(Luận văn thạc sĩ) assessment of adaptive capacity of aquaculture households to climate change in cho moi district, an giang province, vietnam

VIETNAM NATIONAL UNIVERSITY, HANOI VIETNAM JAPAN UNIVERSITY THAI TRONG NGHIA ASSESSMENT OF ADATIVE CAPACITY OF AQUACULTURE HOUSEHOLDS TO CLIMATE CHANGE IN CHO MOI DISTRICT, AN GIANG

VIETNAM NATIONAL UNIVERSITY, HANOI

VIETNAM JAPAN UNIVERSITY

THAI TRONG NGHIA

ASSESSMENT OF ADATIVE CAPACITY OF

AQUACULTURE HOUSEHOLDS TO

CLIMATE CHANGE IN CHO MOI DISTRICT,

AN GIANG PROVINCE, VIETNAM

MASTER’S THESIS

PLEDGE

I assure that this thesis is the result of my own research and has not been published The use of other research‟s results and other documents must comply with the regulations The citations and references to documents, books, research paper, and websites must be in the list of references of the thesis

Author of the thesis

TABLE OF CONTENTS

PLEDGE i

TABLE OF CONTENTS ii

LIST OF TABLES iv

LIST OF FIGURES v

LIST OF ABBREVIATION vii

ACKNOWLEDGEMENT viii

FOREWORD ix

CHAPTER 1 INTRODUCTION 1

1.1 Research issues 1

1.2 Research questions and objectives, and hypothesis 4

1.2.1 Research questions 4

1.2.2 Research objectives 4

1.2.3 Hypothesis 4

1.3 Background of the Study 5

1.3.1 Concepts 5

1.3.2 Research history 8

1.4 Study Area 16

1.4.1 Natural characteristic 16

1.4.2 Socio-economic and environmental characteristics 19

1.4.3 Characteristics of climate change and natural disaster of Cho Moi district 23

1.4.4 Characteristics of aquaculture activity in Cho Moi district 29

CHAPTER 2 METHODOLOGY 31

2.1 Research approach 31

2.2 Research methods 34

2.2.1 Secondary data 34

2.2.2 Establishing and developing a set of AC indicators 35

2.2.3 Data collection 37

2.2.4 Data analysis 42

CHAPTER 3 RESULTS AND DISCUSSION 44

3.1 General information about the study areas 44

3.2 Characteristics of economy, society and environment of households 49

3.2.1 Economic characteristic 49

3.2.2 Social characteristic 52

3.2.3 Environmental characteristic 53

3.2.4 Climate change adaptation characteristics 65

3.3 Assessment of AC of aquaculture households 70

3.3.1 Overall AC assessment 70

3.3.2 Assessment of economic component 73

3.3.3 Assessment of social component 74

3.3.4 Assessment of environmental component 75

3.3.5 Assessment of CC adaptation component 76

CHAPTER 4 RECOMMENDATIONS TO INCREASE LOW ADAPTIVE CAPACITY INDICATORS OF AQUACULTURE HOUSEHOLDS TO CLIMATE CHANGE IN CHO MOI DISTRICT 78

4.1 Overview 78

4.2 Solutions to increase AC of aquaculture households in Cho Moi district 78

4.2.1 Recommendations for management solutions for the government 78

4.2.2 Recommendations for increasing autonomous adaptation for households 81

4.3 Technological recommendation for increasing AC of aquaculture households 82

4.3.1 RAS introduction 83

4.3.2 RAS strengths 86

Chapter 5 CONCLUSIONS 87

REFERENCES 89

APPENDIX 94

LIST OF TABLES

Table 1.1 Economic structure value of Cho Moi during the phase of 2014-2018 20

Table 2.1 Set of indicators to assess AC of aquaculture households in Cho Moi 355

Table 2.2 the number of aquaculture households was randomly chosen for data collection in Cho Moi district 37

Table 2.3 Parameters of water quality were directly measured at study sites 39

Table 2.4 The number of times to measure water samples at the study sites 41

Table 3.1 Average area and yield of aquaculture households at the study sites 48

Table 3.2 Profit margin of each aquaculture type at study areas 49

Table 3.3 SWOT matrix to analyze strengths, weaknesses, opportunities and challenges of each aquaculture system 69

LIST OF FIGURES

Figure 1.1 Geographical location and natural condition map of Cho Moi district, An

Giang 17

Figure 1.2 A structure of the working-age population (left) and structure of population capable of work in economic sectors (right) 21

Figure 1.3 Water surface of Hau river (left) and Tien river (right) in flood season 22 Figure 1.4 Flooding peaks during 1998-2019 phase were measured at upstream and downstream stations in An Giang province 24

Figure 1.5 The map of storm and depression trajectories impacted An Giang during the phase of 1951-2015 27

Figure 1.6 A landslide scene of a riverside resident along the Vam Nao river, Cho Moi district, An Giang 29

Figure 1.7 Profit margin of pangasius households in the phase of 2007-2012 was proportionate with fluctuated peaks of Tien and Hau River in An Giang 30

Figure 2.1 Cause and effect chain approach in climate change 31

Figure 2.2 Study framework was applied to assess AC of aquaculture households 34 Figure 2.3 Residents on floating house was interviewed for data collection 38

Figure 2.4 The methods for the water sampling at inlet and outlet point 40

Figure 2.5 Water samples were collected at the study sites 41

Figure 3.1 The three aquaculture systems located in 6 commutes are shown on maps of the study sites (red circle) 44

Figure 3.2 Popular aquaculture systems in Cho Moi district 46

Figure 3.3 Comparison of average members, labors and female labors between aquaculture types and Cho Moi district 47

Figure 3.4 Comparison of average household income and income per capita between aquaculture systems and Cho Moi district 48

Figure 3.5 The scalability of aquaculture types at study areas 53

Figure 3.6 Waste treatment system of cement/rubber tank (left) and waste effluent of floating house (right) at study sites 54

Figure 3.7 pH indexes of 3 systems were measured at the 3 different points 56

Figure 3.8 DO content of 3 systems was measured at the three different points 58

Figure 3.9 Temperature value of 3 systems was measured at 3 different points 59

Figure 3.10 COD content of 3 systems were measured at the 3 different points 61

Figure 3.11 NH4-N content of 3 systems were measured at the 3 different points 60

