Flood vulnerability and its influencing factors

Pathak, Santosh; Panta, Hari Krishna; Bhandari, Thaneshwar; Paudel, Krishna P.

doi:10.1007/s11069-020-04267-3

Cited by 30 publications

(14 citation statements)

References 48 publications

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“…The peak discharge was calculated using the SWAT model, and the peak discharge was included as one of the indications. The General Circulation Models (GCM) data were used to forecast future rainfall, while Landsat pictures were used to create land use and land (Singh and Pandey, 2021), (Hosseini et al, 2021) (Nazeer and Bork, 2021), (Hussain et al, 2021) (Pathak et al, 2020), (Hoque et al, 2019) (Mavhura et al, 2017), (Terti et al, 2015) (Eidsvig et al, 2014), (Zhang, 2009) Physical vulnerability Interdependency analysis, indicator methodology, decision-making trial method., Indicator based approach, morphometric parameters were derived from SRTM DEM data using (GIS), Weighted Sum Approach (WSA), Principal Component Analysis (PCA), and an Integrated Approach (IA), GIS-Based Multi-Criteria Approach, Geospatial Indicator-Based Approach and Participatory Analytical Hierarchy Process, Flood generating factors: slope, elevation, land use/land cover, drainage density, rainfall, and soil types were rated and collected to mark out flood vulnerability zones using (GIS), Regression and GIS conditioning factors include digital elevation model (DEM), Pearson's correlation, multicollinearity, and heteroscedasticity analyses (Singh and Pandey, 2021), (Hosseini et al, 2021), (Nazeer and Bork, 2021), (Hussain et al, 2021), (Vignesh et al, 2021), (Usman Kaoje et al, 2021), (Desalegn and Mulu, 2021), (Usman Kaoje et al, 2021), (Sami et al, 2020), (D'Ayala et al, 2020), (Chuang et al, 2020), (Yin et al, 2019), (Hoque et al, 2019), Sajjad, 2019), Hübl et al, 2016), (Al-Juaidi et al, 2018), (Hazarika et al, 2018), (Walliman et al, 2012) and, (Mehebub et al, 2015) Environmental…”

Section: Vulnerability Assessment Methods and A Brief Discussion On P...mentioning

confidence: 99%

A systematic review of the flood vulnerability using geographic information system

Chan

Abid

Sulaiman

et al. 2022

Heliyon

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Section: Vulnerability Assessment Methods and A Brief Discussion On P...mentioning

confidence: 99%

A systematic review of the flood vulnerability using geographic information system

Chan

Abid

Sulaiman

et al. 2022

Heliyon

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“…Although this study dealt with historical and present-day flood vulnerabilities in Mopani District, projections of future vulnerabilities under climate change are even more important. Moreover, focusing on regional sensitivity, adaptive capacity and local exposure is critical in understanding local vulnerabilities and flood-related impacts [80]. This helps the policy and decision makers, and civil protection and disaster managers, to know exactly where to concentrate and invest to deal with risk and hazards.…”

Section: Discussionmentioning

confidence: 99%

Vulnerability and Adaptation to Flood Hazards in Rural Settlements of Limpopo Province, South Africa

Munyai

Chikoore

Musyoki

et al. 2021

Water

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Climate change has increased the frequency of extreme weather events such as heavy rainfall leading to floods in several regions. In Africa, rural communities are more vulnerable to flooding, particularly those that dwell in low altitude areas or near rivers and those regions affected by tropical storms. This study examined flood vulnerability in three rural villages in South Africa’s northern Limpopo Province and how communities are building resilience and coping with the hazard. These villages lie at the foot of the north-eastern escarpment, and are often exposed to frequent rainfall enhanced by orographic factors. Although extreme rainfall events are rare in the study area, we analyzed daily rainfall and showed how heavy rainfall of short duration can lead to flooding using case studies. Historical floods were also mapped using remote sensing via the topographical approach and two types of flooding were identified, i.e., those due to extreme rainfall and those due to poor drainage or blocked drainage channels. A field survey was also conducted using questionnaires administered to samples of affected households to identify flood vulnerability indicators and adaptation strategies. Key informant interviews were held with disaster management authorities to provide additional information on flood indicators. Subsequently, a flood vulnerability index was computed to measure the extent of flood vulnerability of the selected communities and it was found that all three villages have a ‘vulnerability to floods’ level, considered a medium level vulnerability. The study also details temporary and long-term adaptation strategies/actions employed by respondents and interventions by local authorities to mitigate the impacts of flooding. Adaptation strategies range from digging furrows to divert water and temporary relocations, to constructing a raised patio around the house. Key recommendations include the need for public awareness; implementation of a raft of improvements and a sustainable infrastructure maintenance regime; integration of modern mitigations with local indigenous knowledge; and development of programs to ensure resilience through incorporation of Integrated Development Planning.

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“…The standardized value is multiplied with the component 1 score obtained from the PCA to get the respective index value. Similar procedure was used by Pathak et al [36] on study of flood vulnerability in Saptari district of Nepal. A higher value of vulnerability index indicates lower vulnerability and vice versa.…”

Section: Vulnerability Assessmentmentioning

confidence: 98%

Soil erosion vulnerability and adaptation strategies in maize field of Sindhukhola sub-watershed region, Nepal

Panta¹,

Bhandari

Paudel

2020

SN Appl. Sci.

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Erosion is a major concern of hill maize farming system. Watersheds with steep slope and fragile land are more prone to erosion. A perception based semi structured questionnaire survey was carried out in Thakani and Sindhukot of Melamchi municipality in Sindhupalchowk district to study relationships of erosion in maize field along with assessment of vulnerability and factors affecting adoption of prevention measures. Index ranking method and descriptive statistics were used to rank the perception of farmers pertaining to occurrence, causes and available control measures of erosion. Logit regression further assessed the determinants of adoption of erosion prevention measures where as vulnerability was assessed using integrated vulnerability assessment approach following Intergovernmental Panel on Climate Change (IPCC) guideline. Most of the surveyed farmers responded heavy rainfall as major cause of the erosion followed by weak geography whereas the intensity of erosion was moderately increasing. Majority of the respondents (72.5%) have not adopted any erosion prevention measures mainly due to no support from government and low income. Among various adaptation measures, most of the farmers have shifted cultivation time, improved drainage system and decreased weeding frequency. The logit regression showed that among the independent variables, income, education, gender, access to extension services and involvement in organizations are positively significant to the adoption decision. This implies farmers in prone area need support from government to adopt prevention measures. Low income household dependent on agriculture and marginal farmers were more vulnerable to erosion as they have low adaptive capacity and resilience power.

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Flood vulnerability and its influencing factors

Cited by 30 publications

References 48 publications

A systematic review of the flood vulnerability using geographic information system

A systematic review of the flood vulnerability using geographic information system

Vulnerability and Adaptation to Flood Hazards in Rural Settlements of Limpopo Province, South Africa

Soil erosion vulnerability and adaptation strategies in maize field of Sindhukhola sub-watershed region, Nepal

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