Multi Source Data Fusion Approach for Precise Flood Forecasting (PAP014419)

Código

PAP014419

Autores

Shahab Araghinejad, Reza bazaz

Tema

Flood forecasting and early warning systems

Resumo

Flood, as more important natural water hazards, cause intense human and financial losses. Therefore, one of the main concerns of governmental agencies is flood monitoring and forecasting. Recently the use of multi-source data fusion in to the hydrologic estimation has raised accuracy and precision of forecasting. In this research, the technique of multi-source data fusion is applied to combine information received from different sources of data including CMORPH and TRMM as well as the recording gauges to calibrate real time storms for the purpose of flood forecasting and nowcasting in the Karoun basin in the western part of Iran. A multi-source data fusion scheme is used on data sources to determine amount of contribution for each of data sources. The results demonstrate the supremacy of the proposed dynamic approach of data fusion over the conventional approaches.