Figure 3.12 PO4-P content of 3 systems measured at the three different points 65

Figure 3.13 Quantities of solutions by model for CC adaptation and resilience to a shortage of water, inundation in flood season and extreme events 68

Figure 3.14 The result of AC assessment at different systems of aquaculture 71

Figure 3.15 The result of overall AC assessment of households in Cho Moi district 70

Figure 3.16 The assessment results show indicators increase/decrease AC 70

Figure 3.17 AC assessment of economic indicators by aquaculture systems 73

Figure 3.18 AC assessment of social indicators by aquaculture systems 74

Figure 3.19 AC assessment of environmental indicators by aquaculture systems 75

Figure 3.20 AC assessment of CC adaptation component by aquaculture systems 77 Figure 4.1 The survey result of household‟s anticipation for implementing RAS to improve their current farming practices 80

Figure 4.2 Diagram describes RAS operation 84

Figure 4.3 The composition of a mechanical filtration system 85

Figure 4.4 Three layers of a bio filter are introduced to purify water quality 85

SDGs Sustainable development goals

RCP Representative concentration pathways

RAS Recirculating aquaculture system

ACKNOWLEDGEMENT

The master thesis "Assessment of the Adaptive Capacity of Aquaculture Households to Climate Change in Cho Moi District, An Giang Province" was completed at the program of Climate Change and Development, Vietnam Japan University, Vietnam National University, Hanoi I would like to thank all the teachers and staff who have fully supported and gave valuable comments to this thesis

In particular, I would like to express my deepest thanks to the two supervisors, Assoc Dr Koshi Yoshida and Dr Nguyen Tai Tue who not only closely guide me on the knowledge and experience but also share the skills for me

to become a professional researcher In addition, I would like to thank some individuals and units such as An Giang Rural Development Sub-Department, Mr Huynh Van Thai, Head of Water Resource and Climate Change Department, An Giang Department of Natural Resources and Environment, Mr Nguyen Van Tien - Head of Snakehead Farming Association of Long Kien Commune- Cho Moi District, Master Nguyen Thi Hao who have provided the necessary information and created favorable conditions for me to complete this thesis This thesis is hugely supported by the national projects, entitled “Research, assessment the impacts of climate change, disasters, human activities for proposing solutions, sustainable development models in adjacent areas of Hau River”, code: BĐKH.39/16-20

Once again, I would like to express my sincere gratitude to all of those for their interest, encouragement, and motivation for me to fulfil my master's thesis The precious things that I learned during the course of doing my thesis will help me

a lot in my future research

Sincerely!

FOREWORD

Aquaculture in Vietnamese Mekong Delta (VMD) plays important role in Vietnam, its population as well However, many studies predicted that this area is one of the most vulnerable region by climate change and sea level rise in the world

In addition, the impacts of the upstream hydroelectric construction exacerbate the existing problems VMD‟s aquaculture, therefore, is the most affected sectors by climate and non-climate actors

The thesis title “Assessment of Adaptive Capacity of Aquaculture Households to Climate Change in Cho Moi District, An Giang Province, Vietnam” aimed to find out adaptive capacity (AC) to reduce vulnerability of aquaculture households in VMD to climate change A set of indicators to assess AC was created

by reliable studies, current policies on coping with climate change and reaching sustainable development goals (SGDs) The set was established with 17 indicators belonging to 4 components CC adaptation (6 indicators), economy (5 indicators), society (3 indicators), and environment (3 indicators) The AC index was collected

by the two activities First, the study interviewed 60 households at 06 communes in Cho Moi district that represent the three aquaculture systems (20 households/system) to find out the score of AC1-AC15 Second, water quality measurement was conducted at the aquaculture ponds to calculate the score of AC16-AC17 The score of overall AC was totalled each individual indicator by the use of Min-Max formula Sustainable solutions for aquaculture households were given to increase low AC indicators, especially technological solutions like recirculating aquaculture system (RAS)

CHAPTER 1 INTRODUCTION

1.1 Research issues

Climate change (CC) is one of the biggest challenges for human beings in the

21st century It puts all natural-social systems at risk, particularly developing countries (Eckstein, Hutfils, & Winges, 2018; C C IPCC, 2014; Weiss, 2009) Global warming, sea level rise, natural disasters and extreme weather events are threatening throughout the world In particular, Vietnam is considered as one of the most vulnerable countries by CC (Eckstein et al., 2018; Van et al., 2012; Weiss, 2009) Over the last half century, the average temperature increased by 0.62oC, while rainfall decreased in the North and increased in the South Extreme weather events such as storms, floods, subsidence, drought and saline intrusion have yearly increased in both frequency and intensity that claimed thousands of human life and hugely damaged on sustainable development goals (SDGs) (Beilfuss & Triet, 2014; MONRE, 2016)

CC is forecasted to affect many regions and socio-economic sectors in Vietnam, especially low elevation regions and densely populated areas like the Vietnamese Mekong Delta (VMD) (Duong, Phi Hoang, Bui, & Rutschmann, 2016; IPCC, 2007; A L Tuan, Thuy, T.H., & Ngoan, V.V, 2014; VIMHE, 2011) According to representative concentration pathways (RCP) 8.5, by the end of this century, the region's average temperature could increase by 3-3.5oC, rainfall could increase by over 20% and sea level rise by 48 - 106 cm The scenario for 1-meter sea level rise could make 38.9% of the VMD area at risk of flooding, 35% of the population of losing their houses (Hoang et al., 2018; MONRE, 2016) In the coming decades, CC in the VMD will unpredictably fluctuate Temperature, precipitation, wind, and CC-related hazards will change in frequency, intensity, and duration (Hoanh, Jirayoot, Lacombe, & Srinetr, 2010) Frequent extreme weather events such as abnormal rains, floods, drought, changes in flow, subsidence and saline intrusion will seriously impact the area (Hoanh et al., 2010; MRC, 2009; A

