tailieunhanh - Data assimilation method in flood forecasting for red river system using high performent computer

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. | Vietnam Journal of Mechanics, VAST, Vol. 37, No. 1 (2015), pp. 29 – 42 DOI: DATA ASSIMILATION METHOD IN FLOOD FORECASTING FOR RED RIVER SYSTEM USING HIGH PERFORMENT COMPUTER Nguyen Thanh Don1,∗ , Nguyen Van Que2 , Tran Quang Hung3 , Nguyen Hong Phong1 1 Institute of Mechanics, Vietnam Academy of Science and Technology, Hanoi, Vietnam 2 Air Defence – Air Force Academy, Hanoi, Vietnam 3 Centre for Informatics and Computing, Vietnam Academy of Science and Technology, Hanoi, Vietnam ∗ E-mail: ntdon@ Received November 19, 2014 Abstract. 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 (. Manning coefficients and initial conditions) and time-dependent parameters (. 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. Keywords: 2D shallow water flows, DassFlow-Shalow, sensitivity analysis, variational data assimilation, identify discharge, Red river. 1. INTRODUCTION Increasing pressures on our vital water resources signify that confidence in the quality of stream flow forecast, simulate and records is today, more than ever, an essential prerequisite for the sustainable management of these critical resources. Quantity of stream flow forecast, simulate and records need to ensure are stages (water level,