River Water Level Prediction Using Physically Based and Data Driven Models

The ability to simulate the propagation of flood waves is of crucial importance for planning and operational management of river floods. Hydrodynamic and hydrologic numerical models provide such capabilities and represent conventional approaches to river flood modelling. In the recent years, data driven models such as artificial neural networks (ANNs), and neurofuzzy systems have also emerged as viable tools for this purpose.

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