In the field of operational flood forecasting, uncertainties linked to hydrological forecast are often crucial. In this work, data assimilation techniques are employed to improve hydrological variable estimates coming from numerical simulations using all the available real-time water level measurements. The proposed assimilation scheme, a classical Kalman filter extension to non-linear systems,...

WaSiM-ETH (Gurtz et al., 2001), a widely used water balance simulation model, is tested for its suitability to serve for flow analysis in the context of rainfall runoff modelling and flood forecasting. In this paper, special focus is on the resolution of the process domain in space as well as in time. We try to couple model runs with different calculation time steps in order to reduce the effor...

The predictability of the flood event affecting Soverato (Southern Italy) in September 2000 is investigated by considering three different configurations of ECMWF ensemble: the operational Ensemble Prediction System (EPS), the targeted EPS and a high-resolution version of EPS. For each configuration, three successive runs of ECMWF ensemble with the same verification time are grouped together so...

This paper reports on experience with developing the flood forecasting model for the Upper Danube basin and its operational use since 2006. The model system consists of hydrological and hydrodynamic components, and involves precipitation forecasts. The model parameters were estimated based on the dominant processes concept. Runoff data are assimilated in real time to update modelled soil moistu...

The catchment area of the dam on Mono River in Nagbeto measures about 180 km 2 and counts among the small watersheds in the world. Forecasting in small watersheds (some hundreds of km 2 ) takes generally into account rainfall. That’s why a rainfallrunoff concept is adopted for the study. According to our observations, the feeling process in the basin of the dam on a river follows the same law a...

The present study describes the assimilation of river water level observations and the resulting improvement in flood forecasting. The Kalman Filter algorithm was built on top of a onedimensional hydraulic model which describes the Saint-Venant equations. The assimilation algorithm folds in two steps: the first one was based on the assumption that the upstream flow can be adjusted using a three...

For the modelling of the flood routing in the lower reaches of the Freiberger Mulde river and its tributaries the one-dimensional hydrodynamic modelling system HECRAS has been applied. Furthermore, this model was used to generate a database to train multilayer feedforward networks. To guarantee numerical stability for the hydrodynamic modelling of some 60 km of streamcourse an adequate resoluti...

The applicability and performance of the so-called M5 model tree machine learning technique is investigated in a flood forecasting problem for the upper reach of the Huai River in China. In one of configurations this technique is compared to multilayer perceptron artificial neural network (ANN). It is shown that model trees, being analogous to piecewise linear functions, have certain advantages...

In recent years, the interest in the prediction and prevention of natural hazards related to hydrometeorological events has grown due to the increased frequency of extreme rainstorms. Several research projects have been developed to test hydrometeorological models for real-time flood forecasting. However, flood forecasting systems are still not widespread in operational context. Real-world exam...

A watershed simulation and forecasting system is widely used in Finland for simulation of hydrological cycle and for making real-time forecasts. The system is based on a watershed model. This was based originally on the HBV-model and simulates the hydrological cycle using standard meteorological data. The model simulates the whole land area of Finland, including cross-border watersheds. This is...