L Tuan, Thuy, T.H., & Ngoan, V.V, 2014) Several models have been developed to simulate CC and its impacts on the VMD in the future In particular, most of studies stated that CC and upstream hydropower development on the upstream Mekong River will change the hydrological regime, as well as weather patterns (Beilfuss & Triet, 2014; Chinvanno, 2011; Duong et al., 2016; Hoanh et al., 2010; Wassmann, Hien, Hoanh, & Tuong, 2004) In the rainy season, increasing rainfall combines with a rise of upstream flow will rapidly increase the flood peak and intensity that most of this region would be submerged (Plan, 2013; Team, 2018) In the dry season, dozens of studies predict that drought will become more severe The rising sea levels together with the influence of upstream hydroelectric dams will make saline intrusion reach deeper inland Therefore, rice production and freshwater aquaculture will be affected (Kam, Badjeck, Teh, & Tran, 2012; Kantoush, Van BINH, Sumi, & Trung, 2017)

The VMD is also known as the largest granary and fishery in Vietnam Aquaculture plays a key role in the socio-economic development and livelihoods for thousands of households in this region According to the General Headquarter of Fisheries, this area accounted for 100% of the total area and production of

Vietnam‟s pangasius sector, and 92% of the total area, and 83% of the total

production of Vietnam‟s shrimp sector in 2016 Many studies demonstrated the Mekong Delta was severely impacted by CC and extreme events (Barange et al., 2018; Beilfuss & Triet, 2014; Blumstein, 2017) The coastal zones of VMD, shrimp farms, were seriously impacted by the historical drought event in the year 2016 The saltwater could reach 55-60 km in the Hau River and 45-60 km in the Tien River, being further inland 20-25 km than normal drought seasons This event only caused 3.771 shrimp hectares to be damaged Lately, the 2020 drought is even more damaging than the 2016 year when saltwater intrudes beyond the recent saline boundary In contrast to coastal area, the inland region, dominantly cultivates

freshwater fish like pangasius, had negative effects on aquaculture production due

to unstable annual floods At the upstream of VMD, a normal flood could bring

many benefits for locality and its inhabitants but the fluctuating flood peaks during

the 2007-2012 phase made the profit of pangasius producers varying For instance,

the lowest flood peak recorded in 2010 at the upstream of Tien and Hau river were

320 cm and 282 cm respectively, having the profit margin of (-3,020) VND/kg while the highest peak in 2011 was 486 cm and 427 cm, having the profit margin of 3.187 VND/kg It proves that the freshwater aquaculture depends on the duration and flow of the flood

To mitigate CC consequences, the urgent solution is to improve resilience to vulnerable sectors through increased adaptive capacity (AC) and the adoption of technical and non-technical solutions (ADB, 2009; C C IPCC, 2014; F C IPCC, 2014) (FAO, 2018) stated that CC awareness needs to be adaptable enough to cope with long-term, a sudden and unpredictable changing climate for fishery based livelihood communities The link between CC and sustainable development (Zarfl, Lumsdon, Berlekamp, Tydecks, & Tockner) plays a key role to manage fisheries comprehensively Assessment of AC to CC has many levels, including household, community, sector, region and national level Specially, household level has the advantages of coping well with natural disasters in the short term and reflects the actual position, the role of broad and complex policies and institutions in responding with CC (Elrick-Barr, Preston, Thomsen, & Smith, 2014; Navy, Krittasudthacheewa, Voladet, & Thin, 2019; Thomas, Christiaensen, Do, & Trung, 2010) To date, various assessment methods of AC have used indicators that relate

to household level such as human, financial, economic, natural, social and economic issues, and infrastructure (Nhuan, Tue, Hue, Quy, & Lieu, 2016; Sietchiping, 2006; Thanvisitthpon, Shrestha, Pal, Ninsawat, & Chaowiwat, 2020) However, there have not been many studies to advance the link between AC and SD indicators in the VMD

Cho Moi district, An Giang province is located geographically adjacent to Tien and Hau rivers, two main tributaries of the Mekong River Freshwater aquaculture flourishes with a variety of aquaculture types and subjects However,

the combination of CC and upstream hydropower development has caused a significant impact on this locality The issues of local people's livelihoods are considered in a few studies (Can, Tu, & Hoanh, 2013; Kam et al., 2012) There are lacked of study to assess the impacts of CC on the aquaculture in this area

Therefore, the thesis "Assessment of the adaptive capacity of aquaculture

households to climate change in Cho Moi district, An Giang province, Vietnam" has

been chosen to give out solutions to the problems of aquaculture in the VMD

1.2 Research questions and objectives, and hypothesis

(2) What are key factors affecting to AC of aquaculture households to CC?

(3) What are sustainable solutions to increase AC of aquaculture production

at household level?

1.2.2 Research objectives

To answer the aforementioned research questions, the three objectives of the research were formed: (1) Establish a set of indicators to assess AC to CC at the household level relied on the relationship between CC and SD (2) Identify factors that would increase/decrease AC based on the expected results of AC assessment (3) Propose appropriate solutions to improve the household's AC in Cho Moi district, An Giang province for sustainable aquaculture development

1.2.3 Hypothesis

Aquaculture production inherently depends on the water quality of the Mekong River affected by climate change and human-made actors

1.3 Background of the Study

1.3.1 Concepts

Climate Change

“Climate change refers to a change in the state of the climate that can be identified (e.g., by using statistical tests) by changes in the mean and/or the variability of its properties, and that persists for an extended period, typically decades or longer Climate change may be due to natural internal processes or external forces such as modulations of the solar cycles, volcanic eruptions, and persistent anthropogenic changes in the composition of the atmosphere or in land use” (IPCC, 2014)

Another definition is defined by UNFCCC as “The UNFCCC thus makes a distinction between climate change attributable to human activities altering the atmospheric composition, and climate variability attributable to natural causes”

Climate change is also manifested by increasing the intensity, frequency and volatility of extreme weather events such as heat, prolonged cold weather, drought and saltwater intrusion, storms and tropical depressions, floods, etc Climate change threatens all existing social systems and ecosystems, especially lowlands and coastal areas (Nhuan, 2016)

Vulnerability

Vulnerability is the degree to which a system is susceptible to, and unable to cope with, adverse effects of climate change, including climate variability and extremes Vulnerability is a function of the character, magnitude, and rate of climate change and variation to which a system is exposed, the sensitivity and adaptive capacity of that system (IPCC, 2007)

Adaptive Capacity

IPCC defines adaptive capacity (AC) as “The ability of systems, institutions, humans, and other organisms to adjust to potential damage, to take advantage of opportunities, or to respond to consequences

