Authors Topic Method Set of criteria Weights
OZ et al. (2013)
Evaluating Sea Level Rise Adaptation Options on the Gold Coast, Australia: An MCDA Approach
The final AHP structure was developed after further consultation with
three local stakeholders (Politicians, Experts and
Residents).
Applicability, Effectiveness, Sustainability, Flexibility,
and Cost
Effectiveness and sustainability are the most important indicators in the
hierarchical tree, while costs are least important
Promentilla, Cruz, Angeles,
& Tan (2013)
Evaluating Climate Change Mitigation
Options in the Philippines with Analytic Hierarchy Process
(AHP)
AHP
Environmental effectiveness (EE), economic viability (EV),
technical
implementability (TI), and social acceptability (SA).
EE gets the highest point (0.337), followed by EV
and IT (0.262, 0.205 respectively). SA ranks the
lowest (0.196)
Camare & Lane (2015)
Adaptation analysis for environmental
change in coastal communities
Multi-participant formulation of the Analytical Hierarchy
Process (AHP)
Sustainability - economy, culture, society and
environment
The maximum weight for the Community Social
pillar (0.39) while the Business sector gives maximum weight to the
Economic pillar for the community (0.45). The Professionals group provides maximum weight to the Environment
pillar (0.30).
Choi, Yoon, Kim, & Moon
(2018)
Dam Rehabilitation Assessment Using the
Delphi-AHP Method for Adapting
to Climate Change
Delphi-AHP where professional experience of
panel participants has been combined with the
AHP method.
Economic Feasibility, Environmental Characteristics, Social policy, Hydrologic Safety,
Impact of CC
Hydrological safety is evaluated to be the most important, followed by CC impact and environmental factors. Economic factors and social policy factors
are the least important.
Guo, et al., (2020)
Improved evaluation method for soil wind erosion intensity based
on
the cloud–AHP model under the stress of global climate change
Cloud-AHP is the AHP method with the cloud
model -realizes the transformation between a
qualitative concept and a quantitative numerical representation,
which refers to the fuzziness and randomness of the
concept
Wind field intensity (WFI), surface dryness
(SD), vegetable cover (VG), snow cover days
(SCN), soil erodibility (SE), soil crust factor (SCF), terrain roughness
(TR)
VG achieves the highest point (0.280), followed by WFI, SE, SCF and TR with points are 0.2, 0.135, 0.127, 0.115 respectively. SCN
and SD have the same lowest point (0.069)
(Source: Authors’ synthesis, 2020)
Figure S1: Stakeholders involved in climate change adaption
(Source: Authors’ synthesis, 2020)
Appendix C:
Appendix C1: Key informants list
1. Assoc. Prof Nguyen Dang Hao, Dean of Faculty of Business and Administration, College of Economics, Hue University
2. Assoc. Prof Le Thi Hoa Sen, Vice Dean of Faculty, Lecturer at Hue University of Agriculture and Forestry
3. Mr. Tran Quang Phuoc, Head of Division of Agriculture, Department of Agriculture and Rural Development of Thua Thien Hue Province
4. Mr Le Muon, Vice Dean of Department of Agriculture and Rural Development of Quang Nam Province
5. Mr Mai Van Xuan, Vice Head of People’s Committee of Quang Dien District, Thua Thien Hue Province
6. Mr Tran Van Thuc, Vice Head of People’s Committee of Duy Xuyen District, Quang Nam Province
7. Mr Tran Van Ke, Head of Division of Department of Society and Economy of Thua Thien Hue Province
8. Mr Nguyen Van Mau, Head of Division of Department of Planning and Investment of Thua Thien Hue Province
(Source: Authors’ note, 2020)
Table S2: Background information on the FGDs
Time Place Participants Outline
First FGD 8am – 12am, 3rd October 2017
Base of Quang Dien People’s Community,
Thua Thien Hue Province
1. Truong Tan Quan – Assoc. Prof, Dr in Agricultural Economics. Lecturer from College of Economics, Hue University
2. Ms Le Thi Hoa Sen – Assoc. Prof, Dr in Rural Development. Lecturer from Hue University of Agriculture and Forestry
3. Mr. Tran Quang Phuoc, Head of Division of Agriculture, Department of Agriculture and Rural Development, Thua Thien Hue Province
4. Nguyen Van Tien, Head of Society and Economy Division of Quang Dien District, Thua Thien Hue Province
5. Mai Van Xuan, Vice Head of People’s Committee of Quang Dien District, Thua Thien Hue Province
6. Tran Dinh Quang, Head of Agricultural Extension Office, Quang Dien District, Thua Thien Hue Province
7. Le Muon, Vice Dean of Department of Agriculture and Rural Development, Quang Nam Province
8. Ngo Dinh Phu, Head of Society and Economy Division of Duy Xuyen District, Quang Nam Province
9. Tran Thi Minh Tien, Vice Head of People’s Community of Duy Xuyen District, Quang Nam Province
10. Tran Hung, Head of Agricultural Extension, Duy Xuyen District
Introduce the problem at hand to the participants of FGD in as much detail as possible, while at the same time being open to add, adjust or remove
components and indicators.
