considered for marking the actual position of glacier outlines. Ice walls in topographic maps are also considered as the part of glacier but in present satellite image they are free from ice.

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.

High-resolution satellite data is used to extract ice-sheet features in Princess-Astrid Coast of Queen Maud Land, in Droning Maud Land between 70° and 72°S and 5°-20°E, East Antarctica. Their mapping and monitoring is cumbersome and time-consuming using traditional survey methods. Therefore, to achieve desirable results, RS based methods were employed. The main ice-sheet and glacial features mapped are BlueIce-Area (BIA), melt water channels, glacier radar zones, crevasse, nunataks, moraine, supraglacial lakes, and wind scoop. Support-vector-machine (SVM) and supervised classification algorithm were applied over Landsat-8, RISAT-1 and Sentinel-1 data to classify these features. Surface patterns of snow and clouds were found in the continental ice-sheet, which becomes an obstacle to clearly extract sub-surface icesheet features in optical data. Therefore, to improve mapping of snow and ice features, high-resolution microwave data was also used. By comparing optical and microwave data, it was found that more sub-surface features could be mapped using microwave data. Further, RS was used to map the temporal change in the glacial features using two-year images for the austral summer of 2016 and 2017. It was found that diurnal as-well-as seasonal changes in surface ice features occur due to changes in local weather and can be mapped using temporal RS data.

Cryosphere studies are very critical for understanding the behaviour of the global climate system. The cryosphere components such snow cover, glacier ice, ice sheets, icebergs, etc. need to be studied, from Earth’s energy and water balance point of view. However, their quantification and mapping is tedious on field using tradition survey methods. This review paper summarizes the major research work done in field of remote sensing based cryosphere studies in Indian Himalaya and Polar Regions. The traditional survey methods using terrestrial photogrammetry and aerial photography for snow and glacier studies are presented, initially. Then, remote sensing methods of snow and glacier mapping using visible, infrared and thermal spectral bands are presented. Later, the application of these techniques and method in Indian conditions is discussed. The advanced methods of microwave sensors based inversion models for snow physical properties retrieval are also explained. The separate sub-sections are given to highlight the use of remote sensing in glacier and polar studies. In each section, the current status and advances of the technology are discussed. The future prospects of remote sensing technology for each cryosphere theme are highlighted with emphasis to Indian scenario.

Monitoring and assessment of hydrological parameters are the key elements for the sustainable development of water resources of any country. The various components of the hydrological cycle also known as hydrological parameters are highly dynamic in space and time. Quantification of hydrological parameters using traditional methods provides limited, point based, information which is not sufficient for assessing spatio-temporal variations in these parameters. Satellite based remote sensing has proven its usefulness in effective mapping/retrieval and monitoring of hydrological parameters such as precipitation, interception, soil moisture, surface runoff, water level and river flow, evapotranspiration, change in terrestrial water storage, etc. This review paper highlights the major work done in India for estimation of hydrological parameters using remote sensing. The basics of retrieval techniques, their applications in India, their validation and limitations are discussed in this paper. The progress of each technique from conventional optical remote sensing based to advance microwave remote sensing based hydrological parameters estimation has been presented. The integration of remote sensing derived hydrological parameters in water balance and land surface model is also presented.

Climatic changes alter the climate system, leading to a decrease of glacier mass volumes and swelling glacial lakes. This study provides a new inventory of glacial and high-altitude lakes for Sikkim, Eastern Himalaya, and evaluates the susceptibility of lakes to Glacial Lake Outburst Flood (GLOF). By using satellite data of high spatial resolution (5 m), we obtain 1104 glacial and high-altitude lakes with total area 30.498 km 2 , of which 472 have an area > 0.01 km 2 . Applying pre-defined GLOF susceptibility criteria on these 472 lakes yields 21 lakes susceptible to GLOF, which all increased in area from 1972–2015. Using Analytic Hierarchy Processes (AHP), the pairwise comparison matrix further reveals that 5 of these glacial lakes have low, 14 have medium and 2 have high GLOF susceptibility. Especially these 16 glacial lakes with high and medium GLOF susceptibility may threaten downstream communities and infrastructure and need further attention.