(USAID, 2009b) defines that AC to CC is a society's capacity to change in a way that makes it better equipped to manage risks or sensitivities from the impacts

of climate change

AC is a concept derived from ecological science to describe the ability of a system to maintain or restore function in case of external impacts (Martin-Breen & Anderies, 2011) AC is a combination of all the strengths, attributes, and resources available to an individual, community, society, or organization that can be used to prepare and implement actions to reduce adverse effects and damage or take advantage of opportunities Adaptive capacity refers to the ability to anticipate and change structures, functions, or organizations to better respond to the disaster (Tran

et al., 2015)

Current AC is an important condition for establishing and developing an effective CC adaptation strategy (Brooks & Adger, 2005) AC is also seen as the opposite of vulnerability, as a key component of vulnerability assessment (Brooks

& Adger, 2005; IPCC, 2007)

AC consists of three main pillars: natural resilience, social resilience and the ability to transform challenges into opportunities AC depends on factors such as human, infrastructure, finance, social capital, nature, information technology, institutions and equity (Nhuan, 2016)

AC is uneven and dispersed on a global scale (IPCC, 2007)

AC is heterogeneous in a society Many studies show that human capital and social capital are the two determinants of AC not less than other factors such as income and technology level However, the two types of capital mentioned above are very uneven for different strata in society

Adaptation measures

AC is expressed through activities and measures of adaptation to reduce vulnerability There are many different types of adaptation measures (technology, finance, information, institution, etc.) and are implemented at different levels (individuals, households, communities, industries, regions, and nations)

Adaptation measures were categorized by (USAID, 2009a) as follows:

- Based on the timing of adaptation strategies:

+ Preventive adaptation: is the adaptation measures carried out before the impacts of CC occur in order to proactively prevent possible damages

+ Reactive adaptation (reactive adaptation): the adaptation measures are taken after the impact of CC has occurred to reduce the damage

- Based on policy considerations when implementing adaptation strategies:

+ Autonomous adaptation: adaptation measures are conducted in a

"spontaneous" and "reflective" way (mainly of the private sector) in order to cope with actual impacts of CC underway without policy intervention These are usually temporary adjustments and usually occur in the short term

+ Planned adaptation: adaptation measures are planned and take careful consideration of public sector policies to adapt to anticipated CC Planned adaptation is, therefore, often a proactive, strategic adjustment to address climate risks in a way that meets society's goals at best and often takes place over the long term

- Based on the subject of adaptive strategies:

+ Private adaptation: adaptation measures are carried out by individuals, households, and businesses

+ Public adaptation: Adaptation measures are carried out by government agencies at all levels

1.3.2 Research history

In the America

CC and variability impact across the continent The extent of the damage depends on the different types of weather from tropical to cold in various regions, and other factors like topography, economy, ecosystem, governance structure, and culture The diversity and complexity of this area are and will affect vulnerability, risk, impact, and AC (F C IPCC, 2014)

(Wall & Marzall, 2006) assessed community-level AC in rural Canada The authors argued that improving capacity derived from both internal and external factors can increase the long-term sustainability of rural areas The method of assessing AC at community level is given based on the literature review on sustainability to find out its application results The set of indicators and common variables is selected according to the specific event and the type of adaptation The research uses the basic framework and profiling tool („amoeba‟) to describe latent

AC in the community The researchers classified AC indicators into 5 components, including society, people, institutions, nature, and economy The study concludes that the indicators used in this study cannot be replicated in other rural communities but the framework and profiling tool makes sense for future studies

(Simoes et al., 2010) study aims to improve AC for smallholders in semi-arid regions in Northeast Brazil This area is home to many poor people, who are most affected by CC The authors presented several specific initiatives to enhance AC of the Pintadas rural community Developing comprehensive methods is a basic step to help smallholder farmers adapt to CC The integration between AC and adaptation strategy was introduced in order to develop an effective adaptation method to help farmers escape poverty and reduce the impact of CC The conclusion highlights the need for a study of community vulnerability and practical experiences

(Selm, Hess, Peterson, Beck, & McHale, 2018) study conducted in North Carolina, US to assess household AC in the test area Because household-level AC will affect resilience at the community level, it is necessary to have systematic measurement tools The authors used scales and tools to measure proactive AC aspects of urban households Applying a 4-capital livelihood approach: social, human, physical and financial, the study collected data from 200 households and checked the effectiveness of scales and measuring instruments by analysing the main components The results of the study identified the effectiveness and practicality of this approach when determining three main parameters: financial capital, political awareness and access to resources to measure AC in different households The findings match with other studies when selecting AC indicators related to income inequality and political awareness However, the research emphasizes that this study should only be applied to urban areas because of the complexity in the relationships between livelihoods, financial, physical and human

In Asia

CC has strongly impacted the region by increasing the frequency and intensity of extreme weather events such as heat waves, drought, floods and tropical storms CC has increased the adverse conditions for the region The risks of water shortages, stagnant agriculture and food insecurity, forest fires, coastal degradation, and human health are threatening the region Therefore, improving AC is an urgent priority for Southeast Asia in the context of future climate change that is irregular and unpredictable Building resilience covering areas such as policies and institutional framework, information and knowledge, social resources has been identified as priorities in the near future (ADB, 2009)

(Defiesta & Rapera, 2014) paper identifies to determine the AC level of farmer households in the Philippines to find suitable adaptive solutions The set of indicators were based on previous studies related to AC and vulnerability including

5 indicators of human resources, physical, financial, information and diversity

Differences in each resource of information, material and financial were the cause

of the changes in AC These three indicators determined the AC of the household to high or low Meanwhile, the author also found that farmers with high AC have implemented various adaptation measures

(Thanvisitthpon et al., 2020) developed a framework for assessing household flood adaptation in urban areas of Thailand The set of AC indicators used for evaluation includes 06 components: economic resources, social resources, awareness and training, technology, infrastructure, institutions and policies Statistical methods and structural equation models were applied to build suitable indicators and components This information was collected from household interviews in urban flood areas The study showed that if there are improvements in economic resources and infrastructure, AC will be high The framework of this study can serve as a basis for assessing urban flood adaptability, and integrated flood risk management and assessment

