INTRODUCTION
The Necessity of the Research
Climate change is a global issue with varying impacts across different regions, countries, sectors, and communities In the coming year, its effects will become increasingly evident, posing significant challenges for many communities Additionally, climate change has adversely affected agricultural production, driven by rising air temperatures and alterations in rainfall patterns, leading to floods, droughts, and saltwater intrusion.
Southeast Asia is one of the regions most vulnerable to climate change, particularly affecting poor and agricultural populations in developing countries due to their limited access to alternative production methods and coping mechanisms Countries like Vietnam, which has a long coastline and a high concentration of population and economic activities in coastal areas, are particularly at risk The reliance on agriculture, natural resources, and forestry for livelihoods makes these communities even more susceptible to the adverse effects of climate change Furthermore, existing inequalities and marginalization exacerbate the challenges faced by vulnerable populations in the region.
The criteria for vulnerability assessment have evolved through the IPCC Assessment Reports (AR) To evaluate the impacts of climate change, utilize the vulnerability framework suggested by the IPCC in its Third Assessment Report (TAR).
The Fourth Assessment Report (AR4) by the IPCC outlines vulnerability as a function of exposure, sensitivity, and adaptive capacity Within this framework, exposure is defined as a hazard-focused concept, with indicators such as the heatwave duration index, drought intensity, and flood frequency serving as key metrics to assess environmental risks.
The vulnerability assessment outlined in the IPCC's Fifth Assessment Report (AR5) identifies key elements of exposure, including people, assets, services, resources, infrastructure, and ecosystems Vulnerability is defined as the interplay between sensitivity to harm and the capacity to cope and adapt Within the AR5 risk framework, both exposure and vulnerability are emphasized as critical components in understanding risk.
Figure1.2 The risk (R) assessment framework in the IPCC SREX/AR5 (IPCC 2012,
Recent studies on climate-related vulnerability assessments primarily utilized the AR4 framework (Nguyen et al 2016, 2017; Crane et al 2017; Aslam et al 2018; Filho et al 2018; Foden et al 2019) However, the IPCC's focus has evolved from hazard-centered assessments to risk-centered evaluations, emphasizing the interplay of exposure, vulnerability, and hazard intensity, as highlighted in the SREX and AR5 reports This shift reveals that communities with low greenhouse gas emissions are disproportionately impacted by climate change (IPCC 2022) Consequently, a new vulnerability framework has been adopted since AR5 to enhance discussions on this topic, which is also employed in the present study.
Vietnam is the most vulnerable country in the region to climate change, facing significant risks such as rising sea levels and an increased frequency of natural disasters, including typhoons, floods, and droughts, as highlighted by Yusuf and Francisco (2009).
In the last decade, severe climatic disasters have impacted over 15 million people, with natural disaster losses in 2006 alone estimated at nearly 1.2 billion US dollars Vietnam experiences six to ten storms and tropical depressions annually, resulting in heavy rainfall and flooding that significantly diminish agricultural productivity (Mendoza et al 2014).
The Vietnamese Mekong River Delta (VMD) faces significant threats from a projected 1-meter rise in sea levels, which could lead to severe flooding and salt intrusion, ultimately damaging crops As one of the world's most productive rice-growing regions, the VMD plays a crucial role in Vietnam's agricultural output, which reached approximately 42.7 million tons of rice.
2020, making it the fifth-largest producer of rice in the world and the second-largest exporter of rice (General Statistical Office of Vietnam, GSO 2021)
This research examines Can Tho City, located in the Mekong Delta region, which is bordered by five provinces and comprises five urban districts and four rural districts Established in 2004 after the division of Can Tho Province, the city has a population density of 859 people per square kilometer as of 2021, with key sectors including industry, commercial services, and agriculture Agriculture, in particular, is highly susceptible to climate conditions, making farmers in Can Tho City particularly vulnerable to flooding, which poses a significant threat due to riverbank erosion affecting riverside residents.
Can Tho City, particularly in the Thot Not, Vinh Thanh, and Co Do Districts, features significant agricultural production areas that are prone to flooding due to their low-lying geography (Huynh et al 2020) Notably, only Thot Not District is traversed by the Mekong River, encompassing nine wards, including Tan Loc and Thoi Thuan, which were selected for this study to represent both a river-adjacent ward and one that is not While Huynh et al (2020) evaluated vulnerability in Can Tho City, their research primarily focused on various sectors rather than specifically on agricultural farmers and relied largely on secondary data.
