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dc.contributor.advisorGoïta, Kalifafr
dc.contributor.advisorDe Sève, Daniellefr
dc.contributor.advisorRoyer, Alainfr
dc.contributor.authorVachon, Françoisfr
dc.date.accessioned2014-05-15T18:09:51Z
dc.date.available2014-05-15T18:09:51Z
dc.date.created2009fr
dc.date.issued2009fr
dc.identifier.isbn9780494528617fr
dc.identifier.urihttp://savoirs.usherbrooke.ca/handle/11143/2806
dc.description.abstractThe snow cover (extent, depth and water equivalent) is an important factor in assessing the water balance of a territory. In a context of deregulation of electricity, better knowledge of the quantity of water resulting from snowmelt that will be available for hydroelectric power generation has become a major challenge for the managers of Hydro-Québec's generating plant. In fact, the snow on the ground represents nearly one third of Hydro-Québec's annual energy reserve and the proportion is even higher for northern watersheds. Snowcover knowledge would therefore help optimize the management of energy stocks.The issue is especially important when one considers that better management of water resources can lead to substantial economic benefits.The Research Institute of Hydro-Quebec (IREQ), our research partner, is currently attempting to optimize the streamflow forecasts made by its hydrological models by improving the quality of the inputs. These include a parameter known as the snow water equivalent (SWE) which characterizes the properties of the snow cover. At the present time, SWE data is obtained from in situ measurements, which are both sporadic and scattered and does not allow the temporal and spatial variability of SWE to be characterized adequately for the needs of hydrological models. This research project proposes to provide the Québec utility's hydrological models with distributed SWE information about its northern watersheds.The targeted accuracy is 15% for the proposed period of analysis covering the winter months of January, February and March of 2001 to 2006.The methodology is based on the HUT snow emission model and uses the passive microwave remote sensing data acquired by the SSM/I sensor. Monitoring of the temporal and spatial variations in SWE is done by inversion of the model and benefits from the assimilation of in situ data to characterize the state of snow cover during the season. Experimental results show that the assimilation technique of in situ data (density and depth) can reproduce the temporal variations in SWE with a RMSE error of 15.9% (R[subscript 2] =0.76).The analysis of land cover within the SSMI pixels can reduce this error to 14.6% (R[subscript 2] =0.66) for SWE values below 300 mm. Moreover, the results show that the fluctuations of SWE values are driven by changes in snow depths. Indeed, the use of a constant value for the density of snow is feasible and makes it possible to get as good if not better results. These results will allow IREQ to assess the suitability of using snow cover information provided by the remote sensing data in its forecasting models. This improvement in SWE characterization will meet the needs of IREQ for its work on optimization of the quality of hydrological simulations.The originality and relevance of this work are based primarily on the type of method used to quantify SWE and the site where it is applied.The proposed method focuses on the inversion of the HUT model from passive remote sensing data and assimilates in situ data. Moreover, this approach allows high SWE values (> 300 mm) to be quantified, which was impossible with previous methods. These high SWE values are encountered in areas with large amounts of snow such as northern Québec.fr
dc.language.isofrefr
dc.publisherUniversité de Sherbrookefr
dc.rights© François Vachonfr
dc.subjectSpatialisationfr
dc.subjectSuivi temporelfr
dc.subjectAssimilation de donnéesfr
dc.subjectInversion satellitairefr
dc.subjectModèlefr
dc.subjectÉquivalent en eau de la neige (ÉEN)fr
dc.subjectMicro-ondesfr
dc.subjectTélédétectionfr
dc.titleEstimation de l'équivalent en eau de la neige en milieu subarctique du Québec par télédétection micro-ondes passivesfr
dc.typeThèsefr
tme.degree.disciplineGéomatique appliquéefr
tme.degree.grantorFaculté des lettres et sciences humainesfr
tme.degree.levelDoctoratfr
tme.degree.namePh.D.fr


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