This study introduces about the parameterization of hydrological modelling for Asan and Song river basin the whole Doon Valley. SWAT an empirical hydrological model, VIC a physical hydrological model and HEC-HMS a semi distributed hydrological model are used for flood peak generation at predetermined locations. The land cover mapping of Doon Valley was attempted using remotely sensed images of Landsat and Google Earth imagery. The specific objectives are hydrological modelling for peak flow hydrograph generation, to observe LULC change scenarios between 1995, 2005 and 2014 year, comparison and validation of the simulated runoff using three different hydrological models (VIC, SWAT and HEC-HMS). The VIC model performance was found good and a close agreement between the observed and simulated values was obtained for 2014 LULC map. Model performance was also found good for other subbasins. The various input parameters are the meteorological data, discharge and sediment data were processed as per requirement of the SWAT model. The model was calibrated for the year 2006 to 2010. The Hydrological modeling indicates that the curve number is most influence parameter into the total discharge. Land use and vegetative cover play an important role in watershed runoff and stream flow discharge patterns over time, including peak flows. Increased human interventions have caused rapid transitions in land cover, adversely affecting the watershed processes and hydrological cycle in the long run. It may be concluded that the impact of land cover changes are most pronounced during low flows and that during high flows, role of land cover becomes comparatively less.

Indian scientists have been involved in studies of cryosphere in Polar Regions from past 35 years. For continuous monitoring and expanding research in the fields of atmospheric science, geosciences, glaciology, environmental sciences, etc. specific to these regions, the ESSO - National Centre for Antarctic and Ocean Research (ESSO-NCAOR) has established three permanent research stations in Antarctica. This paper addresses efforts by Indian scientists in last five years in cryospheric studies on the Antarctica using remote sensing data. Inventories of Antarctic glaciers and ice sheet features prepared by Indian researchers have facilitated for detailed long-term studies on glacier dynamics, sea ice, fluctuations of the continental ice margin and snouts of glaciers. For safe and optimal navigation of ships, a sea ice advisory has been also set up. This paper also addresses recent efforts of using high-resolution earth observation satellite data which were acquired for geospatial mapping of cryospheric features and glacial landforms and for delineation of wind induced snow deposition zones in part of the Antarctica. Spatiotemporal dynamics of surface melting over Antarctic was further studied by using moderate resolution satellite data.

The water resources status and availability of any river basin is of primary importance for overall and sustainable development of any river basin. This study has been done in Beas river basin which is located in North Western Himalaya for assessing the status of water resources in present and future climate change scenarios. In this study hydrological modelling approach has been used for quantifying the water balance components of Beas river basin upto Pandoh. The variable infiltration capacity (VIC) model has been used in energy balance mode for Beas river basin at 1km grid scale. The VIC model has been run with snow elevation zones files to simulate the snow module of VIC. The model was run with National Centre for Environmental Prediction (NCEP) forcing data (Tmax, Tmin, Rainfall and wind speed at 0.5degree resolution) from 1 Jan. 1999 to 31 Dec 2006 for calibration purpose. The additional component of glacier melt was added into overall river runoff using semi-empirical approach utilizing air temperature and glacier type and extent data. The ground water component is computed from overall recharge of ground water by water balance approach. The overall water balance approach is validated with river discharge data provided by Bhakra Beas Management Board (BBMB) from 1994-2014. VIC routing module was used to assess pixel wise flow availability at daily, monthly and annual time scales. The mean monthly flow at Pandoh during study period varied from 19 - 1581 m3/s from VIC and 50 to 1556 m3/sec from observation data, with minimum water flow occurring in month of January and maximum flow in month of August with annual R2 of 0.68. The future climate change data is taken from CORDEX database. The climate model of NOAA-GFDL-ESM2M for IPCC RCP scenario 4.5 and 8.5 were used for South Asia at 0.44 deg. grid from year 2006 to 2100. The climate forcing data for VIC model was prepared using daily maximum and minimum near surface air temperature, daily precipitation and daily surface wind speed. The GFDL model also gives validation phase scenarios from 2006 to 2015, which are used to test the overall model performance with current data. The current assessment made by hydrological water balance based approach has given reasonable good results in Beas river basin. The main limitation of this study is lack of full representation of glacier melt flow using fully energy balance model. This component will be addressed in coming time and it will be integrated with tradition hydrological and snowmelt runoff models. The other limitation of current study is dependence on NCEP or other reanalysis of climate forcing data for hydrological modelling, this leads to mismatch between actual and simulated water balance components. This problem can be addressed if more ground based and fine resolution grid based hydro meteorological data are used as input forcing data for hydrological modelling.

