Social vulnerability of rural households to flood hazards in western mountainous regions of Henan province, China

Abstract

Abstract. Evaluating social vulnerability is a crucial issue in risk and disaster management. In this study, a household social vulnerability index (HSVI) to flood hazards was developed and used to assess the social vulnerability of rural households in western mountainous regions of Henan province, China. Eight key indicators were identified using existing literature and discussions with experts from multiple disciplines and local farmers, and their weights were determined using principle component analysis (PCA) and an expert scoring method. The results showed that (1) the ratio of perennial work in other places, hazard-related training and illiteracy ratio (15+) were the most dominant factors of social vulnerability. (2) The numbers of high, moderate and low vulnerability households were 14, 64 and 16, respectively, which accounted for 14.9, 68.1 and 17.0 % of the total interviewed rural households, respectively. (3) The correlation coefficient between household social vulnerability scores and casualties in a storm flood in July 2010 was significant at 0.05 significance level (r = 0.748), which indicated that the selected indicators and their weights were valid. (4) Some mitigation strategies to reduce household social vulnerability to flood hazards were proposed, which included (1) improving the local residents' income and their disaster-related knowledge and evacuation skills, (2) developing emergency plans and carrying out emergency drills and training, (3) enhancing the accuracy of disaster monitoring and warning systems and (4) establishing a specific emergency management department and comprehensive rescue systems. These results can provide useful information for rural households and local governments to prepare, mitigate and respond to flood hazards, and the corresponding strategies can help local households to reduce their social vulnerability and improve their ability to resist flood hazard.

Measuring social vulnerability to natural hazards at the district level in Botswana

“…The District Social Vulnerability Index Model was computed because it quantifies the social vulnerability of different communities in a district to natural hazards, using social vulnerability indicators. It is based on the statistical method used in the Household Social Vulnerability Index (HSVI) methodology by Liu and Li (2016). The HSVI model does so by statistically assessing both the socio-economic and demographic factors influencing people’s capacity to cope and recover from environmental hazards.…”

The Influence of Poverty Alleviation Resettlement on Rural Household Livelihood Vulnerability in the Western Mountainous Areas, China

“…Previous studies have mostly focused on vulnerability assessment at the national and regional levels, and few existing studies have evaluated vulnerability from the perspective of micro communities and rural households (especially in the context of PAR). Due to the potentially higher vulnerability degree of the susceptible populations, the large-scale household vulnerability assessment at the national level can mask significant local-level susceptibility at the household or community level in terms of access to assets and entitlements, thus, the rural households in contiguous poor areas seem less vulnerable than they fundamentally are [12,24]. Based on the existing related literature and the livelihood characteristics of rural households in the study region, this study intended to consider the response of local farmers to the implementation of the resettlement policy, beginning with the exposure, sensitivity and adaptive capacity of the farmers, respectively, and designed an evaluation index system for rural household livelihood vulnerability (see Table 1) as well as the assessment model.…”

Construction of an integrated social vulnerability index in urban areas prone to flash flooding

“…However, it did not provide information on the relative significance of variables within each group, making it necessary to subsequently perform a PCA (Cutter et al, 2003(Cutter et al, , 2013Fekete, 2009;Nelson et al, 2015;Hummell et al, 2016). Regarding the weighting method used here, although many authors support the idea of assigning the factors equal weight (Chakraborty et al, 2005), it seems reasonable to suppose that not all factors have the same importance in the construction of the ISVI (Brooks et al, 2005;Eakin and Luers, 2006;Liu and Li, 2016), especially when there may be variations in the number of variables forming each factor and their explained variance. It is even possible that there is a spatial variation in each factor's importance.…”