Front. Earth Sci. Frontiers in Earth Science Front. Earth Sci. 2296-6463 Frontiers Media S.A. 707556 10.3389/feart.2021.707556 Earth Science Correction Corrigendum: Prediction of Maximum Flood Inundation Extents with Resilient Backpropagation Neural Network: Case Study of Kulmbach Lin et al. Corrigendum: XXX Lin Qing * Leandro Jorge Wu Wenrong Bhola Punit Disse Markus Department of Civil, Geo and Environmental Engineering, Technical University of Munich, Munich, Germany

Edited and reviewed by: Mingfu Guan, The University of Hong Kong, Hong Kong

 *Correspondence: Qing Lin, tsching.lin@tum.de

This article was submitted to Hydrosphere, a section of the journal Frontiers in Earth Science

 16 07 2021 2021 9 707556 10 05 2021 26 05 2021 Copyright © 2021 Lin, Leandro, Wu, Bhola and Disse. 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.

 A Corrigendum on: Prediction of Maximum Flood Inundation Extents With Resilient Backpropagation Neural Network: Case Study of Kulmbach by Lin Q, Leandro J, Wu W, Bhola P and Disse M (2020) Prediction of Maximum Flood Inundation Extents With Resilient Backpropagation Neural Network: Case Study of Kulmbach. Front. Earth Sci. 8:332. doi:10.3389/feart.2020.00332 hazard maximum inundation extent artificial neural network Resilient backpropagation urban flood forecast

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.