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Lake Maggiore - Italy, 3-6 April 2000

Combined use of VEGETATION and RADARSAT data for updating snowpack cover and water equivalent in the HYDROTEL hydrological forecasting model

Monique Bernier*, Jean-Pierre Fortin, Yves Gauthier, Richard Turcotte and Ali El Battay
*INRS-Eau, 2800 rue Einstein, C.P. 7500, Sainte-Foy (Québec) G1V 4C7 Canada
Tel.: (418)-654-2585; Fax: (418)- 654-2600;

Paper (pdf file, 1.27 M)

Accurate forecasting of snowmelt in Spring is a very important component of any flood prevention strategy. Yet, the use of remotely sensed data and even hydrological models is far from being a daily practice in most forecasting agencies, for various reasons mostly related to a strong reluctance to change. Other agencies, like Hydro-Québce, are prepared and willing to make the necessary steps.

In the meantime, researchers at INRS-Eau have been working for many years on the development of both application of remote sensing to hydrology and distributed hydrological models able to use remotely sensed and GIS data. Within the framework of the VEGETATION Preparatory Program, we have developed a snow mapping methodology at the sub-pixel level as well as a reflectance estimation of individual land use classes from the Vegetation data. Concurrently, in the framework of similar RADARSAT programs, we have developed a software package called EQeau, for the distributed estimation of the water equivalent of a dry snowpack. Also, the HYDROTEL hydrological model has been adapted to hydrological forecasting.

In this communication, we will first explain why hydrological models do need updating of their state variables for more accurate streamflow forecasts. During the winter and for complete snow cover over the studied watershed, VEGETATION data can help to monitor changes of reflectance in the various bands as a result of new snowfalls while RADARSAT data will be used to furnish a new distribution of snow water equivalents. The albedo values as well as the water equivalents as simulated by the model will be updated using that information. During the snowmelt period, liquid water in the snowpack will reduce the reflectance in each VEGETATION band and the backscattering in the RADARSAT data. The distinction between dry and wet snow could be facilitated using both sensors. At the same time, VEGETATION data will be used to monitor the areal reduction of the snow cover over the watershed. Again, the available information will be very useful to verify if the model is making the proper distinction between hydrological units on which melt has begun and those on which snow is still dry. Also, VEGETATION data will be used to monitor snow cover in the model during the melt period. Examples will be taken from applications of VEGETATION and RADARSAT data over Québec territory and from application of the HYDROTEL model over watersheds located in Québec.

We will conclude with comments on the interest of using remotely sensed data for hydrological forecasting.