Journal article

Artificial neural network based hybrid modeling approach for flood inundation modeling

S Xie, W Wu, S Mooser, QJ Wang, R Nathan, Y Huang

Journal of Hydrology | Elsevier | Published : 2021


Flood inundation models are important tools in flood management. Commonly used flood inundation models, such as hydrodynamic or simplified conceptual models, are either computationally intensive or cannot simulate the temporal behavior of floods. Therefore, emulation models based on data-driven methods, such as artificial neural networks (ANNs), have been developed. However, the performance of ANN models, like any other data-driven models, is limited by available data and will not perform well in data-sparse regions. In this study, we developed an ANN-based hybrid modeling approach to improve model performance in data-sparse regions by leveraging better model performance in data-rich regions..

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