PMID- 36929259
OWN - NLM
STAT- MEDLINE
DCOM- 20230425
LR  - 20230425
IS  - 1614-7499 (Electronic)
IS  - 0944-1344 (Linking)
VI  - 30
IP  - 19
DP  - 2023 Apr
TI  - A multi-criteria decision-making approach to vulnerability assessment of rural 
      flooding in Khyber Pakhtunkhwa Province, Pakistan.
PG  - 56786-56801
LID - 10.1007/s11356-023-25609-1 [doi]
AB  - Assessment of rural regions' vulnerability to flooding is gaining prominence on a 
      global scale. However, researchers are greatly undermined in their efforts to 
      make a comprehensive assessment owing to the multidimensional and non-linear link 
      between different indicators and flood risk. Thus, a multi-criteria 
      decision-making (MCDM) approach is proposed to assess the multifaceted 
      vulnerability of rural flooding in Khyber Pakhtunkhwa Province, Pakistan. This 
      research presents a hybrid model for flood vulnerability assessment by combining 
      TOPSIS and the entropy weight method. Households' vulnerability to flooding in 
      rural areas is assessed through four components (social, economic, physical, and 
      institutional) and twenty indicators. All indicator weights are derived using the 
      entropy weight method. The TOPSIS method is then used to rank the selected 
      research areas based on their flood vulnerability levels. The ranking results 
      reveal that flood vulnerability is highest in the Nowshehra District, followed by 
      the Charsadda, Peshawar, and D.I. Khan Districts. The weighting results show that 
      physical vulnerability is the most important component, while location of 
      household's house from the river source (< 1 km) is the key indicator for 
      assessing flood vulnerability. A sensitivity analysis is provided to study the 
      impact of indicator's weights on the comprehensive ranking results. The 
      sensitivity results revealed that out of twenty indicators, fourteen indicators 
      had the lowest sensitivity, three indicators were reported with low sensitivity 
      while the other three were considered highly sensitive for flood vulnerability 
      assessment. Our research has the potential to offer policymakers specific 
      guidelines for lowering flood risk in flood-prone areas.
CI  - (c) 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, 
      part of Springer Nature.
FAU - Khan, Abid
AU  - Khan A
AUID- ORCID: 0000-0001-7208-6518
AD  - School of Management Science and Engineering, Nanjing University of Information 
      Science & Technology, Nanjing, 210044, China. abidmath706@yahoo.com.
FAU - Gong, Zaiwu
AU  - Gong Z
AD  - School of Management Science and Engineering, Nanjing University of Information 
      Science & Technology, Nanjing, 210044, China.
FAU - Shah, Ashfaq Ahmad
AU  - Shah AA
AD  - School of Public Administration, Hohai University, Nanjing, China.
FAU - Haq, Mirajul
AU  - Haq M
AD  - Department of Mathematics, Abdul Wali Khan University, Mardan, Pakistan.
LA  - eng
PT  - Journal Article
DEP - 20230316
PL  - Germany
TA  - Environ Sci Pollut Res Int
JT  - Environmental science and pollution research international
JID - 9441769
SB  - IM
MH  - Humans
MH  - *Floods
MH  - Pakistan
MH  - *Family Characteristics
MH  - Rural Population
MH  - Rivers
OTO - NOTNLM
OT  - Disaster risk management
OT  - Entropy weight method
OT  - Khyber Pakhtunkhwa
OT  - MCDM
OT  - Rural flooding
OT  - TOPSIS
OT  - Vulnerability assessment
EDAT- 2023/03/18 06:00
MHDA- 2023/04/25 10:20
CRDT- 2023/03/17 09:57
PHST- 2022/11/14 00:00 [received]
PHST- 2023/01/24 00:00 [accepted]
PHST- 2023/04/25 10:20 [medline]
PHST- 2023/03/18 06:00 [pubmed]
PHST- 2023/03/17 09:57 [entrez]
AID - 10.1007/s11356-023-25609-1 [pii]
AID - 10.1007/s11356-023-25609-1 [doi]
PST - ppublish
SO  - Environ Sci Pollut Res Int. 2023 Apr;30(19):56786-56801. doi: 
      10.1007/s11356-023-25609-1. Epub 2023 Mar 16.