A web based tool for operational real-time flood forecasting using data assimilation to update hydraulic states

• Published in: Environmental modelling & software : with environment data news Vol. 84; pp. 35 - 49
• Main Authors: Mure-Ravaud, Mathieu, Binet, Guillaume, Bracq, Michael, Perarnaud, Jean-Jacques, Fradin, Antonin, Litrico, Xavier
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2016
• Subjects: Computational fluid dynamics; Computer simulation; Data assimilation; Flood forecasting; Flood forecasting system; Fluid flow; Freshwater; Hydraulics; Hydrology models; Mathematical models; Real time; Semi-distributed hydrologic model; Stationary Kalman filter; ANE, France; France, Dijon; Semi-distributed hydrologic model; Stationary Kalman filter; Flood forecasting system; Data assimilation
• ISSN: 1364-8152
• DOI: 10.1016/j.envsoft.2016.06.002

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. •An operational flood forecasting system is described.•The stationary Kalman filter is used to assimilate real-time flow data.•The system uses a semi-distributed hydrologic model.•The system is developed as a SaaS, Software as a Service.•It offers powerful data management tools and an elaborated graphical interface.