|
|||||
|
|
A web based tool for operational real-time flood forecasting using data assimilation to update hydraulic states |
|
| Affiliation: | 1. State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China;2. Changjiang River Scientific Research Institute, Changjiang Water Resources Commission, Wuhan, 430010, China;3. Hubei Province Key Laboratory of River Basin Water Resources and Ecological Environment Science, Changjiang River Scientific Research Institute, Wuhan, 430010, China;4. Hubei Provincial Water Resources and Hydropower Planning Survey and Design Institute, Wuhan, 430064, China;5. Hubei Water Resources Research Institute, Wuhan, 430070, China |
| Abstract: | This article describes an operational flood forecasting system set up for the city of Dijon, France. This system assimilates real-time flow data at an hourly time step with the stationary Kalman filter to update hydraulic states. It uses a semi-distributed hydrologic model to integrate rainfall measurements and forecasts and provide discharge forecasts at several points on the watershed. It also offers powerful data management tools and an elaborated graphical interface available from any computer connected to the Internet. The hydrologic model was calibrated using a semi-distributed approach. Its simulation and forecasting performances are analyzed. The performances of the system on a recent flood event are also investigated. |
| Keywords: | Flood forecasting system Semi-distributed hydrologic model Stationary Kalman filter Data assimilation |
| 本文献已被 ScienceDirect 等数据库收录！ | |