Vulnerability assessment employs two primary methodologies: the top-down and bottom-up approaches The top-down approach emphasizes analyzing the long-term effects of climate change, offering valuable insights for decision-making regarding environmental impacts However, it falls short in effectively demonstrating interactions with local environments and adaptation strategies.
The bottom-up strategy, also referred to as the climate change adaptation approach, emphasizes community involvement and adaptation to local conditions This approach is particularly beneficial for addressing short-term climate change issues, as it leverages indigenous skills, local coping mechanisms, and regional capacities (UNFCCC 2007) Research by Huynh et al (2020) exemplifies this strategy, focusing on short-term impacts and highlighting the importance of social surveys to develop tailored recommendations for affected areas.
This research assesses climate-related vulnerability among agricultural farmers by utilizing household survey data, employing a bottom-up approach to evaluate vulnerability levels and adaptation strategies to climate change impacts Our findings highlight effective practices adopted by farmers in the surveyed areas Furthermore, we examined the discrepancies between secondary data-based and primary data-based approaches in understanding these vulnerabilities.
Research Objectives, Questions and Hypotheses
1.2.1 Research Objectives a) To identify the climate change impacts on the livelihood activities in the study site b) To investigate the current level of vulnerability to CC of farm households by calculating a vulnerability score based on household survey and using the IPCC’s AR5 vulnerability concept c) To assess the awareness of the farmers related to CC and its impact
This study investigates five key research questions focused on climate change impacts in Can Tho City, particularly concerning local farmers' livelihoods It explores the specific effects of climate change on these livelihoods and assesses the current vulnerability levels of farmers in the region Additionally, the research examines the various livelihood practices employed by the farmers and seeks to identify strategies for enhancing awareness to improve adaptability among farmers in the Vietnamese Mekong Delta, especially in the targeted study areas.
In order to clarify above these issues, I have hypothesized as follows:
Climate change impacts, including rising temperatures, flooding, sea level rise, and extreme weather events, significantly threaten the livelihoods of agricultural farmers in Can Tho City, making them one of the most vulnerable populations in the area.
Scope of the Research
This study evaluates the vulnerability of agricultural and livelihood activities at the household level in two wards of Thot Not District, Can Tho City, using the AR5 risk framework established by the IPCC Additionally, the research provides recommendations aimed at promoting sustainable livelihoods in the area.
RESEARCH METHODOLOGY
Research Framework
This chapter outlines the research approach and methods used in this study, beginning with a household survey targeting farmers to gather data on their practices and adaptations in livelihood strategies.
CC over the ten years in the study site As the second step, the study created a set of indicators to measure how vulnerable household-level on livelihood production is
In the third step, we categorized vulnerability index scores into three levels: high, medium, and low for each area based on the survey data Subsequently, the fourth step involved comparing these results with findings from previous studies Ultimately, we drew conclusions and engaged in discussions based on a comprehensive analysis of household-level data.
Household surveys for farmers in Can Tho City
Vulnerability assessment due to the impact of climate change
Calculation of the vulnerability index score
Comparison of the results with the previous studies
Findings and recommendations for sustainable livelihood indicators, followed by a suggested solution to increase sustainability and decrease vulnerability.
Research Methods
This research utilized the IPCC's AR5 risk framework definition of vulnerability to evaluate the study site's susceptibility Vulnerability is determined by two key factors: sensitivity and adaptive capacity.
In the equation, where V is vulnerability, S is Sensitivity, and AC is Adaptive
Vulnerability (V) is defined as a multifaceted concept that includes sensitivity to harm and the inability to cope or adapt effectively Table 2.1 provides a detailed overview of the vulnerability concept as outlined in the IPCC's AR5 report.
Table 2.1 Vulnerability concept based on the IPCC’s AR5
Livelihood sensitivity (S2) Health sensitivity (S3) Infrastructure sensitivity (S4) Financial sensitivity (S5)
2 Adaptative capacity (AC) Economic capacity (AC1)
Livelihood capacity (AC2) Human capacity (AC3)
Climate change vulnerability assessment of farm households is calculated based on the following research methods and objectives (Table 2.2)
Table 2.2 Vulnerability concept based on the IPCC’s AR5
Description Objectives Name of methodology
To find out the current status of livelihoods & agricultural production In order to determine how vulnerable households in the survey areas are due to the impacts of climate change
Identify the information concerning the livelihood (housing, financial status, etc.) and how disasters affected them
In-depth- interview (Local authorities)
In order to gain a better understanding of overall livelihood status, climate change conditions of the areas
Data Collection
The study focuses on two selected wards, Tan Loc and Thoi Thuan, in Thot Not District, Can Tho City, chosen for their geographical and agricultural production characteristics A random sampling method was employed within these wards, and the sample size was determined using the Yamane formula (1967).
