Application of livelihood vulnerability index to assess risks for farmers in the Sukoharjo Regency and Klaten Regency, Indonesia

Suryanto, Suryanto; Rahman, Aulia

doi:10.4102/jamba.v11i1.739

Cited by 31 publications

(23 citation statements)

References 7 publications

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“…Vulnerability is one factor determining whether people have risks to their livelihoods in agricultural land or not (Suryanto & Rahman, 2019). Thus, the index is used for comparison among the communities.…”

Section: Constructing Livelihood Vulnerability Indexmentioning

confidence: 99%

Assessing The Impacts of Climate Variability on Rural Households in Agricultural Land Through The Application of Livelihood Vulnerability Index

Gitima

Legesse

Biru³

2021

Geos. Ind.

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Climate variability adversely affects rural households in Ethiopia as they depend on rain-fed agriculture, which is highly vulnerable to climate fluctuations and severe events such as drought and pests. In view of this, we have assessed the impacts of climate variability on rural household’s livelihoods in agricultural land in Tarchazuria district of Dawuro Zone. A total of 270 samples of household heads were selected using a multistage sampling technique with sample size allocation procedures of the simple random sampling method. Simple linear regression, the standard precipitation index, the coefficient of variance, and descriptive statistics were used to analyze climatic data such as rainfall and temperature. Two livelihood vulnerability analysis approaches, such as composite index and Livelihood Vulnerability Index-Intergovernmental Panel on Climate Change (LVI-IPCC) approaches, were used to analyze indices for socioeconomic and biophysical indicators. The study revealed that the variability patterns of rainfall and increasing temperatures had been detrimental effects on rural households' livelihoods. The result showed households of overall standardized, average scores of Wara Gesa (0.60) had high livelihood vulnerability with dominant major components of natural, physical, social capital, and livelihood strategies to climate-induced natural hazards than Mela Gelda (0.56). The LVI-IPCC analysis results also revealed that the rural households in Mela Gelda were more exposed to climate variability than Wara Gesa and slightly sensitive to climate variability, considering the health and knowledge and skills, natural capitals, and financial capitals of the households. Therefore, interventions including road infrastructure construction, integrated with watershed management, early warning information system, providing training, livelihood diversification, and SWC measures' practices should be a better response to climate variability-induced natural hazards. Keywords: Households; Livelihood Vulnerability Index; climate variability; Tarchazuria District Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

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Section: Constructing Livelihood Vulnerability Indexmentioning

confidence: 99%

Assessing The Impacts of Climate Variability on Rural Households in Agricultural Land Through The Application of Livelihood Vulnerability Index

Gitima

Legesse

Biru³

2021

Geos. Ind.

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“…Subsequently, we calculate the LVI and the corresponding contributing factors for each of the analyzed states based on our developed framework (Table A2). Our methods for computing the LVI follows a similar approach to [18,27]. Before the computation, we need to interpret whether the magnitude of each indicator value, under each contributing factor, is influencing the contributing factor positively or negatively.…”

Section: Calculationmentioning

confidence: 99%

“…They show that an increase in the adoption of irrigation practices have increased the short-term adaptive capacity while displacing small-scale farming. Studies, such as [27], have also used the LVI approach to assess the livelihood vulnerability of flood risks to farmers for different regions in Indonesia. Results indicate that regions with similar physical characteristics and agricultural dependencies show similar vulnerability levels.…”

Section: Introductionmentioning

confidence: 99%

How Vulnerable Are American States to Wildfires? A Livelihood Vulnerability Assessment

Baijnath-Rodino

Kumar

Rivera

et al. 2021

Fire

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Quantifying livelihood vulnerability to wildland fires in the United States is challenging because of the need to systematically integrate multidimensional variables into its analysis. We aim to measure wildfire threats amongst humans and their physical and social environment by developing a framework to calculate the livelihood vulnerability index (LVI) for the top 14 American states most recently exposed to wildfires. The LVI is computed by assessing each state’s contributing factors (exposure, sensitivity, and adaptive capacity) to wildfire events. These contributing factors are determined through a set of indicator variables that are categorized into corresponding groups to produce an LVI framework. The framework is validated by performing a principal component analysis (PCA), ensuring that each selected indicator variable corresponds to the correct contributing factor. Our results indicate that Arizona and New Mexico experience the greatest livelihood vulnerability. In contrast, California, Florida, and Texas experience the least livelihood vulnerability. While California has one of the highest exposures and sensitivity to wildfires, results indicate that it has a relatively high adaptive capacity, in comparison to the other states, suggesting it has measures in place to withstand these vulnerabilities. These results are critical to wildfire managers, government, policymakers, and research scientists for identifying and providing better resiliency and adaptation measures to support states that are most vulnerable to wildfires.

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“…Disruption to the socio-economic conditions in an area can increase the vulnerability of the area and a high level of vulnerability will affect poverty. Vulnerability itself is a condition or a consequence of circumstances (physical, social, economic, and environmental) that affects disaster prevention and management efforts (Lawal & Arokoyu, 2015); (Suryanto & Rahman, 2019).…”

Section: Socio-economic Effectmentioning

confidence: 99%

Do Social-Economy Vulnerability Index and Poverty Index Have Correlation? Study in Bengawan Solo Watershed

Suryanto

Kumalasari

Guritno

et al. 2021

IJBS

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The components to measure of disaster risk (i.e flood) are level of hazard, vulnerability of individual/community, and capacity of individual/community. Research related to vulnerability is based on the level of probability of a region experiencing a disaster, while vulnerability is based on conditions where individual/community cannot cope with disasters. The aim of the study was to measure the level of vulnerability of the socio-economic and institutional society. This research tried to explain the level of social vulnerability among the communities in upper Bengawan Solo watershed. SoVI makes more appropriate parameters for measuring social vulnerability than relying only on partial socioeconomic data. The data generated from relevan institution, such as Central Bureau of Statistic (Badan Pusat Statistik–BPS), Social Service Institution (Dinas Sosial), National Population and Family Planning Board. Data needed such as socio-economic community, demography, age, family structure, village-city, education, and unemployment rate. We find the data from the related agencies. The first step analysis is to adapt the measurement of vulnerability (SoVI) that has been developed. After the measurement of the SoVI is carried out then it is classified relatively between districts (Sragen, Sukoharjo, Wonogiri, and Karanganyar) in the upstream Bengawan Solo Watershed. The results show highest SoVI total score (the most vulnerability) is Sragen Regency, followed by Wonogiri and Sukoharjo, and the lowest is Karanganyar. Meanwhile, Sragen has the highest scores in social-economy components score such as age, gender, rural/urban, occupation, and family structure. It implies that when disasters attack to Sragen, their community will be more suffering potentially.

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Application of livelihood vulnerability index to assess risks for farmers in the Sukoharjo Regency and Klaten Regency, Indonesia

Cited by 31 publications

References 7 publications

Assessing The Impacts of Climate Variability on Rural Households in Agricultural Land Through The Application of Livelihood Vulnerability Index

Assessing The Impacts of Climate Variability on Rural Households in Agricultural Land Through The Application of Livelihood Vulnerability Index

How Vulnerable Are American States to Wildfires? A Livelihood Vulnerability Assessment

Do Social-Economy Vulnerability Index and Poverty Index Have Correlation? Study in Bengawan Solo Watershed

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