Identifying indicators and sub- indicators for the different components
that are withheld.
Take into account the social and economic context of the problem Consider the SWI tendency for the last five years and scenarios for the future.
Indicate the elements or attributes related to the adaptation options.
Make reference to successful SWI adaptation models in the other regions.
Second FGD 8am- 12am 5th November 2017
Base of Quang Dien People’s Committee, Thua Thien Hue
Province
1. Pham Xuan Hung, Director of Xuan An Cooperative 2. Tran Van Chuong, Director of Quang Phuoc Cooperative 3. Nguyen Van Quy, Director of Quang Thanh Cooperative
4. Phan Dinh Suu, Head of People’s Committee of Quang Thanh Commune 5. Phan Hung Son, Head of People’s Committee of Quang Phuoc Commune 6. Tran Nuoc, Head of People’s Committee of Quang An Commune 7. Nguyen Thi Dieu Lien, Vice Head of Farmers’ Union
8. Nguyen Ngoc Phu, Head of Plant Protection Center 9. Tran Dinh Quang, Head of Agricultural Extension Office
10. Tran Dinh Chinh, Head of Division of Agriculture, Quang Dien District 11. Nguyen Thi Mai Anh, Vice Head of Women’s Union, Quang Dien district
Make pairwise comparison of indicators and sub-indicators.
What are the potential adaptation options that can be considered in study
areas?
8am- 12am 16th November 2017
Base of Duy Xuyen People’s Committee, Quang Nam Province
1. Ly Chuong, Director of Duy Vinh Cooperative 2. Pham Van Nam, Director of Duy Phuoc Cooperative 3. Nguyen Anh Tu, Director of Duy Nghia Cooperative
4. Tran Van Thanh, Head of People’s Committee of Duy Vinh Commune 5. Phan Dinh Nam, Head of People’s Committee of Duy Nghia Commune 6. Le Trung Ba, Head of People’s Committee of Duy Phuoc Commune 7. Le Dinh Cong, Vice Head of Farmers’ Union
8. Pham Xuan Hung, Head of Plant Protection Center 9. Tran Manh Hung, Head of Agricultural Extension Office 10. Le Van Xuan, Vice Head of Division of Agriculture, Duy Xuyen 11. District Le Dao Yen, Head of Women’s Union, Duy Xuyn district
Make pairwise comparison of indicators and sub-indicators.
What are the potential adaptation options that can be considered in study
areas?
Third FGD
8am-12am, 2nd December 2017
Base of Xuan An Cooperative, Quang Dien, Thua Thien Hue
Province
1. Pham Xuan Hung, Director of Xuan An Cooperative 2. Tran Van Chuong, Director of Quang Phuoc Cooperative 3. Nguyen Van Quy, Director of Quang Thanh Cooperative
4. Phan Dinh Suu, Head of People’s Committee of Quang Thanh Commune 5. Phan Hung Son, Head of People’s Committee of Quang Phuoc Commune 6. Tran Nuoc, Head of People’s Committee of Quang An Commune 7. Dang Phuoc Hung, Head of An Xuan Dong Village
8. Dang Phuoc Phu, Head of An Xuan Bac Village 9. Hoang Trong Thuy, Head of An Xuan Tay Village 10. Tran Van Chinh, farmer from An Xuan Bac Village 11. Dang Van Dang, farmer from An Xuan Bac Village 12. Tran Quang Loc, farmer from An Xuan Bac Village 13. Tran Dinh Ba, farmer from An Xuan Tay Village 14. Hoang Loi, farmer from An Xuan Tay Village 15. Tran Quang Long, farmer from An Xuan Tay Village 16. Tran Huu Ty, farmer from An Xuan Dong Village 17. Van Dinh Chung, farmer from An Xuan Tay Village 18. Hoang Minh Cam, farmer from An Xuan Tay Village
Rating last level of sub-indicator by 5 Likert scales with respect to each
adaptation option.
1pm-5pm, 17th December 2017
Base of Duy Vinh Cooperative, Duy Xuyen
District
1. Ly Chuong, Director of Duy Vinh Cooperative 2. Pham Van Nam, Director of Duy Phuoc Cooperative 3. Nguyen Anh Tu, Director of Duy Nghia Cooperative
4. Tran Van Thanh, Head of People’s Committee of Duy Vinh Commune 5. Phan Dinh Nam, Head of People’s Committee of Duy Nghia Commune
Rating last level of sub-indicator by 5 Likert scales with respect to each
adaptation option.