In the equation, 'n' represents the sample size, 'N' denotes the total population in the survey area, and 'e' indicates the sampling error, which was set at 10% Applying this formula, it was determined that 100 household surveys are required for both Tan Loc Ward (Area 1, A1) and Thoi Thuan Ward (Area 2, A2) Consequently, the total population for the survey is established.
Figure 2.2 Map of Thot Not District at Can Tho City
Figure 2.3 Map of two survey areas in Thot Not District
Table 2.3 presents the number of households interviewed in the study areas, with a total of 48 households participating in interviews conducted in February 2023 at locations A1 and A2 In A2, after removing duplicate entries, the count of unique households was recorded.
Table 2.3 Sample size of the survey
Name of wards Number of households
Expected population (estimated assuming a family of four)
Ideal population (estimated by equation 2)
A qualitative survey method was employed for the household survey, tailored to the research objectives and vulnerability indicators related to climate change at the village and farmer levels The field survey utilized a questionnaire, detailed in Appendix A, featuring closed-ended questions to facilitate data collection Similar questionnaires were administered across two survey locations to ensure consistency in gathering relevant information for analysis It is important to note that the survey respondents represent a sample of the local population in the research areas.
Field observations were conducted in A1 and A2 of Thot Not District to validate primary data concerning human aspects, livelihood resources, social networking, communication, and demographic conditions, as well as the impacts of climate change stemming from natural disasters The population density in Thoi Thuan was recorded at 1,996 people/km², while Tan Loc Ward had a density of 881.2 people/km², according to the Cần Thơ Municipality Districts and Communes Population Statistics.
In 2009, rice production emerged as the primary livelihood activity in the region, with cultivation occurring across three seasons annually Residents traditionally stored rainwater in clay pots to support their agricultural practices (People’s Committee of Thoi Thuan Ward, 2023) Additionally, farmers in Tan Loc Ward relied on the production of Bell Apples and Guavas as their main sources of income, as illustrated by observation photos in Appendix C.
The in-depth interview design incorporated both open-ended and closed-ended questions to gain insights into the livelihood status and climate change conditions in the surveyed areas Local authorities in Thot Not District were asked close-ended questions regarding the impacts of climate change over the past decade, local natural disasters, and the most significant effects of climate change in Can Tho City Detailed survey information can be found in Appendix B.
Two primary methods exist for evaluating vulnerability: the top-down scientific approach and the bottom-up regional strategy This study emphasizes a community-based adaptation approach, empowering local residents to recognize their future risks and actively engage in the creation and execution of adaptation measures.
This research utilizes the IPCC's 2014 definition of vulnerability from the SREX AR5 framework, focusing on the development of vulnerability indicators (V) that consist of two primary components: sensitivity (S) and adaptive capacity (AC) Indicators from Tier I are derived from Tier II, while Tier III indicators are further informed by Tier III The identification of these indicators at Tier II and Tier III is based on a combination of literature review and practical experience, as detailed in Table 2.4 The indicators are aligned with the works of Oo et al (2018) and Mendoza et al (2014).
Table 2.4 A set of indicators for vulnerability assessment at the household
Tier II indicators Tier III indicators Direction
Dependency ratio in the sample (Child dependency ratio: Age < 18 years)
Female-headed households in the sample
Household heads not achieving secondary education
Households with unemployed family members (age between 16 to over 60)
Households not receiving any support from government or private organization
Households having own land for livelihood production (‒)
Households with family members have any health issues (physical or mental) or disabilities (hearing or speech)
Households joined public health insurance (‒)
Tier II indicators Tier III indicators Direction
Households which stored foods and other essential items (+)
Households which have access to clean water (+)
Households which had medical services and facilities (+)
Households which have a workable drainage system and toilet (+)
Households with normal housing condition (+)
Households dependent on agriculture as the primary source of income (+)
Economic capacity (AC1) Average annual income (‒)
Average year of farming experiences (‒)
Households with family members migrated to work in the other developed places
Households have experienced impacts of natural disaster during the past five years
Households participated in a social group (farmer, authorities, women group etc.)
Tier II indicators Tier III indicators Direction development
(AC3) Households knowing the importance of capacity-building activities to improve the household income
Households receiving technical workshops or seminars related to livelihood production
Level of education (schooling years that household head finished) (+)
Number of working household members (‒)
Households participated in a social group (farmer, authorities, women group etc.)
