A result of Wahid’s master thesis work is now published in an international journal, Journal of Hydrology; Regional Studies.
Hussainzada W., Lee H.S.*, Vinayak B., and Khpalwak G.F., 2021. Sensitivity of snowmelt runoff modelling to the level of cloud coverage for snow cover extent from daily MODIS product Collection 6. J. Hydrol.-Reg. Stud., 36. 100835. Open access
The Balkhab River Basin in northern Afghanistan
Snowmelt is a primary water resource in mountainous regions of the world. Remotely sensed snow cover products are useful for obtaining spatial snow information but have unsolved cloud cover issues. Thus, this study demonstrates (1) a spatiotemporal combination approach for reducing cloud cover and improving the accuracy in snow cover extent (SCE) estimation from 2010 to 2018 using the MODIS daily snow cover product version 6 and (2) the sensitivity of snowmelt runoff modelling to SCE inputs with different levels of cloud cover from 2012 to 2014 using a snowmelt runoff model (SRM).
New Hydrological Insights for the Region
The average cloud coverages of the original MODIS Aqua and Terra daily products for the study region and period were reduced from 37.66 % and 31.88 % to 25.9 % after the spatial combination and to 14.28 % and 8.94 %, respectively, after the temporal combination. The temporal combination with previous and following days yielded a substantial improvement in cloud removal. The sensitivity of the SRM results to the different levels of clouds clearly depicts the gradual improvement in the simulated snowmelt runoffs with a cloud cover reduction in the SCE input. Interestingly, the SRM performances with the direct SCE input from Aqua or Terra products are degraded in some cases compared to those without SCE input in the SRM. Thus, careful attention is needed when directly applying remotely sensed snow cover products as input variables in snow hydrological modelling. The simulated snowmelt runoffs are improved substantially in the melting season in March-May. The snowmelt runoff peaks in May are due to the temperature increase and are mainly responsible for extreme floods in the arid study region. This study contributes further to agricultural water resource management for crop cultivation during the dry season from June to September and to flood protection during the snowmelt runoff peaks in May with a potential hydraulic engineering solution.