An assessment of multidimensional flood vulnerability at the provincial scale in China based on the DEA method

Huang, Dapeng; Zhang, Renhe; Huo, Zhiguo; Mao, Fei; You-hao, E; Zheng, Wei

doi:10.1007/s11069-012-0323-1

Cited by 79 publications

(41 citation statements)

References 24 publications

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“…Then, a "medium vulnerability" state was grouped based on the state with the vulnerability score range from the mean minus one standard deviation to the mean. Lastly, a "low vulnerability" state was grouped based on the state with the vulnerability score that is less than the mean minus one standard deviation (Huang et al, 2012). In Population Vulnerability, the mean and standard deviation are 0.577 and 0.201 respectively, while, in Social Vulnerability, the mean and standard deviation are 0.141 and 0.316 respectively.…”

Section: Resultsmentioning

confidence: 99%

“…However, the efficiency result can reflect the vulnerability level in natural disaster analysis (Wei et al, 2004). The flood vulnerability can be calculated by the ratio between the input and output variables which the process of flood hazard is observed as "input-output" system (Huang et al, 2012). Normally, flood vulnerability is described as the degree of damage by flood disaster.…”

Section: Methodsmentioning

confidence: 99%

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Spatial Flood Vulnerability Assessment in Peninsular Malaysia using Data Envelopment Analysis (Dea)

Saharizan

Zahid

Husin

2018

JTMB

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Flood has caused an enormous negative impact on the environment and the population safety in Malaysia. Many areas are found to be vulnerable to flood due to heavy rainfall during monsoon seasons. However, not many studies were done to identify how vulnerable the prone areas are affected. This study focused on developing flood vulnerability measurement in Peninsular Malaysian states. Data Envelopment Analysis (DEA) was applied on a set of secondary data consisting of several input and output variables across 11 years from 2004 to 2014. The flood vulnerability index for each dimension was computed based on three aspects of flood vulnerability dimensions, i.e. the Population Vulnerability, the Social Vulnerability and the Biophysical Vulnerability. The result showed that Johor was the most vulnerable state among all the states in Peninsular Malaysia in terms of the Population Vulnerability. Meanwhile, Kelantan was the most vulnerable state in the Social Vulnerability and Kedah was the most vulnerable state in the Biophysical Vulnerability. The assessment of flood vulnerability can provide multi-information that may well contribute to a deeper understanding of flood disaster scenario in Malaysia.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Spatial Flood Vulnerability Assessment in Peninsular Malaysia using Data Envelopment Analysis (Dea)

Saharizan

Zahid

Husin

2018

JTMB

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“…Table 2 displays Table 1 Comparison vulnerability assessment methods. Source: Huang et al (2012), Balica et al (2013), Nasiri and Shahmohammadi-kalalagh (2013) …”

Section: Malaysia Case Studymentioning

confidence: 99%

“…There are diverse distinctions in the current methodologies for hazard vulnerability around the world. As regards to previous works with emphasizes on flood hazard, vulnerability assessment primary methods can be clustered into three groups (Huang et al 2012). Table 1 mentions these methods which are used by other researchers and describes the brief weaknesses and strengths of each group.…”

Section: Introductionmentioning

confidence: 99%

District flood vulnerability index: urban decision-making tool

Nasiri

Yusof

Ali

et al. 2018

Int. J. Environ. Sci. Technol.

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Flood vulnerability assessment as an essential part of the urban flood management is done by various methods by several researchers. In fact, the improvement in assessment methods is related to the necessity for enhanced decision-making procedures; for instance, economic or infrastructural investments in cities can be assigned in the best form. To achieve this aim, introducing indices for evaluating vulnerability and identifying more vulnerable zones and then doing relevant comparisons can be useful. District flood vulnerability index (DFVI) developed by the author uses 25 indicators in its calculation. Nevertheless, it is obvious that some of these indicators have no effect on the consequences. This paper presents the results of the analysis for the selection of the most significant indicators of the DFVI construction. This index is appropriate for urban district scaling (or: the urban district scale) and the various components of flood vulnerability (social, economic, environmental and physical). DFVI was made by analyzing the indicators' relevance and by studying the main indicators needed to depict reality of the urban district floods in an effective way. For this purpose, expert elicitation was done by Delphi and AHP method in two separate phases. Then, all these results were combined in order to construct DFVI equations. Finally, the index was implemented in Kuala Lumpur city's districts. This paper outlines which district of cities (in this case Kuala Lumpur) are most vulnerable to flood hazard with regard to the system's components, that is, social, physical, environmental and economic.

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“…Some of the major disasters in China are floods [36][37][38][39], droughts [40][41][42], earthquakes [43,44], typhoons [45][46][47], landslides [48][49][50][51] and others. The center of droughts, floods, typhoons and landslides is identified in central, southern, southwest and southeast areas of China [50].…”

Section: Historical Earthquake Data For Yunnan Province Chinamentioning

confidence: 99%