F. FotopoulosCorresponding author contact information, C. Makropoulos, M.A. Mimikou (Department of Water Resources and Environmental Engineering, School of Civil Engineering, National Technical University of Athens, Greece)
Using satellite data for flood forecasting in catchments located in mid-latitudes is challenging to engineers and model developers, in no small part due to the plethora of data sets that need to be retrieved, combined, calibrated and used for simulation in real time. The differences between the various satellite rainfall data products and the continuous improvement in their quantity and quality render the development of a single software tool, able to read and process all the different data sets, particularly difficult. Even if such an endeavour was undertaken, the degree of flexibility and extensibility that such a tool would require to accommodate future versions of data sets, available in different file formats as well as different temporal and spatial resolution should not be underestimated. This paper describes the development of a flood forecasting system that addresses this issue through a modular architecture based on the use of the Open Modeling Interface (OpenMI) standard, which facilitates the interaction between a number of separate software components. It is suggested that this approach greatly simplifies programming and debugging and eliminates the need to create spatial and temporal transformation functions without significantly compromising the overall execution speed. The approach and system were tested for forecasting flood events within a particularly challenging transboundary catchment, the Evros catchment, extending between Greece, Bulgaria and Turkey. The system uses two sets of data sources, as an example (NASA’s TRMM 3B42 and 3B42RT satellite data sets) to forecast flooding in the Evros catchment. Results indicate that OpenMI greatly facilitates the complex interaction of various software components and considerably increases the flexibility and extensibility of the overall system and hence its operational value and sustainability.