Python program for spatial reduction and reconstruction method in flood inundation modelling

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dc.contributor.authorZhou, Y.
dc.contributor.authorWu, W.
dc.contributor.authorNathan, R.
dc.contributor.authorWang, Q.J.
dc.date.issued2021
dc.description.abstractFast and accurate modelling of flood inundation has gained increasing attention in recent years. One approach gaining popularity recently is the development of emulation models using data driven methods, such as artificial neural networks. These emulation models are often developed to model flood depth for each grid cell in the modelling domain in order to maintain accurate spatial representation of the flood inundation surface. This leads to redundancy in modelling, as well as difficulties in achieving good model performance across floodplains where there are limited data available. In this paper, a spatial reduction and reconstruction (SRR) method is developed to (1) identify representative locations within the model domain where water levels can be used to represent flood inundation surface using deep learning models; and (2) reconstruct the flood inundation surface based on water levels simulated at these representative locations. The SRR method is part of the SRR-Deep-Learning framework for flood inundation modelling and therefore, it needs to be used together with data driven models. The SRR method is programmed using the Python programming language and is freely available from https: //github.com/yuerongz/SRR-method.
dc.description.statementofresponsibilityYuerong Zhou, Wenyan Wu, Rory Nathan, Quan J. Wang
dc.identifier.citationMethodsX, 2021; 8:101527-1-101527-12
dc.identifier.doi10.1016/j.mex.2021.101527
dc.identifier.issn2215-0161
dc.identifier.issn2215-0161
dc.identifier.orcidWu, W. [0000-0003-3907-1570]
dc.identifier.urihttps://hdl.handle.net/2440/140360
dc.language.isoen
dc.publisherElsevier BV
dc.relation.granthttp://purl.org/au-research/grants/arc/DE210100117
dc.relation.granthttp://purl.org/au-research/grants/arc/DE210100117
dc.rights© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
dc.source.urihttps://doi.org/10.1016/j.mex.2021.101527
dc.subjectFlood inundation modelling; Surface hydrology; Spatial reduction; Spatial reconstruction; Drainage path delineation; Flood mapping
dc.titlePython program for spatial reduction and reconstruction method in flood inundation modelling
dc.typeJournal article
pubs.publication-statusPublished

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