6. Le Trung Ba, Head of People’s Committee of Duy Phuoc Commune 7. To Dinh Tung, Head of Tra Nam Village
8. Huynh Van Khuong, Head of Vinh Nam village 9. Vo Xuyen, Head of Hoa Thuan village
10. Nguyen To, farmer from Cao Lau Dong village 11. Dang Minh Hoa, farmer from Ha Nhuan village 12. Nguyen Van Hoa, farmer from Ha Nhuan village 13. Nguyen Thi Luong, farmer from Ha Nhuan village 14. Le Van Sanh, farmer from Vinh Nam village 15. Nguyen Van To, Head of My Phuoc Village 16. Pham Loi, farmer from My Phuoc village 17. Le Ba Tich, farmer from My Phuoc village
18. Nguyen Van Mau, farmer from Cao Lau Dong village
(Source: Authors’ note, 2020)
Appendix D: Table S3: Table of potential indicators
Component Weiland, et al. (2015) Adger et al. (2005) Dixit & McGray
(2013) Sen (2016) Ndamani & Watanabe
(2017) Brooks et al. (2011) [46]
Coherence
Interactions
(conflicts/synergies) with other measures
Does the option offer co-benefits?
With natural condition Integration with policy
domains, programs or projects
With ability of community
Vertical integration With policies on
economy and society Horizontal integration
Efficiency
Cost/benefit ratio Distribution of cost and benefits
Achieved outputs optimal relative to allocated resources
Economy Resilience
Likely to be assessed in terms of the ratio of
benefits to costs Total cost Timing of adaptation
actions Society Short-term/medium/ long
response
Benefit Concerning non-
market benefits Environment
Frequency of unintended consequences Criticality of unintended
consequences Current society Future generation
Ability to Confront and Adapt
Confront extreme natural phenomenon
Adapt flexibly for season Adapt to income
diversity
Sustainability Proportion of beneficiaries
Identifying who gains and who loses
from any impact or adaptation policy
decision
Benefit vulnerable groups and communities
Suitable for local
development policies Vulnerable group
Equitable interventions might be seen as those
that provide the greatest degree of assistance to
the poorest.
Suitable for market
Attention to most vulnerable groups
Suitable for climate change tendency
Adaptation interventions are compatible with
environmental sustainability as usual
Ability to upscale
The benefits of adaptation interventions
will continue after the termination of the projects and programs
under which they are implemented.
Interventions designed to deliver adaptation benefits in the near-term
do not increase vulnerability or drive
maladaptation in the medium to long-term.
Interventions can be managed by mandated
organizations into the medium and long term.
Equity
Proportion of Beneficiaries Attention to the most vulnerable
groups
Measures to reduce poverty and increase
access to resources could reduce
present-day vulnerability as well
as vulnerability to both climatic variability and climate change
Benefit vulnerable groups and communities
Equity will also require that adaptation interventions do not result in the (further) marginalization of
certain groups
Feasibility/
Practicality
Can be implemented within relevant
timescales
Knowledge, skills and past experience Competence Finance
Technical feasibility Sufficient management
capacity and implementation
Cost
Effectiveness
Level of resilience Vulnerability
Sensitive Exposure Adaptive capacity
Reducing risks Avoiding danger Promoting security
Impact of an intervention at the institutional level Impact of an intervention
on the Vulnerability of individuals, groups or
other entities Impact of an intervention
on outcomes Robustness Regret or no regret
Robust under a range of future climate projections
(Source: Authors’ synthesis, 2020)
9
Appendix E: Table S4: Short list of indicators
Components Indicators
Coherence
Integration with policy domains, programs or projects With natural condition
With ability of community
With policies on economy and society
Efficiency
Total cost Benefit
Concerning non-market benefits Economy
Society Environment Ability to Confront and Adapt
Confront extreme natural phenomenon Adapt with flexibility for season Adapt to income diversity
Sustainability and Equity
Attention to most vulnerable groups Suitable for market
Suitable for climate change tendency Ability to upscale
Equity
(Source: Authors’ synthesis, 2020)
Appendix F: Table S5: List of 11 alternatives
Situation Potential alternatives Shortened Alternatives
Current: applied in study area Apply new varieties of paddy Apply new varieties of paddy Switch to shrimp production Switch to shrimp production Vegetable Production Vegetable Production Apply lotus-fish model Apply lotus-fish model
Plant papyrus Plant papyrus
Potential: applied in other areas Apply paddy-shrimp model Apply paddy-shrimp model Plant bitter melon in drought season Plant bitter melon in drought season Plant watermelon in drought season Plant watermelon in drought season Apply coconut-fish model Apply coconut-fish model
Polyculture of mullets Polyculture of mullets Multi-plant
Plant ratoon rice Plant maize-green bean Plant grass for beef feeding
(Source: Authors’ synthesis, 2020)
10
1. Changing production structure in accordance with reality and with forecast changes in the scenario for climate change and SLR, with the purpose of improving adaptive capacities, diversifying production methods, thereby reducing risks and creating sustainable livelihoods
2. Testing agricultural insurance models; drought and salinity management associated with basins and water resource management that are considered as regular management tasks
3. Consolidating and upgrading the agricultural infrastructure system, developing the
“hard construction” system coordinating with “soft solutions” (planting coastal protection forests, planting mangroves) etc.
