Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Attribution of Flood Forecasting Errors From a Multi‐Model Perspective in Milan Urbanized River Basins
https://orcid.org/0000-0002-2594-5655
https://orcid.org/0000-0001-9224-4843
ABSTRACTIn synergy with hydraulic works, hydro‐meteorological forecasts and related preventive protection measures are effective tools for mitigating flood risk. Nevertheless, the performance and reliability of coupled prediction systems in real‐time operations are often influenced by errors in meteorological and hydrological models and their interactions. The paper discusses the source and magnitude of such combined errors, analyzing the functionality of a warning system to predict river floods in northern Italian catchments. The proposed flood alert tool consists of a hydrological model, driven by atmospheric forcings from various weather models and ground observations. This study aims to analyze the sources of flood forecasting errors in small urbanized river basins by disentangling the uncertainties in precipitation and discharge predictions. The results emphasize the relationship between quantitative precipitation and peak discharge forecast errors during convective and stratiform events, with a prevalent tendency toward underestimation of peak flows. The paper highlights the added value and limitations of the real‐time multi‐model approach as an effective compromise amidst the wide spread of model forecasts. This assessment is based on 4 years of operational simulations (2019–2022) on the river Seveso, where a municipal monitoring system for flood alerts (MOCAP) has also been implemented to support local civil protection procedures.
Attribution of Flood Forecasting Errors From a Multi‐Model Perspective in Milan Urbanized River Basins
https://orcid.org/0000-0002-2594-5655
https://orcid.org/0000-0001-9224-4843
ABSTRACTIn synergy with hydraulic works, hydro‐meteorological forecasts and related preventive protection measures are effective tools for mitigating flood risk. Nevertheless, the performance and reliability of coupled prediction systems in real‐time operations are often influenced by errors in meteorological and hydrological models and their interactions. The paper discusses the source and magnitude of such combined errors, analyzing the functionality of a warning system to predict river floods in northern Italian catchments. The proposed flood alert tool consists of a hydrological model, driven by atmospheric forcings from various weather models and ground observations. This study aims to analyze the sources of flood forecasting errors in small urbanized river basins by disentangling the uncertainties in precipitation and discharge predictions. The results emphasize the relationship between quantitative precipitation and peak discharge forecast errors during convective and stratiform events, with a prevalent tendency toward underestimation of peak flows. The paper highlights the added value and limitations of the real‐time multi‐model approach as an effective compromise amidst the wide spread of model forecasts. This assessment is based on 4 years of operational simulations (2019–2022) on the river Seveso, where a municipal monitoring system for flood alerts (MOCAP) has also been implemented to support local civil protection procedures.
Attribution of Flood Forecasting Errors From a Multi‐Model Perspective in Milan Urbanized River Basins
https://orcid.org/0000-0002-2594-5655
https://orcid.org/0000-0001-9224-4843
ABSTRACTIn synergy with hydraulic works, hydro‐meteorological forecasts and related preventive protection measures are effective tools for mitigating flood risk. Nevertheless, the performance and reliability of coupled prediction systems in real‐time operations are often influenced by errors in meteorological and hydrological models and their interactions. The paper discusses the source and magnitude of such combined errors, analyzing the functionality of a warning system to predict river floods in northern Italian catchments. The proposed flood alert tool consists of a hydrological model, driven by atmospheric forcings from various weather models and ground observations. This study aims to analyze the sources of flood forecasting errors in small urbanized river basins by disentangling the uncertainties in precipitation and discharge predictions. The results emphasize the relationship between quantitative precipitation and peak discharge forecast errors during convective and stratiform events, with a prevalent tendency toward underestimation of peak flows. The paper highlights the added value and limitations of the real‐time multi‐model approach as an effective compromise amidst the wide spread of model forecasts. This assessment is based on 4 years of operational simulations (2019–2022) on the river Seveso, where a municipal monitoring system for flood alerts (MOCAP) has also been implemented to support local civil protection procedures.
Attribution of Flood Forecasting Errors From a Multi‐Model Perspective in Milan Urbanized River Basins
J Flood Risk Management
Ceppi, A. (Autor:in) / Gambini, E. (Autor:in) / Ravazzani, G. (Autor:in) / Lombardi, G. (Autor:in) / Cerri, L. (Autor:in) / Meucci, S. (Autor:in) / Mancini, M. (Autor:in)
01.03.2025
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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