1. An ensemble neural network model for real-time prediction of urban floods
- Author
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Lothar Fuchs, Insa Neuweiler, and Simon Berkhahn
- Subjects
Artificial neural network ,010504 meteorology & atmospheric sciences ,Computer science ,Computation ,0207 environmental engineering ,02 engineering and technology ,Real time prediction ,computer.software_genre ,01 natural sciences ,Echtzeit Vorhersage ,Data-driven ,Ensemble neuronale Netze ,ddc:690 ,Flash flood ,ddc:530 ,020701 environmental engineering ,0105 earth and related environmental sciences ,Water Science and Technology ,Urbane Sturzfluten ,Real-time forecast ,Numerical models ,Ensemble neural network ,Flooding (computer networking) ,Künstliche neuronale Netze ,Dewey Decimal Classification::600 | Technik::690 | Hausbau, Bauhandwerk ,Urban flooding ,Data mining ,Dewey Decimal Classification::500 | Naturwissenschaften::530 | Physik ,computer - Abstract
The real-time forecasting of urban flooding is a challenging task for the following two reasons: (1) urban flooding is often characterized by short lead times, (2) the uncertainty in precipitation forecasting is usually high. Standard physically based numerical models are often too slow for the use in real-time forecasting systems. Data driven models have small computational costs and fast computation times and may be useful to overcome this problem. The present study presents an artificial neural network based model for the prediction of maximum water levels during a flash flood event. The challenge of finding a suitable structure for the neural network was solved with a new growing algorithm. The model is successfully tested for spatially uniformly distributed synthetic rain events in two real but slightly modified urban catchments with different surface slopes. The computation time of the model in the order of seconds and the accuracy of the results are convincing, which suggest that the method may be useful for real-time forecasts. Bundesministerium für Bildung und Forschung/Sonderprogramm GEOTECHNOLOGIEN/03G0846A/EU
- Published
- 2019
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