(Thathsarani & Gunaratne, 2018) develops a set of AC indicators that respond to CC at the community and family level in Sri Lanka The authors highlight that AC is constantly changing in each region, each community, and each group A five-asset scales: economic, social, human, natural and physical scales were used to measure AC Many households were interviewed to collect the data Using the Weighted Principle Component Analysis (WPCA), Multiple Factor Analysis for Mixed Data and inter-household analysis to analyse household data Research results showed that the types of assets were proportional to AC, including social, physical and economic In contrast, humans were the type of property that was inversely related to AC Poor households, regardless of geography, had fewer resources The study offered recommendations to improve AC for households with less assets

In Africa

CC has had a severe impact on the ecosystem and is expected to be even more serious in the future CC in combination with non-climate actors and stresses will exacerbate the vulnerability of the agricultural system, especially in semi-arid regions Achieved control risks during food production in the context of current and future extreme weather events do not guarantee the safety in the long-term CC The continent's adaptive experiences highlight valuable lessons to improve and expand adaptive responses (F C IPCC, 2014)

The study of (Abdul-Razak & Kruse, 2017) assessed the AC of smallholder farmers in Ghana where CC severely affected agricultural production It implements

6 determinants to assess AC, including economic, social, awareness and training, technology, infrastructure and institutions The literature review and qualitative interviews with livelihood and agricultural experts were used to select 3-5 indicators per component Research results showed that awareness and training, economics, and technology were the most interested factors by farmers, while the other factors like infrastructure, institutions and social capital are less important In addition, gender inequality and education levels made AC different among households and the recommendations to improve AC for women and low-income people were given

In Europe

Climate change and sea level rise have a great impact on many regions, sectors, fields and ecosystems across the continent However, this continent is more adaptive to CC than other continents (C C IPCC, 2014)

The ((Williges, Mechler, Bowyer, & Balkovic, 2017) study developed an AC assessment method to reduce the risk and damage of drought on agriculture in Europe The author used the Sustainable Livelihoods Approach method based on the type of assets (capitals) to assess the future recovery and resilience of natural systems, human with CC variability The study assessed and forecasted that Central and Northern Europe had higher AC levels than the rest However, the research also

had limitations with the lack of important data and background to identify how to select AC indicators

In Australia and New Zealand

Extreme weather events have caused significant damage to ecosystems and human in much of Australia and New Zealand The frequency and intensity of these events are expected to continue in the future Without adaptive solutions, many sectors and areas of this region such as water resources, marine ecosystems, infrastructure, health, agriculture and biodiversity will be threatened Adaptation plans and solutions in this area have been implemented and integrated but only at conceptual level rather than practical applications High AC in many systems but limited in applicability, especially transition responses at local and community levels (F C IPCC, 2014)

(Keogh, Apan, Mushtaq, King, & Thomas, 2011) study was conducted in Charleville, a small town in rural Australia to study the vulnerability, resilience and

AC of communities here during the 2008 flood Both quantitative and qualitative methods were used to analyse and assess the vulnerability of the community by interviewing of households, business owners and local institutional staff The results

of the analysis show that Charleville was highly resistant to flooding, which was manifested by the highly-valued criteria for organization and operation, institutional networks and social functions

(Sietchiping, 2006) applied AC and CC indicators to the north-west of Australia at industry and community level The set of indicators was formed primarily based on government policies, expert advice and practical arguments that consists of three factors: social, economic, institutional/infrastructure These factors represented the target groups of research subjects, as well as their adaptive experience to CC Each factor would have a different measurement and different operating environments The study used global positioning systems to collect and analyse data and space of relevant indicators The weights, methods, and factors are

determined through a symposium of experts The paper concluded that adaptability across communities and across industry varies greatly spatially

In Vietnam

CC adaptation strategies have been developed and implemented at different levels from households to regions The study of building a set of indicators to adapt

to CC has also attracted many researchers

(VIMHE, 2011) provided a set of technical guidelines on how to assess vulnerability and recommend adaptation measures That document includes 9 steps from scenarios preparation for CC and sea level rise to releasing adaptation plans to these events The impact assessment framework was set up to find out AC of assessed by overviewing current adaptation measures and plans The assessment method includes three components: assess the impact on natural environment (land, water, air, ecosystem and biodiversity, and marine), assess the impact on the economy, and assess the impact on society

(L A Tuan, Du, & Skinner, 2012) conducted a study and published a report

"Rapid assessment, synthesis of vulnerability and AC to CC in three coastal districts

of Ben Tre Province The authors used the method of "assessing CC adaptation based on ecosystems" to conserve and restore ecological processes in order to enhance resilience and self-reliance Restoring ecosystems and communities to CC through maintaining ecosystem values that play a role in protecting and supporting human livelihood and production activities as well as public properties In this report, community AC is determined by assessing current coping and adaptive solutions as well as ecological and institutional capacity to cope with hazards and risks

The book of (Nhuan, 2016) on urban AC with CC is a premise for the research and development of AC assessment method in the future study The method was used to analyse, evaluate and suggest the model of SD urban and actively responds to natural disasters The research provided a common set of

indicators based on components including natural resilience, social resilience, the ability to transform challenges into opportunities Due to distinct differences among topographic, economic, cultural, social characteristics, infrastructure, environment, etc., different AC indicators could be implemented at the different types of urban regions The other study of (Nhuan et al., 2016) emphasized the importance of increasing AC components at the household level in coastal urban areas like Da Nang An AC framework of 23 indicators was developed to collect socio-economic data for urban households The research results showed that wealth indexes, housing conditions, long-term assets are highly appreciated, while indicators related to livelihood diversity and knowledge with CC are underestimated The conclusion was given that economic, social and adaptive methods are the determinants of urban household adaptation The set of indicators in this study can be applied to assess AC

in other coastal cities These studies are scientific basis, highly effective in proposing activities, solutions to adapt and respond to climate change In addition, there is another study on urban-level household adaptation, the study (Dung & Minh, 2019) conducted in Quang Dien district, Thua Thien Hue province A set of

AC indicators including 19 indicators in 4 components including economy, infrastructure, society and humans were built The findings indicated that most households prefer to adopt adaptation measures in the short term Therefore, the research made some recommendations for households such as raising awareness and understanding of CC, improving infrastructure, diversifying livelihoods to increase their income that were main factors to increase AC