Snow physical properties, snow cover and glacier facies are important parameters which are used to quantify snowpack characteristics, glacier mass balance and seasonal snow and glacier melt. This study has been done using C-band synthetic aperture radar (SAR) data of Indian radar imaging satellite, radar imaging satellite-1 (RISAT)-1, to estimate the seasonal snow cover and retrieve snow physical properties (snow wetness and snow density), and glacier radar zones or facies classification in parts of North West Himalaya (NWH), India. Additional SAR data used are of Radarsat-2 (RS-2) satellite, which was used for glacier facies classification of Smudra Tapu glacier in Himachal Pradesh. RISAT-1 based snow cover area (SCA) mapping, snow wetness and snow density retrieval and glacier facies classification have been done for the first time in NWH region. SAR-based inversion models were used for finding out wet and dry snow dielectric constant, dry and wet SCA, snow wetness and snow density. RISAT-1 medium resolution scan-SAR mode (MRS) in HV polarization was used for first time in NWH for deriving time series of SCA maps in Beas and Bhagirathi river basins for years 2013–2014. The SAR-based inversion models were implemented separately for RISAT-1 quad pol. FRS2, for wet snow and dry snow permittivity retrieval. Masks for layover and shadow were considered in estimating final snow parameters. The overall accuracy in terms of R2 value comes out to be 0.74 for snow wetness and 0.72 for snow density based on the limited ground truth data for subset area of Manali sub-basin of Beas River up to Manali for winter of 2014. Accuracy for SCA was estimated to be 95 % when compared with optical remote sensing based SCA maps with error of ±10 %. The time series data of RISAT-1 MRS and hybrid data in RH/RV mode based decompositions were also used for glacier radar zones classification for Gangotri and Samudra Tapu glaciers. The various glaciers radar zones or facies such as debris covered glacier ice, clean or bare glacier ice radar zone, percolation/refreeze radar zone and wet snow, ice wall etc., were identified. The accuracy of classified maps was estimated using ground truth data collected during 2013 and 2014 glacier field work to Samudra Tapu and Gangotri glaciers and overall accuracy was found to be in range of 82–90 %. This information of various glacier radar zones can be utilized in marking firn line of glaciers, which can be helpful for glacier mass balance studies.

The snow cover plays an important role in Himalayan region as it contributes a useful amount to the river discharge. So, besides estimating rainfall runoff, proper assessment of snowmelt runoff for efficient management and water resources planning is also required. A Land Surface Model, VIC (Variable Infiltration Capacity) is used at a high resolution grid size of 1 km. Beas river basin up to Thalot in North West Himalayas (NWH) have been selected as the study area. At first model setup is done and VIC has been run in its energy balance mode. The fluxes obtained from VIC has been routed to simulate the discharge for the time period of (2003-2006). Data Assimilation is done for the year 2006 and the techniques of Data Assimilation considered in this study are Direct Insertion (D.I) and Ensemble Kalman Filter (EnKF) that uses observations of snow covered area (SCA) to update hydrologic model states. The meteorological forcings were taken from 0.5 deg. resolution VIC global forcing data from 1979-2006 with daily maximum temperature, minimum temperature from Climate Research unit (CRU), rainfall from daily variability of NCEP and wind speed from NCEP-NCAR analysis as main inputs and Indian Meteorological Department (IMD) data of 0.25 °. NBSSLUP soil map and land use land cover map of ISRO-GBP project for year 2014 were used for generating the soil parameters and vegetation parameters respectively. The threshold temperature i.e. the minimum rain temperature is -0.5°C and maximum snow temperature is about +0.5°C at which VIC can generate snow fluxes. Hydrological simulations were done using both NCEP and IMD based meteorological Forcing datasets, but very few snow fluxes were obtained using IMD data met forcing, whereas NCEP based met forcing has given significantly better snow fluxes throughout the simulation years as the temperature resolution as given by IMD data is 0.5°C and rainfall resolution of 0.25°C. The simulated discharge has been validated using observed data from BBMB (Bhakra Beas Management Board) and coefficient of Correlation(R2) measured for (2003-2006) was 0.67 and 0.61 for the year 2006.But as VIC does not consider snowmelt runoff as a part of the total discharge, snowmelt runoff has been estimated for the simulation both with and without D.A. The snow fluxes as generated from VIC gives basin average estimates of Snow Cover, SWE, Snow Depth and Snow melt. It has been observed to be overestimated when model predicted snow cover is compared with MODIS SCA of 500 m resolution from MOD10A2 for each year. So MODIS 8-day snow cover area has been assimilated directly into the model state as well as by using EnKF after every 8 days for the year 2006.D.I Technique performed well as compared to EnKF. R2 between Model SCA and MODIS SCA is estimated as 0.73 after D.I with Root Mean Square Error (RMSE) of +0.19. After direct Insertion of D.A, SCA has been reduced comparatively which resulted in 7% reduction of annual snowmelt contribution to total discharge.The assimilation of MODIS SCA data hence improved the snow cover area (SCA) fraction and finally updated other snow components.

