Assessment of rice farmers’ adaptive capacity to environmental change in An Giang province

AGU International Journal of Sciences – 2019, Vol. 7 (1), 85 – 97

ASSESSMENT OF RICE FARMERS’ ADAPTIVE CAPACITY TO ENVIRONMENTAL
CHANGE IN AN GIANG PROVINCE
Duong Truong Phuc1
1

University of Social Sciences and Humanities, VNU - HCM

Information:
Received: 29/09/2018
Accepted: 06/12/2018
Published: 11/2019
Keywords:
Adaptation, Rice Farmer,
Livelihood, Climate Change,
Vulnerability

ABSTRACT
The Vietnamese Mekong Delta is comprised of deposited alluvium from the
Mekong River. Based on favorable conditions of soil, climate, and
hydrology, farmers have developed this region as an area specializing in
food crops. In particular, rice is a major crop, and its cultivation is the main
livelihood of millions of farmers. It has Vietnam’s highest level of exposure
and dependence on natural and socio-economic factors.Simultaniously, the
production environment has hosted specific changes due to the interaction
between climate change (natural) and human activity (socio-economic),
which creates risks that can make agricultural livelihoods vulnerable. In this
context, the adaptation of farmers' livelihoods has attracted widespread
attention. This article aims to assess the adaptive capacity of farmers
through an adaptive capacity index using a case study in An Giang province.

The results showed that farmers are unable to diversify their income as well
as to adapt to changes. Consequently, they are vulnerable to external
shocks. On this basis, the article proposes some solutions to improve
adaptive capacity, which is "enhancing livelihood asset" and multifunctional agricultural transformation..

Klein, & Wandel, 2000; Smit & Pilifosova,
2003).

1. INTRODUCTION
Adaptation
is
essential
to
external
environmental change (Adger et al., 2009). The
term derives from natural science, especially
evolutionary biology, through Charles Darwin's
studies of natural evolution and selection (Smit
& Wandel, 2006). In the context of
environmental change, adaptation is the
behavioral modification of groups and
organizations to reduce vulnerability to climate
change (Pielke, 1998) or the adjustment of
socio-ecological responses to climate stimuli
and effects (Adger et al., 2009; Smit, Burton,

Agricultural production is the primary source of
income for most rural communities.
Consequently, adapting to the adverse effects of
environmental change is necessary to

stabilizing livelihoods and ensuring food
security (Bryan, Deressa, Gbetibouo, &
Ringler, 2009). Agricultural adaptation to
climate/environmental change is a complex and
multi-dimensional process (Bryant et al., 2000),
involving a wide range of stakeholders,
including policymakers, extension agents, non-

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AGU International Journal of Sciences – 2019, Vol. 7 (1), 85 – 97

governmental organizations, researchers, and
local communities (Bryan et al., 2009).

livelihood. The level of vulnerability depends in
part on the adaptability of farmers through
access to and ownership of livelihood assets
that support livelihood strategies. Therefore, the
understanding and assessment of the status of
household livelihood assets are necessary for
the context of many changes in the production
environment. From there, some strategies for
improving livelihoods have been proposed,
with implications for farmers to reduce
vulnerability and poverty.

There are many measures to adapt to climate
change in agriculture (Bradshaw, Dolan, &

Smit, 2004; Kurukulasuriya & Mendelsohn,
2008; Mertz, Mbow, Reenberg, & Diouf, 2009)
and various factors affecting the use of any
adaptation measures (Deressa, Hassan, Ringler,
Alemu, & Yesuf, 2009). Some research
suggests that individual characteristics affect
adaptation, while others suggest that production
experience, access to information, credit, and
agricultural extension services strengthen the
ability to apply adaptive measures (Maddison,
2007; Nhemachena & Hassan, 2007).

2. METHOD
The paper is based on i) Secondary data studies
on farmer’s livelihood and livelihood
adaptation; ii) Primary data from a survey of
240 rice farmers in Tri Ton, An Giang on the
status of livelihood assets and awareness of
flood and drought. Also, in order to quantify
access to livelihood assets in support of
adaptive strategies, the paper also provides an
index to measure it adapt to (Hahn, Riederer, &
Foster, 2009) through several steps as follows:

An Giang farmers choose rice as the main crop
for their agricultural livelihood from the time of
reclamation as a behavior due to a natural
environment with a favorable climate,
hydrology, and soil. However, under the impact
of climate change and human activities, the

production environment has provided many
adverse changes for farmers. Besides,
commodity-oriented farmers need to ensure
livelihood security and survival levels have led
to market risks.