Several state-level scientific projects have also contributed to the development of AC indicators in different fields and levels The study of (Toan, 2014) aims to build a set of criteria of community-based cc adaptation eco-village,

as a basis for designing and implementing as a norm for replicating that model in the Mekong Delta region, especially coastal areas, much affected regions by CC and sea-level rise The study used some typical traditional methods such as expert interviews, participatory rural appraisal (PRA) As a result, the project has

developed a set of criteria for ecological villages associated with people's lives and ensures the climate change adaptation goals in the Mekong Delta The criteria include 8 components and 24 indicators as domestic water supply, domestic wastewater treatment, solid waste treatment, transportation, public lighting, energy, greenery, community houses

A set of AC indicators serving for the CC state management was researched and developed by (Huong, 2015) It has created an adaptive framework of 03 steps, including assessing the adaptive situation (step 1), evaluating the effectiveness of adaptation activities (step 2), and assessing the adaptive results (step 3), respectively with 04 sets of indicators to find the desired data in term of natural resilience, vulnerability, ability to mitigate CC risks and the effectiveness of adaptation strategies These indicators were based on previous studies and have specific screening criteria The set of indicators is a basis for managers to assess and make appropriate adaptive decisions for the locality However, the project notes that provincial/city managers need to build a database system to serve the calculation of indicator sets or add some necessary parameters for calculating indicator sets

Another typical study is the topic of (Thang, 2015) that built a set of AC indicators as a scientific basis for the selection and improvement of CC adaptive models in the central provinces, Vietnam The set of indexes was formed through the 04-step process of Louise Twining-Ward The set of indicators included 14 indicators corresponding to 04 components, including CC adaptation, economic efficiency, social efficiency and environmental efficiency Based on the results of assessing the level of CC adaptation of the models, the project divided 40 models into 5 levels: High, Fairly High, Medium, Low and Very Low The reliable results

of that study include a set of CC adaptive indicators that are the basis for assessing the AC of climate change adaptation models in future scientific studies Besides, the topic "Research and assess the impact of climate change, natural disasters and human activities to propose solutions and models of sustainable development along the Hau river" by Mai Trong Nhuan et al creates the set of criteria for evaluating

SD models in the field of aquaculture in Hau river areas in the context of CC, natural disasters and human activities based on a number of Vietnam's important programs and policies related to CC and SD There are 38 indicators and 06 components: economic efficiency, social efficiency, environmental efficiency, climate change adaptation, mitigation adaptation, scalability The set is the basis for conducting evaluation studies on AC in the context of SD and finding appropriate adaptive strategies

Figure 1.1 Geographical location and natural condition map of Cho Moi, An Giang

(Source: Long & Nguyen, 2018) Cho Moi terrain is mainly flat, alluvial plain, and small inclination The average height is 1.3 - 3 m above sea level and gradually decreases from the riverside to the interior Thanks to silt accretion from the Mekong River, its soil is fertile and pH stability There are three main types of terrain: dunes, basin terrain, and inclined terrain (higher in the riverbanks and lower into the fields)

Temperature

Cho Moi lies in the typical tropical monsoon climate, high temperature, and little change During the period of 1985-2015, the average temperature was 27.4oC The highest average temperature was April: 28.6-28.8o C, while the least temperature was January: 25.7oC From February, the average temperature increases rapidly to the maximum one in April and then the temperature turns milder from May The year with the highest average monthly temperature was April 2010: 30.3oC, and the lowest was December 1986: 24.3oC

Humidity

Humidity changes by seasons and is divided into dry and rainy seasons During the period 1985-2015, the average annual humidity was 80-83% The lowest monthly average humidity was April: 77-79%, coinciding with the time of drought and little rain, while the highest monthly average humidity was September: 82-88%

Precipitation

Precipitation varies significantly over space and time and is divided into two seasons throughout the year The rainy season lasts from May to November and the dry season lasts from December to April next year The annual rainfall ranges from 1,200 – 1,500 mm/year The average annual rainfall in the rainy season accounts for 83% - 89% of the total annual rainfall In contrast, rainfall in the dry season only accounts for 11-17% of the total annual rainfall The difference between the months

with the highest rainfall (from August to October) and the months with the lowest rainfall (from January to March) is up to 300 mm

During 1985-2015, the average annual rainfall ranged from 892-1,312 mm, the month with the average rainfall and the highest number of rainy days in October, with 155-239 mm and 14.7-18.9 days, while the month with average rainfall and the lowest number of rainy days was February, with 2-7mm and 0-0.3 days

Sunshine

An Giang is one of the provinces having a long time of sunshine with average hours of 2,482 hours/year During the period 1985-2015, the number of sunshine hours tended to decrease The year with the longest time of sunshine was 2,854 hours, in contrast, the year with the shortest time of sunshine hours was 2,130 hours In the dry season, from December to April was the month with the most sunshine time, the average monthly was from 220-250 hours, each day had an average of 7-9 hours In the rainy season, the less sunny months were from August

to October, the average sunshine time per month was 150-160 hours, in which each day had 5-6 hours The difference in the number of sunshine hours between the rainy and dry season months reflected clearly features of the separate seasons

Wind

Cho Moi has a tropical monsoon climate and is influenced by the northeast and southwest monsoon Due to the change in atmospheric circulation patterns, the wind regime also changes From May to November, the prevailing wind direction is the Southwest, but the east wind direction has a negligible frequency From December to April of the following year, the prevailing wind direction in this season is a high frequency of Southeast to South winds The west winds have a not significant frequency

Hydrology

The whole district has 03 main rivers, namely Tien, Hau, and Vam Nao River (the Mekong river system), with a length of 190.3 km The average annual water flow is 13,500 m3/s Water flow can reach 24,000 m3/s during the flood season, and downs 5,020 m3/s during the dry season In addition, the district also has 653 canals and inner field canals with a total length of 271.3 km The hydrological regime of the district is mainly influenced by the semi-diurnal tide regime in the East Sea and is influenced by Mekong river flows, inland rainfall regime, and morphological characteristics of canals

Due to the flood starting in the rainy time, 70% of the land area in An Giang province, including Cho Moi, was flooded in the years of 2000s, with a rising water level of 1-2.5m The inundation period was from 2.5 to 5 months, from the middle

of August to December However, up to now, after the enclosed dike system has been put into operation, it has changed the flood situation in the locality In the dry season, some areas have localized but not serious water shortage In general, agricultural production activities are still relatively smooth