Extreme precipitation events are responsible for major floods in any part of the world. In recent years, simulations and projection of weather conditions to future, with Numerical Weather Prediction (NWP) models like Weather Research and Forecast (WRF), has become an imperative component of research in the field of atmospheric science and hydrology. The validation of modelled forecast is thus have become matter of paramount importance in case of forecasting. This study delivers an all-inclusive assessment of 5 high spatial resolution gridded precipitation products including satellite data products and also climate reanalysis product as compared to WRF precipitation product. The study was performed in river basins of North Western Himalaya (NWH) in India. Performance of WRF model is evaluated by comparing with observational gridded (0.25° × 0.25°) precipitation data from Indian Meteorological Department (IMD). Other products include TRMM Multi Satellite Precipitation Analysis (TMPA) 3B42-v7 product (0.25° × 0.25°) and Global Precipitation Measurement (GPM) product (0.1° × 0.1°). Moreover, climate reanalysis rainfall product from ERA Interim is also used. Bias, Mean Absolute Error, Root Mean Square Error, False Alarm Ratio (FAR), Probability of False Detection (POFD), and Probability of Detection (POD) were calculated with particular rainfall thresholds. TRMM and GPM products were found to be sufficiently close to the observations. All products showed better performance in the low altitude areas i.e. in planes of Upper Ganga and Yamuna basin and Indus basin, and increase in error as topographical variation increases. This study can be used for identifying suitability of WRF forecast data and assessing performance of other rainfall datasets as well.

Flood is one of the most the most re-occurring natural hazard in the state of Bihar, as well as in India. The major rivers responsible for flood in the state of Bihar are Kosi, Gandak, Ghagra and Bagmati, which are the tributary rivers of Ganges. The head water catchment area of these rivers lies in the Himalayan state of Nepal. The high rainfall in Nepal, siltation of hydraulic structures, rivers and low topography of North Bihar causes flood occurrence in these areas on regular basis. Remote sensing and GIS plays an important role in mapping, monitoring and providing spatial database for all flood related studies. The present work focuses on the use remote sensing based topography and images in GIS environment for integrated flood study of Bagmati River, which is one of the most flood prone rivers of North Bihar. The Digital Elevation Model (DEM) from shuttle radar topography mission (SRTM) was used to create detailed sub-basin and river network map of entire Bagmati basin. The floods of July–August 2002 were mapped using RADARSAT-1 data using threshold based method. The SRTM DEM and ground based river cross-section from Dheng to Benibad stretch of Bhagmati River were used to create 1-dimensional hydrodynamic (1-D HD) model for simulating flood water level, discharge and flood inundation. Validation of simulated flood flows was done using observed water level of central water commission (CWC) from Dheng to Runisaidpur stations, with coefficient of correlation of 0.85. Finally, an integrated framework for flood modelling and management system is proposed.