Step 1: Overviewing of rice cultivation
livelihood research for the selection of
indicators.
Step 2: Classifying the selected indicators into
five types of livelihood assets.

For environmentally sensitive livelihoods such
as rice cultivation, changes in flood and drought
levels create risks that could lead to vulnerable

Step 3: Weighting for each criterion of an
indicator as follows:

Table 1. Weight for Criteria

Serial

First

Second

Third

Weight

0.33

0.67

1.00

Step 4: Providing a set of official Indicators:
Table 2. The Indicator of Measuring Livelihood Assets

Capital
Human Capital
(H)

Indicator

Education

Criteria

Weight

Lowest through primary school

0.33

Secondary school

0.67

High school through highest

1.00

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AGU International Journal of Sciences – 2019, Vol. 7 (1), 85 – 97

Capital

Indicator

Criteria

Weight

Frequently get disease

0.33

Sometimes get disease

0.67

Not get disease

1.00

<4 people

0.33

4-5 people

0.67

>5 people

1.00

Based on experience

0.33

Apply science and technology

0.67

Combination of both

1.00

Never

0.33

Sometimes (<3 times/year)

0.67

Frequently (>=3 times/year)

1.00

Never
Weather and pest information
Sometimes (<3 times/year)
update
Frequently (>=3 times/year)

0.33

Health

Household size

Farming method

Agricultural training

0.33

Sometimes (<3 times/year)

0.67

Frequently (>=3 times/year)

1.00

Never

0.33

Sometimes (<3 times/year)

0.67

Frequently (>=3 times/year)

1.00

Never

0.33

Sometimes (<3 times/year)

0.67

Frequently (>=3 times/year)

1.00

Never
Local
government's
Sometimes (<3 times/year)
production support

Frequently (>=3 times/year)

0.33

Neighbors’ support

Relationship’s support

(S)

1.00

Never
Market information update

Social Capital

0.67

Local
government's
support

Never
life
Sometimes (<3 times/year)
Frequently (>=3 times/year)

Agricultural
center’s support

extensionNever
Sometimes (<3 times/year)

87

0.67
1.00
0.33
0.67
1.00
0.33
0.67


AGU International Journal of Sciences – 2019, Vol. 7 (1), 85 – 97

Capital

Indicator

Starting capital

Criteria

Weight

Frequently (>=3 times/year)

1.00

Underfunding

0.33

Little, need other loans

0.67

Much, no need other loans

1.00

Not loan

0.33

Loan from friends, neighbors Low-interest rate loan

0.67

No need

1.00

Not loan

0.33

Loan

0.67

No need

1.00

Not loan
Non-official loan (blackLoan
market, trade credit...)
No need

0.33

Official loan
Financial Capital (bank, credit fund...)
(F)

Only rice cultivation

Income

0.67
1.00
0.33

More income than rice cultivation (<2
0.67
livelihoods)
More income than rice cultivation (>=2

1.00
livelihoods)

Housing

Running water

Physical Capital
(P)

Traffic vehicle

Means of production

Traffic road

Temporary

0.33

Semi-durable

0.67

Durable

1.00

River-water, well-water

0.33

Rain-water

0.67

Tap-water

1.00

Bicycle

0.33

Bicycle, motorcycle

0.67

Bicycle, motorcycle, car

1.00

Rent

0.33

Work exchange

0.67

Own

1.00

Dirt road

0.33

Gravel road

0.67

Asphalt road

1.00

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AGU International Journal of Sciences – 2019, Vol. 7 (1), 85 – 97

Capital

Indicator

Rice variety

Land area

Land quality

Natural Capital
(N)
Water supply

Water quality

Criteria

Weight

Not access

0.33

Access, little diversity

0.67

Access, diversity

1.00

Small (0,0ha≤S≤0,9ha)

0.33

Average (1,0ha≤S≤1,9ha)

0.67

Large (2,0ha≤S≤3,0ha)