1.4.2 Socio-economic and environmental characteristics

Economic characteristic

The economic structure of Cho Moi district consists of two main pillars: (1) agricultural, forestry and fishery production, and (2) industrial production - construction and trade The value of commodity production of the two above fields increased in the period 2014-2018 The sector value (1) in 2014 was VND 9,436.3 billion, in 2018, it increased slightly to VND 10,342.73 billion, in which only the fishery group grew in the total value structure (1) increased from 13.75% to 28.31%

in 2018 The sector value (2) increased rapidly from VND 7,617.8 billion in 2014 to VND 10,219.17 billion in 2018 (see table 1.1)

Table 1.1 Economic structure value of Cho Moi during the phase of 2014-2018

the following year higher than the previous year, specifically, the average income per capita in 2018 reached 46.64 million VND, an increase of 7.44 million VND compared to 2017

Social characteristic

Cho Moi district has 16 communes and 02 towns An average population of the district in 2018 of 348,206 people, of which female was 175,728 people The rate of natural increase was 0.97% The average population density was 943 people/km2 The population was not evenly distributed in the district area, mainly concentrated in urban areas such as Cho Moi town, My Luong town, Kien Thanh commune, My An commune, Long Giang, and Hoa An commune with a populate density of more than 1,000 people/km2, and sparse in the communes of An Thanh Trung, Binh Phuoc Xuan, with a density of fewer than 700 people/km2

Figure 1.2 A structure of the working-age population (left) and structure of

population capable of work in economic sectors (right) The total number of people of working age in 2018 was 212,521, accounting for 61.03% of the total population of the district, including 188,007 employed laborers In particular, classified by sex, female laborers in the working-age are 96,798 people, accounting for 51.5% of the total number of people of working age, and there were 81,601 employed people, accounting for 42.4% of total employed

88.47%

4.13%

1.66% 5.75%

people capable of work in economic sectors

schoole age people

people incapable of work

unstable job people

laborers Classified by economic structure, the total number of people working in the national economic sectors is 188,007 people, of which the field of agriculture, forestry, and fishery is at large with 71,681 people, industry and handicrafts with 33,489 people, construction with 6,019 people, services with 20,958 people, commerce with 25,175 people, and other sectors with 3,813 people (see figure 1.2)

The structure of the working-age population in the district varied slightly but was generally stable over years However, the number of people who were able to work in all economic sectors, the number of people of school age and the number of people without stable jobs tended to increase, the increase rates were respectively 0.079%, 1.53% and 2.01%; in contrast, the number of people who were unable to work tends to decrease, the reduction rate was 6.49% The number of laborers capable of working in agriculture, forestry, and fisheries tended to decrease, with a decrease of 0.035%

Environmental characteristic

Figure 1.3 Water surface of Hau river (left) and Tien river (right) in flood season Water quality parameters change at different times and places (see figure 1.3) During the flood season, the DO index was high due to strong water flow, and vice versa during the dry season, the DO was low Meanwhile, the density of BOD and total suspended solids (TSS) always exceeds the permitted limit many times

The remaining parameters NH4-N, PO43- fluctuated around the permitted content for aquaculture According to the 2019 report of An Giang Department of Natural Resources and Environment, surface water quality on the Hau river was lower than the Tien river; however, most measured environmental parameters of the two water bodies were only used for irrigation, aquaculture, and water transportation

Surface water quality in Cho Moi district in particular and An Giang in general, has been affected by many factors Firstly, over-exploitation of natural resources, minerals in the river basin, and overproduction of aquaculture in the river have reduced the quality of surface water and ecosystems in this area Next, the establishment and development of industrial zones and production facilities exacerbated the situation of surface water pollution These facilities are so small, scattered, without centralized waste and wastewater treatment systems In addition, the system of stilt houses along banks of rivers and canals is dense and people there have a habit of directly discharging into the rivers, without collection and treatment systems Finally, an equally important factor is climate change, and the development of hydroelectricity dams at the upstream often diminishing surface water quality and deteriorated environmental standards

1.4.3 Characteristics of climate change and natural disaster of Cho Moi district

Flooding

The changes in water level and flood flow to the delta were also considered

to be partly influenced by flow volatility from the upstream which frequently caused consecutive small flood years from 2002 to the present, except for large floods in 2011 The course of flood in recent years also has unusual changed The

2014 large flood appeared prior to the 2015 small flood, contrary to the law of flood operation Floods irregularly occur up to half a month later than before and the duration of floods was shorter, especially in 2013 and 2015

In the period from 1998-2019, the peak of flood measured at the hydrographic stations in An Giang province largely fluctuated The year 2000 was

the flood peak reached the highest and the year 2015 was the lowest peak The water level in Tien and Hau's rivers measured at upstream and downstream locations in these points was significantly different At the upstream, on the Tien River, the peak of the flood measured at Tan Chau station was 506 cm in 2000, suddenly reduced to 255 cm in 2015, while at the Hau River at Chau Doc station, the flood peak decreased correspondingly from 490 cm to 235 cm At the same time, the flood peak measured at the downstream, on the Tien River at Cho Moi station had a sudden decrease from 358 cm to 220 cm, while on the Hau River at Long Xuyen station, a corresponding decrease from 263 cm to 216 cm (see figure 1.4)

Figure 1.4 Flooding peaks during 1998-2019 phase were measured at upstream and

downstream stations in An Giang province (Source: An Giang Committee for Incidents and Disaster Response, and Search and

Rescue)

In the early 2000s, flood season in An Giang regularly appeared with great intensity and frequency The province had issued the project 31 /ĐA.BCS and Decision 1536/QĐ-UBND "exploiting the advantages of flooding season" to help

people mitigate losses and to live in harmony with floods The project had positively supported for people to develop effective models and trades in the flood season such as fishing net production, aquatic vegetable planting, interwoven weaving, etc The most striking result of the project was the harmonization of economic benefits and the environment, ensuring both increased their income and compensate alluvium and wash alum to improve their soil Therefore, the orientation of agricultural production of the province in this period is to "live with floods" for a long time

Due to both objective and subjective reasons, the situation of large floods has not occurred frequently in the province since 2003 up to now (except for the year of 2011) that forced the province to propose corrective measures and adapt to changes Implemented solutions during this period achieved certain results, helping farmers

to increase income through increasing productivity and agricultural output The policy orientation of the province was focusing on economic development, increasing agricultural production, contributing to ensuring food security but also arising a several consequences such as the depletion of land, water resources, and ecosystem destruction

