Hydrological processes are complex to compute in hilly areas when compared to plain areas. The governing processes behind runoff generation on hillslopes are subsurface storm flow, saturation excess flow, overland flow, return flow and pipe storage. The simulations of the above processes in the soil matrix require detailed hillslope hydrological modelling. In the present study, a hillslope experimental plot has been designed to study the runoff generation processes on the plot scale. The setup is designed keeping in view the natural hillslope conditions prevailing in the Northwestern Himalayas, India where high intensity rainfall events occur frequently. A rainfall simulator was installed over the experimental hillslope plot to generate rainfall with an intensity of 100 mm/h, which represents the dominating rainfall intensity range in the region. Soil moisture sensors were also installed at variable depths from 100 to 1000 mm at different locations of the plot to observe the soil moisture regime. From the experimental observations it was found that once the soil is saturated, it remains at field capacity for the next 24-36 h. Such antecedent moisture conditions are most favorable for the generation of rapid stormflow from hillslopes. A dye infiltration test was performed on the undisturbed soil column to observe the macropore fraction variability over the vegetated hillslopes. The estimated macropore fractions are used as essential input for the hillslope hydrological model. The main objective of the present study was to develop and test a method for estimating runoff responses from natural rainfall over hillslopes of the Northwestern Himalayas using a portable rainfall simulator. Using the experimental data and the developed conceptual model, the overland flow and the subsurface flow through a macropore-dominated area have been estimated/analyzed. The surface and subsurface runoff estimated using the developed hillslope hydrological model compared well with the observed surface runoff for a rainfall intensity of 100 mm/h. The surface runoff hydrograph was very well predicted by the model, with correlation coefficient (R 2 ) and Nash-Sutcliffe efficiency coefficient (E) as 0.95 and 0.91, respectively. The observed soil/macropore storage component was estimated with the help of water balance equation and compared with the model predicted macropore storage. The error in computing the soil/macropore storage was estimated as 0.38 mm i.e., 13%.
<p><strong>Abstract.</strong> 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.</p>
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.
Abstract. Remote sensing and hydrological models are one of the foremost tools for rapid and comprehensive study of flood hazards and disasters in any parts of the world. Current study is focused on severe 2018 Kerala flood, and is done using various remote sensing data, geospatial tools and combination of hydrological/hydrodynamic/topographical models. Flood mapping is done with pre and post floods remote sensing datasets. For pre-Flood analysis, Normalized Difference Water Index (NDWI) map was prepared on Google Earth Engine (GEE), using Sentinel-2 images for the period of Feb. 2017 to identify permanent water bodies. For post-Flood analysis, GEE was used to download the pre-processed and thermal noise removed Sentinel-1 SAR image for Aug. 9, 2018, Aug. 14 and Aug. 21, 2018 and flood maps were generated using this data. In addition to SAR data, probable flood inundation areas using topography-based flood inundation tool HAND (Height Above Nearest Drainage tool) was also utilized. Hydrological simulation was carried out for all 12 major river sub-basins of Kerala, where floods are reported. Indian Meteorological Department-Global Precipitation Measurement (IMD-GPM) gridded daily data is used as input meteorological data for hydrological simulations. The hydrological simulations results were verified using published Central Water Commission (CWC) reports and reservoirs data for India-WRIS. The hydrodynamic simulation was also performed for simulating the Idukki dam release data and flood condition in downstream areas. Overall, an integrated study and developed approach can be utilized by state and central water and disaster management agencies to develop flood early warning systems.
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