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In the present study, an attempt has been made to study the quantitative geomorphological analysis and hydrological characterization of 95 micro-watersheds (MWS) of Baira river watershed in Himachal Pradesh, India with an area of 425.25 Km2. First time in the world, total 173 morphometric parameters have been generated in a single watershed using satellite remote sensing data (i.e. IRS-P6 ResourceSAT-1 LISS-III, LandSAT-7 ETM+, and LandSAT-8 PAN & OLI merge data), digital elevation models (i.e. IRS-P5 CartoSAT-1 DEM, ASTER DEM data), and soI topographical maps of 1: 50,000 scale. The ninety-five micro-watersheds (MWS) of Baira river watershed have been prioritized through the morphometric analysis of different morphometric parameters (i.e. drainage network, basin geometry, drainage texture analysis, and relief characterizes ). The study has concurrently established the importance of geomorphometry as well as the utility of remote sensing and GIS technology for hydrological characterization of the watershed and there for better resource and environmental managements.

The torrential rains in June 2013 combined with melting of snow caused voluminous floods in the rivers of Uttarakhand and subsequently triggered widespread mud, landslides and debris deposition. The event caused instability of the channel by shifting the banks. Erosion rendered many locations along the banks vulnerable to economic and human loss. The shifts in reaches are calculated by digitizing the bank line using satellite imageries of year 2005, 2010 and 2015. The extent and magnitude of risks have been assessed based on information of past events, rapid field assessments, current mitigation measures and interactions with the locals. The findings from these interactions, and secondary data based on geospatial analysis of bank line changes have been used in the identification of vulnerable reaches along the major rivers. Criteria to identify the vulnerable reaches are based on risk, exposure and hazards in that area. The magnitude of risks due to flood hazards on various exposures along the riverbank is calculated based on qualitatively derived scores. River basins focusing on rainfall, topography, drainage pattern, soil, landslide and exiting infrastructure in relation to vulnerability of the region using GIS data are discussed in details. A fuller understanding will enable decision makers towards more efficient resources management for prevention and protection of river banks due to flood events. In addition to this, an official online decision support system (www.urmis .dhi-india .com) with collaborating partners and organizations for relevant data, information and document has been created.

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The Brahmaputra River is one of the world's largest river systems, India's largest braided river, and its springtime runoff and downstream streamflow are mostly due to snowmelt processes. This study analysed and used TRMM/GFS rainfall, PET, and snowmelt data as inputs to a RR model, which is based on the MIKE Hydro River NAM software package. The mathematical model was calibrated against the available observed discharge data for the sub-catchments. The model performed reasonably well and simulated discharge in good agreement with observed discharge in terms of timing, rate, volume, and shape of the hydrograph. During the calibration procedure, the optimum values of the nine RR-NAM parameters are obtained. The performance of each model has been checked against measured discharge using a coefficient of determination (R2). It is observed that the value of R2 varies from 0.6 to 0.86. This is deemed acceptable for the purposes of this study. In addition to R2, the overall Water Balance error is also checked. The WBL error is less than 6%. Despite the inherent uncertainties in hydrological modelling, it is determined that the calibrated RR-NAM model can be utilized for the Brahmaputra basin's Flood Forecasting and Early Warning System design, as well as water resource management and planning.