4. Developing mechanisms and policies to replicate methods such as: Good agricultural practices (VietGAP), 1 must done; 5 decrease; 3 decreases, 3 increases; rotation of shrimp-rice and rice-fish farming; fishery integrated mangrove protection and management, etc.
5. Developing plant varieties and animal breeds that can adapt to unfavorable weather conditions (drought and salinity), along with building seed banks.
6. Promoting the development of community-based disaster risk management models.
7. Raising awareness of climate change for the community and people in combination with improving the effectiveness of forecasting and warnings about weather and climate.
(Source: Second Action Program, MONRE 2019)
Appendix H: Description of components and indicators
A. Coherence: the adaptive measure is coherent with current and future conditions and policies within the study area. This component is evaluated by four indicators, such as coherence with natural conditions, community capacity and with local customs and policies.
Coherence with natural conditions: This introduces the degree to which an adaptation method complies with the characteristics of soil, climate and ecosystems in study areas. Since natural conditions are the main driver of agricultural production, the decision to select and apply an adaptation method is affected by the degree to which it fits into this indicator.
Coherence with community capacity: This represents the individual ability of each farmer to adopt and maintain adaptation measures. Almost all farms in rural areas of Vietnam are underdeveloped and farmers are not well educated, making one adaptation method for this targeted group less complicated and highly appropriate for farmers’ ability. An adaptation method cannot be considered successful if it is not affordable for farmers. In particular, for poor groups, a high investment requirement is a barrier to implementing adaptation measures.
Coherence with local customs and policies: Local people tend to actively support one adaptation method that is based on community need. Indeed, the tight community relationships in rural areas of Vietnam control farmers’ decision-making. An adaptation measure that is suitable for the community’s need has a high chance of being successful. However, the chance to upscale depends on the appropriateness of this adaptation method to local policies.
B. Efficiency: the results of the adaptation method should consider whether the economic and non-economic benefits obtained are greater than the cost of implementation and maintenance.
Economic efficiency: The crucial factor that governs the final decision by farmers for an adaptation method is how much they can earn from this measure. Farmers need to consider whether they can afford the cost of the adaptation option. In particular, huge initial investment places greater financial pressure on farmers and makes them postpone developing firm adaptation measures.
11
Hence, assessment of the economic efficiency of adaptation measures needs to be considered first, the cost and benefit, and the second risk1 involved.
Social efficiency: As mentioned above, almost all farmers in rural areas of Vietnam belong to a low-income group and consequently they are a vulnerable group in society. In a male-dominant society, women farmers, who account for the majority, are more vulnerable and resource limited.
Good adaptation options also need to ensure equal distribution of job opportunities and income between rich and poor people.
Environmental efficiency: The third issue in evaluating the efficiency of adaptation measures concerns non-market benefit which mostly relates to the environment. It is noted that current adaptations might impose bad effects on the future environment. For example, building a dam or changing new crops obviously impacts on the whole ecosystem. Consequently, in spite of the fact that farmers in rural areas of Vietnam do not prioritize environmental issues when making decisions about adaptations, risks relating to soil, water and air are of concern in our paper.
C. Ability to confront and adapt: this indicator was developed to assess the adaptation methods for the risks of SWI in study areas. We only focus on adaptation methods at farm-level, meaning that adaptation action is climate-proofing. Hence, this group of indicators is very important to check whether or not the adaptation method in our study is good.
Ability to confront: The study area in this paper located in central Vietnam suffers many natural disasters such as: floods, storms, drought, etc. For this reason, the adaptation measures are able to cope with not only SWI but also flood and drought.
Ability to adapt: It is documented that predicted sea level rise is highest for Central Coastal Vietnam and could drive problems of saltwater intrusion. Hence, adaptation measures have to (1) be more flexible to time adjustment (2) recover after SWI and (3) be ready for a worsening SWI situation in the future.
D. Sustainability and Equity: the adaptive measure can be applied at a larger scale and maintained over a longer timeframe, while its benefits are distributed equitably and with a focus on the most vulnerable groups
Sustainability: This indicator reflects the appropriateness of the adaptation method to the CC scenario long term. Moreover, in this paper, we evaluate the success of one adaptation option by its ability to develop and upscale in the long term.
Equity: Last but not least, equity is one indicator that was mentioned when answering the question “what is good adaptation?” in developing countries. This indicator evaluates the fairness of stakeholders in taking the benefits and ensures that vulnerable groups win from adaptation.
Farmers have weak powers in rural society in Vietnam and, hence, they need to be prioritized in accessing information and support to implement adaptation options.
