Validation of GlobSnow-2 snow water equivalent over Eastern Canada

• Published in: Remote sensing of environment Vol. 194; pp. 264 - 277
• Main Authors: Larue, Fanny, Royer, Alain, De Sève, Danielle, Langlois, Alexandre, Roy, Alexandre, Brucker, Ludovic
• Format: Journal Article
• Language: English
• Published: Goddard Space Flight Center Elsevier Inc 01.06.2017; Elsevier
• Subjects: Earth Resources And Remote Sensing; Eastern Canada; GlobSnow-2; In situ SWE measurements; Land cover; Passive microwave; Water resources; Land cover; Passive microwave; In situ SWE measurements; GlobSnow-2; Water resources; Eastern Canada; Water Resources; Globsnow-2; Microwave Radiometry; Snow Water Equivalent; passive microwave; water resources; land cover; in situ SWE measurements
• ISSN: 0034-4257; 1879-0704
• DOI: 10.1016/j.rse.2017.03.027

In Québec, Eastern Canada, snowmelt runoff contributes more than 30% of the annual energy reserve for hydroelectricity production, and uncertainties in annual maximum snow water equivalent (SWE) over the region are one of the main constraints for improved hydrological forecasting. Current satellite-based methods for mapping SWE over Québec's main hydropower basins do not meet Hydro-Québec operational requirements for SWE accuracies with less than 15% error. This paper assesses the accuracy of the GlobSnow-2 (GS-2) SWE product, which combines microwave satellite data and in situ measurements, for hydrological applications in Québec. GS-2 SWE values for a 30-year period (1980 to 2009) were compared with space- and time-matched values from a comprehensive dataset of in situ SWE measurements (a total of 38,990 observations in Eastern Canada). The root mean square error (RMSE) of the GS-2 SWE product is 94.1±20.3mm, corresponding to an overall relative percentage error (RPE) of 35.9%. The main sources of uncertainty are wet and deep snow conditions (when SWE is higher than 150mm), and forest cover type. However, compared to a typical stand-alone brightness temperature channel difference algorithm, the assimilation of surface information in the GS-2 algorithm clearly improves SWE accuracy by reducing the RPE by about 30%. Comparison of trends in annual mean and maximum SWE between surface observations and GS-2 over 1980–2009 showed agreement for increasing trends over southern Québec, but less agreement on the sign and magnitude of trends over northern Québec. Extended at a continental scale, the GS-2 SWE trends highlight a strong regional variability. •Over Québec, GlobSnow2 and in situ SWE data are compared with an extensive database.•The highest deviations are for dense boreal forest areas.•The GlobSnow2 SWE does not reach the accuracy required for hydrologic simulations.•The GlobSnow2 product provides good trends of the annual mean SWE over 30years.