The dynamics of water mass transport in the Taiwan Straits is complicated. The time variations of transport in the strait may be influenced by local wind, remote wind, the sea-level gradient between two ends of the strait and the intrusion of Kuroshio etc. This research was aiming for the regional wind effect and the transport variation of the strait. The main data set to be applied in this study is the QSCAT wind. The transport data were the results calculated in EASNFS model of Dr. Dong-Shan Ko (Naval Research Laboratory, Stennis Space Center USA). In order to validate the accuracy of the QSCAT wind, comparisons of QSCAT wind and that of four land weather stations near the Taiwan were conducted. The analysis showed that the variation of QSCAT wind, qualitively, was similar to that of land stations. However, the amplitude of QSCAT wind was larger. In general, the wind speed of QSCAT multiplied by a factor 0.6 would about be equal to the wind speed of land based weather station. The major methods apply to wind data were the Empirical Orthogonal Function(EOF) and correlation analyses. All the available QSCAT data near Taiwan were collected and were divided into remote wind (East China Sea, Yellow Sea and South China Sea) and local wind (Taiwan Strait). The EOF spatial patterns and time variation were then put together with the strait transport. The results of EOF analysis of QSCAT satellite observation derived wind showed that the regional wind field near Taiwan (100~450N¡A1050~1400E) were mainly dominated by monsoons (mode 1). There was a good correlation between the monsoon wind and transport variation in Taiwan Strait, with correlation coefficient (r) 0.73. The mode 2 typhoon signal showed week correlation with the transport variation of the strait. The reason is unknown which requires further exploration. In the winter northeastern monsoon season, the Yellow Sea, East China Sea remote wind and Taiwan Strait local wind all showed good correlation with the transport of the strait. However, in southwest monsoon period, the South China Sea wind field and the Taiwan Strait local wind field showed poor correlation with the transport of the strait. Advanced analysis of south sea wind stress curl suggested that the wind stress curl may influence the South China Sea circulation and the Kuroshio intrusion, and then caused the transport variations of the Taiwan Strait.

The Centre d'expertise hydrique du Québec (CEHQ) operates a distributed hydrological model (MOHYSE), which integrates a snow model (SPH-AV), for the management of dams in the south of Québec. It appears that the estimation of the water quantity of snowmelt in spring remains a variable with a large uncertainty. This research aims to evaluate the potential of remote sensing data for the characterization of snow and ultimately to develop methods of integration of satellite data in the snow model for the improvement of the simulations of spring floods. Remote sensing snow cover area (SCA) products (MODIS[subscript SCN] & IMS) are compared with snow depth surveys at Environment Canada stations and initial simulations of the models. Thru these comparisons, an effective method of integration (seuil[subscript ÉEN]) of remote sensing SCA products, based on the hypothesis that satellites can not identify small amount of snow because snow become"dirty" and discontinuous, was developed.The improvement of the Nash coefficient and the root mean square error for spring 2004 to 2007 for the simulations with the approach developed compared with streamflow simulated without remote sensing is 0.11 and 21% on the optimized watershed (du Nord) and 0.13 and 22% on the verification watershed (aux Écorces).The method also relies to improve peaks identification as much as 36% on the du Nord watershed and 19% on the aux Écorces watershed.The study also shows the potential of QSCAT data for the characterization of snow cover. Overall accuracies around 90% are obtained for the detection of melt during the month of April from 2001 to 2007 on both studied watersheds.The relation between the rise of the backscatter coefficient and the snow depth surveys shows good correlation for the 2004 to 2006 years for the Lachute and St-Jérôme stations (0.64 to 0.93), but less interesting results for the St-Hippolyte station (0.29 to 0.73). QSCAT products considering only the descendant orbit give best results.The integration of remote sensing albedo product did not allow improvement in the simulations because of holes in the temporal series caused by cloud cover. Also, the relation between fractional snow cover and snow depth did not show interesting results in an operational context.The study shows the interest to create new remote sensing SCA products more precise on the studied region. Future works should also evaluate the possibility to adapt the seuil[subscript ÉEN] method for a Kalman filter approach. A more spatially extensive study and a better comprehension of the backscatter response in microwaves of the different elements might eventually permit to obtain useful results with QSCAT data.

In recent years, the scientific community has expressed interest in the ability to observe global climate indicators such as polar sea ice. Advances in microwave remote sensing technology have allowed a large-scale and detailed study of sea ice characteristics. This thesis provides the analysis and development of sea ice mapping algorithms for the SeaWinds scatterometer. First, an in-depth analysis of the Remund Long (RL) algorithm for SeaWinds is performed. From this study, several improvements are made to the RL algorithm which enhance its performance. In addition, a new method for automated polar sea ice mapping is developed for the SeaWinds instrument. This method is rooted in Bayes decision theory, and incorporates an adaptive model for seasonally fluctuating sea ice and ocean microwave signatures. The new approach is compared to the RL algorithm, to passive microwave data, and to high-resolution SAR imagery for validation.