1 Risk related to consumer market
12
(Source: Authors’ analysis, 2020)
Appendix J: Detailed AHP results
Table S6: Pairwise comparison matrix of indicators with respect to A1 and A2 in Duy Xuyen district
B1 B2 B3 Priorities B4 B5 B6 Priorities
B1 1 1/2 1/5 0.118 B4 1 6 3 0.627
B2 2 1 1/4 0.201 B5 1/6 1 1/5 0.081
B3 5 4 1 0.681 B6 1/3 5 1 0.292
𝜆𝑚𝑎𝑥 = 3.0247 CI= 0.0123 CR= 0.0212 𝜆𝑚𝑎𝑥 = 3.095 CI= 0.047 CR= 0.082 (Source: Authors’ calculation, 2020) Table S7: Pairwise comparison matrix of indicators with respect to A3 and A4 in Duy Xuyen district
B7 B8 Priorities B9 B10 Priorities
B7 1 1 0.5 B9 1 7 0.9
B8 1 1 0.5 B10 1/7 1 0.1
(Source: Authors’ calculation, 2020) Table S8: Pairwise comparison matrix of sub-indicators with respect to B1, B2 and B3 in Duy Xuyen District
C1 C2 C3 Priorities C4 C5 C6 Priorities C7 C8 C9 Priorities
C1 1 1/7 1/3 0.081 C4 1 3 1/3 0.627 C7 1 1/6 1 0.1299
C2 7 1 6 0.739 C5 1/3 1 1/4 0.081 C8 6 1 5 0.7320
C3 3 1/6 1 0.178 C6 3 4 1 0.292 C9 1 1/5 1 0.1267
𝜆𝑚𝑎𝑥 = 3.102 CI= 0.051 CR= 0.088 𝜆𝑚𝑎𝑥 = 3.074 CI= 0.037 CR= 0.063 𝜆𝑚𝑎𝑥 = 3.008 CI= 0.004 CR= 0.007 (Source: Authors’ calculation, 2020)
13
Table S9: Pairwise comparison matrix of sub-indicators with respect to B4, B5 and B6 in Duy Xuyen district
C10 C11 C12 C13 C14 C15 Priorities C16 C17 C18 Priorities C19 C20 C21 C22 Priorities C10 1 1 1/7 3 1/6 1/7 0.065 C16 1 3 1/5 0.1932 C19 1 1 1/6 3 0.139 C11 1 1 1/5 1 1/3 1/6 0.055 C17 1/3 1 1/7 0.0833 C20 1 1 1/5 5 0.176
C12 7 5 1 5 1 1/3 0.232 C18 5 7 1 0.7235 C21 6 5 1 7 0.629
C13 1/3 1 1/5 1 1/3 1/5 0.052 C22 1/3 1/5 1/7 1 0.056
C14 6 3 1 3 1 1/3 0.186
C15 7 6 3 5 3 1 0.410
𝜆𝑚𝑎𝑥 =6.448 CI= 0.089 CR= 0.072 𝜆𝑚𝑎𝑥 = 3.065 CI= 0.0329 CR= 0.056 𝜆𝑚𝑎𝑥 = 4.184 CI= 0.061 CR= 0.068 (Source: Authors’ calculation, 2020) Table S10: Pairwise comparison matrix of sub-indicators with respect to B7 and B8 in Duy Xuyen district
C23 C24 C25 Priorities C26 C27 C28 Priorities
C23 1 1/7 1/5 0.078 C26 1 1/7 1/5 0.074
C24 7 1 1 0.487 C27 7 1 3 0.643
C25 5 1 1 0.435 C28 5 1/3 1 0.283
λmax = 3.102 CI= 0.006 CR= 0.010 λmax = 3.065 CI= 0.037 CR= 0.056
(Source: Authors’ calculation, 2020) Table S11: Pairwise comparison matrix of sub-indicators with respect to B9 and B10 in Duy Xuyen district
C29 C30 C31 C32 Priorities C33 C34 C35 Priorities
C29 1 6 1/3 1/5 0.142 C33 1 1/6 3 0.179
C30 1/6 1 1/7 1/9 0.040 C34 6 1 7 0.739
C31 3 7 1 1/3 0.264 C35 1/3 1/7 1 0.082
C32 5 9 3 1 0.554
λmax = 4.225 CI= 0.075 CR= 0.083 λmax =3.102 CI= 0.051 CR= 0.088 (Source: Authors’ calculation, 2020) Table S12: Pairwise comparison matrix of indicators with respect to A1 and A2 in Quang Dien district
B1 B2 B3 Priorities B4 B5 B6 Priorities
B1 1 3 7 0.656 B4 1 7 3 0.643
B2 1/3 1 4 0.265 B5 1/7 1 1/5 0.074
B3 1/7 1/4 1 0.080 B6 1/3 5 1 0.283
λmax = 3.032 CI= 0.016 CR= 0.028 λmax = 3.065 CI= 0.032 CR= 0.056 (Source: Authors’ calculation, 2020)
Table S13: Pairwise comparison matrix of indicators with respect to A3 and A4 in Quang Dien district
B7 B8 Priorities B9 B10 Priorities
B7 1 5 0.833 B9 1 4 0.8
B8 1/5 1 0.167 B10 0.25 1 0.2
(Source: Authors’ calculation, 2020)
14
Dien district
C1 C2 C3 Priorities C4 C5 C6 Priorities C7 C8 C9 Priorities
C1 1 1/4 1 0.221 C4 1 6 1 0.484 C7 1 1/2 1 0.234
C2 4 1 4 0.685 C5 1/6 1 1/4 0.093 C8 2 1 4 0.579
C3 1/3 1/6 1/3 0.093 C6 1 4 1 0.423 C9 1 1/4 1 0.155
