Assimilation of spatially distributed water levels into a shallow-water flood model. Part I: Mathematical method and test case

Xijun Lai (1) , Jerome Monnier (2)

1 Niglas - Nanjing Institute of Geography and Limnology
2 IMT - Institut de Mathématiques de Toulouse UMR5219

Recent applications of remote sensing techniques produce rich spatially distributed observations for flood monitoring. In order to improve numerical flood prediction, we have developed a variational data assimilation method (4D-var) that combines remote sensing data (spatially distributed water levels extracted from spatial images) and a 2D shallow water model. In the present paper (part I), we demon- strate the efficiency of the method with a test case. First, we assimilated a single fully observed water level image to identify time-independent parameters (e.g. Manning coefficients and initial conditions) and time-dependent parameters (e.g. inflow). Second, we combined incomplete observations (a time ser- ies of water elevations at certain points and one partial image). This last configuration was very similar to the real case we analyze in a forthcoming paper (part II). In addition, a temporal strategy with time over- lapping is suggested to decrease the amount of memory required for long-duration simulation.

Mots clés: Shallow water equations; Flood model; Variational data assimilation (4D-var); Satellite image; Parameter identification; Temporal strategy

Domaines: Optimisation et contrôle [math.OC]; Equations aux dérivées partielles [math.AP]; Modélisation et simulation; Environnement et Société

Xijun Lai, Jerome Monnier. Assimilation of spatially distributed water levels into a shallow-water flood model. Part I: Mathematical method and test case. Journal of Hydrology, 2009, 377, pp.1-11. ⟨hal-00908258⟩