Mapping Vulnerability to Climate Change

Heltberg, Rasmus; Bonch-Osmolovskiy, Misha

doi:10.1037/e601752012-001

Cited by 26 publications

(18 citation statements)

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“…Most of the literature on climate impact focuses on vulnerability and the related concepts of exposure, sensitivity and adaptability (Smit and Wandel, 2006;Heltberg and Bonch-Osmolovskiy, 2011). Several factors that influence climate vulnerability include (Cui et al, 2010): (1) Exposure-the degree of climate stress upon a particular unit of analysis.…”

Section: Vulnerability Assessment Of Water Resourcesmentioning

confidence: 99%

Sensitivity and vulnerability of water resources in the arid Shiyang River Basin of Northwest China

Wan

Xia

et al. 2014

J. Arid Land

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The sensitivity and vulnerability of water resources to climate change is difficult to assess. In this study, we used a conceptual hydrologic model to investigate the sensitivity of streamflow to climate change. We also proposed a framework to evaluate the vulnerability of water resources in arid regions. We applied this framework to a case study of the Shiyang River Basin in Northwest China. Results showed that the precipitation and streamflow in Shiyang River Basin exhibited no significant trends of change from 1956 to 2010. In the past five decades, however, the temperature increased significantly by 0.37°C per decade. According to the sensitivity assessment, a 10% increase in precipitation and a 1°C increase in temperature altered mean annual streamflow by averages of 14.6% and -0.5%, respectively, from 1988 to 2005. In the 2000s, the calculated vulnerability of water resources in Shiyang River Basin was more than 0.95, indicating severe vulnerability. The increase in the amount of precipitation and the implementation of water-saving measures can reduce the vulnerability of water resources in the future; if precipitation increases by 10% per decade and the use of irrigation water decreases by 15% in the 2030s, the evaluated value of water resources vulnerability will be reduced to 0.79. However, the region remains highly vulnerable. The proposed framework for vulnerability assessment can be applied to the arid regions in Northwest China, and the results of our efforts can identify adaptation strategies and improve the management of water resources in such regions.

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Section: Vulnerability Assessment Of Water Resourcesmentioning

confidence: 99%

Sensitivity and vulnerability of water resources in the arid Shiyang River Basin of Northwest China

Wan

Xia

et al. 2014

J. Arid Land

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“…The founder states that lack of education is among the variable that put farm households to be vulnerable in the area. Since well-educated people are in better position to manage risks related to climate change and its impact [34].…”

Section: Social Vulnerabilitymentioning

confidence: 99%

“…In this regard, the global poor, particularly in developing countries are adversely impacted by climate change since they live in heavily influenced countries and locations within those countries; and depend on natural resource-based livelihoods that are disproportionately affected by climate change [9]. This is mainly due to a dependence of the poor on rain-fed agriculture for their living in all aspect (including for their social and economic wellbeing) which is significantly affected and the most vulnerable sectors to climate change [6,10].…”

Section: Introductionmentioning

confidence: 99%

Farm Household Vulnerability to Climate Change and Its Determinants: The Case of Ada’a Berga District of West Shewa, Ethiopia

Tofu

Dedefa

2018

JSRR

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The main objective of this study was to analyse the vulnerability of households to the impacts of climate change and factors that influence houses to be vulnerable in Ada'a Berga districts of western Shewa zone. To achieve the objective, study area and sample households' were selected by using multi-stage sampling procedure. Descriptive statistical analysis, Principal Component Analysis (PCA) and Ordinal Logit Model were applied to a set of primary data collected from 421 randomly sampled farmers with the aid of semi-structured questionnaire in six purposively selected kebeles'. The analytical results of descriptive statistics indicates that households that are headed with above 65 years of age, illiterate, less experienced in farming, with more number of dependent family members, and tenants who are not frequently visited with extension workers, lack of access to climate information, depend only on rain fed farming, no own land, no access to credit at all, no

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“…Common characteristics in the exposure assessments include: They 1) are estimated for a range of spatial scales from household to regional to global (O'Brien et al 2004a;O'Brien et al 2004b;Baettig et al 2007;Challinor et al 2010;Fraser et al 2013); 2) are estimated for a variety of crops; 3) use a CF to represent a stressor; 4) are calculated using data from multiple sources, such as measured data (Simelton et al 2009;Heltberg and Bonch-Osmolovskiy 2011;Antwi-Agyei et al 2012), modeled data (O'Brien et al 2004b;Baettig et al 2007;Gbetibouo et al 2010), survey data (Pandey and Jha 2012), satellite remote-sensing products (Dong et al 2012), maps (Anh 2011), and/or earlier studies (Bhattacharya and Das 2007); 5) are estimated at multiple time periods such as past, present, and/or future - (O'Brien et al 2004a;Simelton et al 2009;Antwi-Agyei et al 2012;Fraser et al 2013); and 6) require an aggregation method when multiple CFs are used (Table S.1b). These characteristics are arranged in steps and used in the development of the flowchart to estimate EI.…”

Section: Review Of Exposure Methods: Index-based Approachesmentioning

confidence: 99%

A system’s approach to assess the exposure of agricultural production to climate change and variability

2016

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Estimating the exposure of agriculture to climate variability and change can help us understand key vulnerabilities and improve adaptive capacity, which is vital to secure and increase world food production to feed its growing population. A number of indices to estimate exposure are available in literature. However, testing or validating them is difficult and reveals a considerable variability, and no systematic methodology has been developed to guide users in selecting indices for particular applications. This need is addressed in this paper by developing a flowchart from a conceptual model that uses a system's approach. Also, we compare five approaches to estimate exposure indices (EIs) to study the exposure of agriculture to climate variability and change: single stressor-mean climate, single stressor-extreme climate, multiple stressor-mean climate, multiple stressor-extreme climate; and combinations of the above approaches. The developed flowchart requires gathering information on the region of study, including its agriculture, stressor(s), climate factor(s) (CF), period of interest and the method of aggregation. The flowchart was applied to a case study in Kansas to better understand the five approaches to estimate EIs and the implications of the choices made in each step on the estimated the exposure. The flowchart provides options that guide EI estimation by selecting the most appropriate stressor(s), associated CF(s), and aggregation methods when a detailed methodological analysis is possible, or proposes a default method when data or resources do not allow a detailed analysis. Climate adaptation involves integration of a multitude of factors across complex systems. A more standardized approach to Climatic Change (2016) 136:647-659

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Mapping Vulnerability to Climate Change

Cited by 26 publications

References 0 publications

Sensitivity and vulnerability of water resources in the arid Shiyang River Basin of Northwest China

Sensitivity and vulnerability of water resources in the arid Shiyang River Basin of Northwest China

Farm Household Vulnerability to Climate Change and Its Determinants: The Case of Ada’a Berga District of West Shewa, Ethiopia

A system’s approach to assess the exposure of agricultural production to climate change and variability

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