Predicted low flood situation and climate change would still be lasting in the coming decades An Giang agriculture and aquaculture sector are and will face many potential risks, especially the significant increase in production costs, and threaten the ecological environment Therefore, the province needs to have breakthrough solutions and strategic steps to balance economic and environmental factors, and inspires the motto of “developing agriculture associated with solutions

to cope with the degradation of water resources due to climate change and the impact of water use activities in the upper VMD”

Drought and sea level rise

Because of topography without the sea, An Giang was not affected by drought and saline intrusion over the last 5 years However, these extreme events

have been increasing in intensity and frequency In particular, salinity concentration

in the dry season 2015-2016 increased to 0.01-0.2 ‰ at where has a border with Kien Giang province For the reason that the dry season in that year was the result

of the abnormal low flood peaks of the year after

According to the Department of Natural Resources and Environment of An Giang, there was a large fluctuation in water flow in the Mekong River The unusually rapid decline in the early dry season and abnormally slow rise at the beginning of the rainy season were the main causes of drought in the upstream of VMD The accumulation and discharge of hydropower reservoirs have altered the flow in the downstream Although the average water flows during the dry season increased, the downstream flow changes were detrimental to agricultural production and fisheries

Cho Moi district is located far away from the saline area, so it is not available statistics of this phenomenon impacts on the economy, society in general, and aquaculture activities in particular In some areas, prolonged drought has led to changes in soil structure causing landslides in some areas of the district

Tropical cyclones and depressions

The Mekong Delta is less affected by storms and tropical depressions than other regions across the country In the period of 1951 - 2015, the whole region lightly impacted by 09 tropical storms from the East Sea (see figure 1.5), excluding from Lynda storm in 1997 That typhoon left 3,000 people dead, 200,000 houses destroyed, 83,000 people homeless and causing $385 million in economic damage (Takagi & Le Tuan Anh, 2017)

Figure 1.5 The map of storm and depression trajectories impacted An Giang during

the phase of 1951-2015 (Source: http://kttv.angiang.gov.vn/ban-do-khi-hau) Cho Moi district is located far from the storm center, no damage statistics have been recorded in the above period The impact of typhoons in this area was mainly the heavy rains accompanied by tornadoes, which inundated and stagnated local agricultural production activities This phenomenon usually lasts from August

to November, coinciding with the rainy season

Heavy rain and whirlwind

In An Giang, heavy rain and whirlwind often occur from April to November, coinciding with the rainy season These phenomena depend on the topography, periods of the rainy season However, these extreme events have happened abnormal and unpredictable over 5 years The consequences annually cause little damage to humans but significantly destroy local property, agriculture, and

aquaculture The most affected communes by whirlwinds are Tan Chau, Phu Tan, Cho Moi, Tinh Bien, and An Phu

Cho Moi district is less affected by whirlwind compared to other localities in

An Giang Affected communes were often located along Tien and Hau rivers such

as Hoi An, Binh Phuoc Xuan, Hoa Binh, Nhon My, Long Kien, Kien An, My Hoi Dong, Long Giang, and Long Dien A Notably in 2016, a whirlwind in Cho Moi district killed 01 people, damaged 39 houses, 4.717 ha of agricultural production area, the value of the damage was about 29,937 million VND, according to Cho Moi people‟s committee

Land erosion

Riverbank erosion is one of the threats to the lives and property of people in the Mekong Delta, which An Giang is one of the localities most seriously affected The time of occurrence of landslides is often in the dry season and the beginning of the rainy season There are many causes of the serious situation in upstream provinces rather than the downstream Mainly due to the influence of upstream dams associated with mining activities, and socioeconomic factors have made the amount of mud and sand decline seriously, reducing the possibility of sediment accumulation, change the water flow, the geological structure of the riverbank, tectonic movement of the river

In the period of 1989-2014, the landslide in An Giang province took place at

a very fast level, highest in the period 2000-2005 (average speed of 318.97 ha/year), the period of 2014-2017 was slower with average speed (28.38 ha/year) The total damaged area of this period was 3146.94 ha (Điệp, Minh, Trường, Thành, & Vinh, 2019) According to the report of An Giang Department of Natural Resources and Environment, the whole province has 52 river sections at risk of erosion, with a total length of 44,000m along Tien River, Hau River, and small tributaries of the Mekong River For instance, 07 communes and towns were listed at risk of riverbank landslides, of the Tien River including Kien An commune, Cho Moi

town, Long Dien A commune, My Luong town, Tan My commune, commune My Hiep, Binh Phuoc Xuan commune; with 6 communes of the Hau river: My Hoi Dong, Nhon My, An Thanh Trung, Hoa Binh, Hoa An Kien An

Figure 1.6 A landslide scene of a riverside resident along the Vam Nao river, Cho

Moi district, An Giang (Source: baoangiang.com.vn)

1.4.4 Characteristics of aquaculture activity in Cho Moi district

According to 2018 statistical yearbook, Cho Moi district has 453 aquaculture households with an area of 395 hectares, the second-largest in An Giang province There were was 371.38 ha of the farming area in the earthen pond and 923 floating houses The total aquaculture production was 88,076 tons Compared to 2014, the number of aquaculture households decreased by 12.55%, but the area increased by 30.35% Other figures such as the area of the earthen pond, the number of floating houses, and aquaculture production increased by 30.35%, 108%, and 38.28%, respectively

Aquaculture activities in Cho Moi district were generally less directly affected by CC and extreme weather but have indirectly impacted on the fluctuations of production cost due to these events During the flooding season

increasingly/decreasingly according to the flood peak For instance, in 2011 farmers had a high-profit margin (3,187 VND / kg) proportional to high flood peaks (measured in Cho Moi district on the Tien River at 349 cm, in the Hau River at 281 cm) In the same period of 2010, farmers had a low-profit margin (-3.020 VND / kg) corresponding to low flood peaks (on Tien River 242 cm and on Hau River 233 cm) (see figure 1.7)

Figure 1.7 Profit margin of pangasius households in the phase of 2007-2012 was

proportionate with fluctuated peaks of Tien and Hau River in An Giang

(Source: Hong, 2017)

-4000 -3000 -2000 -1000 0 1000 2000 3000 4000