𝜆𝑚𝑎𝑥 = 3.054 CI= 0.027 CR= 0.046 𝜆𝑚𝑎𝑥 = 3.018 CI= 0.009 CR= 0.015 𝜆𝑚𝑎𝑥 = 3.074 CI= 0.037 CR= 0.064 (Source: Authors’ calculation, 2020) Table S15: Pairwise comparison matrix of sub-indicators with respect to B4, B5 and B6 in Quang Dien district
C10 C11 C12 C13 C14 C15 Prioritie
s C16 C17 C18 Prioritie
s C19 C20 C21 C22 Prioritie s C10 1 1/5 1/7 1 1/5 1/8 0.035 C16 1 1/2 1/6 0.103 C19 1 1/7 1/4 1 0.070 C11 5 1 1/7 6 1 1/6 0.123 C17 2 1 1/5 0.174 C20 7 1 5 9 0.649
C12 7 7 1 4 3 1 0.325 C18 6 5 1 0.723 C21 4 1/5 1 4 0.216
C13 1 1/6 1/4 1 1/5 1/6 0.044 C22 1 1/9 1/4 1 0.065
C14 5 1 1/3 5 1 1/3 0.137
C15 8 6 1 6 3 1 0.335
𝜆𝑚𝑎𝑥 =6.570 CI= 0.11 CR= 0.09 𝜆𝑚𝑎𝑥 = 3.029 CI= 0.014
CR=
0.0252
𝜆𝑚𝑎𝑥 = 4.116 CI= 0.039 CR=
0.043 (Source: Authors’ calculation, 2020) Table S16: Pairwise comparison matrix of sub-indicators with respect to B7 and B8 in Quang Dien district
C23 C24 C25 Priorities C26 C27 C28 Priorities
C23 1 2 1/3 0.230 C26 1 3 7 0.643
C24 1/2 1 1/5 0.122 C27 1/3 1 5 0.283
C25 3 5 1 0.648 C28 1/7 1/5 1 0.074
λmax = 3.003 CI= 0.0018 CR= 0.003 λmax = 3.065 CI= 0.032 CR= 0.056
(Source: Authors’ calculation, 2020) Table S17: Pairwise comparison matrix of sub-indicators with respect to B9 and B10 in Quang Dien district
C29 C30 C31 C32 Priorities C33 C34 C35 Priorities
C29 1 8 5 1/3 0.323 C33 1 1/3 1/2 0.164
C30 1/8 1 1/3 1/7 0.049 C34 3 1 2 0.539
C31 1/5 3 1 1/5 0.103 C35 2 1/2 1 0.297
C32 3 7 5 1 0.525
λmax = 4.240 CI= 0.080 CR= 0.089 λmax =3.009 CI= 0.004 CR= 0.007
(Source: Authors’ calculation, 2020)
15
TableS18: Scoring alternatives in Duy Xuyen district
Component Indicator Sub indicator Priorit
y
New varietie
s (A)
Shrimp Productio
n (B)
Coconut -Fish
(C)
Papyrus
(D) P*A P*B P*C P*D
Coherence 0.045
Coherent with natural
conditions 0.118
Coherent with soil condition 0.082 0.000 5.000 5.000 5.000 5.000 0.002 0.002 0.002 0.002
Coherent with climate 0.739 0.004 5.000 3.000 4.000 5.000 0.020 0.012 0.016 0.020
Coherent with ecosystem 0.179 0.001 4.000 3.000 4.000 5.000 0.004 0.003 0.004 0.005
Coherent with capacity of community
0.201
Coherent with skills and knowledge of farmers 0.272 0.002 3.000 3.000 3.000 4.000 0.007 0.007 0.007 0.010 Coherent with local experiences and local backgrounds (not too new) 0.120 0.001 4.000 1.000 2.000 5.000 0.004 0.001 0.002 0.005 Coherent with financial and investment capacity of farmers 0.608 0.005 3.000 1.000 1.000 3.000 0.016 0.005 0.005 0.016 Coherent
with social- culture and policies
0.681
Coherent with local policies 0.130 0.004 3.000 3.000 2.000 2.000 0.012 0.012 0.008 0.008
Coherent with needs of community 0.732 0.022 3.000 1.000 3.000 3.000 0.067 0.022 0.067 0.067
Coherent with local customs 0.127 0.004 5.000 1.000 2.000 3.000 0.019 0.004 0.008 0.012
Efficiency 0.241
Economic efficiency 0.627
Yield (1=very low, 5=very high) 0.065 0.010 2.000 3.000 5.000 4.000 0.020 0.029 0.049 0.039
Cost of production (1= very high, 5= very low) 0.055 0.008 3.000 5.000 5.000 1.000 0.025 0.041 0.041 0.008
Profit (1=very low, 5=very high) 0.232 0.035 2.000 1.000 3.000 1.000 0.070 0.035 0.105 0.035
Risks (1= very high, 5= very low) 0.052 0.008 3.000 1.000 3.000 5.000 0.024 0.008 0.024 0.040
Stability of Input price (1=absolutely not stable, 5= very stable) 0.186 0.028 2.000 2.000 1.000 1.000 0.056 0.056 0.028 0.028 Stability of Output market (1=absolutely not stable, 5= very stable) 0.410 0.062 1.000 2.000 4.000 1.000 0.062 0.124 0.248 0.062 Social
efficiency 0.081
Improving ability of target groups (women, children, poor people..) (1=
