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Variationnal data assimilation of AirSWOT and SWOT data into the 2D shallow water model Dassflow, method and test case on the Garonne river (France)

机译:将空气SWOT和SWOT数据的变种数据同化到2D浅水模型中加龙河上的基础流量,方法和测试案例(法国)

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摘要

For river hydraulic studies, water level measurements are fundamental information, yet they are currently mostly provided by gauging stations mostly located on the main river channel. That is why they are sparsely distributed in space and can have gaps in their time series (because of floods damages on sensors or sensors failures). These issues can be compensated by remote sensing data, which have considerably contributed to improve the observation of physical processes in hydrology and hydraulics in general and, in particular, in flood hydrodynamic. Indeed, the new generation of satellites is equipped with sensors of metric resolution. Remotely-sensed images from satellites such as SWOT (Surface Water and Ocean Topography) would give spatially distributed information on water elevations with a high accuracy (able to observe river wider than100m with a vertical precision ~dm) and periodic in time (revisiting ~week at mid-latitude). Gathering pre-mission data over specific and varied science targets is the purpose of the AirSWOT airborne campaign in order to implement and test SWOT products retrieval algorithms. A reach of the Garonne River, downstream of Toulouse (FRANCE), is a proposed study area for AirSWOT flights. This choice is motivated by previous hydraulic and thermal studies (Larnier et al., 2010) already performed on this section of 100km reach of the river. Moreover, on this highly instrumented and studied portion of river many typical free surface flow modelling issue has been encountered, and this river reach represents the limit of SWOT observation capability. The 2DH (vertically integrated) free surface flow model Dassflow (Honnorat et al., 2005; Honnorat et al., 2007; Honnorat et al., 2009; Hostache et al., 2010; Lai and Monnier, 2009) especially designed for variational data assimilation, will be used on this portion of the Garonne River. Mathematical methodologies such as twin experiments (Roux and Dartus, 2005; Roux and Dartus, 2006) will be performed on several modelling hypothesis in order to identify main characteristic of the river. An identification strategy would allow to retrieve spatial roughness along the main channel, variation of the local topographic slope or else temporal evolution of the streamflow.ud
机译:对于河流水力研究而言,水位测量是基本信息,但目前大多数由主要位于主要河道上的计量站提供。这就是为什么它们在空间上稀疏分布并且在时间序列上可能会有间隔的原因(因为洪水会损坏传感器或导致传感器故障)。这些问题可以通过遥感数据来弥补,遥感数据在很大程度上改善了对水文学和水力学尤其是洪水流体力学中物理过程的观察能力。实际上,新一代卫星配备了公制分辨率传感器。来自诸如SWOT(地表水和海洋地形)之类的卫星的遥感图像将以高准确度(能够以垂直精度〜dm观察宽于100m的河流)并定期(大约一周的时间)给出水位的空间分布信息。在中纬度)。为了实现和测试SWOT产品检索算法,AirSWOT空降战役的目的是收集特定和不同科学目标上的飞行前数据。图卢兹(FRANCE)下游的加龙河(Garonne River)是AirSWOT航班的拟议研究区域。该选择是受之前在这条100公里河段进行的水力和热力研究(Larnier等人,2010)的推动。此外,在这条经过高度仪器化和研究的河段上,遇到了许多典型的自由表面流模拟问题,并且该河段代表了SWOT观测能力的极限。 2DH(垂直积分)自由表面流模型Dassflow(Honnorat等,2005; Honnorat等,2007; Honnorat等,2009; Hostache等,2010; Lai和Monnier,2009)是专门为变分设计的数据同化将用于加龙河的这一部分。为了确定河流的主要特征,将在几个建模假设上执行数学方法,例如双生实验(Roux和Dartus,2005; Roux和Dartus,2006)。识别策略将允许检索沿主通道的空间粗糙度,局部地形坡度的变化或流的时间演变。

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