Online flood forecasting in fast responding catchments on the basis of a synthesis of artificial neural networks and process models
Zum Verlinken/Bookmarken: http://dx.doi.org/10.23689/fidgeo-322
A detailed and comprehensive description of the state of the art in the field of flood forecasting opens this work. Advantages and shortcomings of currently available methods are identified and discussed. Amongst others, one important aspect considers the most exigent weak point of today’s forecasting systems: The representation of all the fundamentally different event specific patterns of flood formation with one single set of model parameters. The study exemplarily proposes an alternative for overcoming this restriction by taking into account the different process characteristics of flood events via a dynamic parameterisation strategy...