The seasonal snow cover and permanent ice in form of Himalayan glaciers provide fresh water to many perineal rivers of Himalayas. The melt water from seasonal snow and glaciers, especially during of 15 March to 15 June acts as important source of water for drinking, hydropower and irrigation requirements of many areas in North India. This work has highlights the use of C-band Synthetic Aperture Radar (SAR) data from RISAT-1, Sentinel-1A and 1B satellites and ALOS-PALSAR-2 PolInSAR data for snow cover and glacier dynamics study for parts of North West Himalaya. Glacier velocity was derived using InSAR based method using 6 day temporal interval images from Sentinel-1 satellites and 14 day interval for PALSAR-2 satellite. High coherence was obtained for main glacier in both the data sets, which resulted accurate line of site (LOS) glacier velocity estimates for test glaciers. These InSAR data glacier velocity results are obtained after a gap of 21 years. Glacier facies was estimated using multi-temporal SAR image composition based classification. All these maps were verified by extensive ground surveys done at these sites during 2014–2017. The time series data of C-band SAR in VV/VH polarisation was also used to map snow cover in test basins of Bhagirathi and Beas River. The VV/VH data clearly shows difference between dry and wet snow, thus helping in improved snow cover mapping using SAR data. This study will help in refining algorithms to be used for such studies using upcoming NASA-ISRO SAR (NISAR) mission.

In all mesoscale models with urban parameterizations, urban area represented as a single entity to represent the influence of urban morphology. In the last few years, many Urban Canopy Models (UCM) have been developed by many researchers to model the urban energy fluxes, but their spatial resolution is too coarse. These models proves to be a hindrance in obtaining improved results for urban climatic studies due to their coarser resolution. So downscaling of climatic variables in an urban area is primary significance for urban climatic studies. Weather Research Forecasting Model (WRF) is the one of the models that has been used widely for downscaling the climatic variables at urban scale and it has been also integrated with UCM along with a number of urban sub physics options. In this study, modified high resolution Land Use Land Cover (LULC) representing three urban classes for the city of Chandigarh has been ingested into the model to examine and validate the model output with respect to ground observations. The model has been configured with two domains with a resolution of 3KM and 1KM and simulations were carried out for three days of the of four seasons of India, winter, summer, monsoon and post-monsoon for the analysis of seasonal variation. Improved values of Root Mean Square Error (RMSE) for surface temperature, relative humidity and wind speed was observed with modified high resolution LULC with BEM option as compared to single urban built up class. In terms of temperature, summer season showed very less RMSE than other seasons, i.e, 0.76 °C and . In terms of relative humidity, monsoon season showed very less RMSE than other seasons, i.e., 2.63% and in terms of wind speed, post monsoon season is giving less RMSE i.e., 1.01 m/s.

The monitoring of inland water and continental ice sheets is very important from water management and global climate related studies. The current study utilizes the SGDR data from Saral-Altika during 2013–2017 to estimate and monitor water level in 24 major reservoirs of India. The R² value for majority of reservoirs was more than 0.99 and RMSE error value also was less than 0.40 m. In addition, wide rivers of India such as Mahanadi River, was also monitored using Altika data covering part of Mahanadi River from Khairmal to Naraj gauging sites during 2013–2016 time period. One dimensional hydro-dynamic (1D-HD) model was setup for this part of river to generate river Discharge at virtual gauge. The part of Antarctic ice sheet South of Indian research station Maitri, East Antarctica, was studied for ice sheet elevation changes using ground based stake network as well as space based altimeter/LIDAR datasets during 2003–2017 time period. 2003–2009 time was used for getting elevation changes using Icesat-1 level 2 altimetry product, and Geophysical Data Record (GDR) data from Altika was used with slope correction from 2013–2016 time period. An extensive network of ground based stake networks were used for validating the derived elevation changes. The ice sheet and glacier line of site velocity was estimated using Sentinel-1 based InSAR data with 6 to 12 day time interval data sets for year 2016 and 2017. The derived glacier velocity was comparable with optical image (Landsat-8) based glacier velocity for same year and also with historical Radarsat-1 based glacier velocity results.