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L'apport de la télédétection à un modèle de neige appliqué à un système d'aide à la gestion des barrages dans le sud du Québec

机译:遥感对降雪模型的贡献应用于魁北克南部的大坝管理辅助系统

摘要

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.
机译:魁北克水文专家中心(CEHQ)运营着一个分布式水文模型(MOHYSE),该模型集成了一个降雪模型(SPH-AV),用于管理魁北克南部的大坝。似乎对春季融雪水量的估计仍然是一个不确定性很大的变量。这项研究的目的是评估遥感数据在表征雪中的潜力,并最终开发出在雪模型中整合卫星数据的方法,以改善春季洪水的模拟。将遥感积雪面积(SCA)产品(MODIS [subscript SCN]&IMS)与加拿大环境局的积雪深度调查以及模型的初始模拟进行了比较。通过这些比较,开发了一种有效的遥感SCA产品集成方法(seuil [subjectÉEN]),该假设基于以下假设:卫星由于雪变得“脏”且不连续而无法识别少量积雪。与优化后的分水岭(杜北)的模拟流相比,使用无遥感方法模拟的流量在2004年至2007年春季的Nash系数和均方根误差在优化分水岭(杜北)上分别为0.11%和21% (auxÉcorces)。该方法还依赖于在du Nord分水岭和auxÉcorces分水岭提高多达36%的峰识别能力。该研究还显示了QSCAT数据在雪盖表征中的潜力。 2001年至2007年4月这两个研究流域的融雪检测总体精度约为90%.2004年至2006年,后向散射系数的上升与雪深测量之间的关系显示出良好的相关性。 Lachute和St-Jérôme站(0.64至0.93),但St-Hippolyte站(0.29至0.73)的结果则不太有趣。仅考虑后裔轨道的QSCAT产品提供了最佳结果。由于云层覆盖造成的时间序列中的空洞,遥感反照率产品的集成无法改善模拟。此外,在操作环境下,积雪分数与积雪深度之间的关系也未显示出有趣的结果。研究表明,有兴趣在研究区域内更精确地创建新的遥感SCA产品。未来的工作还应评估将seuil [下标ÉEN]方法用于卡尔曼滤波方法的可能性。一项更广泛的空间研究以及对不同元素微波中反向散射响应的更好理解,最终可能会获得QSCAT数据的有用结果。

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    Roy Alexandre;

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  • 年度 2009
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  • 正文语种 fre
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