Abstract
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(R<sup>2</sup>) 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. R<sup>2</sup> 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.
Highlights
Snow is one of the key environmental parameter which maintains the earth’s radiation balance and plays an important role in river discharge
This study aims at assimilating the MODIS snow cover product into an Energy balanced Land Surface model known as Variable Infiltration Capacity (VIC).This is known as Data Assimilation
In order to improve the simulated snow water equivalent,snow depth and snow melt and river flow, MODIS snow cover fraction has been directly inserted into the model state file and has been inserted using the Ensemble Kalman Filter (EnKF) technique as explained in Eq 1,2,3. 8-day 500 m resolution MODIS Snow Cover Area (SCA) data has been resampled into 1 km Cloud cover has been removed and SCA has been modified using the snow line elevation
Summary
Snow is one of the key environmental parameter which maintains the earth’s radiation balance and plays an important role in river discharge. Snow Cover Area (SCA), portion of the watershed covered by the snow is one of the vital parameter in terms of snowmelt runoff estimation. It forms a firm basis for improving other snow components i.e. Snow water equivalent (SWE), Snow depth and Snow Melt. Over the past two decades, Satellite remote sensing came into notice as the conventional methods of acquiring snow properties becomes very much difficult in inaccessible mountainous regions It has opened the possibility of data acquisition at regular intervals, monitoring the existing conditions and has been considered useful for several runoff forecasting and water management systems (Jain and Rathore, 2001).
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