Data assimilation method in flood forecasting for Red river system using high performent computer

Nguyen Thanh Don, Nguyen Van Que, Tran Quang Hung, Nguyen Hong Phong


Around the world, the data assimilation framework has been reported to be of great interest for weather forecasting, oceanography modeling and for shallow water flows particularly for flood model. For flood model this method is a power full tool to identify time-independent parameters (e.g. Manning coefficients and initial conditions) and time-dependent parameters (e.g. inflow). This paper demonstrates the efficiency of the method to identify time-dependent parameter: inflow discharge with a real complex case Red River. Firstly, we briefly discuss about current methods for determining flow rate which encompasses the new technologies, then present the ability to recover flow rate of this method. For the case of very long time series, a temporal strategy with time overlapping is suggested to decrease the amount of memory required. In addition, some different aspects of data assimilation are covered from this case.


2D shallow water flows; DassFlow-Shalow; sensitivity analysis; variational data assimilation; identify discharge; Red river

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