Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Nat. Hazards Earth Syst. Sci., 17, 515-531, 2017
https://doi.org/10.5194/nhess-17-515-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
03 Apr 2017
Extreme weather exposure identification for road networks – a comparative assessment of statistical methods
Matthias Schlögl and Gregor Laaha
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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: 'Comments on "Extreme weather exposure identification for road networks – a comparative assessment of statistical methods"', Anonymous Referee #1, 26 Dec 2016 Printer-friendly Version 
 
RC2: 'nhess-2016-373', Dan Rosbjerg, 18 Jan 2017 Printer-friendly Version Supplement 
 
AC1: 'Author response to nhess-2016-373', Matthias Schlögl, 03 Mar 2017 Printer-friendly Version Supplement 
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (further review by Editor) (03 Mar 2017) by Vassiliki Kotroni  
AR by Matthias Schlögl on behalf of the Authors (07 Mar 2017)  Author's response  Manuscript
ED: Publish as is (07 Mar 2017) by Vassiliki Kotroni
CC BY 4.0
Publications Copernicus
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Short summary
Different extreme value analysis approaches and fitting methods are compared with respect to their value for assessing the exposure of transport networks to extreme precipitation and temperature impacts. The merits of simultaneous analysis and combined plotting of various approaches are shown. The use of conditional performance metrics is proposed as an additional measure for assessing model goodness of fit. Findings of the study can be transferred to a range of environmental variables.
Different extreme value analysis approaches and fitting methods are compared with respect to...
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