PMID- 35803988
OWN - NLM
STAT- MEDLINE
DCOM- 20220712
LR  - 20220916
IS  - 2045-2322 (Electronic)
IS  - 2045-2322 (Linking)
VI  - 12
IP  - 1
DP  - 2022 Jul 8
TI  - Integrated socio-environmental vulnerability assessment of coastal hazards using 
      data-driven and multi-criteria analysis approaches.
PG  - 11625
LID - 10.1038/s41598-022-15237-z [doi]
LID - 11625
AB  - Coastal hazard vulnerability assessment has been centered around the 
      multi-variate analysis of geo-physical and hydroclimate data. The representation 
      of coupled socio-environmental factors has often been ignored in vulnerability 
      assessment. This study develops an integrated socio-environmental Coastal 
      Vulnerability Index (CVI), which simultaneously combines information from five 
      vulnerability groups: biophysical, hydroclimate, socio-economic, ecological, and 
      shoreline. Using the Multi-Criteria Decision Making (MCDM) approach, two CVI 
      (CVI-50 and CVI-90) have been developed based on average and extreme conditions 
      of the factors. Each CVI is then compared to a data-driven CVI, which is formed 
      based on Probabilistic Principal Component Analysis (PPCA). Both MCDM and PPCA 
      have been tied into geospatial analysis to assess the natural hazard 
      vulnerability of six coastal counties in South Carolina. Despite traditional 
      MCDM-based vulnerability assessments, where the final index is estimated based on 
      subjective weighting methods or equal weights, this study employs an entropy 
      weighting technique to reduce the individuals' biases in weight assignment. 
      Considering the multivariate nature of the coastal vulnerability, the validation 
      results show both CVI-90 and PPCA preserve the vulnerability results from 
      biophysical and socio-economic factors reasonably, while the CVI-50 methods 
      underestimate the biophysical vulnerability of coastal hazards. Sensitivity 
      analysis of CVIs shows that Charleston County is more sensitive to socio-economic 
      factors, whereas in Horry County the physical factors contribute to a higher 
      degree of vulnerability. Findings from this study suggest that the PPCA technique 
      facilitates the high-dimensional vulnerability assessment, while the MCDM 
      approach accounts more for decision-makers' opinions.
CI  - (c) 2022. The Author(s).
FAU - Tanim, Ahad Hasan
AU  - Tanim AH
AD  - Civil and Environmental Engineering, University of South Carolina, C206, 300 Main 
      St., Columbia, SC, 29082, USA.
FAU - Goharian, Erfan
AU  - Goharian E
AD  - Civil and Environmental Engineering, University of South Carolina, C206, 300 Main 
      St., Columbia, SC, 29082, USA. goharian@cec.sc.edu.
FAU - Moradkhani, Hamid
AU  - Moradkhani H
AD  - Center for Complex Hydrosystems Research, Civil, Construction and Environmental 
      Engineering, The University of Alabama, Tuscaloosa, AL, USA.
LA  - eng
PT  - Journal Article
DEP - 20220708
PL  - England
TA  - Sci Rep
JT  - Scientific reports
JID - 101563288
SB  - IM
MH  - *Conservation of Natural Resources
MH  - Humans
MH  - Oceans and Seas
MH  - South Carolina
PMC - PMC9270473
COIS- The authors declare no competing interests.
EDAT- 2022/07/09 06:00
MHDA- 2022/07/14 06:00
PMCR- 2022/07/08
CRDT- 2022/07/08 23:20
PHST- 2022/02/01 00:00 [received]
PHST- 2022/06/21 00:00 [accepted]
PHST- 2022/07/08 23:20 [entrez]
PHST- 2022/07/09 06:00 [pubmed]
PHST- 2022/07/14 06:00 [medline]
PHST- 2022/07/08 00:00 [pmc-release]
AID - 10.1038/s41598-022-15237-z [pii]
AID - 15237 [pii]
AID - 10.1038/s41598-022-15237-z [doi]
PST - epublish
SO  - Sci Rep. 2022 Jul 8;12(1):11625. doi: 10.1038/s41598-022-15237-z.