Assessing vulnerability of horticultural smallholders’ to climate variability in Ghana: applying the livelihood vulnerability approach

Williams, Portia Adade; Abu, Mumuni

doi:10.1007/s10668-018-0292-y

Cited by 35 publications

(31 citation statements)

References 27 publications

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“…It is susceptibility driven rooted in social, economic and largely, environmental factors. Measurement of vulnerability to single natural hazards including floods and droughts has been conducted in Sub-Saharan Africa (Ahmadalipour & Moradkhani, 2018;Mwale et al, 2015;Williams et al, 2018;Zacarias, 2019). More importantly, a coupled IPCC and UNISDR framework has been applied tested on floods (Mwale et al 2015).…”

Section: Discussionmentioning

confidence: 99%

A Multi Hazard Perspective in Flood and Drought Vulnerability: Case Study of Malawi

Kamanga¹,

Tantanee²,

Mwale³

et al. 2020

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The prominence of vulnerability assessments cannot be over emphasized. They are key in informing policy by supporting holistic, multi-disciplinary and evidence based policy implementation. They foster delineation of locales and sectors requiring resources and interventions. About 90% of the population in Malawi and most of sub-Saharan Africa rely on rain fed agriculture. Due to this overreliance, people's livelihoods and economy are vulnerable to hydrological hazards such as flood and droughts, which account for 70% of all the hazards in the region. This paper employs indicators to couple exposure, susceptibility, capacity measures and economic, social, physical and environmental components to measure multiple hazard vulnerability. It then utilizes the Community Based Disaster Risk Index in the analysis. Results show that Karonga is an area of medium and high multi hazard vulnerability. The lead contributor to this vulnerability is susceptibility, which manifests itself as high and very high, with predominance in the high levels. Exposure manifests on the lower end of vulnerability spectrum. Lack of capacity is predominantly medium. Socio economic and environmental aspects underlie this susceptibility. Reducing vulnerability in these economies will demand radical programs that target infrastructural investment, socioeconomic empowerment, environmental management and strengthening of institutional capacity.

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Section: Discussionmentioning

confidence: 99%

A Multi Hazard Perspective in Flood and Drought Vulnerability: Case Study of Malawi

Kamanga¹,

Tantanee²,

Mwale³

et al. 2020

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“…Health problems could result in a shortage of family labour for operating agricultural lands. A similar study in Ghana revealed that the sensitivity of farmers to the impacts of climate variability was partly contributed from their higher exposure, especially in households who do not own enough livelihood capital to support agricultural labour [24].…”

Section: Sensitivitymentioning

confidence: 93%

“…Several researchers have attempted to explore the blend between livelihood approaches and vulnerability dimensions as part of a broader study of sustainable livelihood development. Many studies in Africa and elsewhere have found varied results in terms of which factors contribute to overall livelihood vulnerability [19][20][21][22][23][24][25]. Other studies in this continent (e.g., [7][8][9]) have indicated that lower adaptive capacity and higher exposure to climate-related hazards (e.g., drought) are the major contributors to livelihood vulnerability and consequently undermine the sustainability of small-scale farmers' livelihood bases.…”

Section: Livelihood Vulnerability To Climate Changementioning

confidence: 99%

Communities’ Livelihood Vulnerability to Climate Variability in Ethiopia

et al. 2019

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Ethiopia has experienced more than 10 major drought episodes since the 1970s. Evidence has shown that climate change exacerbates the situation and presents a daunting challenge to predominantly rain-fed agricultural livelihoods. The aim of this study was to analyze the extent and sources of smallholder famers’ livelihood vulnerability to climate change/variability in the Upper Blue Nile basin. We conducted a household survey (n = 391) across three distinct agroecological communities and a formative composite index of livelihood vulnerability (LVI) was constructed. The Mann–Kendall test and the standard precipitation index (SPI) were employed to analyze trends of rainfall, temperature, and drought prevalence for the period from 1982 to 2016. The communities across watersheds showed a relative difference in the overall livelihood vulnerability index. Aba Gerima (midland) was found to be more vulnerable, with a score of 0.37, while Guder (highland) had a relatively lower LVI with a 0.34 index score. Given similar exposure to climate variability and drought episodes, communities’ livelihood vulnerability was mainly attributed to their low adaptive capacity and higher sensitivity indicators. Adaptive capacity was largely constrained by a lack of participation in community-based organizations and a lack of income diversification. This study will have practical implications for policy development in heterogeneous agroecological regions for sustainable livelihood development and climate change adaptation programs.

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“…Since households with limited assets are at an increased exposure to climate-induced variability and their ability to cope is restricted [48], livelihood vulnerability can be expressed as the sum of exposure and adaptability. Hence, the third flood vulnerability indicator FVI 3 can be obtained from livelihood vulnerability LV linearly aggregated from exposure E and lack of adaptability A along with sensitivity S in Equation (3), by adopting the framework in previous studies [22][23][24][25][26][27]:…”

Section: Aggregation Frameworkmentioning

confidence: 99%

“…where u i is the normalized value of the original value x i for the proxy variable i, max(x i ) and min(x i ) are the maximum and the minimum values, respectively of the proxy variable i, and s max and s min are the maximum of 100 and the minimum of 1, respectively of the normalized value u i . Following previous studies [19,[22][23][24][25][26][27][29][30][31][32][33][34][35]38,39], the normalized proxy variables are then linearly aggregated into each component indicator such as exposure E, sensitivity S, lack of adaptability A, potential impact PI, livelihood vulnerability LV, or internal factor IF, respectively with the weighting factor w i for the total number k of proxy variables for each component indicator:…”

Section: Indicator Constructionmentioning

confidence: 99%

Comparative Analysis of Flood Vulnerability Indicators by Aggregation Frameworks for the IPCC’s Assessment Components to Climate Change

Lee

Choi

2019

Applied Sciences

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As severe flood damages have been increasing due to climate change, the flood vulnerability assessment is needed in the flood mitigation plans to cope with climate-related flood disasters. Since the Intergovernmental Panel on Climate Change Third Assessment Report (IPCC TAR) presented the three assessment components, such as exposure, sensitivity, and adaptability for the vulnerability to climate change, several aggregation frameworks have been used to compile individual components into the composite indicators to measure the flood vulnerability. It is therefore necessary to select an appropriate aggregation framework for the flood vulnerability assessments because the aggregation frameworks can have a large influence on the composite indicator outcomes. For a comparative analysis of flood vulnerability indicators across different aggregation frameworks for the IPCC’s assessment components, the composite indicators are derived by four representative types of aggregation frameworks with all the same proxy variable set in the Republic of Korea. It is found in the study site that there is a key driver component of the composite indicator outcomes and the flood vulnerability outcomes largely depend on whether the key component is treated independently or dependently in each aggregation framework. It is concluded that the selection of an aggregation framework can be based on the correlation and causality analysis to determine the relative contribution of the assessment components to the overall performance of the composite indicators across different aggregation frameworks.

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Assessing vulnerability of horticultural smallholders’ to climate variability in Ghana: applying the livelihood vulnerability approach

Cited by 35 publications

References 27 publications

A Multi Hazard Perspective in Flood and Drought Vulnerability: Case Study of Malawi

A Multi Hazard Perspective in Flood and Drought Vulnerability: Case Study of Malawi

Communities’ Livelihood Vulnerability to Climate Variability in Ethiopia

Comparative Analysis of Flood Vulnerability Indicators by Aggregation Frameworks for the IPCC’s Assessment Components to Climate Change

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