The Himalayas are one of the largest reservoirs of freshwater in the form of glaciers and snow outside the Polar region (Mani 1981). There are around 32,392 glaciers, covering an area of about 71,182 km2 in the Indian part of the Himalaya (SAC 2011). Among all, North Western Himalaya (NWH) has the largest area under seasonal and perennial snow cover. This snow/glacier melt contributes significantly to perennial rivers like the Ganga and the Indus during lean time. The Indus Basin is comprised of Chennab, Jhelum, Rawi, Satluj and Beas River subbasins, whereas Upper Ganga Basin is comprised of Bhagirathi, Alaknanda, Mandakini, Dhauliganga and Pindar subbasins. Moreover, these basins have huge hydropower potential, which is a matter of concern during lean period (Kasturirangan et al. 2013).

Himalaya is also known as the “third pole” of the Earth due to the presence of the largest area and volume of seasonal snow and glacier ice outside the polar regions. Most visible effects of climate change are found in this region (Immerzeel et al. 2010; IPCC-5 2014 WGII AR5 Section 28.3). The Indian states of Uttarakhand (UK), Himachal Pradesh (HP) and Jammu and Kashmir (JK National Remote Sensing Centre 2013). This chapter highlights remote sensing (RS) and geographical information system (GIS)-based studies of major components of NWH cryosphere such as seasonal SC, GI, GL and permafrost. This also includes subsections for mapping, monitoring and quantification of SC, GI in NWH along with retrieval and modelling of snowpack properties, snowmelt and glacier mass balance.

Northwest Himalaya (NWH) has unique topographical and climate settings which makes this area prone to various types of hydrometeorological hazards such as flash floods, hail storms, glacier lake outburst floods, avalanches and mudflows. These hazards have high probability of turning into natural disasters if proper planning of natural resources, infrastructure and man-made structures is not done. Floods of June 2013 in Uttarakhand (Dobhal et al. 2013; Thakur et al. 2014) and 2014 floods of Srinagar (Bhatt et al. 2016) are prime examples of such hazards turning into the major disasters. Northwest Himalayan states in the last few years have experienced large number of hydrometeorological disasters such as high-intensity precipitation, cloud burst and subsequent flash flooding in downstream areas, snow avalanches, glacier lake outburst floods (GLOF), hail storms, drought and rainfall-induced mudflows (Kumar et al. 2015; Gupta et al. 2013; Kumar et al. 2012; Rana et al. 2012). This chapter gives an overview of various hydrometeorological hazards which are reoccurring in NWH and provides insights in few such hazards by providing some actual case studies related to such hazards.

The present study aims to investigate the impact of climate change on water availability and hydrological extremes in the Krishna River basin, the second largest eastward draining river of Peninsular India. The hydrological response of the basin for the past observed climatic data (1985–2005) and future climatic scenarios (RCP 4.5 and RCP 8.5, respectively, for 2006–2099) is simulated using the Variable Infiltration Capacity (VIC) model. The soil, vegetation, topographic, and meteorological inputs for the model are derived from remote sensing and field-observed data. The model calibration is performed using observed discharge data at 4 gauging stations for the time period of 21 years (1985–2005); the coefficients of determination (R2) are in the range of 0.81–0.95. The model validation is carried out at the Vijayawada station (R2 = 0.82), near the basin outlet. The meteorological forcing consisting of future climatic inputs for the entire century (2006–2099) for RCP 4.5 and RCP 8.5 scenarios extracted from IITMRegCM4-4 predictions are used to simulate the future hydrological regime of the basin. The hydrological response analysis shows increase in annual discharge by 13.8 and 27.8 cumec under RCP 4.5 and RCP 8.5, respectively. The hydrological extreme events are also found to increase under RCP 4.5 and RCP 8.5 scenarios as compared with the past records of 1985–2005. The peak discharge is observed to increase in the range of 57.7–76.8 and 68.5–77.5% under RCP 4.5 and RCP 8.5, respectively. The study highlights that the annual water potential and hydrological extremes in the Krishna basin will increase under the future climatic scenarios.

