Data Assimilation (4D-VAR) for Shallow-Water Flow: The Case of the Chicoutimi River
Data Assimilation (4D-VAR) for Shallow-Water Flow: The Case of the Chicoutimi River
复制标题
浅水流数据同化 (4D-VAR)：希库蒂米河案例
DOI：
10.1007/s10069-003-0009-7
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
A. Fortin
中科院分区：
文献类型：
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作者：
É. Bélanger;A. Vincent;A. Fortin
这是2002年6月9日至11日在温莎大学举行的加拿大CFD学会第10届年会“CFD 2002”上发表的工作的网络报告。本文介绍了四维变分资料同化（4D-VAR）技术作为洪水预报的一种工具。这次讨论将限于水文预报。我们假设气象部门已经预报了天气，这里是一场大暴雨。在4D-VAR技术中，我们需要在拉格朗日的意义下最小化一个成本函数，该成本函数测量预测与观测之间的差异。物理方程充当一组约束。在这里，模型是浅水方程修改，包括泥沙输运。通过使用最速下降算法找到最小值。这是可能的，因为成本函数的梯度可以通过使用模型的伴随方程来解析地计算。为了说明4D-VAR技术，旁路一个简单的理论大坝以及更复杂的溢出Chute-Garneau大坝（1996年洪水期间）的Chikoutimi河进行了研究。
This is a web presentation of the work presented at the 10th Annual Conference of the CFD Society of Canada, “CFD 2002”, at the University of Windsor on June 9-11, 2002. This discussion paper presents the four-dimensional variational data assimilation (4D-VAR) technique as a tool to forecast floods. This discussion will be limited to hydrological forecast. We assume that the weather, here a large rainstorm, had already been forecasted by the meteorological services. In the 4D-VAR technique, we need to minimize, in the sense of Lagrange, a cost function which measures the difference between the forecast and the observations. The physical equations acts as a set of constraints. Here, the model is the shallow-water equations modified to include sediment transport. The minimum was found by using the steepest descent algorithm. This is made possible because the gradient of the cost function can be calculated analytically by using the adjoint equations of the model. To illustrate the 4D-VAR technique, the bypass of a simple theoretical dam as well as the more complex overflowing of the Chicoutimi River at the Chute-Garneau dam (during the 1996 flood) are investigated.