Abstract

<p>Flood forecasting agencies and hydropower companies require cost effective approaches for accurate estimation of snow water equivalent (SWE) to improve spring flow forecast and to make informed decision about reservoir operation.  The lack of accurate SWE estimation at the watershed scale is an issue in northern watersheds, as snow surveys are either absent, or sparsely distributed and infrequent (monthly to bi-weekly). Remotely sensed SWE data sets retrieved from passive microwave satellites, such as GlobSnow, offers the advantage of high frequent coverage of the Northern Hemisphere at the watershed scale.  The main issue is that SWE is typically underestimated because of vegetation. Also, the signal saturates for deep snowpacks.  An approach is therefore required to correct GlobSnow which does not resort to local SWE measurements.</p><p>A correction factor approach which focuses on improving the Maximum Snow Water Equivalent (MSWE) estimate for a watershed produced by publicly available regional databases, such as GlobSnow, has been developed. The method does not require point SWE measurements and assumes that the spring runoff volume calculated from historical streamflow observations equals the total snow melt volume retrieved from GlobSnow’s MSWE, less infiltration into frozen ground. The latter is calculated from freely available hydro-meteorological information. The method presented below introduces a cost-effective approach which can bridge the temporal and spatial sparsity that is often associated with the snow survey programs.</p><p>The results from applying this approach to the regional GlobSnow database to northern watersheds in Quebec show that the Corrected GlobSnow (C-Glob) more accurately correlates to the manual snow surveys, compared to the uncorrected GlobSnow data source. The corrected database may prove especially useful for watersheds where no SWE measurements are available, may serve as a supplementary source of information to better understand what takes place over the entire watershed by filling gaps of manual surveys.</p>

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