Due to the penetration capacity of synthetic aperture radar (SAR) data through clouds and hazy atmospheric circumstances like fog, smog, light rain, mist etc., it has ability to continuous observation of flood events for producing accurate, rapid and cost effective flood mapping. A study using time series RADARSAT SAR images in flood water detection, monitoring of spatial extent and propagation of flood inundation were described and analysed in this paper. The SAR images were first calibrated, geometrically corrected and filtered. Afterward, threshold method was applied to extract the inundated areas from the SAR images. In threshold method, density slicing technique was used to separate the open water and non-water (land) areas from the images. Later, to delineate the actual flooded area, permanent water bodies (e.g. river, lake, ponds etc.) were subtracted from the open water. Flood maps were super-imposed and analysed to find out the nature of spatial extent, duration of flood and to show how flooding spread through time. This study illustrates that the SAR data along with GIS can be used effectively for flood water mapping, monitoring and analysing the propagation of flood water in a flood prone area. Therefore, the findings of this study will help to take initiative to reduce the flood hazard impact and increase the flexibility in the process of flood management. Keywords: SAR data, GIS, Flood mapping, Flood extent, Flood duration

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.

In the present study, behavior of the SARAL/AltiKa (Satellite with ARgos and ALtiKa) waveforms over Maithon Reservoir (∼65 km2 of surface area), Jharkhand, India, has been studied. The estimated water level has been compared with the in situ measurements 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 the in-situ measurements 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 ...

Summary This study monitors the great Himalayas between the year 1998–2008 using satellite data. The Landsat satellite data was used to monitor variations in the area of glacier. Further the snow-covered area (SCA) of the part of Alaknanda basin was computed both for the winter and the summer season. The analysis for the same was done between 1998 and 2008. It was observed that the amount of decrease in the SCA was more in winter season compared to summer season, which also shows the rate of retreat of glacier. This study also classifies the snow into two categories (1) dry snow and (2) wet snow. The pattern in the change in area of these two categories was analysed both for the winter and summer season.

The sustainability of water resources mainly depends on planning and management of land use; a small change in it may affect water yield largely, as both are linked through relevant hydrological processes, explicitly. However, human activities, especially a significant increase in population, in-migration and accelerated socio-economic activities, are constantly modifying the land use and land cover (LULC) pattern. The impact of such changes in LULC on the hydrological regime of a basin is of widespread concern and a great challenge to the water resource engineers. While studying these impacts, the issue that prevails is the selection of a hydrological model that may be able to accommodate spatial and temporal dynamics of the basin with higher accuracy. Therefore, in the present study, the capabilities of variable infiltration capacity hydrological model to hydrologically simulate the basin under varying LULC scenarios have been investigated. For the present analysis, the Pennar River Basin, Andhra Pradesh, which falls under a water scarce region in India, has been chosen. The water balance components such as runoff potential, evapotranspiration (ET) and baseflow of Pennar Basin have been simulated under different LULC scenarios to study the impact of change on hydrological regime of a basin. Majorly, increase in built-up (13.94% approx.) and decrease in deciduous forest cover (2.44%) are the significant changes observed in the basin during the last three decades. It was found that the impact of LULC change on hydrology is balancing out at basin scale (considering the entire basin, while routing the runoff at the basin outlet). Therefore, an analysis on spatial variation in each of the water balance components considered in the study was done at grid scale. It was observed that the impact of LULC is considerable spatially at grid level, and the maximum increase of 265 mm (1985–2005) and the decrease of 48 mm (1985–1995) in runoff generation at grid were estimated. On the contrary, ET component showed the maximum increase of 400 and decrease of 570 mm under different LULC change scenario. Similarly, in the base flow parameter, an increase of 70 mm and the decrease of 100 mm were observed. It was noticed that the upper basin is showing an increasing trend in almost all hydrological components as compared to the lower basin. Based on this basin scale study, it was concluded that change in the land cover alters the hydrology; however, it needs to be studied at finer spatial scale rather than the entire basin as a whole. The information like the spatial variation in hydrological components may be very useful for local authority and decision-makers to plan mitigation strategies accordingly.

In recent years the microwave remote sensing using Synthetic Aperture Radar (SAR) has immerged as a great technique for snow and glacier related studies. Due to the penetration power of the microwave inside the dry snow cover, and property of interacting with it dielectrically, focuses the researcher's attention in developing a SAR based robust method for retrieval of various snow parameters. Snow cover regions are mostly covered with clouds and hazy weather. SAR provides all weather, day-night space borne data in the nearly meter range resolution, even for those areas which are mostly covered with clouds and haze whole year operating in the long wavelength region. Various studies based on different backscatter based models like IEM and Small perturbation model have been done for the calculating the snow properties. Different semi-empirical model based techniques [1] also been implemented in the past which are region dependent and provides good accuracy for a given area only. This study focuses on developing a PolInSAR based technique for finding various snow parameters, mainly snow depth and snow water equivalent. The high resolution X-band spaceborne data has been used for this study. The Polarimetric SAR Interferometric technique provides us opportunity to utilize both polarimetric and interferometric properties of the SAR data for snow parameter retrieval with high accuracy. The coherence amplitude method is used for snow depth retrieval. The ground data was acquired by the ground station of SASE, DRDO in the Dhundi region of Manali, Himachal Pradesh for the same dates of Space borne TerraSAR-X acquisitions