not improved, 5= very improved) 0.193 0.004 1.000 3.000 1.000 2.000 0.004 0.011 0.004 0.008
Risk of increasing social gap (1=very high, 5= very low) 0.083 0.002 5.000 1.000 5.000 5.000 0.008 0.002 0.008 0.008 Job opportunities (1= very low, 5= very high) 0.724 0.014 1.000 5.000 4.000 4.000 0.014 0.071 0.056 0.056 Environment
al efficiency 0.292
Risk of soil erosion and land degradation (1=high risk, 5= low risk) 0.139 0.010 1.000 1.000 5.000 5.000 0.010 0.010 0.049 0.049 Risk of polluting water quality (1=high risk, 5= low risk) 0.176 0.012 1.000 3.000 5.000 5.000 0.012 0.037 0.062 0.062 Risk of exhausting water source (1=high risk, 5= low risk) 0.629 0.044 1.000 1.000 5.000 5.000 0.044 0.044 0.221 0.221 Risk of polluting air environment (1=high risk, 5= low risk) 0.056 0.004 1.000 1.000 2.000 5.000 0.004 0.004 0.008 0.020
Ability to confront and adapt
0.185
Ability to confront 0.500
Ability to confront flood (1=very low, 5=very high) 0.078 0.007 1.000 3.000 5.000 5.000 0.007 0.022 0.036 0.036 Ability to confront drought (1=very low, 5=very high) 0.487 0.045 5.000 3.000 4.000 4.000 0.225 0.135 0.180 0.180 Ability to confront salt water intrusion (1=very low, 5=very high) 0.435 0.040 5.000 4.000 5.000 5.000 0.201 0.161 0.201 0.201 Ability to
adapt 0.500
Ability to recover after saltwater intrusion (1=very low, 5=very high) 0.074 0.007 5.000 5.000 1.000 5.000 0.034 0.034 0.007 0.034 Crop season flexibility to avoid SWI (1=low flexibility, 5=high flexibility) 0.643 0.060 1.000 5.000 5.000 5.000 0.060 0.298 0.298 0.298 Adapt limitation to SWI in order to achieve high yield (1= narrow
limitation, 5- large limitation) 0.283 0.026 1.000 5.000 3.000 5.000 0.026 0.131 0.078 0.131
Sustainabil ity and
Equity
0.529 Sustainability 0.900
Income diversity (1=low diversity, 5=high diversity) 0.142 0.067 5.000 5.000 5.000 3.000 0.337 0.337 0.337 0.202 Coherent with CC scenarios ( 1= not coherent, 5= very coherent) 0.040 0.019 5.000 5.000 5.000 4.000 0.096 0.096 0.096 0.077 Expanding ability (adaptation method can be upscaled) (1=very low,
5=very high) 0.264 0.126 5.000 5.000 3.000 2.000 0.629 0.629 0.378 0.252
Developing ability (adaptation method can be maintained for a long
time) (1=very low, 5=very high) 0.554 0.264 5.000 5.000 5.000 2.000 1.318 1.318 1.318 0.527
16
Equity 0.100
proportion) 0.179 0.009 5.000 1.000 5.000 5.000 0.047 0.009 0.047 0.047
All farmers impacted by SWI can apply the adaptation measures (1=
very small proportion, 5= very large proportion) 0.739 0.039 5.000 1.000 5.000 5.000 0.196 0.039 0.196 0.196 Vulnerable groups (women, poor people, elderly) are the target group
for adaptation measures (1=strongly disagree, 5=strongly agree) 0.082 0.004 1.000 1.000 5.000 4.000 0.004 0.004 0.022 0.017
FINAL SCORE 3.686 3.755 4.217 2.980
(Source: Authors’ calculation, 2020)
17
Table S19: Scoring alternatives in Quang Dien district
Component Indicator Sub indicator Priority
New varietie
s (A) Lotu s-fish
(B)
Shrimp Producti on ©
P*A P*B P*C
Coherence 0.061
Coherent with natural conditions
0.656
Coherent with soil condition 0.221 0.009 3 4 5 0.027 0.036 0.045
Coherent with climate 0.685 0.028 4 5 3 0.110 0.138 0.083
Coherent with ecosystem 0.093 0.004 5 4 5 0.019 0.015 0.019
Coherent with capacity of community
0.265
Coherent with skills and knowledge of farmers 0.484 0.008 4 4 5 0.031 0.031 0.039
