See the published version of this preprint at Geoenvironmental Disasters.
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Deepak S
College of Engineering Trivandrum
Corresponding Author
ORCiD: https://orcid.org/0000-0002-2305-2036
License:
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Recent years have shown a significant increase in the occurrence of floods globally, with an impact on habitation and different sectors of the economy. This, in turn, necessitates the use of different flood mitigation strategies, wherein flood vulnerability assessment plays a significant role. The proposed work presents a methodology that combines vulnerability under physical-environmental and socio-economic domains to assess the overall flood vulnerability at the local self-government level. The methodology was illustrated to the case of Aluva municipality, located on the banks of River Periyar, in Kerala state, India. The spatial variation of hazard inducing factors and population statistics were analysed using Geographic Information System (GIS) tools. The machine learning algorithm, Random Forest, which uses hazard inducing factors as input was implemented for the evaluation of physical-environmental vulnerability. The social vulnerability of the region was analysed using the GIS Multi-criteria decision analysis approach (MCDA), with criteria weights to incorporate the interests of different stakeholders. The critical combinations of the two domains of vulnerability in the assessment of the vulnerability to flood, to have efficient flood management in local self-government was demonstrated in this study and can be made use of for any flood event.
Keywords
Socio-economic vulnerability, Physical-environmental vulnerability, GIS-MCDA, Random Forest, Flood Vulnerability
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View the published article at Geoenvironmental Disasters.
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Editorial decision: Accept
On 29 Nov, 2020
Editor assigned
On 19 Nov, 2020
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On 19 Nov, 2020
Editor invited
On 19 Nov, 2020
No comments provided
Editorial decision: Minor Revision
On 21 Oct, 2020
Reviewer #2 agreed
On 14 Oct, 2020
Review #2 received
Received 14 Oct, 2020
Reviewer #1 agreed
On 08 Oct, 2020
Review #1 received
Received 08 Oct, 2020
Reviewers invited
Invitations sent on 07 Oct, 2020
Editor assigned
On 05 Aug, 2020
Submission checks complete
On 04 Aug, 2020
Editor invited
On 04 Aug, 2020
No comments provided
Editorial decision: Minor Revision
On 16 Jul, 2020
Review #1 received
Received 17 Jun, 2020
Editor assigned
On 09 Jun, 2020
Reviewers invited
Invitations sent on 09 Jun, 2020
Reviewer #1 agreed
On 09 Jun, 2020
Submission checks complete
On 08 Jun, 2020
Editor invited
On 08 Jun, 2020
No comments provided
Editorial decision: Major Revision
On 20 May, 2020
Review #1 received
Received 10 May, 2020
Review #2 received
Received 26 Apr, 2020
Reviewer #2 agreed
On 20 Apr, 2020
Reviewers invited
Invitations sent on 19 Apr, 2020
Reviewer #1 agreed
On 19 Apr, 2020
Editor assigned
On 14 Apr, 2020
Submission checks complete
On 13 Apr, 2020
Editor invited
On 13 Apr, 2020
First submitted
On 12 Apr, 2020
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See the published version of this preprint at Geoenvironmental Disasters.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Deepak S
College of Engineering Trivandrum
Corresponding Author
ORCiD: https://orcid.org/0000-0002-2305-2036
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at Geoenvironmental Disasters.
Version 4
Posted 02 Dec, 2020
No community comments so far
Editorial decision: Accept
On 29 Nov, 2020
Editor assigned
On 19 Nov, 2020
Submission checks complete
On 19 Nov, 2020
Editor invited
On 19 Nov, 2020
No comments provided
Editorial decision: Minor Revision
On 21 Oct, 2020
Reviewer #2 agreed
On 14 Oct, 2020
Review #2 received
Received 14 Oct, 2020
Reviewer #1 agreed
On 08 Oct, 2020
Review #1 received
Received 08 Oct, 2020
Reviewers invited
Invitations sent on 07 Oct, 2020
Editor assigned
On 05 Aug, 2020
Submission checks complete
On 04 Aug, 2020
Editor invited
On 04 Aug, 2020
No comments provided
Editorial decision: Minor Revision
On 16 Jul, 2020
Review #1 received
Received 17 Jun, 2020
Editor assigned
On 09 Jun, 2020
Reviewers invited
Invitations sent on 09 Jun, 2020
Reviewer #1 agreed
On 09 Jun, 2020
Submission checks complete
On 08 Jun, 2020
Editor invited
On 08 Jun, 2020
No comments provided
Editorial decision: Major Revision
On 20 May, 2020
Review #1 received
Received 10 May, 2020
Review #2 received
Received 26 Apr, 2020
Reviewer #2 agreed
On 20 Apr, 2020
Reviewers invited
Invitations sent on 19 Apr, 2020
Reviewer #1 agreed
On 19 Apr, 2020
Editor assigned
On 14 Apr, 2020
Submission checks complete
On 13 Apr, 2020
Editor invited
On 13 Apr, 2020
First submitted
On 12 Apr, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Environmental Policy
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Geoenvironmental Disasters.
Recent years have shown a significant increase in the occurrence of floods globally, with an impact on habitation and different sectors of the economy. This, in turn, necessitates the use of different flood mitigation strategies, wherein flood vulnerability assessment plays a significant role. The proposed work presents a methodology that combines vulnerability under physical-environmental and socio-economic domains to assess the overall flood vulnerability at the local self-government level. The methodology was illustrated to the case of Aluva municipality, located on the banks of River Periyar, in Kerala state, India. The spatial variation of hazard inducing factors and population statistics were analysed using Geographic Information System (GIS) tools. The machine learning algorithm, Random Forest, which uses hazard inducing factors as input was implemented for the evaluation of physical-environmental vulnerability. The social vulnerability of the region was analysed using the GIS Multi-criteria decision analysis approach (MCDA), with criteria weights to incorporate the interests of different stakeholders. The critical combinations of the two domains of vulnerability in the assessment of the vulnerability to flood, to have efficient flood management in local self-government was demonstrated in this study and can be made use of for any flood event.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
This is a list of supplementary files associated with this preprint. Click to download.
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