Social vulnerability influences the ability to prepare for, respond to, and recover from disasters. The identification of vulnerable populations and factors that contribute to their vulnerability are crucial for effective disaster risk reduction. Nepal exhibits multihazard risk and has experienced socioeconomic and political upheaval in recent decades, further increasing susceptibility to hazards. However, we still know little regarding social vulnerability in Nepal. Here, we investigate social vulnerability in Nepal by adapting Social Vulnerability Index (SoVI) methods to the Nepali context. Variables such as caste, and populations who cannot speak/understand Nepali were added to reflect the essence of the Nepali context. Using principal component analysis, 39 variables were reduced to seven factors that explained 63.02% of variance in the data. Factor scores were summarized to calculate final SoVI scores. The highest levels of social vulnerability are concentrated in the central and western Mountain, western Hill, and central and eastern Tarai regions of Nepal, while the least vulnerable areas are in the central and eastern Hill regions. These findings, supplemented with smaller-scale analyses, have the potential to assist village officers, policymakers, and emergency managers in the development of more effective and geographically targeted disaster management programs.
Natural hazard risk assessment generally focuses on a single hazard type, such as earthquakes, landslides, or floods. This emphasis tends to consider physical processes in isolation. However, most locations are simultaneously at risk to multiple, interacting hazards that generate cascading effects or synergies. Although scholars have proposed a multi-hazard risk framework based on probabilities, the quality and quantity of data required for such an approach are often unavailable in developing countries. Using geospatial and socioeconomic data, this study represents a first step in assessing multi-hazard risk in the city of Dharan, Nepal. Three hazards-landslides, floods, and earthquakes-were considered for an integrated hazard assessment using statistical methods and the Analytic Hierarchy Process (AHP). We employed a Social Vulnerability Index (SoVI) to create a vulnerability map of the study area, which was then combined with a multi-hazard hazard map to produce a total risk map. Our results indicate that eastern Dharan along the Seuti River and southwestern Dharan on the left bank of the Sardu River are at high risk to multiple hazards. Central Dharan and the hills in the western portion of the city are categorized as low risk areas. Data limitations, such as availability and spatial resolution, did not allow for dynamic modeling; however, our results identified the spatial extent of low to high risk areas, which can inform future disaster planning. For example, the methodology and results of this study could assist in the development of disaster risk reduction programs and policies. ARTICLE HISTORY
Building disaster resilience is a stated goal of disaster risk reduction programs. Recent research emphasizes a need for a greater understanding of community disaster response and recovery capacity so that communities can absorb shocks and withstand severe conditions and progress through the recovery period more efficiently. Nepal, which is prone to a multitude of hazards and having recently experienced a large earthquake in 2015, provides a unique opportunity for exploring disaster resilience in the developing world context. To date, no study investigating community disaster resilience across the entire country of Nepal exists. This study quantifies disaster resilience at Nepal’s village level, primarily using census data. Guided by the Disaster Resilience of Place (DROP) model, 22 variables were selected as indicators of social, economic, community, infrastructure, and environmental resilience. Community resilience was assessed for 3971 village development communities (VDCs) and municipalities while using a principal component analysis. Additionally, a cluster analysis was performed to distinguish spatial patterns of resilience. Analyses reveal differential community disaster resilience across the country. Communities in the capital city Kathmandu and in the western and far western Hill are relatively resilient. While the entire Tarai region, which holds the greatest proportion of Nepal’s population, exhibits relatively low levels of resilience when compared to the rest of the county. The results from this analysis provide empirical evidence with the potential to help decision-makers in the allocation of scarce resources to increase resilience at the local level.
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