No abstract

Extremely low water level events have frequently occurred in the middle–lower Yangtze River (MLYR) in recent years (2006–2011). Most of these drought events coincided with the initial operation of the Three Gorges Dam (TGD). The TGD was therefore the focus of controversy about the causes of the hydrological droughts of the rivers and lakes of the region. We quantified the effects of the TGD's operation on water levels from 2006 to 2011 using a newly developed hydrodynamic model. The operation of the TGD significantly exacerbated the severe hydrological droughts that occurred in late September to November because of water impoundment, but it increased water levels from April to early June in the MLYR because of the drawdown of TGD water levels. Evidence suggests that the recent extremely low water levels were mainly because of the remarkable decline in inflows to the MLYR resulting from precipitation changes and possible human activities. Nevertheless, it should be noted that the effects of the TGD on downstream rivers and lakes will be intensified in the foreseeable future. Copyright © 2013 John Wiley & Sons, Ltd.

HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

No abstract

No abstract

No abstract

International audienceRecent 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 demonstrate 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 series 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 overlapping is suggested to decrease the amount of memory required for long-duration simulation

Abstract.A variational data assimilation (4D-Var) method is proposed to directly assimilate flood extents into a 2-D dynamic flood model to explore a novel way of utilizing the rich source of remotely sensed data available from satellite imagery for better analyzing or predicting flood routing processes. For this purpose, a new cost function is specially defined to effectively fuse the hydraulic information that is implicitly indicated in flood extents. The potential of using remotely sensed flood extents for improving the analysis of flood routing processes is demonstrated by applying the present new data assimilation approach to both idealized and realistic numerical experiments.