1.00

Bad (Alkaline)

0.33

Average (Conditioning)

0.67

Good (Alluvium)

1.00

Shortage

0.33

Full

0.67

Copious

1.00

Bad (Pollution beyond standards)

0.33

Average (Simple process)

0.67

Good (Direct use)

1.00

Step 5: Setting the Calculated Formula
Table 3. The Calculated Formula

Human capital

H = (Wi1+…+Wi7)/7

Social capital

S = (Wi1+…+Wi5)/5

Financial capital

F = (Wi1+…+Wi5)/5

Physical capital

P = (Wi1+…+Wi6)/6

Natural capital

N = (Wi1+…+Wi4)/4

Adaptive Capacity Index

ACI= (H+S+F+P+N)/5

Calculated results are divided into three levels
Table 4. Classifying the Calculated Result

Level

Low

Moderate

High

Value

0.00-0.49

0.50-0.69

0.70-1.00

3. RESULTS AND DISCUSSIONS

prerequisite for adaptation (Nelson, Adger, &
Brown, 2007). This process requires an

understanding of the farmer's perceptions of
environmental change, internal and external

Farmer household adaptability assessment is the
process that corresponds to vulnerability
assessment and is considered a base-line

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AGU International Journal of Sciences – 2019, Vol. 7 (1), 85 – 97

resources, the ability to combine these
resources, and some factors affecting the
adaptive capacity. Such as assessing the
adaptability of rice farmers based on i)
perceptions of environmental change (flood and
drought); and sustainable access to livelihood
assets such as human capital, social capital,
financial capital, physical capital, and natural
capital.

Floods bring a large amount of sediment to
improve the fertility of the soil and clean the
fields. They also create income for people
through fishing and tourism services (Đào Công
Tiến, 2001; Nguyễn Thế Bình, 2011). However,
construction works such as closed dikes and
hydro-electric dams have reduced their benefits,
causing a significant impact on production. The

monitoring results from the MODIS satellite
image show that the period 2009-2015 saw a
severe decline in the flooded areas in An Giang
province, especially in the research-targeted
areas such as Tri Ton (Fig 1).

3.1 Farmers’ Perceptions of Environmental
Change
3.1.1 Floods
Floods are a natural phenomenon occurring
from July to November in An Giang province.

Figure 1. Distribution of Flooded Area in An Giang province During 2009-2015
Source: (Phạm Duy Tiễn, 2016)

In Tri Ton, the percentage of farmers who think
that the flood level has decreased significantly
compared to previous floods accounted for
87.31% while only 49.46% think flood level

decrease had an impact on rice cultivation.
Thus, although farmers perceive that flooding
decreases, they do not think that the change has
affected production (Table 5).

Table 5. Perceptions of farmers about flood change

Impact
Perception

No (%)

Yes (%)

Total (%)

More decrease

49.46

37.85

87.31

Less decrease

4.48

4.42

8.90

Unchanged

0.95

2.85

3.80

Total

54.89

45.12

100.00

Source: Survey data in May 2017

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AGU International Journal of Sciences – 2019, Vol. 7 (1), 85 – 97

3.1.2 Droughts

monitoring results from the period 2010-2015
showed an expanded tendency in drought areas,
especially semi-mountainous areas such as Tinh
Bien-Tri Ton (Fig. 2).

Droughts can occur year-round in the Mekong
Delta, mainly
meteorological droughts.
However, climate change has increased the
area, intensity, and frequency of droughts. The

Figure 2. Distribution of Drought Areas in An Giang During 2010-2015
Source: (NRED, 2016)

the notion of possible risks affecting rice yields
and postharvest consumption resulting in
adaptive measures to mitigate losses such as the
transfer of crop plants, the storage of
production water, and a reduction of chemical
fertilizer use. However, in the study area,
58.33% of farmers agreed that the production
environment had changed but had not yet taken
adaptive measures (Table 7).

