In the original article, there was a mistake in that Figures 1–11 and Tables 1–4 were published as supplementary material. The authors would like to move all figures and tables to the main article and remove the supplementary material to improve readability.
The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
Summary
Keywords
hazard, maximum inundation extent, artificial neural network, Resilient backpropagation, urban flood forecast
Citation
Lin Q, Leandro J, Wu W, Bhola P and Disse M (2021) Corrigendum: Prediction of Maximum Flood Inundation Extents with Resilient Backpropagation Neural Network: Case Study of Kulmbach. Front. Earth Sci. 9:707556. doi: 10.3389/feart.2021.707556
Received
10 May 2021
Accepted
26 May 2021
Published
16 July 2021
Volume
9 - 2021
Edited and reviewed by
Mingfu Guan, The University of Hong Kong, Hong Kong
Updates
Copyright
© 2021 Lin, Leandro, Wu, Bhola and Disse.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Qing Lin, tsching.lin@tum.de
This article was submitted to Hydrosphere, a section of the journal Frontiers in Earth Science
Disclaimer
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