Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 10, 3391-3409, 2017
https://doi.org/10.5194/gmd-10-3391-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Model description paper
14 Sep 2017
A Bayesian framework based on a Gaussian mixture model and radial-basis-function Fisher discriminant analysis (BayGmmKda V1.1) for spatial prediction of floods
Dieu Tien Bui and Nhat-Duc Hoang
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Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
 
RC1: 'Review comments for Tien Bui and Hoang, BayGmmKda for flood spatial predction', Anonymous Referee #1, 15 Feb 2017 Printer-friendly Version 
AC1: 'Author comment in reply to reviewer 1', Nhat-Duc Hoang, 15 Mar 2017 Printer-friendly Version 
 
RC2: 'Reviewer comments, gmd-2016-311', Anonymous Referee #2, 04 Mar 2017 Printer-friendly Version 
AC2: 'Author comment in reply to reviewer 2', Nhat-Duc Hoang, 15 Mar 2017 Printer-friendly Version 
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
AR by Nhat-Duc Hoang on behalf of the Authors (04 Apr 2017)  Author's response  Manuscript
ED: Referee Nomination & Report Request started (12 May 2017) by Jeffrey Neal
RR by Anonymous Referee #2 (26 May 2017)  
RR by Anonymous Referee #1 (27 May 2017)  
ED: Reconsider after major revisions (12 Jun 2017) by Jeffrey Neal  
AR by Nhat-Duc Hoang on behalf of the Authors (25 Jun 2017)  Author's response  Manuscript
ED: Publish subject to minor revisions (Editor review) (13 Jul 2017) by Jeffrey Neal  
AR by Nhat-Duc Hoang on behalf of the Authors (17 Jul 2017)  Author's response  Manuscript
ED: Publish subject to technical corrections (10 Aug 2017) by Jeffrey Neal  
AR by Nhat-Duc Hoang on behalf of the Authors (12 Aug 2017)  Author's response  Manuscript
CC BY 4.0
Publications Copernicus
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Short summary
A probabilistic model, named BayGmmKda, is proposed for flood susceptibility assessment in central Vietnam. The model is a combination of Gaussian mixture model and radial-basis-function Fisher discriminant analysis. A geographic information system (GIS) database has been established for model construction. The proposed model can accurately establish a flood susceptibility map for the study region. Local authorities can use this map for land-use planning.
A probabilistic model, named BayGmmKda, is proposed for flood susceptibility assessment in...
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