Based on production experience, most of the
respondents said that drought had increased
over the previous period (87.46%) and had a
negative impact on production (62.11%) (Table
6).
Local farmers are relatively well aware of
environmental changes, agreeing that there has
been decreasing flood and increasing drought
activity. Based on that perception, farmers form
Table 6. Perceptions of Farmers About Drought Change

Impact

Yes (%)

No (%)

Total (%)

Increase

62.11

25.35

87.46

Unchanged

3.97

3.77

7.74

Decrease

1.80

3.00

4.80

Total

67.88

32.12

100.00

Perception

Source: Survey data in May 2017

Table 7. Farmers' Perceptions of the Implementation of Adaptation Measures

Perception

Adaptive measures

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AGU International Journal of Sciences – 2019, Vol. 7 (1), 85 – 97

Proceed (%)

Not proceed (%)

Total (%)

Yes (%)

36.88

58.33

95.21

No (%)

1.66

3.13

4.79

Total (%)

38.54

61.46

100.00

Source: Survey data in May 2017

Therefore, although farmers may have access to
the information on environmental change
through the media and have agreed in theory,
very few farmers have taken adaptive measures
to mitigate their livelihood risks.

achieve the desired livelihood outcomes (DFID,
1999). Evaluation of human capital is based on
indicators such as education, health, household
size, farming techniques, and access to
information. From the calculation results, the

human capital in the study area was moderate
(H = 0.52). Among them, the lowest was
householder’s education (0.25), and the highest
was householder’s health (0.64). In general,
there were 59.17% of farmers with low human
capital and 36.83% of them with moderate
human capital (Table 8).

3.2 Farmers’ Access to Livelihood Assets
3.2.1 Human Capital
The first livelihood asset which affects farmer
household livelihood outcome is human capital.
This is a significant asset within a farmer's
internal resources; a resource which effectively
governs the use of the remaining assets to

Table 8. The Status of Human Capital

Level

Percentage (%)

Low

59.17

Moderate

36.83

High

4.00

Total

100.00
Source: Survey data in May 2017

3.2.2 Social Capital

their friends and neighbors, as well as
government and social organizations. Locally,
the results showed that social capital was low
(S = 0.45). In particular, the local government's
support (policy) was lowest (0.37), and the
agricultural extension center’s support was
highest (0.68). In terms of distribution, 59.17%
of farmers had low social capital, 36.04% of
them had moderate social capital (Table 9).

The second livelihood asset, which affects
farmer household livelihood outcomes is social
capital. This is considered a safety net and
compensates for the shortage of other types of
capital to ensure livelihoods (DFID, 1999). The
assessment of social capital is an examination
of the ability of external support to develop the
adaptive capacity for the farmer household
through aspects such as support among farmers,

Table 9.The Status of Social Capital

Level

Percentage (%)

Low

59.17

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AGU International Journal of Sciences – 2019, Vol. 7 (1), 85 – 97

Moderate

36.04

High

4.79

Total

100.00
Source: Survey data in May 2017

3.2.3 Financial Capital

study area, the results show that financial
capital was low (F = 0.39), with the lowest
being starting capital (0.30) and the highest
being conventional loans (0.67). Also, 63.13%
of farmers had low financial capital, and
33.12% of them had moderate financial capital
(Table 10).

The third livelihood asset, which affects the
farmers’ household livelihood outcomes is
financial capital. This is the most flexible asset
and can be converted to the remaining assets
(DFID, 1999), evaluating financial capital
through ownership and access to capital for
production and income diversification. In the

Table 10. The Status of Financial Capital

Level

Percentage (%)

Low

63.13

Moderate

33.12

High

3.75

Total

100.00
Source: Survey data in May 2017

3.2.4 Physical Capital

water,
vehicles, production means, and
roadways .

The fourth livelihood asset, which affects the
farmers’ household livelihood outcome is
physical capital. This is an asset that enhances
farmers' access and connectivity and actively
supports livelihood strategies (DFID, 1999).
The assessment of physical capital can be made
through the consideration of housing, running

From the results of the calculation, physical
capital was moderate (P = 0.53), of which the
lowest value was production means (0.14), and
the highest value was housing ( 0.67). Also, in
the local residents, 50.92% of farmers had
moderate physical capital, and 43.88% of them

had low physical capital (Table 11).

Table 11. The Status of Physical Capital

Level

Percentage (%)

Low

43.88

Moderate

50.92

High

5.21

Total

100.00
Source: Survey data in May 2017

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production. From the calculation results, the
natural capital in the study area was low (N =
0.48), in which the lowest value was the land
area (0.32) and the highest value was water
quality (0.67). According to the results from
Table 12, 54.58% of farmers had low natural
capital, and 43.13% of them had moderate
natural capital.