Calculation Methods
To assess vulnerability indicators, primary data from the household survey was utilized Given that each Tier II indicator is measured in different units, it is essential to standardize them to a uniform system The standardization of each subcomponent, or Tier III indicator, is achieved using a specific equation When a rise in the value of a Tier III indicator correlates with increased vulnerability, the normalization value is calculated based on equation (3).
X is the Tier III indicator (25 subcomponents factors), indicates the minimum value of a Tier III indicator, and = the maximum value of a Tier III indicator
If the value of a Tier III indicator results in a decrease in the vulnerability index score, the normalized value is calculated using equation (4):
Based on the value of Tier III indicators, the vulnerability index can be determined based on the value of the two factors in the following equation (5):
The Vulnerability Index (VI), based on the IPCC AR5 framework, is determined by the interplay of sensitivity (S) and adaptive capacity (AC) This indicates that vulnerability is directly influenced by the combination of these two factors, highlighting the importance of both sensitivity and adaptive capacity in assessing overall vulnerability.
In this study, the vulnerability index (VI) was scaled from (0 to 1) with four level of vulnerability
I 0 to ≤ 0.25 represented as low level of vulnerability
II 0.26 to ≤ 0.50 represented as medium level of vulnerability
III 0.51 to ≤ 0.75 represented as high level of vulnerability
IV 0.76 to ≤ 1 represented as very high level of vulnerability
Households with a vulnerability index score of 0.76 or lower are classified as having a very high vulnerability to climate-related risks In this study, all indicators used to calculate the vulnerability index were assigned equal weights.
This chapter presents the findings derived from research questions, field observations, and household surveys, highlighting the challenges encountered during the research process It also details the overall vulnerability score (V), calculated through an indicator-based assessment method in line with the SREX/AR5 framework established by the IPCC in 2014, focusing on each component (S and AC).
Households Survey (M1)
3.1.1 Impacts of Climate Change on the Livelihood Activities in the Study Areas 3.1.1.1 Impacts of Climate Change on Agriculture in A1
Fruit farmers in Tan Loc Ward (A1) face significant vulnerability to natural disasters, as highlighted by a household survey The survey revealed that 70% of the 20 interviewed households experienced flooding, while 50% were affected by storms during September and October, particularly impacting Bell Apple and Guava cultivation Notably, the total percentage exceeds 100 due to multiple responses Climate change exacerbates these challenges, with flooding and storms identified as primary factors contributing to reduced fruit production, accounting for a 50% decrease in crop yield Additionally, 9 households reported being affected solely by flooding.
7 households affected by 2 kinds of natural disasters and 3 households affected by 3 different kinds of natural disasters
Table 3.1 The impacts of natural disasters in Tan Loc Ward (A1), Thot Not
Data source: Household survey (Question number 7) 3.1.1.2 Impacts of Climate Change on Agriculture in A2
A household survey in Thoi Thuan Ward (A2) revealed that rice farmers face five types of natural disasters, significantly affecting their production The survey indicated that 39% of the 28 interviewed households experienced flooding and heavy rain, particularly impacting the winter-spring crop season from November to February As a result, approximately 60% of the crop yield has been lost or damaged due to these adverse weather conditions.
Natural disasters and troubles by natural disaster
The primary climatic challenges faced by farmers in the two regions include heavy rainfall, flooding, and storms, leading to significant crop losses and damage To address these issues, the local agricultural department must consider implementing adaptation strategies that enhance resilience in farming practices Consequently, a medium level of vulnerability has been identified regarding the capacity development of farmers.
Table 3.2 The impacts of natural disasters in Thoi Thuan Ward (A2), Thot Not
Data source: A household survey (Question number 7) 3.1.2 Sensitivity (S) for Survey Areas
This section presents the calculated sensitivity scores based on five key factors: demographic sensitivity (S1), livelihood sensitivity (S2), health sensitivity (S3), infrastructure sensitivity (S4), and financial sensitivity (S5) Table 3.3 illustrates the sensitivity scores for each area derived from 15 subcomponent indicators The scores for areas A1 and A2 were found to be 0.41 and 0.42, indicating that both areas exhibit similar medium levels of sensitivity to climate change (CC) While these wards are not classified as high-sensitivity areas, they still fall within the medium sensitivity range.
Natural disasters and troubles by natural disasters
No of affected households % of affected households
Table 3.3 The results of the sensitivity in Tan Loc Ward (A1) and Thoi Thuan
No Main factor Subcomponent factor A1 A2
Child dependency ratio (age