Snow parameters play a very important role in hydrological cycle, local weather pattern, and climate change, eventually influencing total runoff, river flows, and water availability through the amount and timing of snow melt. In this paper, the spatiotemporal variations of snow parameters in Dibang basin, Arunachal Pradesh, India, for a period of 10 years (2006-2015) were analyzed using Spatially Distributed Snowmelt Runoff Model (SDSRM) coupled with remote sensing and GIS techniques. SDSRM was selected due of its capability to simulate snow parameters in scarcely/un-gauged basin where observed data are not available. Moderate Resolution Imaging Spectroradiometer (MODIS) albedo at 500 m resolution from Terra satellite was used to obtain daily snow albedo for the study area. The analysis of 10 years showed that maximum average snow density occurred in the month of June and minimum in the month of December; maximum average snow depth in January and minimum in July; maximum average snow water equivalent (SWE) in January and minimum in July and August; maximum average degree-day factor (DDF) in June and minimum in December; maximum average snowmelt depth in July and minimum in the month of January. Considering the yearly maximum and minimum average, snow density ranged from 404.84 to 522.84 kg/m(3) with an average of 461.76 kg/m(3); snow depth ranged from 0.01 to 0.68 m with an average of 0.24 m; SWE ranged from 0.01 to 0.29 m with an average of 0.11 m; DDF ranged from 0.45 to 0.58 cm/ degrees C-day with the average of 0.51 cm/ degrees C-day; and snowmelt depth ranged from 0.02 to 0.11 m/day with the average of 0.06 m/day. From the yearly temporal analysis, only snow density showed a slight decreasing trend, while the other snow parameters like snow depth, SWE, DDF, and snowmelt depth had a slight increasing trend. Based on yearly temporal analysis of each month, March and November showed an increasing trend for all the snow parameters out of which snow density and DDF showed a significant increasing trend in the month of March, while a slight decreasing trend was observed in the month of August, September, and October. The modeled SWE was compared with the observed SWE, and it was found that they were in good agreement with each other. The other snow parameters were also found to be within comparable ranges reported by other studies. Thus, this study demonstrated the capability of SDSRM to simulate snow parameters over an alpine watershed in Eastern Himalaya and can be recommended for use in un-gauged/scarcely gauged basins over the Himalayan region.