3.2.5 Natural Capital
The final livelihood asset, which affects the
farmers’ household livelihood outcome is
natural capital. This is an essential input source
for agricultural livelihood, not only in regards
to ownership but also exposure (DFID, 1999).
The assessment of natural capital can be made
through area and quality of cultivated land,
supply, and quality water sources for

Table 12. The Status of Natural Capital

Level

Percentage (%)

Low

54.58

Moderate

43.13

High

2.29

Total

100.00
Source: Survey data in May 2017

capital (P = 0.53) (Fig. 3). In future, as
production risks increase, farmers will not
improve their livelihood assets; their adaptive
capacity will decline, and their livelihoods will
be compromised, leading to lower incomes and
a rising risk of poverty.

Through the process of understanding and
assessing the status of livelihood assets of rice
farmers in the Tri Ton district, An Giang
province, most of the livelihood assets are
evaluated from low to moderate, lowest
financial capital (F = 0.41) and highest physical

Figure 3. The Status of Farmers’ Household Livelihood Assets
Source: Survey data in May 2017

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3.3 Assessment of Farmers’
Adaptive Capacity

Household

assessment of livelihood assets combined with
farmers' perceptions of changes in floods and
droughts. The results show that the adaptive
capacity of the area is generally low (ACI =
0.47) (Table 13).

The assessment of the adaptability of rice
farmers based on the adaptive capacity index
was synthesized from the results of the

Table 13. The Result of Adaptive Capacity in the Study Area

Livelihood assets

Value

Human capital

H

0.52

Social capital

S

0.47

Financial capital

F

0.41

Physical capital

P

0.53

Natural capital

N

0.45

Adaptive Capacity Index

ACI

0.47

Source: Survey data in May 2017

Concerning distribution, 95.87% of households
have low to moderate adaptive capacity, and
only 4.13% of farmers are highly adaptable to
the risks of environmental change (Table 14).

In the future, when the risks and environmental
risks increase. If the adaptive capacity of
farmers is not improved, the level of livelihoods
will be increased.

Table 14. The Status of Adaptive Capacity

Adaptive capacity

Percentage (%)

Low

64.81

Moderate

31.06

High

4.13

Total

100.00
Source: Survey data in May 2017

4. CONCLUSIONS
RECOMMENDATIONS

AND

adaptive measures. Besides, the status of
household livelihood assets in the study area is
low to moderate, so the adaptive capacity of
households is not high. In the future , when the
risks from environmental change crease,
farmers will need to strengthen their adaptive
capacity. Based on the survey results, this paper
proposes some measures which can support
adaptation for farmers as strengthening the
livelihood
assets
and
encouraging
multifunctional agricultural transformation.

In order to assess the adaptability of rice
farmers in An Giang province it is essential to
understand their perceptions of changes in the
production environment, their intent to

implement adaptation measures and the status
of livelihood assets which can support
livelihood strategies. Research results showed
that although farmers perceive the production
environment as having many changes and
adverse effects few households implement

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AGU International Journal of Sciences – 2019, Vol. 7 (1), 85 – 97

For strengthening access to livelihood assets,
the paper deals with i) enhancing access to
information (farmers should actively refer to
the information from media, agricultural
training, agricultural conference, agricultural
extension officers, and local governments); ii)
expanding social networks (farmers should
maintain relationships with other farmers,
especially good farmers, build relationships
with rice traders, regularly attend agricultural
training sessions, and discuss issues related to
rice production with agricultural extension
officers); iii) diversifying incomes (farmers
should select suitable varieties and apply
science-technology to increasing productivity,
diversifying income by expanding their skillsets (agriculture + non-agriculture), decreasing
production costs maximal, saving the
production cost, selecting preferential loans,

(low-interest rates); and accumulating land
(farmers should borrow more money to buy or
rent more land) collaborating with neighboring
farmers to expand production areas, preparing
appropriate administrative procedures to
streamline land accumulation is not obstructed).

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Multifunctional agriculture is becoming
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multifunctional
agricultural
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weak. In some vulnerable areas, such as rural
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additional tourism functions that are necessary
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