<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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 moisture. An analysis of the model performance indicates 88% of the snow cover in the basin to be modelled correctly on more than 80% of the days. Runoff forecasting errors decrease with catchment area and increase with forecast lead time. The forecast ensemble spread is shown to be a meaningful indicator of the forecast uncertainty. During the 2013 flood, there was a tendency for the precipitation forecasts to underestimate event precipitation and for the runoff model to overestimate runoff generation which resulted in, overall, rather accurate runoff forecasts. It is suggested that the human forecaster plays an essential role in interpreting the model results and, if needed, adjusting them before issuing the forecasts to the general public.</p></abstract>

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 moisture. An analysis of the model performance indicates 88% of the snow cover in the basin to be modelled correctly on more than 80% of the days. Runoff forecasting errors decrease with catchment area and increase with forecast lead time. The forecast ensemble spread is shown to be a meaningful indicator of the forecast uncertainty. During the 2013 flood, there was a tendency for the precipitation forecasts to underestimate event precipitation and for the runoff model to overestimate runoff generation which resulted in, overall, rather accurate runoff forecasts. It is suggested that the human forecaster plays an essential role in interpreting the model results and, if needed, adjusting them before issuing the forecasts to the general public.

Real time flood forecasting in the Upper Danube basin

Journal of Hydrology and Hydromechanics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Real time flood forecasting in the Upper Danube basin"}

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...

Real time flood forecasting in the Upper Danube basin

Publié en ligne: 21 oct. 2016

Pages: 404 - 414

Reçu: 01 déc. 2015

Accepté: 17 mai 2016

DOI: https://doi.org/10.1515/johh-2016-0033

Mots clés
Hydrological model, Real time forecasting, Dominant processes, Data assimilation

© 2016 Thomas Nester et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Real time flood forecasting in the Upper Danube basin

Publié en ligne: 21 oct. 2016

Pages: 404 - 414

Reçu: 01 déc. 2015

Accepté: 17 mai 2016

DOI: https://doi.org/10.1515/johh-2016-0033

Mots clésHydrological model, Real time forecasting, Dominant processes, Data assimilation

© 2016 Thomas Nester et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
Hydrological model, Real time forecasting, Dominant processes, Data assimilation