Author(s): Singh, SK; Jain, G; Siddiqui, A; Naik, S; Rathore, BP; Garg, V; Snehmani; Kumar, V; Bahuguna, IM; Sharma, SA; Shekhar, C; Thakur, PK; Mishra, K; Kumar, P; Painter, TH; Dozier, J | Abstract: 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.

Climate change and its impact on hydrological processes are causes for widespread concern and challenge. In this regard, large numbers of global and regional circulation models (GCMs and RCMs) have been developed to study the future climate. However, these GCMs and RCMs have large uncertainties in defining climate scenarios. The uncertainties associated with these models provided an opportunity to investigate the impact of climate change on the runoff potential of a major basin in India under different assumed plausible hypothetical scenarios. These scenarios were developed by increasing the temperature by 1°C, 2°C and 3°C and rainfall by 5%, 10% and 15%, and then combinations of both. Understanding the hydrologic response of very large river basins again poses a huge challenge to hydrologists. Therefore, an attempt has been made to exploit the capabilities of a variable-infiltration-capacity macro-scale hydrological model to simulate the Satluj river basin. It was found that a slight change in climate ma...

The current study has used Synthetic Aperture Radar (SAR) satellite data to estimate the Snow Cover Area (SCA) in Manali watershed of Beas River in Northwest Himalayas of Himachal Pradesh, India. SAR data used in this study is of Radarsat-2 (RS2) and Environmental Satellite (ENVISAT), Advanced Synthetic Aperture Radar (ASAR). The SAR preprocessing was done with SAR image processing tools for converting raw SAR images into calibrated geo-coded backscatter images. Maps for forest, built area, layover and shadow were created and used for masking snow cover in these areas. The backscattering ratio of wet snow to reference image threshold method with value range from −2 to −3 db was used to estimate wet SCA for study area. In this technique, if the threshold is too high (≥-2 db) wet SCA is overestimated and if it is too low (≤-3db), this method underestimates the SCA. The wet SCA is under/over estimated (+6 % to−8 % on average) in late spring season due to the inherent terrain and SAR imaging effects of layover/foreshortening and shadow and also due to the masking of forest areas. Overall, the SCA derived from SAR data matches well when compared with total SCA derived from cloud free optical remote sensing data products, especially during wet season.

The Indian Space Research Organisation (ISRO) and the Centre National d'etudes Spatiales (CNES) jointly launched SARAL/AltiKa (Satellite with ARgos and ALtiKa) in February 2013. AltiKa is the first mono frequency (Ka-band) radar altimeter with dual frequency radiometer. SARAL/AltiKa promises reliable results on retrieving water level of inland water and coastal bodies, though recognition pattern as well as interpreting and modeling of AltiKa waveforms at land water boundary is still a challenge. Different Retracking methods are widely used for determining the water level more correctly. An altimetry waveform also gives vital information about the reflecting surface. So, waveform classification is many times needed for retrieving surface information or before applying retracking method. In this paper, SARAL/AltiKa 40 Hz waveform dataset (Pass #152) over the Maithon Reservoir, Jharkhand, India were classified using evolutionary minimize indexing function (EMIF) with k-means. A fitness function was used in EMIF to map sampled AltiKa waveforms into single valued scalar. Four waveform groups were identified according to reflection from water, land and land-water boundary. Land-water boundary again divided into two classes viz., land-to-water and water-to-land based on direction of the AltiKa pass over the reservoir. Normalized Differenced Water Index (NDWI) derived from Landsat 8 OLI and Google Earth imagery of nearest date of AltiKa pass was used for accuracy assessment of the proposed method. It was found that the waveforms were classified with 85.7 kappa accuracy. The results of the proposed EMIF will be helpful for identify the SARAL/AltiKa waveforms classes over the inland water bodies.