Coherent with local experiences and local backgrounds (not too new) 0.093 0.002 4 4 5 0.006 0.006 0.008 Coherent with financial and investment capacity of farmers 0.423 0.007 4 2 2 0.028 0.014 0.014 Coherent with
social-culture and policies
0.080
Coherent with local policies 0.234 0.001 5 4 5 0.006 0.005 0.006
Coherent with needs of community 0.579 0.003 5 4 5 0.014 0.011 0.014
Coherent with local customs 0.155 0.001 5 4 2 0.004 0.003 0.002
Efficiency 0.102
Economic
efficiency 0.643
Yield (1=very low, 5=very high) 0.035 0.002 3 5 5 0.007 0.012 0.012
Cost of production (1= very high, 5= very low) 0.123 0.008 5 4 1 0.040 0.032 0.008
Profit (1=very low, 5=very high) 0.325 0.021 2 3 4 0.043 0.064 0.085
Risks (1= very high, 5= very low) 0.044 0.003 3 2 1 0.009 0.006 0.003
Stability of Input price (1=absolutely not stable, 5= very stable) 0.137 0.009 2 3 1 0.018 0.027 0.009 Stability of Output market (1=absolutely not stable, 5= very stable) 0.335 0.022 1 4 1 0.022 0.088 0.022
Social efficiency 0.074
Improving ability of target groups (women, children, poor people..) (1= not
improved, 5= very improved) 0.103 0.001 4 3 1 0.003 0.002 0.001
Risk of increasing social gap (1=very high, 5= very low) 0.174 0.001 2 2 1 0.003 0.003 0.001
Job opportunities (1= very low, 5= very high) 0.723 0.005 1 1 2 0.005 0.005 0.011
Environmental efficiency 0.283
Risk of soil erosion and land degradation (1=high risk, 5= low risk) 0.070 0.002 4 5 5 0.008 0.010 0.010 Risk of polluting water quality (1=high risk, 5= low risk) 0.649 0.019 1 3 1 0.019 0.056 0.019 Risk of exhausting water source (1=high risk, 5= low risk) 0.216 0.006 1 3 1 0.006 0.019 0.006 Risk of polluting air environment (1=high risk, 5= low risk) 0.065 0.002 1 5 5 0.002 0.009 0.009
Ability to confront and
adapt
0.383
Ability to
confront 0.833
Ability to confront flood (1=very low, 5=very high) 0.230 0.073 1 1 1 0.073 0.073 0.073
Ability to confront drought (1=very low, 5=very high) 0.122 0.039 2 2 1 0.078 0.078 0.039 Ability to confront salt water intrusion (1=very low, 5=very high) 0.648 0.207 4 4 3 0.827 0.827 0.620 Ability to adapt 0.167
Ability to recover after saltwater intrusion (1=very low, 5=very high) 0.643 0.041 4 3 3 0.164 0.123 0.123 Crop season flexibility to avoid SWI (1=low flexibility, 5=high flexibility) 0.283 0.018 5 4 2 0.090 0.072 0.036 Adapt limitation to SWI in order to achieve high yield (1= narrow limitation,
5- large limitation) 0.074 0.005 5 1 3 0.024 0.005 0.014
Sustainability
and Equity 0.454 Sustainability 0.800
Income diversity (1=low diversity, 5=high diversity) 0.323 0.117 1 4 2 0.117 0.469 0.234 Coherent with CC scenarios ( 1= not coherent, 5= very coherent) 0.049 0.018 5 4 3 0.089 0.071 0.053 Expanding ability (adaptation method can be upscaled) (1=very low, 5=very
high) 0.103 0.037 2 4 4 0.075 0.149 0.149
Developing ability (adaptation method can be maintained for a long time)
(1=very low, 5=very high) 0.525 0.191 5 5 4 0.953 0.953 0.762
18
Equity 0.200 All farmers impacted by SWI can apply the adaptation measures (1= very
small proportion, 5= very large proportion) 0.539 0.049 5 3 3 0.244 0.147 0.147
Vulnerable groups (women, poor people, elderly) are the target group for
adaptation measures (1=strongly disagree, 5=strongly agree) 0.297 0.027 3 2 2 0.081 0.054 0.054
FINAL SCORE 3.319 3.688 2.775
(Source: Authors’ calculation, 2020)
19
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