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  • 1
    Publication Date: 2006-09-26
    Description: WaSiM-ETH (Gurtz et al., 2001), a widely used water balance simulation model, is tested for its suitability to serve for flow analysis in the context of rainfall runoff modelling and flood forecasting. In this paper, special focus is on the resolution of the process domain in space as well as in time. We try to couple model runs with different calculation time steps in order to reduce the effort arising from calculating the whole flow hydrograph at the hourly time step. We aim at modelling on the daily time step for water balance purposes, switching to the hourly time step whenever high-resolution information is necessary (flood forecasting). WaSiM-ETH is used at different grid resolutions, thus we try to become clear about being able to transfer the model in spatial resolution. We further use two different approaches for the overland flow time calculation within the sub-basins of the test watershed to gain insights about the process dynamics portrayed by the model. Our findings indicate that the model is very sensitive to time and space resolution and cannot be transferred across scales without recalibration.
    Print ISSN: 1680-7340
    Electronic ISSN: 1680-7359
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 2
    Publication Date: 2006-09-26
    Description: For the modelling of the flood routing in the lower reaches of the Freiberger Mulde river and its tributaries the one-dimensional hydrodynamic modelling system HEC-RAS has been applied. Furthermore, this model was used to generate a database to train multilayer feedforward networks. To guarantee numerical stability for the hydrodynamic modelling of some 60 km of streamcourse an adequate resolution in space requires very small calculation time steps, which are some two orders of magnitude smaller than the input data resolution. This leads to quite high computation requirements seriously restricting the application – especially when dealing with real time operations such as online flood forecasting. In order to solve this problem we tested the application of Artificial Neural Networks (ANN). First studies show the ability of adequately trained multilayer feedforward networks (MLFN) to reproduce the model performance.
    Print ISSN: 1680-7340
    Electronic ISSN: 1680-7359
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
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