Ice sheet features, glacier velocity estimation and glacier zones or facies classification are important research activities highlighting the dynamics of ice sheets and glaciers in Polar Regions and in inland glaciers. The Cband inSAR data is of ERS 1/2 tandem pairs with one day interval for spring of 1996 and L-band PolinSAR data of ALOS-PALSAR-2 for spring of 2015 is used in glacier velocity estimation. Glacier classification is done using multi-temporal C-and L-band SAR data and also with single date full polarization and hybrid polarization data. In first part, a mean displacement of 9 cm day-1 was recorded using SAR interferometric technique using ERS 1/2 tandem data of 25-26 March 1996. Previous studies using optical data based methods has shown that Gangotri glacier moves with an average displacement of 4 cm and 6 cm day-1. As present results using ERS 1/2 data were obtained for one day interval, i.e., 25th March 05:00pm to 26th March 05:00 pm, 1996, variation in displacement may be due to presence of snow or wet snow melting over the glacier, since during this time snow melt season is in progress in Gangotri glacier area. Similarly the results of glacier velocity derived using ALOSPALSAR- 2 during 22 March – 19 April 2015 shows the mean velocity of 5.4 to 7.4 cm day-1 during 28 day time interval for full glacier and main trunk glacier respectively. This L-band data is already corrected for Faraday’s rotation effects by JAXA, and tropospheric correction are also being applied to refine the results. These results are significant as it is after gap of 20 years that DInSAR methods has given glacier velocity for fast moving Himalayan glacier. RISAT-1 FRS-1 hybrid data is used to create Raney’s decompositions parameters, which are further used for glacier zones classification using support vector machine based classification method. The Radarsat-2 and ALOS-PALSAR-2 fully polarized data of year 2010 and 2015 are also used for glacier classification. The identified and classified glaciers zones in Gangotri area are debris covered ice, clean ice, percolation zone, wet snow zone, ice wall, supra-glacier lakes and moraines, similarly ice sheet features and glacier landforms such as such as nunataks, wind scoop, glacier flow paths, moraine, horn, sastrugi, and crevasses were identified in Antarctic. RISAT-1 FRS-1 data was also successful in mapping the Crevasses hidden under wind-blown ice in Antarctic’s study area.

Climate change, whether as a natural cycle variability and/or due to anthropogenic reasons, is affecting and likely to further affect the water resources, which is a vital necessity for existence of life form. The predicted intensification of hydrological cycle would change all of its constituents both in time and space domain. This is a long term phenomenon and the necessity is to understand the intensity of the effects on various aspects of water resources by way of scientific studies backed by the available field data. Therefore, in the present study, the impact of climate and land use land cover change on entire India under different assumed plausible hypothetical scenarios has been studied. These scenarios were developed by increasing; temperature by 1, 2 and 30C; rainfall by 5, 10 and 15%; and then the combination of both. To carry out this analysis, variable infiltration capacity (VIC) semi-distributed macroscale hydrological model has been investigated. It was found that slight change in climate may pose huge difference on hydrological cycle and its component.

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.

The main source to fulfill the enormous needs of water both for domestic and agricultural purposes in the densely cultivated region of Yamuna Nagar district of Haryana (India) is the water under earth. Since enough quantity of good quality water has been readily available, the water quality concerns are often neglected. In the present study analysis of the geochemical characteristics of groundwater to assess its suitability for domestic and irrigation purposes has been done. Fifty-five samples were collected in the months of June (pre-monsoon) and October (post-monsoon) from the bore wells. These samples were analysed for various parameters and were compared with various national and international standards to determine the suitability of water for domestic and irrigation use. The thematic maps for hydrogen ion concentration (pH), total dissolved solids (TDS), total hardness (TH), electric conductivity (EC), sodium adsorption ratio (SAR), percent sodium (Na%) and residual sodium carbonate (RSC) were prepared in GIS environment. These maps were further classified as per given standards to study the spatial variations of quality parameters and their suitability for drinking and irrigation purposes. Investigations revealed that groundwater in general was hard for domestic use. However it was within the safe limits for drinking. Furthermore groundwater quality was well within the desirable to permissible limits for irrigation purpose.